From 60efcad481f68c3d650c810df7ba5e45d2826574 Mon Sep 17 00:00:00 2001
From: Eduardo Chiarotti <dudumelgaco@hotmail.com>
Date: Fri, 18 Oct 2024 15:45:01 -0300
Subject: [PATCH 001/126] feat: add poetry.lock to uv migration (#1468)

---
 src/crewai/cli/update_crew.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/src/crewai/cli/update_crew.py b/src/crewai/cli/update_crew.py
index e2d39590d..d38e11a25 100644
--- a/src/crewai/cli/update_crew.py
+++ b/src/crewai/cli/update_crew.py
@@ -1,3 +1,4 @@
+import os
 import shutil
 
 import tomli_w
@@ -94,6 +95,15 @@ def migrate_pyproject(input_file, output_file):
     shutil.copy2(input_file, backup_file)
     print(f"Original pyproject.toml backed up as {backup_file}")
 
+    # Rename the poetry.lock file
+    lock_file = "poetry.lock"
+    lock_backup = "poetry-old.lock"
+    if os.path.exists(lock_file):
+        os.rename(lock_file, lock_backup)
+        print(f"Original poetry.lock renamed to {lock_backup}")
+    else:
+        print("No poetry.lock file found to rename.")
+
     # Write the new pyproject.toml
     with open(output_file, "wb") as f:
         tomli_w.dump(new_pyproject, f)

From 84f48c465d602a2b121a82d464fe701f84160e9f Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Fri, 18 Oct 2024 14:56:56 -0400
Subject: [PATCH 002/126] fix tool calling issue (#1467)

* fix tool calling issue

* Update tool type check

* Drop print
---
 src/crewai/agent.py                      |   2 +-
 src/crewai/agents/crew_agent_executor.py |   8 +-
 src/crewai/tools/tool_usage.py           |  10 +-
 tests/tools/test_tool_usage.py           | 143 +++++++++++++++++++++++
 4 files changed, 154 insertions(+), 9 deletions(-)
 create mode 100644 tests/tools/test_tool_usage.py

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 3f81ece21..165a40656 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -394,7 +394,7 @@ class Agent(BaseAgent):
         """
         tool_strings = []
         for tool in tools:
-            args_schema = str(tool.args)
+            args_schema = str(tool.model_fields)
             if hasattr(tool, "func") and tool.func:
                 sig = signature(tool.func)
                 description = (
diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index b901fe132..b11782ca1 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -2,6 +2,7 @@ import json
 import re
 from typing import Any, Dict, List, Union
 
+from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
 from crewai.agents.parser import (
     FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE,
@@ -19,7 +20,6 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 )
 from crewai.utilities.logger import Logger
 from crewai.utilities.training_handler import CrewTrainingHandler
-from crewai.agents.agent_builder.base_agent import BaseAgent
 
 
 class CrewAgentExecutor(CrewAgentExecutorMixin):
@@ -323,9 +323,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             if self.crew is not None and hasattr(self.crew, "_train_iteration"):
                 train_iteration = self.crew._train_iteration
                 if agent_id in training_data and isinstance(train_iteration, int):
-                    training_data[agent_id][train_iteration]["improved_output"] = (
-                        result.output
-                    )
+                    training_data[agent_id][train_iteration][
+                        "improved_output"
+                    ] = result.output
                     training_handler.save(training_data)
                 else:
                     self._logger.log(
diff --git a/src/crewai/tools/tool_usage.py b/src/crewai/tools/tool_usage.py
index f75a9443a..71c02fc3c 100644
--- a/src/crewai/tools/tool_usage.py
+++ b/src/crewai/tools/tool_usage.py
@@ -6,14 +6,13 @@ from difflib import SequenceMatcher
 from textwrap import dedent
 from typing import Any, List, Union
 
+import crewai.utilities.events as events
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.task import Task
 from crewai.telemetry import Telemetry
 from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
 from crewai.tools.tool_usage_events import ToolUsageError, ToolUsageFinished
 from crewai.utilities import I18N, Converter, ConverterError, Printer
-import crewai.utilities.events as events
-
 
 agentops = None
 if os.environ.get("AGENTOPS_API_KEY"):
@@ -300,8 +299,11 @@ class ToolUsage:
         descriptions = []
         for tool in self.tools:
             args = {
-                k: {k2: v2 for k2, v2 in v.items() if k2 in ["description", "type"]}
-                for k, v in tool.args.items()
+                name: {
+                    "description": field.description,
+                    "type": field.annotation.__name__,
+                }
+                for name, field in tool.args_schema.model_fields.items()
             }
             descriptions.append(
                 "\n".join(
diff --git a/tests/tools/test_tool_usage.py b/tests/tools/test_tool_usage.py
new file mode 100644
index 000000000..d0a6ec0b0
--- /dev/null
+++ b/tests/tools/test_tool_usage.py
@@ -0,0 +1,143 @@
+import json
+import random
+from unittest.mock import MagicMock, patch
+
+import pytest
+from crewai_tools import BaseTool
+from pydantic import BaseModel, Field
+
+from crewai import Agent, Crew, Task
+from crewai.tools.tool_usage import ToolUsage
+
+
+class RandomNumberToolInput(BaseModel):
+    min_value: int = Field(
+        ..., description="The minimum value of the range (inclusive)"
+    )
+    max_value: int = Field(
+        ..., description="The maximum value of the range (inclusive)"
+    )
+
+
+class RandomNumberTool(BaseTool):
+    name: str = "Random Number Generator"
+    description: str = "Generates a random number within a specified range"
+    args_schema: type[BaseModel] = RandomNumberToolInput
+
+    def _run(self, min_value: int, max_value: int) -> int:
+        return random.randint(min_value, max_value)
+
+
+# Example agent and task
+example_agent = Agent(
+    role="Number Generator",
+    goal="Generate random numbers for various purposes",
+    backstory="You are an AI agent specialized in generating random numbers within specified ranges.",
+    tools=[RandomNumberTool()],
+    verbose=True,
+)
+
+example_task = Task(
+    description="Generate a random number between 1 and 100",
+    expected_output="A random number between 1 and 100",
+    agent=example_agent,
+)
+
+
+def test_random_number_tool_usage():
+    crew = Crew(
+        agents=[example_agent],
+        tasks=[example_task],
+    )
+
+    with patch.object(random, "randint", return_value=42):
+        result = crew.kickoff()
+
+    assert "42" in result.raw
+
+
+def test_random_number_tool_range():
+    tool = RandomNumberTool()
+    result = tool._run(1, 10)
+    assert 1 <= result <= 10
+
+
+def test_random_number_tool_with_crew():
+    crew = Crew(
+        agents=[example_agent],
+        tasks=[example_task],
+    )
+
+    result = crew.kickoff()
+
+    # Check if the result contains a number between 1 and 100
+    assert any(str(num) in result.raw for num in range(1, 101))
+
+
+def test_random_number_tool_invalid_range():
+    tool = RandomNumberTool()
+    with pytest.raises(ValueError):
+        tool._run(10, 1)  # min_value > max_value
+
+
+def test_random_number_tool_schema():
+    tool = RandomNumberTool()
+
+    # Get the schema using model_json_schema()
+    schema = tool.args_schema.model_json_schema()
+
+    # Convert the schema to a string
+    schema_str = json.dumps(schema)
+
+    # Check if the schema string contains the expected fields
+    assert "min_value" in schema_str
+    assert "max_value" in schema_str
+
+    # Parse the schema string back to a dictionary
+    schema_dict = json.loads(schema_str)
+
+    # Check if the schema contains the correct field types
+    assert schema_dict["properties"]["min_value"]["type"] == "integer"
+    assert schema_dict["properties"]["max_value"]["type"] == "integer"
+
+    # Check if the schema contains the field descriptions
+    assert (
+        "minimum value" in schema_dict["properties"]["min_value"]["description"].lower()
+    )
+    assert (
+        "maximum value" in schema_dict["properties"]["max_value"]["description"].lower()
+    )
+
+
+def test_tool_usage_render():
+    tool = RandomNumberTool()
+
+    tool_usage = ToolUsage(
+        tools_handler=MagicMock(),
+        tools=[tool],
+        original_tools=[tool],
+        tools_description="Sample tool for testing",
+        tools_names="random_number_generator",
+        task=MagicMock(),
+        function_calling_llm=MagicMock(),
+        agent=MagicMock(),
+        action=MagicMock(),
+    )
+
+    rendered = tool_usage._render()
+
+    # Updated checks to match the actual output
+    assert "Tool Name: random number generator" in rendered
+    assert (
+        "Random Number Generator(min_value: 'integer', max_value: 'integer') - Generates a random number within a specified range min_value: 'The minimum value of the range (inclusive)', max_value: 'The maximum value of the range (inclusive)'"
+        in rendered
+    )
+    assert "Tool Arguments:" in rendered
+    assert (
+        "'min_value': {'description': 'The minimum value of the range (inclusive)', 'type': 'int'}"
+        in rendered
+    )
+    assert (
+        "'max_value': {'description': 'The maximum value of the range (inclusive)', 'type': 'int'}"
+        in rendered
+    )

From d1737a96fb732d172eb91b503ebd0c1b383af144 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Fri, 18 Oct 2024 17:56:28 -0300
Subject: [PATCH 003/126] cutting new version

---
 pyproject.toml                                     |  8 ++++----
 src/crewai/__init__.py                             |  2 +-
 src/crewai/cli/templates/crew/pyproject.toml       |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml       |  2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml   |  2 +-
 .../cli/templates/pipeline_router/pyproject.toml   |  2 +-
 src/crewai/cli/templates/tool/pyproject.toml       |  2 +-
 uv.lock                                            | 14 +++++++-------
 8 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index e47748e28..436a01170 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.74.0"
+version = "0.74.1"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
@@ -16,7 +16,7 @@ dependencies = [
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
     "instructor>=1.3.3",
     "regex>=2024.9.11",
-    "crewai-tools>=0.13.1",
+    "crewai-tools>=0.13.2",
     "click>=8.1.7",
     "python-dotenv>=1.0.0",
     "appdirs>=1.4.4",
@@ -36,7 +36,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools>=0.12.1"]
+tools = ["crewai-tools>=0.13.2"]
 agentops = ["agentops>=0.3.0"]
 
 [tool.uv]
@@ -51,7 +51,7 @@ dev-dependencies = [
     "mkdocs-material-extensions>=1.3.1",
     "pillow>=10.2.0",
     "cairosvg>=2.7.1",
-    "crewai-tools>=0.12.1",
+    "crewai-tools>=0.13.2",
     "pytest>=8.0.0",
     "pytest-vcr>=1.0.2",
     "python-dotenv>=1.0.0",
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index a72d6e805..41da7aa21 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.74.0"
+__version__ = "0.74.1"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index d387443a1..35931e8e0 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.0,<1.0.0"
+    "crewai[tools]>=0.74.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 9db16e2a2..0e81b72b9 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.0,<1.0.0",
+    "crewai[tools]>=0.74.1,<1.0.0",
     "asyncio"
 ]
 
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 3eb9b73d1..d8c2c64b3 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.74.0,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.74.1,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index dabc8d281..a672ba2b7 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.0,<1.0.0"
+    "crewai[tools]>=0.74.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 0fef250f5..21e520146 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.0"
+    "crewai[tools]>=0.74.1"
 ]
 
diff --git a/uv.lock b/uv.lock
index b0416fa72..1d2f9cb39 100644
--- a/uv.lock
+++ b/uv.lock
@@ -627,7 +627,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.74.0"
+version = "0.74.1"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -687,8 +687,8 @@ requires-dist = [
     { name = "auth0-python", specifier = ">=4.7.1" },
     { name = "chromadb", specifier = ">=0.4.24" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", specifier = ">=0.13.1" },
-    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.12.1" },
+    { name = "crewai-tools", specifier = ">=0.13.2" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.13.2" },
     { name = "instructor", specifier = ">=1.3.3" },
     { name = "json-repair", specifier = ">=0.25.2" },
     { name = "jsonref", specifier = ">=1.1.0" },
@@ -709,7 +709,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
     { name = "cairosvg", specifier = ">=2.7.1" },
-    { name = "crewai-tools", specifier = ">=0.12.1" },
+    { name = "crewai-tools", specifier = ">=0.13.2" },
     { name = "mkdocs", specifier = ">=1.4.3" },
     { name = "mkdocs-material", specifier = ">=9.5.7" },
     { name = "mkdocs-material-extensions", specifier = ">=1.3.1" },
@@ -728,7 +728,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.13.1"
+version = "0.13.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "beautifulsoup4" },
@@ -746,9 +746,9 @@ dependencies = [
     { name = "requests" },
     { name = "selenium" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d5/81/b8a0bb984aea2af49b0072e074c87c75a6c4581902b81f3a3d46f95f01c7/crewai_tools-0.13.1.tar.gz", hash = "sha256:363c7ec717f4c6f9b61cec9314a5ec2fbd026d75e8e6278f49f715ed5915cd4d", size = 816254 }
+sdist = { url = "https://files.pythonhosted.org/packages/96/02/136f42ed8a7bd706a85663714c615bdcb684e43e95e4719c892aa0ce3d53/crewai_tools-0.13.2.tar.gz", hash = "sha256:c6782f2e868c0e96b25891f1b40fb8c90c01e920bab2fd1388f89ef1d7a4b99b", size = 816250 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/09/8a/04c885da3e01d1f11478dd866d3506906bfb60d7587627dd4b132ff10f64/crewai_tools-0.13.1-py3-none-any.whl", hash = "sha256:62067e2502bf66c0ae2e3a833c60b900bd1f793a9a80895a1f10a9cfa1b5dc3c", size = 463444 },
+    { url = "https://files.pythonhosted.org/packages/28/30/df215173b6193b2cfb1902a339443be73056eae89579805b853c6f359761/crewai_tools-0.13.2-py3-none-any.whl", hash = "sha256:8c7583c9559fb625f594349c6553a5251ebd7b21918735ad6fbe8bab7ec3db50", size = 463444 },
 ]
 
 [[package]]

From 40f81aecf5a84dbb5361dfa86044d72990390084 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Fri, 18 Oct 2024 17:57:37 -0300
Subject: [PATCH 004/126] new verison

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 uv.lock                                                 | 2 +-
 8 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 436a01170..772d41b36 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.74.1"
+version = "0.74.2"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 41da7aa21..a41e3827f 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.74.1"
+__version__ = "0.74.2"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 35931e8e0..36ba1548c 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.1,<1.0.0"
+    "crewai[tools]>=0.74.2,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 0e81b72b9..490d66346 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.1,<1.0.0",
+    "crewai[tools]>=0.74.2,<1.0.0",
     "asyncio"
 ]
 
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index d8c2c64b3..517c2a4d1 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.74.1,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.74.2,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index a672ba2b7..b349e4dda 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.1,<1.0.0"
+    "crewai[tools]>=0.74.2,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 21e520146..bd1df942f 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.1"
+    "crewai[tools]>=0.74.2"
 ]
 
diff --git a/uv.lock b/uv.lock
index 1d2f9cb39..729338bcd 100644
--- a/uv.lock
+++ b/uv.lock
@@ -627,7 +627,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.74.1"
+version = "0.74.2"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From b98256e43435817395a288b1752cfc4a3de34640 Mon Sep 17 00:00:00 2001
From: Vini Brasil <vini@hey.com>
Date: Mon, 21 Oct 2024 09:24:03 -0300
Subject: [PATCH 005/126] Adapt `crewai tool install <tool>` to uv (#1481)

This commit updates the tool install comamnd to uv's new custom index
feature.

Related: https://github.com/astral-sh/uv/pull/7746/
---
 pyproject.toml               |  2 +-
 src/crewai/cli/tools/main.py |  8 ++++----
 tests/cli/tools/test_main.py |  4 ++--
 uv.lock                      | 40 ++++++++++++++++++------------------
 4 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 772d41b36..d7920c7b0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,7 +25,7 @@ dependencies = [
     "auth0-python>=4.7.1",
     "litellm>=1.44.22",
     "pyvis>=0.3.2",
-    "uv>=0.4.18",
+    "uv>=0.4.25",
     "tomli-w>=1.1.0",
     "chromadb>=0.4.24",
 ]
diff --git a/src/crewai/cli/tools/main.py b/src/crewai/cli/tools/main.py
index b6237c61d..c875229c3 100644
--- a/src/crewai/cli/tools/main.py
+++ b/src/crewai/cli/tools/main.py
@@ -28,8 +28,6 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
     A class to handle tool repository related operations for CrewAI projects.
     """
 
-    BASE_URL = "https://app.crewai.com/pypi/"
-
     def __init__(self):
         BaseCommand.__init__(self)
         PlusAPIMixin.__init__(self, telemetry=self._telemetry)
@@ -178,12 +176,14 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
     def _add_package(self, tool_details):
         tool_handle = tool_details["handle"]
         repository_handle = tool_details["repository"]["handle"]
+        repository_url = tool_details["repository"]["url"]
+        index = f"{repository_handle}={repository_url}"
 
         add_package_command = [
             "uv",
             "add",
-            "--extra-index-url",
-            self.BASE_URL + repository_handle,
+            "--index",
+            index,
             tool_handle,
         ]
         add_package_result = subprocess.run(
diff --git a/tests/cli/tools/test_main.py b/tests/cli/tools/test_main.py
index fda833a85..e4fc19be3 100644
--- a/tests/cli/tools/test_main.py
+++ b/tests/cli/tools/test_main.py
@@ -75,8 +75,8 @@ def test_install_success(mock_get, mock_subprocess_run):
         [
             "uv",
             "add",
-            "--extra-index-url",
-            "https://app.crewai.com/pypi/sample-repo",
+            "--index",
+            "sample-repo=https://example.com/repo",
             "sample-tool",
         ],
         capture_output=False,
diff --git a/uv.lock b/uv.lock
index 729338bcd..5d4d5b0b7 100644
--- a/uv.lock
+++ b/uv.lock
@@ -703,7 +703,7 @@ requires-dist = [
     { name = "pyvis", specifier = ">=0.3.2" },
     { name = "regex", specifier = ">=2024.9.11" },
     { name = "tomli-w", specifier = ">=1.1.0" },
-    { name = "uv", specifier = ">=0.4.18" },
+    { name = "uv", specifier = ">=0.4.25" },
 ]
 
 [package.metadata.requires-dev]
@@ -4542,27 +4542,27 @@ socks = [
 
 [[package]]
 name = "uv"
-version = "0.4.18"
+version = "0.4.25"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/7d/60/bf5ad6895740e7269ee2f5cf7515cf2756cc8eb06c07c9783abcf1d7860f/uv-0.4.18.tar.gz", hash = "sha256:954964eff8c7e2bc63dd4beeb8d45bcaddb5149a7ef29a36abd77ec76c8b837e", size = 2008833 }
+sdist = { url = "https://files.pythonhosted.org/packages/d0/bc/1a013408b7f9f437385705652f404b6b15127ecf108327d13be493bdfb81/uv-0.4.25.tar.gz", hash = "sha256:d39077cdfe3246885fcdf32e7066ae731a166101d063629f9cea08738f79e6a3", size = 2064863 }
 wheels = [
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 ]
 
 [[package]]

From 71a217b210019cacaeda17b444baa9346c77ce2a Mon Sep 17 00:00:00 2001
From: Sam <sammcj@users.noreply.github.com>
Date: Tue, 22 Oct 2024 02:49:33 +1100
Subject: [PATCH 006/126] fix(docs): typo (#1470)

---
 src/crewai/cli/templates/crew/main.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/crewai/cli/templates/crew/main.py b/src/crewai/cli/templates/crew/main.py
index a20125637..88edfcbff 100644
--- a/src/crewai/cli/templates/crew/main.py
+++ b/src/crewai/cli/templates/crew/main.py
@@ -3,7 +3,7 @@ import sys
 from {{folder_name}}.crew import {{crew_name}}Crew
 
 # This main file is intended to be a way for you to run your
-# crew locally, so refrain from adding necessary logic into this file.
+# crew locally, so refrain from adding unnecessary logic into this file.
 # Replace with inputs you want to test with, it will automatically
 # interpolate any tasks and agents information
 

From 6bcb3d108050b9cf8a710886a336a81d4dedb6c3 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 21 Oct 2024 15:26:30 -0400
Subject: [PATCH 007/126] drop unneccesary tests (#1484)

* drop uneccesary tests

* fix linting
---
 tests/tools/test_tool_usage.py | 28 ++--------------------------
 1 file changed, 2 insertions(+), 26 deletions(-)

diff --git a/tests/tools/test_tool_usage.py b/tests/tools/test_tool_usage.py
index d0a6ec0b0..8af9b8abb 100644
--- a/tests/tools/test_tool_usage.py
+++ b/tests/tools/test_tool_usage.py
@@ -1,12 +1,12 @@
 import json
 import random
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock
 
 import pytest
 from crewai_tools import BaseTool
 from pydantic import BaseModel, Field
 
-from crewai import Agent, Crew, Task
+from crewai import Agent, Task
 from crewai.tools.tool_usage import ToolUsage
 
 
@@ -44,36 +44,12 @@ example_task = Task(
 )
 
 
-def test_random_number_tool_usage():
-    crew = Crew(
-        agents=[example_agent],
-        tasks=[example_task],
-    )
-
-    with patch.object(random, "randint", return_value=42):
-        result = crew.kickoff()
-
-    assert "42" in result.raw
-
-
 def test_random_number_tool_range():
     tool = RandomNumberTool()
     result = tool._run(1, 10)
     assert 1 <= result <= 10
 
 
-def test_random_number_tool_with_crew():
-    crew = Crew(
-        agents=[example_agent],
-        tasks=[example_task],
-    )
-
-    result = crew.kickoff()
-
-    # Check if the result contains a number between 1 and 100
-    assert any(str(num) in result.raw for num in range(1, 101))
-
-
 def test_random_number_tool_invalid_range():
     tool = RandomNumberTool()
     with pytest.raises(ValueError):

From 093259389e2a3afaa45365ec275fc941c68dc028 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 21 Oct 2024 19:32:55 -0400
Subject: [PATCH 008/126] simplify flow (#1482)

* simplify flow

* propogate changes

* Update docs and scripts

* Template fix

* make flow kickoff sync

* Clean up docs
---
 docs/concepts/flows.mdx                       | 200 +++++++-----------
 src/crewai/cli/cli.py                         |   8 +-
 .../cli/{run_flow.py => kickoff_flow.py}      |   6 +-
 src/crewai/cli/templates/flow/main.py         |  46 ++--
 src/crewai/cli/templates/flow/pyproject.toml  |   6 +-
 src/crewai/flow/flow.py                       |   5 +-
 6 files changed, 111 insertions(+), 160 deletions(-)
 rename src/crewai/cli/{run_flow.py => kickoff_flow.py} (78%)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index 65cbb95c2..dee6fd4fa 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -23,9 +23,9 @@ Flows allow you to create structured, event-driven workflows. They provide a sea
 Let's create a simple Flow where you will use OpenAI to generate a random city in one task and then use that city to generate a fun fact in another task.
 
 ```python Code
-import asyncio
 
 from crewai.flow.flow import Flow, listen, start
+from dotenv import load_dotenv
 from litellm import completion
 
 
@@ -67,19 +67,19 @@ class ExampleFlow(Flow):
         return fun_fact
 
 
-async def main():
-    flow = ExampleFlow()
-    result = await flow.kickoff()
 
-    print(f"Generated fun fact: {result}")
+flow = ExampleFlow()
+result = flow.kickoff()
 
-asyncio.run(main())
+print(f"Generated fun fact: {result}")
 ```
 
 In the above example, we have created a simple Flow that generates a random city using OpenAI and then generates a fun fact about that city. The Flow consists of two tasks: `generate_city` and `generate_fun_fact`. The `generate_city` task is the starting point of the Flow, and the `generate_fun_fact` task listens for the output of the `generate_city` task.
 
 When you run the Flow, it will generate a random city and then generate a fun fact about that city. The output will be printed to the console.
 
+**Note:** Ensure you have set up your `.env` file to store your `OPENAI_API_KEY`. This key is necessary for authenticating requests to the OpenAI API.
+
 ### @start()
 
 The `@start()` decorator is used to mark a method as the starting point of a Flow. When a Flow is started, all the methods decorated with `@start()` are executed in parallel. You can have multiple start methods in a Flow, and they will all be executed when the Flow is started.
@@ -119,7 +119,6 @@ Here's how you can access the final output:
 
 <CodeGroup>
 ```python Code
-import asyncio
 from crewai.flow.flow import Flow, listen, start
 
 class OutputExampleFlow(Flow):
@@ -131,26 +130,24 @@ class OutputExampleFlow(Flow):
     def second_method(self, first_output):
         return f"Second method received: {first_output}"
 
-async def main():
-    flow = OutputExampleFlow()
-    final_output = await flow.kickoff()
-    print("---- Final Output ----")
-    print(final_output)
 
-asyncio.run(main())
-```
+flow = OutputExampleFlow()
+final_output = flow.kickoff()
+
+print("---- Final Output ----")
+print(final_output)
+````
 
 ``` text Output
 ---- Final Output ----
 Second method received: Output from first_method
-```
+````
 
 </CodeGroup>
 
-In this example, the `second_method` is the last method to complete, so its output will be the final output of the Flow. 
+In this example, the `second_method` is the last method to complete, so its output will be the final output of the Flow.
 The `kickoff()` method will return the final output, which is then printed to the console.
 
-
 #### Accessing and Updating State
 
 In addition to retrieving the final output, you can also access and update the state within your Flow. The state can be used to store and share data between different methods in the Flow. After the Flow has run, you can access the state to retrieve any information that was added or updated during the execution.
@@ -160,7 +157,6 @@ Here's an example of how to update and access the state:
 <CodeGroup>
 
 ```python Code
-import asyncio
 from crewai.flow.flow import Flow, listen, start
 from pydantic import BaseModel
 
@@ -181,42 +177,38 @@ class StateExampleFlow(Flow[ExampleState]):
         self.state.counter += 1
         return self.state.message
 
-async def main():
-    flow = StateExampleFlow()
-    final_output = await flow.kickoff()
-    print(f"Final Output: {final_output}")
-    print("Final State:")
-    print(flow.state)
-
-asyncio.run(main())
+flow = StateExampleFlow()
+final_output = flow.kickoff()
+print(f"Final Output: {final_output}")
+print("Final State:")
+print(flow.state)
 ```
 
-``` text Output
+```text Output
 Final Output: Hello from first_method - updated by second_method
 Final State:
 counter=2 message='Hello from first_method - updated by second_method'
 ```
+
 </CodeGroup>
 
-In this example, the state is updated by both `first_method` and `second_method`. 
+In this example, the state is updated by both `first_method` and `second_method`.
 After the Flow has run, you can access the final state to see the updates made by these methods.
 
-By ensuring that the final method's output is returned and providing access to the state, CrewAI Flows make it easy to integrate the results of your AI workflows into larger applications or systems, 
+By ensuring that the final method's output is returned and providing access to the state, CrewAI Flows make it easy to integrate the results of your AI workflows into larger applications or systems,
 while also maintaining and accessing the state throughout the Flow's execution.
 
 ## Flow State Management
 
-Managing state effectively is crucial for building reliable and maintainable AI workflows. CrewAI Flows provides robust mechanisms for both unstructured and structured state management, 
+Managing state effectively is crucial for building reliable and maintainable AI workflows. CrewAI Flows provides robust mechanisms for both unstructured and structured state management,
 allowing developers to choose the approach that best fits their application's needs.
 
 ### Unstructured State Management
 
-In unstructured state management, all state is stored in the `state` attribute of the `Flow` class. 
+In unstructured state management, all state is stored in the `state` attribute of the `Flow` class.
 This approach offers flexibility, enabling developers to add or modify state attributes on the fly without defining a strict schema.
 
 ```python Code
-import asyncio
-
 from crewai.flow.flow import Flow, listen, start
 
 class UntructuredExampleFlow(Flow):
@@ -239,12 +231,8 @@ class UntructuredExampleFlow(Flow):
         print(f"State after third_method: {self.state}")
 
 
-async def main():
-    flow = UntructuredExampleFlow()
-    await flow.kickoff()
-
-
-asyncio.run(main())
+flow = UntructuredExampleFlow()
+flow.kickoff()
 ```
 
 **Key Points:**
@@ -254,12 +242,10 @@ asyncio.run(main())
 
 ### Structured State Management
 
-Structured state management leverages predefined schemas to ensure consistency and type safety across the workflow. 
+Structured state management leverages predefined schemas to ensure consistency and type safety across the workflow.
 By using models like Pydantic's `BaseModel`, developers can define the exact shape of the state, enabling better validation and auto-completion in development environments.
 
 ```python Code
-import asyncio
-
 from crewai.flow.flow import Flow, listen, start
 from pydantic import BaseModel
 
@@ -288,12 +274,8 @@ class StructuredExampleFlow(Flow[ExampleState]):
         print(f"State after third_method: {self.state}")
 
 
-async def main():
-    flow = StructuredExampleFlow()
-    await flow.kickoff()
-
-
-asyncio.run(main())
+flow = StructuredExampleFlow()
+flow.kickoff()
 ```
 
 **Key Points:**
@@ -326,7 +308,6 @@ The `or_` function in Flows allows you to listen to multiple methods and trigger
 <CodeGroup>
 
 ```python Code
-import asyncio
 from crewai.flow.flow import Flow, listen, or_, start
 
 class OrExampleFlow(Flow):
@@ -344,22 +325,19 @@ class OrExampleFlow(Flow):
         print(f"Logger: {result}")
 
 
-async def main():
-    flow = OrExampleFlow()
-    await flow.kickoff()
 
-
-asyncio.run(main())
+flow = OrExampleFlow()
+flow.kickoff()
 ```
 
-``` text Output
+```text Output
 Logger: Hello from the start method
 Logger: Hello from the second method
 ```
 
 </CodeGroup>
 
-When you run this Flow, the `logger` method will be triggered by the output of either the `start_method` or the `second_method`. 
+When you run this Flow, the `logger` method will be triggered by the output of either the `start_method` or the `second_method`.
 The `or_` function is used to listen to multiple methods and trigger the listener method when any of the specified methods emit an output.
 
 ### Conditional Logic: `and`
@@ -369,7 +347,6 @@ The `and_` function in Flows allows you to listen to multiple methods and trigge
 <CodeGroup>
 
 ```python Code
-import asyncio
 from crewai.flow.flow import Flow, and_, listen, start
 
 class AndExampleFlow(Flow):
@@ -387,34 +364,28 @@ class AndExampleFlow(Flow):
         print("---- Logger ----")
         print(self.state)
 
-
-async def main():
-    flow = AndExampleFlow()
-    await flow.kickoff()
-
-
-asyncio.run(main())
+flow = AndExampleFlow()
+flow.kickoff()
 ```
 
-``` text Output
+```text Output
 ---- Logger ----
 {'greeting': 'Hello from the start method', 'joke': 'What do computers eat? Microchips.'}
 ```
 
 </CodeGroup>
 
-When you run this Flow, the `logger` method will be triggered only when both the `start_method` and the `second_method` emit an output. 
+When you run this Flow, the `logger` method will be triggered only when both the `start_method` and the `second_method` emit an output.
 The `and_` function is used to listen to multiple methods and trigger the listener method only when all the specified methods emit an output.
 
 ### Router
 
-The `@router()` decorator in Flows allows you to define conditional routing logic based on the output of a method. 
+The `@router()` decorator in Flows allows you to define conditional routing logic based on the output of a method.
 You can specify different routes based on the output of the method, allowing you to control the flow of execution dynamically.
 
 <CodeGroup>
 
 ```python Code
-import asyncio
 import random
 from crewai.flow.flow import Flow, listen, router, start
 from pydantic import BaseModel
@@ -446,15 +417,11 @@ class RouterFlow(Flow[ExampleState]):
         print("Fourth method running")
 
 
-async def main():
-    flow = RouterFlow()
-    await flow.kickoff()
-
-
-asyncio.run(main())
+flow = RouterFlow()
+flow.kickoff()
 ```
 
-``` text Output
+```text Output
 Starting the structured flow
 Third method running
 Fourth method running
@@ -462,16 +429,16 @@ Fourth method running
 
 </CodeGroup>
 
-In the above example, the `start_method` generates a random boolean value and sets it in the state. 
-The `second_method` uses the `@router()` decorator to define conditional routing logic based on the value of the boolean. 
-If the boolean is `True`, the method returns `"success"`, and if it is `False`, the method returns `"failed"`. 
+In the above example, the `start_method` generates a random boolean value and sets it in the state.
+The `second_method` uses the `@router()` decorator to define conditional routing logic based on the value of the boolean.
+If the boolean is `True`, the method returns `"success"`, and if it is `False`, the method returns `"failed"`.
 The `third_method` and `fourth_method` listen to the output of the `second_method` and execute based on the returned value.
 
 When you run this Flow, the output will change based on the random boolean value generated by the `start_method`.
 
 ## Adding Crews to Flows
 
-Creating a flow with multiple crews in CrewAI is straightforward. 
+Creating a flow with multiple crews in CrewAI is straightforward.
 
 You can generate a new CrewAI project that includes all the scaffolding needed to create a flow with multiple crews by running the following command:
 
@@ -485,22 +452,21 @@ This command will generate a new CrewAI project with the necessary folder struct
 
 After running the `crewai create flow name_of_flow` command, you will see a folder structure similar to the following:
 
-| Directory/File                   | Description                                                       |
-|:---------------------------------|:------------------------------------------------------------------|
-| `name_of_flow/`                  | Root directory for the flow.                                      |
-| ├── `crews/`                     | Contains directories for specific crews.                          |
-| │   └── `poem_crew/`             | Directory for the "poem_crew" with its configurations and scripts.|
-| │       ├── `config/`            | Configuration files directory for the "poem_crew".                |
-| │       │   ├── `agents.yaml`    | YAML file defining the agents for "poem_crew".                    |
-| │       │   └── `tasks.yaml`     | YAML file defining the tasks for "poem_crew".                     |
-| │       ├── `poem_crew.py`       | Script for "poem_crew" functionality.                             |
-| ├── `tools/`                     | Directory for additional tools used in the flow.                  |
-| │   └── `custom_tool.py`         | Custom tool implementation.                                       |
-| ├── `main.py`                    | Main script for running the flow.                                 |
-| ├── `README.md`                  | Project description and instructions.                             |
-| ├── `pyproject.toml`             | Configuration file for project dependencies and settings.         |
-| └── `.gitignore`                 | Specifies files and directories to ignore in version control.     |
-
+| Directory/File         | Description                                                        |
+| :--------------------- | :----------------------------------------------------------------- |
+| `name_of_flow/`        | Root directory for the flow.                                       |
+| ├── `crews/`           | Contains directories for specific crews.                           |
+| │ └── `poem_crew/`     | Directory for the "poem_crew" with its configurations and scripts. |
+| │ ├── `config/`        | Configuration files directory for the "poem_crew".                 |
+| │ │ ├── `agents.yaml`  | YAML file defining the agents for "poem_crew".                     |
+| │ │ └── `tasks.yaml`   | YAML file defining the tasks for "poem_crew".                      |
+| │ ├── `poem_crew.py`   | Script for "poem_crew" functionality.                              |
+| ├── `tools/`           | Directory for additional tools used in the flow.                   |
+| │ └── `custom_tool.py` | Custom tool implementation.                                        |
+| ├── `main.py`          | Main script for running the flow.                                  |
+| ├── `README.md`        | Project description and instructions.                              |
+| ├── `pyproject.toml`   | Configuration file for project dependencies and settings.          |
+| └── `.gitignore`       | Specifies files and directories to ignore in version control.      |
 
 ### Building Your Crews
 
@@ -520,7 +486,6 @@ Here's an example of how you can connect the `poem_crew` in the `main.py` file:
 
 ```python Code
 #!/usr/bin/env python
-import asyncio
 from random import randint
 
 from pydantic import BaseModel
@@ -536,14 +501,12 @@ class PoemFlow(Flow[PoemState]):
     @start()
     def generate_sentence_count(self):
         print("Generating sentence count")
-        # Generate a number between 1 and 5
         self.state.sentence_count = randint(1, 5)
 
     @listen(generate_sentence_count)
     def generate_poem(self):
         print("Generating poem")
-        poem_crew = PoemCrew().crew()
-        result = poem_crew.kickoff(inputs={"sentence_count": self.state.sentence_count})
+        result = PoemCrew().crew().kickoff(inputs={"sentence_count": self.state.sentence_count})
 
         print("Poem generated", result.raw)
         self.state.poem = result.raw
@@ -554,18 +517,17 @@ class PoemFlow(Flow[PoemState]):
         with open("poem.txt", "w") as f:
             f.write(self.state.poem)
 
-async def run():
-    """
-    Run the flow.
-    """
+def kickoff():
     poem_flow = PoemFlow()
-    await poem_flow.kickoff()
+    poem_flow.kickoff()
 
-def main():
-    asyncio.run(run())
+
+def plot():
+    poem_flow = PoemFlow()
+    poem_flow.plot()
 
 if __name__ == "__main__":
-    main()
+    kickoff()
 ```
 
 In this example, the `PoemFlow` class defines a flow that generates a sentence count, uses the `PoemCrew` to generate a poem, and then saves the poem to a file. The flow is kicked off by calling the `kickoff()` method.
@@ -587,13 +549,13 @@ source .venv/bin/activate
 After activating the virtual environment, you can run the flow by executing one of the following commands:
 
 ```bash
-crewai flow run
+crewai flow kickoff
 ```
 
 or
 
 ```bash
-uv run run_flow
+uv run kickoff
 ```
 
 The flow will execute, and you should see the output in the console.
@@ -657,13 +619,13 @@ By exploring these examples, you can gain insights into how to leverage CrewAI F
 
 Also, check out our YouTube video on how to use flows in CrewAI below!
 
-<iframe 
-    width="560" 
-    height="315" 
-    src="https://www.youtube.com/embed/MTb5my6VOT8" 
-    title="YouTube video player" 
-    frameborder="0" 
-    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" 
-    referrerpolicy="strict-origin-when-cross-origin" 
-    allowfullscreen
-></iframe>    
\ No newline at end of file
+<iframe
+  width="560"
+  height="315"
+  src="https://www.youtube.com/embed/MTb5my6VOT8"
+  title="YouTube video player"
+  frameborder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
+  referrerpolicy="strict-origin-when-cross-origin"
+  allowfullscreen
+></iframe>
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 55c8e5b43..6c5263345 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -14,11 +14,11 @@ from .authentication.main import AuthenticationCommand
 from .deploy.main import DeployCommand
 from .evaluate_crew import evaluate_crew
 from .install_crew import install_crew
+from .kickoff_flow import kickoff_flow
 from .plot_flow import plot_flow
 from .replay_from_task import replay_task_command
 from .reset_memories_command import reset_memories_command
 from .run_crew import run_crew
-from .run_flow import run_flow
 from .tools.main import ToolCommand
 from .train_crew import train_crew
 from .update_crew import update_crew
@@ -304,11 +304,11 @@ def flow():
     pass
 
 
-@flow.command(name="run")
+@flow.command(name="kickoff")
 def flow_run():
-    """Run the Flow."""
+    """Kickoff the Flow."""
     click.echo("Running the Flow")
-    run_flow()
+    kickoff_flow()
 
 
 @flow.command(name="plot")
diff --git a/src/crewai/cli/run_flow.py b/src/crewai/cli/kickoff_flow.py
similarity index 78%
rename from src/crewai/cli/run_flow.py
rename to src/crewai/cli/kickoff_flow.py
index 2900e59b3..2123a6c15 100644
--- a/src/crewai/cli/run_flow.py
+++ b/src/crewai/cli/kickoff_flow.py
@@ -3,11 +3,11 @@ import subprocess
 import click
 
 
-def run_flow() -> None:
+def kickoff_flow() -> None:
     """
-    Run the flow by running a command in the UV environment.
+    Kickoff the flow by running a command in the UV environment.
     """
-    command = ["uv", "run", "run_flow"]
+    command = ["uv", "run", "kickoff"]
 
     try:
         result = subprocess.run(command, capture_output=False, text=True, check=True)
diff --git a/src/crewai/cli/templates/flow/main.py b/src/crewai/cli/templates/flow/main.py
index 38d2d8736..73684051a 100644
--- a/src/crewai/cli/templates/flow/main.py
+++ b/src/crewai/cli/templates/flow/main.py
@@ -1,65 +1,53 @@
 #!/usr/bin/env python
-import asyncio
 from random import randint
 
 from pydantic import BaseModel
+
 from crewai.flow.flow import Flow, listen, start
+
 from .crews.poem_crew.poem_crew import PoemCrew
 
+
 class PoemState(BaseModel):
     sentence_count: int = 1
     poem: str = ""
 
+
 class PoemFlow(Flow[PoemState]):
 
     @start()
     def generate_sentence_count(self):
         print("Generating sentence count")
-        # Generate a number between 1 and 5
-        self.state.sentence_count = randint(1, 5)  
+        self.state.sentence_count = randint(1, 5)
 
     @listen(generate_sentence_count)
     def generate_poem(self):
         print("Generating poem")
-        print(f"State before poem: {self.state}")
-        result = PoemCrew().crew().kickoff(inputs={"sentence_count": self.state.sentence_count})
-        
+        result = (
+            PoemCrew()
+            .crew()
+            .kickoff(inputs={"sentence_count": self.state.sentence_count})
+        )
+
         print("Poem generated", result.raw)
         self.state.poem = result.raw
-        
-        print(f"State after generate_poem: {self.state}")
 
     @listen(generate_poem)
     def save_poem(self):
         print("Saving poem")
-        print(f"State before save_poem: {self.state}")
         with open("poem.txt", "w") as f:
             f.write(self.state.poem)
-        print(f"State after save_poem: {self.state}")
 
-async def run_flow():
-    """
-    Run the flow.
-    """
+
+def kickoff():
     poem_flow = PoemFlow()
-    await poem_flow.kickoff()
+    poem_flow.kickoff()
 
-async def plot_flow():
-    """
-    Plot the flow.
-    """
+
+def plot():
     poem_flow = PoemFlow()
     poem_flow.plot()
 
 
-def main():
-    asyncio.run(run_flow())
-
-
-def plot():
-    asyncio.run(plot_flow())
-
-
-
 if __name__ == "__main__":
-    main()
+    kickoff()
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 490d66346..f93390741 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -6,13 +6,11 @@ authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
     "crewai[tools]>=0.74.2,<1.0.0",
-    "asyncio"
 ]
 
 [project.scripts]
-{{folder_name}} = "{{folder_name}}.main:main"
-run_flow = "{{folder_name}}.main:main"
-plot_flow = "{{folder_name}}.main:plot"
+kickoff = "{{folder_name}}.main:kickoff"
+plot = "{{folder_name}}.main:plot"
 
 [build-system]
 requires = ["hatchling"]
diff --git a/src/crewai/flow/flow.py b/src/crewai/flow/flow.py
index 66fa49659..de9b2eeb2 100644
--- a/src/crewai/flow/flow.py
+++ b/src/crewai/flow/flow.py
@@ -190,7 +190,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
         """Returns the list of all outputs from executed methods."""
         return self._method_outputs
 
-    async def kickoff(self) -> Any:
+    def kickoff(self) -> Any:
+        return asyncio.run(self.kickoff_async())
+
+    async def kickoff_async(self) -> Any:
         if not self._start_methods:
             raise ValueError("No start method defined")
 

From 873191533097bbe0718e1b4b353ec65bb8b7bd68 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Tue, 22 Oct 2024 13:41:29 -0400
Subject: [PATCH 009/126] Add Cerebras LLM example configuration to LLM docs
 (#1488)

---
 docs/concepts/llms.mdx | 26 ++++++++++++++++++++++++--
 1 file changed, 24 insertions(+), 2 deletions(-)

diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 728c88c36..90e86adaf 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -62,6 +62,8 @@ os.environ["OPENAI_API_BASE"] = "https://api.your-provider.com/v1"
 2. Using LLM class attributes:
 
 ```python Code
+from crewai import LLM
+
 llm = LLM(
     model="custom-model-name",
     api_key="your-api-key",
@@ -95,9 +97,11 @@ When configuring an LLM for your agent, you have access to a wide range of param
 | **api_key**          | `str`             | Your API key for authentication.                                                                 |
 
 
-Example:
+## OpenAI Example Configuration
 
 ```python Code
+from crewai import LLM
+
 llm = LLM(
     model="gpt-4",
     temperature=0.8,
@@ -112,15 +116,31 @@ llm = LLM(
 )
 agent = Agent(llm=llm, ...)
 ```
+
+## Cerebras Example Configuration
+
+```python Code
+from crewai import LLM
+
+llm = LLM(
+    model="cerebras/llama-3.1-70b",
+    base_url="https://api.cerebras.ai/v1",
+    api_key="your-api-key-here"
+)
+agent = Agent(llm=llm, ...) 
+```
+
 ## Using Ollama (Local LLMs)
 
-crewAI supports using Ollama for running open-source models locally:
+CrewAI supports using Ollama for running open-source models locally:
 
 1. Install Ollama: [ollama.ai](https://ollama.ai/)
 2. Run a model: `ollama run llama2`
 3. Configure agent:
 
 ```python Code
+from crewai import LLM
+
 agent = Agent(
     llm=LLM(model="ollama/llama3.1", base_url="http://localhost:11434"),
     ...
@@ -132,6 +152,8 @@ agent = Agent(
 You can change the base API URL for any LLM provider by setting the `base_url` parameter:
 
 ```python Code
+from crewai import LLM
+
 llm = LLM(
     model="custom-model-name",
     base_url="https://api.your-provider.com/v1",

From 4687779702e93f5b4163ea858557e6a4ae064b66 Mon Sep 17 00:00:00 2001
From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Date: Tue, 22 Oct 2024 12:30:30 -0700
Subject: [PATCH 010/126] ensure original embedding config works (#1476)

* ensure original embedding config works

* some fixes

* raise error on unsupported provider

* WIP: brandons notes

* fixes

* rm prints

* fixed docs

* fixed run types

* updates to add more docs and correct imports with huggingface embedding server enabled

---------

Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
---
 docs/concepts/memory.mdx                  | 86 +++++++++++++++++---
 src/crewai/memory/entity/entity_memory.py |  2 +-
 src/crewai/memory/storage/rag_storage.py  | 96 +++++++++++++++++++++--
 3 files changed, 166 insertions(+), 18 deletions(-)

diff --git a/docs/concepts/memory.mdx b/docs/concepts/memory.mdx
index b07096442..de1fb3510 100644
--- a/docs/concepts/memory.mdx
+++ b/docs/concepts/memory.mdx
@@ -105,9 +105,48 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=embedding_functions.OpenAIEmbeddingFunction(
-            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
-        )
+    embedder={
+        "provider": "openai",
+        "config": {
+            "model": 'text-embedding-3-small'
+        }
+    }
+)
+```
+Alternatively, you can directly pass the OpenAIEmbeddingFunction to the embedder parameter.
+
+Example:
+```python Code
+from crewai import Crew, Agent, Task, Process
+from chromadb.utils.embedding_functions.openai_embedding_function import OpenAIEmbeddingFunction
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    verbose=True,
+    embedder=OpenAIEmbeddingFunction(api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"),
+)
+```
+
+### Using Ollama embeddings
+
+```python Code
+from crewai import Crew, Agent, Task, Process
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    verbose=True,
+    embedder={
+        "provider": "ollama",
+        "config": {
+            "model": "mxbai-embed-large"
+        }
+    }
 )
 ```
 
@@ -122,10 +161,13 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=embedding_functions.OpenAIEmbeddingFunction(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model_name="text-embedding-ada-002"
-    )
+    embedder={
+        "provider": "google",
+        "config": {
+            "api_key": "<YOUR_API_KEY>",
+            "model_name": "<model_name>"
+        }
+    }
 )
 ```
 
@@ -181,10 +223,32 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=embedding_functions.CohereEmbeddingFunction(
-        api_key=YOUR_API_KEY,
-        model_name="<model_name>"
-    )
+    embedder={
+        "provider": "cohere",
+        "config": {
+            "api_key": "YOUR_API_KEY",
+            "model_name": "<model_name>"
+        }
+    }
+)
+```
+### Using HuggingFace embeddings
+
+```python Code
+from crewai import Crew, Agent, Task, Process
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    verbose=True,
+    embedder={
+        "provider": "huggingface",
+        "config": {
+            "api_url": "<api_url>",
+        }
+    }
 )
 ```
 
diff --git a/src/crewai/memory/entity/entity_memory.py b/src/crewai/memory/entity/entity_memory.py
index d4f8d9aae..4de0594c7 100644
--- a/src/crewai/memory/entity/entity_memory.py
+++ b/src/crewai/memory/entity/entity_memory.py
@@ -16,7 +16,7 @@ class EntityMemory(Memory):
             if storage
             else RAGStorage(
                 type="entities",
-                allow_reset=False,
+                allow_reset=True,
                 embedder_config=embedder_config,
                 crew=crew,
             )
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index 8d45d9f5a..db98c0036 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -8,6 +8,9 @@ from typing import Any, Dict, List, Optional
 from crewai.memory.storage.base_rag_storage import BaseRAGStorage
 from crewai.utilities.paths import db_storage_path
 from chromadb.api import ClientAPI
+from chromadb.api.types import validate_embedding_function
+from chromadb import Documents, EmbeddingFunction, Embeddings
+from typing import cast
 
 
 @contextlib.contextmanager
@@ -41,16 +44,93 @@ class RAGStorage(BaseRAGStorage):
         self.agents = agents
 
         self.type = type
-        self.embedder_config = embedder_config or self._create_embedding_function()
+
         self.allow_reset = allow_reset
         self._initialize_app()
 
+    def _set_embedder_config(self):
+        import chromadb.utils.embedding_functions as embedding_functions
+
+        if self.embedder_config is None:
+            self.embedder_config = self._create_default_embedding_function()
+
+        if isinstance(self.embedder_config, dict):
+            provider = self.embedder_config.get("provider")
+            config = self.embedder_config.get("config", {})
+            model_name = config.get("model")
+            if provider == "openai":
+                self.embedder_config = embedding_functions.OpenAIEmbeddingFunction(
+                    api_key=config.get("api_key") or os.getenv("OPENAI_API_KEY"),
+                    model_name=model_name,
+                )
+            elif provider == "azure":
+                self.embedder_config = embedding_functions.OpenAIEmbeddingFunction(
+                    api_key=config.get("api_key"),
+                    api_base=config.get("api_base"),
+                    api_type=config.get("api_type", "azure"),
+                    api_version=config.get("api_version"),
+                    model_name=model_name,
+                )
+            elif provider == "ollama":
+                from openai import OpenAI
+
+                class OllamaEmbeddingFunction(EmbeddingFunction):
+                    def __call__(self, input: Documents) -> Embeddings:
+                        client = OpenAI(
+                            base_url="http://localhost:11434/v1",
+                            api_key=config.get("api_key", "ollama"),
+                        )
+                        try:
+                            response = client.embeddings.create(
+                                input=input, model=model_name
+                            )
+                            embeddings = [item.embedding for item in response.data]
+                            return cast(Embeddings, embeddings)
+                        except Exception as e:
+                            raise e
+
+                self.embedder_config = OllamaEmbeddingFunction()
+            elif provider == "vertexai":
+                self.embedder_config = (
+                    embedding_functions.GoogleVertexEmbeddingFunction(
+                        model_name=model_name,
+                        api_key=config.get("api_key"),
+                    )
+                )
+            elif provider == "google":
+                self.embedder_config = (
+                    embedding_functions.GoogleGenerativeAiEmbeddingFunction(
+                        model_name=model_name,
+                        api_key=config.get("api_key"),
+                    )
+                )
+            elif provider == "cohere":
+                self.embedder_config = embedding_functions.CohereEmbeddingFunction(
+                    model_name=model_name,
+                    api_key=config.get("api_key"),
+                )
+            elif provider == "huggingface":
+                self.embedder_config = embedding_functions.HuggingFaceEmbeddingServer(
+                    url=config.get("api_url"),
+                )
+            else:
+                raise Exception(
+                    f"Unsupported embedding provider: {provider}, supported providers: [openai, azure, ollama, vertexai, google, cohere, huggingface]"
+                )
+        else:
+            validate_embedding_function(self.embedder_config)  # type: ignore # used for validating embedder_config if defined a embedding function/class
+            self.embedder_config = self.embedder_config
+
     def _initialize_app(self):
         import chromadb
+        from chromadb.config import Settings
 
+        self._set_embedder_config()
         chroma_client = chromadb.PersistentClient(
-            path=f"{db_storage_path()}/{self.type}/{self.agents}"
+            path=f"{db_storage_path()}/{self.type}/{self.agents}",
+            settings=Settings(allow_reset=self.allow_reset),
         )
+
         self.app = chroma_client
 
         try:
@@ -122,11 +202,15 @@ class RAGStorage(BaseRAGStorage):
             if self.app:
                 self.app.reset()
         except Exception as e:
-            raise Exception(
-                f"An error occurred while resetting the {self.type} memory: {e}"
-            )
+            if "attempt to write a readonly database" in str(e):
+                # Ignore this specific error
+                pass
+            else:
+                raise Exception(
+                    f"An error occurred while resetting the {self.type} memory: {e}"
+                )
 
-    def _create_embedding_function(self):
+    def _create_default_embedding_function(self):
         import chromadb.utils.embedding_functions as embedding_functions
 
         return embedding_functions.OpenAIEmbeddingFunction(

From 9cd4ff05c997fc77c0418c50e6a607419cd42ac2 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 22 Oct 2024 21:31:44 -0400
Subject: [PATCH 011/126] use copy to split testing and training on crews
 (#1491)

* use copy to split testing and training on crews

* make tests handle new copy functionality on train and test

* fix last test

* fix test
---
 src/crewai/crew.py | 19 ++++++----
 tests/crew_test.py | 94 +++++++++++++++++-----------------------------
 2 files changed, 45 insertions(+), 68 deletions(-)

diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 5450e6e67..377b6fec9 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -435,15 +435,16 @@ class Crew(BaseModel):
         self, n_iterations: int, filename: str, inputs: Optional[Dict[str, Any]] = {}
     ) -> None:
         """Trains the crew for a given number of iterations."""
-        self._setup_for_training(filename)
+        train_crew = self.copy()
+        train_crew._setup_for_training(filename)
 
         for n_iteration in range(n_iterations):
-            self._train_iteration = n_iteration
-            self.kickoff(inputs=inputs)
+            train_crew._train_iteration = n_iteration
+            train_crew.kickoff(inputs=inputs)
 
         training_data = CrewTrainingHandler(TRAINING_DATA_FILE).load()
 
-        for agent in self.agents:
+        for agent in train_crew.agents:
             result = TaskEvaluator(agent).evaluate_training_data(
                 training_data=training_data, agent_id=str(agent.id)
             )
@@ -987,17 +988,19 @@ class Crew(BaseModel):
         inputs: Optional[Dict[str, Any]] = None,
     ) -> None:
         """Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures."""
-        self._test_execution_span = self._telemetry.test_execution_span(
-            self,
+        test_crew = self.copy()
+
+        self._test_execution_span = test_crew._telemetry.test_execution_span(
+            test_crew,
             n_iterations,
             inputs,
             openai_model_name,  # type: ignore[arg-type]
         )  # type: ignore[arg-type]
-        evaluator = CrewEvaluator(self, openai_model_name)  # type: ignore[arg-type]
+        evaluator = CrewEvaluator(test_crew, openai_model_name)  # type: ignore[arg-type]
 
         for i in range(1, n_iterations + 1):
             evaluator.set_iteration(i)
-            self.kickoff(inputs=inputs)
+            test_crew.kickoff(inputs=inputs)
 
         evaluator.print_crew_evaluation_result()
 
diff --git a/tests/crew_test.py b/tests/crew_test.py
index c01e84f80..6444b781c 100644
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -9,6 +9,7 @@ from unittest.mock import MagicMock, patch
 import instructor
 import pydantic_core
 import pytest
+
 from crewai.agent import Agent
 from crewai.agents.cache import CacheHandler
 from crewai.crew import Crew
@@ -497,6 +498,7 @@ def test_cache_hitting_between_agents():
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_api_calls_throttling(capsys):
     from unittest.mock import patch
+
     from crewai_tools import tool
 
     @tool
@@ -779,11 +781,14 @@ def test_async_task_execution_call_count():
     list_important_history.output = mock_task_output
     write_article.output = mock_task_output
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync, patch.object(
-        Task, "execute_async", return_value=mock_future
-    ) as mock_execute_async:
+    with (
+        patch.object(
+            Task, "execute_sync", return_value=mock_task_output
+        ) as mock_execute_sync,
+        patch.object(
+            Task, "execute_async", return_value=mock_future
+        ) as mock_execute_async,
+    ):
         crew.kickoff()
 
         assert mock_execute_async.call_count == 2
@@ -1105,6 +1110,7 @@ def test_dont_set_agents_step_callback_if_already_set():
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_crew_function_calling_llm():
     from unittest.mock import patch
+
     from crewai_tools import tool
 
     llm = "gpt-4o"
@@ -1448,52 +1454,6 @@ def test_crew_does_not_interpolate_without_inputs():
             interpolate_task_inputs.assert_not_called()
 
 
-# def test_crew_partial_inputs():
-#     agent = Agent(
-#         role="{topic} Researcher",
-#         goal="Express hot takes on {topic}.",
-#         backstory="You have a lot of experience with {topic}.",
-#     )
-
-#     task = Task(
-#         description="Give me an analysis around {topic}.",
-#         expected_output="{points} bullet points about {topic}.",
-#     )
-
-#     crew = Crew(agents=[agent], tasks=[task], inputs={"topic": "AI"})
-#     inputs = {"topic": "AI"}
-#     crew._interpolate_inputs(inputs=inputs)  # Manual call for now
-
-#     assert crew.tasks[0].description == "Give me an analysis around AI."
-#     assert crew.tasks[0].expected_output == "{points} bullet points about AI."
-#     assert crew.agents[0].role == "AI Researcher"
-#     assert crew.agents[0].goal == "Express hot takes on AI."
-#     assert crew.agents[0].backstory == "You have a lot of experience with AI."
-
-
-# def test_crew_invalid_inputs():
-#     agent = Agent(
-#         role="{topic} Researcher",
-#         goal="Express hot takes on {topic}.",
-#         backstory="You have a lot of experience with {topic}.",
-#     )
-
-#     task = Task(
-#         description="Give me an analysis around {topic}.",
-#         expected_output="{points} bullet points about {topic}.",
-#     )
-
-#     crew = Crew(agents=[agent], tasks=[task], inputs={"subject": "AI"})
-#     inputs = {"subject": "AI"}
-#     crew._interpolate_inputs(inputs=inputs)  # Manual call for now
-
-#     assert crew.tasks[0].description == "Give me an analysis around {topic}."
-#     assert crew.tasks[0].expected_output == "{points} bullet points about {topic}."
-#     assert crew.agents[0].role == "{topic} Researcher"
-#     assert crew.agents[0].goal == "Express hot takes on {topic}."
-#     assert crew.agents[0].backstory == "You have a lot of experience with {topic}."
-
-
 def test_task_callback_on_crew():
     from unittest.mock import MagicMock, patch
 
@@ -1770,7 +1730,10 @@ def test_manager_agent_with_tools_raises_exception():
 @patch("crewai.crew.Crew.kickoff")
 @patch("crewai.crew.CrewTrainingHandler")
 @patch("crewai.crew.TaskEvaluator")
-def test_crew_train_success(task_evaluator, crew_training_handler, kickoff):
+@patch("crewai.crew.Crew.copy")
+def test_crew_train_success(
+    copy_mock, task_evaluator, crew_training_handler, kickoff_mock
+):
     task = Task(
         description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
         expected_output="5 bullet points with a paragraph for each idea.",
@@ -1781,9 +1744,19 @@ def test_crew_train_success(task_evaluator, crew_training_handler, kickoff):
         agents=[researcher, writer],
         tasks=[task],
     )
+
+    # Create a mock for the copied crew
+    copy_mock.return_value = crew
+
     crew.train(
         n_iterations=2, inputs={"topic": "AI"}, filename="trained_agents_data.pkl"
     )
+
+    # Ensure kickoff is called on the copied crew
+    kickoff_mock.assert_has_calls(
+        [mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
+    )
+
     task_evaluator.assert_has_calls(
         [
             mock.call(researcher),
@@ -1822,10 +1795,6 @@ def test_crew_train_success(task_evaluator, crew_training_handler, kickoff):
         ]
     )
 
-    kickoff.assert_has_calls(
-        [mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
-    )
-
 
 def test_crew_train_error():
     task = Task(
@@ -1840,7 +1809,7 @@ def test_crew_train_error():
     )
 
     with pytest.raises(TypeError) as e:
-        crew.train()
+        crew.train()  # type: ignore purposefully throwing err
         assert "train() missing 1 required positional argument: 'n_iterations'" in str(
             e
         )
@@ -2536,8 +2505,9 @@ def test_conditional_should_execute():
 
 
 @mock.patch("crewai.crew.CrewEvaluator")
+@mock.patch("crewai.crew.Crew.copy")
 @mock.patch("crewai.crew.Crew.kickoff")
-def test_crew_testing_function(mock_kickoff, crew_evaluator):
+def test_crew_testing_function(kickoff_mock, copy_mock, crew_evaluator):
     task = Task(
         description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
         expected_output="5 bullet points with a paragraph for each idea.",
@@ -2548,11 +2518,15 @@ def test_crew_testing_function(mock_kickoff, crew_evaluator):
         agents=[researcher],
         tasks=[task],
     )
+
+    # Create a mock for the copied crew
+    copy_mock.return_value = crew
+
     n_iterations = 2
     crew.test(n_iterations, openai_model_name="gpt-4o-mini", inputs={"topic": "AI"})
 
-    assert len(mock_kickoff.mock_calls) == n_iterations
-    mock_kickoff.assert_has_calls(
+    # Ensure kickoff is called on the copied crew
+    kickoff_mock.assert_has_calls(
         [mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
     )
 

From b8a3c2974508a04d250acda40cd44eb4c87d1286 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Wed, 23 Oct 2024 05:34:34 -0300
Subject: [PATCH 012/126] preparing new verison

---
 pyproject.toml                                  |  2 +-
 src/crewai/__init__.py                          |  2 +-
 src/crewai/cli/cli.py                           |  5 +++--
 src/crewai/cli/create_crew.py                   | 17 +++++++++--------
 src/crewai/cli/templates/crew/pyproject.toml    |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml    |  2 +-
 .../cli/templates/pipeline/pyproject.toml       |  2 +-
 .../templates/pipeline_router/pyproject.toml    |  2 +-
 src/crewai/cli/templates/tool/pyproject.toml    |  2 +-
 uv.lock                                         |  2 +-
 10 files changed, 20 insertions(+), 18 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index d7920c7b0..56fdee20d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.74.2"
+version = "0.75.1"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index a41e3827f..1a1439d57 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.74.2"
+__version__ = "0.75.1"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 6c5263345..ae2cac143 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -32,10 +32,11 @@ def crewai():
 @crewai.command()
 @click.argument("type", type=click.Choice(["crew", "pipeline", "flow"]))
 @click.argument("name")
-def create(type, name):
+@click.option("--provider", type=str, help="The provider to use for the crew")
+def create(type, name, provider):
     """Create a new crew, pipeline, or flow."""
     if type == "crew":
-        create_crew(name)
+        create_crew(name, provider)
     elif type == "pipeline":
         create_pipeline(name)
     elif type == "flow":
diff --git a/src/crewai/cli/create_crew.py b/src/crewai/cli/create_crew.py
index f74331a23..f3a50f5f4 100644
--- a/src/crewai/cli/create_crew.py
+++ b/src/crewai/cli/create_crew.py
@@ -70,18 +70,19 @@ def copy_template_files(folder_path, name, class_name, parent_folder):
             copy_template(src_file, dst_file, name, class_name, folder_path.name)
 
 
-def create_crew(name, parent_folder=None):
+def create_crew(name, provider=None, parent_folder=None):
     folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)
     env_vars = load_env_vars(folder_path)
 
-    provider_models = get_provider_data()
-    if not provider_models:
-        return
+    if not provider:
+        provider_models = get_provider_data()
+        if not provider_models:
+            return
 
-    selected_provider = select_provider(provider_models)
-    if not selected_provider:
-        return
-    provider = selected_provider
+        selected_provider = select_provider(provider_models)
+        if not selected_provider:
+            return
+        provider = selected_provider
 
     # selected_model = select_model(provider, provider_models)
     # if not selected_model:
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 36ba1548c..a33e4bfce 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.2,<1.0.0"
+    "crewai[tools]>=0.75.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index f93390741..d0ef63377 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.2,<1.0.0",
+    "crewai[tools]>=0.75.1,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 517c2a4d1..62a69f3a7 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.74.2,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.75.1,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index b349e4dda..20b3a7c07 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.2,<1.0.0"
+    "crewai[tools]>=0.75.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index bd1df942f..c5d6a47e7 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.74.2"
+    "crewai[tools]>=0.75.1"
 ]
 
diff --git a/uv.lock b/uv.lock
index 5d4d5b0b7..ddd57b313 100644
--- a/uv.lock
+++ b/uv.lock
@@ -627,7 +627,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.74.2"
+version = "0.75.1"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From f39a975e208788209ed9b92815e8ee928afae503 Mon Sep 17 00:00:00 2001
From: Rip&Tear <84775494+theCyberTech@users.noreply.github.com>
Date: Wed, 23 Oct 2024 21:41:14 +0800
Subject: [PATCH 013/126] fix/fixed missing API prompt + CLI docs update
 (#1464)

* updated CLI to allow for submitting API keys

* updated click prompt to remove default number

* removed all unnecessary comments

* feat: implement crew creation CLI command

- refactor code to multiple functions
- Added ability for users to select provider and model when uing crewai create command and ave API key to .env

* refactered select_choice function for early return

* refactored  select_provider to have an ealry return

* cleanup of comments

* refactor/Move functions into utils file, added new provider file and migrated fucntions thre, new constants file + general function refactor

* small comment cleanup

* fix unnecessary deps

* Added docs for new CLI provider + fixed missing API prompt

* Minor doc updates

* allow user to bypass api key entry + incorect number selected logic + ruff formatting

* ruff updates

* Fix spelling mistake

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
---
 docs/concepts/cli.mdx         |  33 +++++++-
 src/crewai/cli/create_crew.py | 120 ++++++++++++++++++++---------
 src/crewai/cli/provider.py    | 137 ++++++++++++++++++++++------------
 3 files changed, 206 insertions(+), 84 deletions(-)

diff --git a/docs/concepts/cli.mdx b/docs/concepts/cli.mdx
index 8297ee6aa..2afc6b56c 100644
--- a/docs/concepts/cli.mdx
+++ b/docs/concepts/cli.mdx
@@ -6,7 +6,7 @@ icon: terminal
 
 # CrewAI CLI Documentation
 
-The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews and pipelines.
+The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews & flows.
 
 ## Installation
 
@@ -146,3 +146,34 @@ crewai run
 Make sure to run these commands from the directory where your CrewAI project is set up. 
 Some commands may require additional configuration or setup within your project structure.
 </Note>
+
+
+### 9. API Keys
+
+When running ```crewai create crew``` command, the CLI will first show you the top 5 most common LLM providers and ask you to select one.
+
+Once you've selected an LLM provider, you will be prompted for API keys.
+
+#### Initial API key providers
+
+The CLI will initially prompt for API keys for the following services:
+
+* OpenAI
+* Groq
+* Anthropic
+* Google Gemini
+
+When you select a provider, the CLI will prompt you to enter your API key.
+
+#### Other Options
+
+If you select option 6, you will be able to select from a list of LiteLLM supported providers.
+
+When you select a provider, the CLI will prompt you to enter the Key name and the API key.
+
+See the following link for each provider's key name:
+
+* [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
+
+
+
diff --git a/src/crewai/cli/create_crew.py b/src/crewai/cli/create_crew.py
index f3a50f5f4..f336c3f52 100644
--- a/src/crewai/cli/create_crew.py
+++ b/src/crewai/cli/create_crew.py
@@ -1,8 +1,16 @@
+import sys
 from pathlib import Path
+
 import click
-from crewai.cli.utils import copy_template, load_env_vars, write_env_file
-from crewai.cli.provider import get_provider_data, select_provider, PROVIDERS
+
 from crewai.cli.constants import ENV_VARS
+from crewai.cli.provider import (
+    PROVIDERS,
+    get_provider_data,
+    select_model,
+    select_provider,
+)
+from crewai.cli.utils import copy_template, load_env_vars, write_env_file
 
 
 def create_folder_structure(name, parent_folder=None):
@@ -14,11 +22,19 @@ def create_folder_structure(name, parent_folder=None):
     else:
         folder_path = Path(folder_name)
 
-    click.secho(
-        f"Creating {'crew' if parent_folder else 'folder'} {folder_name}...",
-        fg="green",
-        bold=True,
-    )
+    if folder_path.exists():
+        if not click.confirm(
+            f"Folder {folder_name} already exists. Do you want to override it?"
+        ):
+            click.secho("Operation cancelled.", fg="yellow")
+            sys.exit(0)
+        click.secho(f"Overriding folder {folder_name}...", fg="green", bold=True)
+    else:
+        click.secho(
+            f"Creating {'crew' if parent_folder else 'folder'} {folder_name}...",
+            fg="green",
+            bold=True,
+        )
 
     if not folder_path.exists():
         folder_path.mkdir(parents=True)
@@ -27,11 +43,6 @@ def create_folder_structure(name, parent_folder=None):
             (folder_path / "src" / folder_name).mkdir(parents=True)
             (folder_path / "src" / folder_name / "tools").mkdir(parents=True)
             (folder_path / "src" / folder_name / "config").mkdir(parents=True)
-    else:
-        click.secho(
-            f"\tFolder {folder_name} already exists.",
-            fg="yellow",
-        )
 
     return folder_path, folder_name, class_name
 
@@ -70,38 +81,77 @@ def copy_template_files(folder_path, name, class_name, parent_folder):
             copy_template(src_file, dst_file, name, class_name, folder_path.name)
 
 
-def create_crew(name, provider=None, parent_folder=None):
+def create_crew(name, parent_folder=None):
     folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)
     env_vars = load_env_vars(folder_path)
 
-    if not provider:
-        provider_models = get_provider_data()
-        if not provider_models:
+    existing_provider = None
+    for provider, env_keys in ENV_VARS.items():
+        if any(key in env_vars for key in env_keys):
+            existing_provider = provider
+            break
+
+    if existing_provider:
+        if not click.confirm(
+            f"Found existing environment variable configuration for {existing_provider.capitalize()}. Do you want to override it?"
+        ):
+            click.secho("Keeping existing provider configuration.", fg="yellow")
             return
 
+    provider_models = get_provider_data()
+    if not provider_models:
+        return
+
+    while True:
         selected_provider = select_provider(provider_models)
-        if not selected_provider:
-            return
-        provider = selected_provider
-
-    # selected_model = select_model(provider, provider_models)
-    # if not selected_model:
-    #     return
-    # model = selected_model
-
-    if provider in PROVIDERS:
-        api_key_var = ENV_VARS[provider][0]
-    else:
-        api_key_var = click.prompt(
-            f"Enter the environment variable name for your {provider.capitalize()} API key",
-            type=str,
+        if selected_provider is None:  # User typed 'q'
+            click.secho("Exiting...", fg="yellow")
+            sys.exit(0)
+        if selected_provider:  # Valid selection
+            break
+        click.secho(
+            "No provider selected. Please try again or press 'q' to exit.", fg="red"
         )
 
-    env_vars = {api_key_var: "YOUR_API_KEY_HERE"}
-    write_env_file(folder_path, env_vars)
+    while True:
+        selected_model = select_model(selected_provider, provider_models)
+        if selected_model is None:  # User typed 'q'
+            click.secho("Exiting...", fg="yellow")
+            sys.exit(0)
+        if selected_model:  # Valid selection
+            break
+        click.secho(
+            "No model selected. Please try again or press 'q' to exit.", fg="red"
+        )
 
-    # env_vars['MODEL'] = model
-    # click.secho(f"Selected model: {model}", fg="green")
+    if selected_provider in PROVIDERS:
+        api_key_var = ENV_VARS[selected_provider][0]
+    else:
+        api_key_var = click.prompt(
+            f"Enter the environment variable name for your {selected_provider.capitalize()} API key",
+            type=str,
+            default="",
+        )
+
+    api_key_value = ""
+    click.echo(
+        f"Enter your {selected_provider.capitalize()} API key (press Enter to skip): ",
+        nl=False,
+    )
+    try:
+        api_key_value = input()
+    except (KeyboardInterrupt, EOFError):
+        api_key_value = ""
+
+    if api_key_value.strip():
+        env_vars = {api_key_var: api_key_value}
+        write_env_file(folder_path, env_vars)
+        click.secho("API key saved to .env file", fg="green")
+    else:
+        click.secho("No API key provided. Skipping .env file creation.", fg="yellow")
+
+    env_vars["MODEL"] = selected_model
+    click.secho(f"Selected model: {selected_model}", fg="green")
 
     package_dir = Path(__file__).parent
     templates_dir = package_dir / "templates" / "crew"
diff --git a/src/crewai/cli/provider.py b/src/crewai/cli/provider.py
index f829ca9fd..4bfeb9324 100644
--- a/src/crewai/cli/provider.py
+++ b/src/crewai/cli/provider.py
@@ -1,67 +1,91 @@
 import json
 import time
-import requests
 from collections import defaultdict
+from pathlib import Path
+
 import click
-from pathlib import Path 
-from crewai.cli.constants import PROVIDERS, MODELS, JSON_URL
+import requests
+
+from crewai.cli.constants import JSON_URL, MODELS, PROVIDERS
+
 
 def select_choice(prompt_message, choices):
     """
     Presents a list of choices to the user and prompts them to select one.
-    
+
     Args:
     - prompt_message (str): The message to display to the user before presenting the choices.
     - choices (list): A list of options to present to the user.
-    
+
     Returns:
-    - str: The selected choice from the list, or None if the operation is aborted or an invalid selection is made.
+    - str: The selected choice from the list, or None if the user chooses to quit.
     """
+
+    provider_models = get_provider_data()
+    if not provider_models:
+        return
     click.secho(prompt_message, fg="cyan")
     for idx, choice in enumerate(choices, start=1):
         click.secho(f"{idx}. {choice}", fg="cyan")
-    try:
-        selected_index = click.prompt("Enter the number of your choice", type=int) - 1
-    except click.exceptions.Abort:
-        click.secho("Operation aborted by the user.", fg="red")
-        return None
-    if not (0 <= selected_index < len(choices)):
-        click.secho("Invalid selection.", fg="red")
-        return None
-    return choices[selected_index]
+    click.secho("q. Quit", fg="cyan")
+
+    while True:
+        choice = click.prompt(
+            "Enter the number of your choice or 'q' to quit", type=str
+        )
+
+        if choice.lower() == "q":
+            return None
+
+        try:
+            selected_index = int(choice) - 1
+            if 0 <= selected_index < len(choices):
+                return choices[selected_index]
+        except ValueError:
+            pass
+
+        click.secho(
+            "Invalid selection. Please select a number between 1 and 6 or 'q' to quit.",
+            fg="red",
+        )
+
 
 def select_provider(provider_models):
     """
     Presents a list of providers to the user and prompts them to select one.
-    
+
     Args:
     - provider_models (dict): A dictionary of provider models.
-    
+
     Returns:
-    - str: The selected provider, or None if the operation is aborted or an invalid selection is made.
+    - str: The selected provider
+    - None: If user explicitly quits
     """
     predefined_providers = [p.lower() for p in PROVIDERS]
     all_providers = sorted(set(predefined_providers + list(provider_models.keys())))
 
-    provider = select_choice("Select a provider to set up:", predefined_providers + ['other'])
-    if not provider:
+    provider = select_choice(
+        "Select a provider to set up:", predefined_providers + ["other"]
+    )
+    if provider is None:  # User typed 'q'
         return None
-    provider = provider.lower()
 
-    if provider == 'other':
+    if provider == "other":
         provider = select_choice("Select a provider from the full list:", all_providers)
-        if not provider:
+        if provider is None:  # User typed 'q'
             return None
-    return provider
+
+    return provider.lower() if provider else False
+
 
 def select_model(provider, provider_models):
     """
     Presents a list of models for a given provider to the user and prompts them to select one.
-    
+
     Args:
     - provider (str): The provider for which to select a model.
     - provider_models (dict): A dictionary of provider models.
-    
+
     Returns:
     - str: The selected model, or None if the operation is aborted or an invalid selection is made.
     """
@@ -76,37 +100,49 @@ def select_model(provider, provider_models):
         click.secho(f"No models available for provider '{provider}'.", fg="red")
         return None
 
-    selected_model = select_choice(f"Select a model to use for {provider.capitalize()}:", available_models)
+    selected_model = select_choice(
+        f"Select a model to use for {provider.capitalize()}:", available_models
+    )
     return selected_model
 
+
 def load_provider_data(cache_file, cache_expiry):
     """
     Loads provider data from a cache file if it exists and is not expired. If the cache is expired or corrupted, it fetches the data from the web.
-    
+
     Args:
     - cache_file (Path): The path to the cache file.
     - cache_expiry (int): The cache expiry time in seconds.
-    
+
     Returns:
     - dict or None: The loaded provider data or None if the operation fails.
     """
     current_time = time.time()
-    if cache_file.exists() and (current_time - cache_file.stat().st_mtime) < cache_expiry:
+    if (
+        cache_file.exists()
+        and (current_time - cache_file.stat().st_mtime) < cache_expiry
+    ):
         data = read_cache_file(cache_file)
         if data:
             return data
-        click.secho("Cache is corrupted. Fetching provider data from the web...", fg="yellow")
+        click.secho(
+            "Cache is corrupted. Fetching provider data from the web...", fg="yellow"
+        )
     else:
-        click.secho("Cache expired or not found. Fetching provider data from the web...", fg="cyan")
+        click.secho(
+            "Cache expired or not found. Fetching provider data from the web...",
+            fg="cyan",
+        )
     return fetch_provider_data(cache_file)
 
+
 def read_cache_file(cache_file):
     """
     Reads and returns the JSON content from a cache file. Returns None if the file contains invalid JSON.
-    
+
     Args:
     - cache_file (Path): The path to the cache file.
-    
+
     Returns:
     - dict or None: The JSON content of the cache file or None if the JSON is invalid.
     """
@@ -116,13 +152,14 @@ def read_cache_file(cache_file):
     except json.JSONDecodeError:
         return None
 
+
 def fetch_provider_data(cache_file):
     """
     Fetches provider data from a specified URL and caches it to a file.
-    
+
     Args:
     - cache_file (Path): The path to the cache file.
-    
+
     Returns:
     - dict or None: The fetched provider data or None if the operation fails.
     """
@@ -139,38 +176,42 @@ def fetch_provider_data(cache_file):
         click.secho("Error parsing provider data. Invalid JSON format.", fg="red")
     return None
 
+
 def download_data(response):
     """
     Downloads data from a given HTTP response and returns the JSON content.
-    
+
     Args:
     - response (requests.Response): The HTTP response object.
-    
+
     Returns:
     - dict: The JSON content of the response.
     """
-    total_size = int(response.headers.get('content-length', 0))
+    total_size = int(response.headers.get("content-length", 0))
     block_size = 8192
     data_chunks = []
-    with click.progressbar(length=total_size, label='Downloading', show_pos=True) as progress_bar:
+    with click.progressbar(
+        length=total_size, label="Downloading", show_pos=True
+    ) as progress_bar:
         for chunk in response.iter_content(block_size):
             if chunk:
                 data_chunks.append(chunk)
                 progress_bar.update(len(chunk))
-    data_content = b''.join(data_chunks)
-    return json.loads(data_content.decode('utf-8'))
+    data_content = b"".join(data_chunks)
+    return json.loads(data_content.decode("utf-8"))
+
 
 def get_provider_data():
     """
     Retrieves provider data from a cache file, filters out models based on provider criteria, and returns a dictionary of providers mapped to their models.
-    
+
     Returns:
     - dict or None: A dictionary of providers mapped to their models or None if the operation fails.
     """
-    cache_dir = Path.home() / '.crewai'
+    cache_dir = Path.home() / ".crewai"
     cache_dir.mkdir(exist_ok=True)
-    cache_file = cache_dir / 'provider_cache.json'
-    cache_expiry = 24 * 3600 
+    cache_file = cache_dir / "provider_cache.json"
+    cache_expiry = 24 * 3600
 
     data = load_provider_data(cache_file, cache_expiry)
     if not data:
@@ -179,8 +220,8 @@ def get_provider_data():
     provider_models = defaultdict(list)
     for model_name, properties in data.items():
         provider = properties.get("litellm_provider", "").strip().lower()
-        if 'http' in provider or provider == 'other':
+        if "http" in provider or provider == "other":
             continue
         if provider:
             provider_models[provider].append(model_name)
-    return provider_models
\ No newline at end of file
+    return provider_models

From 7d68e287ccab533ac6235856ac76e76e6d9b3120 Mon Sep 17 00:00:00 2001
From: Maicon Peixinho <maiconpeixinho@icloud.com>
Date: Wed, 23 Oct 2024 09:38:41 -0500
Subject: [PATCH 014/126] chore(readme-fix): fixing step for 'running tests' in
 the contribution section (#1490)

Co-authored-by: Eduardo Chiarotti <dudumelgaco@hotmail.com>
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f79f2a011..ceec198c3 100644
--- a/README.md
+++ b/README.md
@@ -351,7 +351,7 @@ pre-commit install
 ### Running Tests
 
 ```bash
-uvx pytest
+uv run pytest .
 ```
 
 ### Running static type checks

From e1fd83e6a76bec489fc69e57869c3c1cc441c551 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 23 Oct 2024 11:01:00 -0400
Subject: [PATCH 015/126] support unsafe code execution. add in docker install
 and running checks. (#1496)

* support unsafe code execution. add in docker install and running checks.

* Update return type
---
 docs/concepts/agents.mdx |  8 +++++---
 src/crewai/agent.py      | 34 ++++++++++++++++++++++++++++++++--
 2 files changed, 37 insertions(+), 5 deletions(-)

diff --git a/docs/concepts/agents.mdx b/docs/concepts/agents.mdx
index f7e97f186..6c939b321 100644
--- a/docs/concepts/agents.mdx
+++ b/docs/concepts/agents.mdx
@@ -31,16 +31,17 @@ Think of an agent as a member of a team, with specific skills and a particular j
 | **Max RPM** *(optional)*   | `max_rpm`  | Max RPM is the maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified, with a default value of `None`.                                                                               |
 | **Max Execution Time** *(optional)*   | `max_execution_time`  | Max Execution Time is the maximum execution time for an agent to execute a task. It's optional and can be left unspecified, with a default value of `None`, meaning no max execution time.                                                                     |
 | **Verbose** *(optional)*   | `verbose`  | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`.                                                                                              |
-| **Allow Delegation** *(optional)* | `allow_delegation`  | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `False`.
+| **Allow Delegation** *(optional)* | `allow_delegation`  | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `False`.                                                                                                      |
 | **Step Callback** *(optional)* | `step_callback`  | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`.                                                               |
 | **Cache** *(optional)*     | `cache`  | Indicates if the agent should use a cache for tool usage. Default is `True`.                                                                                                                                                                  |
 | **System Template** *(optional)*     | `system_template`  | Specifies the system format for the agent. Default is `None`.                                                                                                                                                                  |
 | **Prompt Template** *(optional)*     | `prompt_template`  | Specifies the prompt format for the agent. Default is `None`.                                                                                                                                                                  |
 | **Response Template** *(optional)*     | `response_template`  | Specifies the response format for the agent. Default is `None`.                                                                                                                                                                  |
 | **Allow Code Execution** *(optional)*     | `allow_code_execution`  | Enable code execution for the agent. Default is `False`.                                                                                                                                                                  |
-| **Max Retry Limit** *(optional)*     | `max_retry_limit`  | Maximum number of retries for an agent to execute a task when an error occurs. Default is `2`.
+| **Max Retry Limit** *(optional)*     | `max_retry_limit`  | Maximum number of retries for an agent to execute a task when an error occurs. Default is `2`.                                                                                                                                                                  |
 | **Use System Prompt** *(optional)*     | `use_system_prompt`  | Adds the ability to not use system prompt (to support o1 models). Default is `True`.                                                                                                                                                                  |
 | **Respect Context Window** *(optional)*     | `respect_context_window`  | Summary strategy to avoid overflowing the context window. Default is `True`.                                                                                                                                                                  |
+| **Code Execution Mode** *(optional)* | `code_execution_mode` | Determines the mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution on the host machine). Default is `safe`.                                                                                                          |
 
 ## Creating an agent
 
@@ -83,6 +84,7 @@ agent = Agent(
   max_retry_limit=2,  # Optional
   use_system_prompt=True,  # Optional
   respect_context_window=True,  # Optional
+  code_execution_mode='safe',  # Optional, defaults to 'safe'
 )
 ```
 
@@ -156,4 +158,4 @@ crew = my_crew.kickoff(inputs={"input": "Mark Twain"})
 ## Conclusion
 
 Agents are the building blocks of the CrewAI framework. By understanding how to define and interact with agents, 
-you can create sophisticated AI systems that leverage the power of collaborative intelligence.
\ No newline at end of file
+you can create sophisticated AI systems that leverage the power of collaborative intelligence. The `code_execution_mode` attribute provides flexibility in how agents execute code, allowing for both secure and direct execution options.
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 165a40656..f68d6401b 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -1,6 +1,8 @@
 import os
+import shutil
+import subprocess
 from inspect import signature
-from typing import Any, List, Optional, Union
+from typing import Any, List, Literal, Optional, Union
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -112,6 +114,10 @@ class Agent(BaseAgent):
         default=2,
         description="Maximum number of retries for an agent to execute a task when an error occurs.",
     )
+    code_execution_mode: Literal["safe", "unsafe"] = Field(
+        default="safe",
+        description="Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution).",
+    )
 
     @model_validator(mode="after")
     def post_init_setup(self):
@@ -173,6 +179,9 @@ class Agent(BaseAgent):
         if not self.agent_executor:
             self._setup_agent_executor()
 
+        if self.allow_code_execution:
+            self._validate_docker_installation()
+
         return self
 
     def _setup_agent_executor(self):
@@ -308,7 +317,9 @@ class Agent(BaseAgent):
         try:
             from crewai_tools import CodeInterpreterTool
 
-            return [CodeInterpreterTool()]
+            # Set the unsafe_mode based on the code_execution_mode attribute
+            unsafe_mode = self.code_execution_mode == "unsafe"
+            return [CodeInterpreterTool(unsafe_mode=unsafe_mode)]
         except ModuleNotFoundError:
             self._logger.log(
                 "info", "Coding tools not available. Install crewai_tools. "
@@ -408,6 +419,25 @@ class Agent(BaseAgent):
 
         return "\n".join(tool_strings)
 
+    def _validate_docker_installation(self) -> None:
+        """Check if Docker is installed and running."""
+        if not shutil.which("docker"):
+            raise RuntimeError(
+                f"Docker is not installed. Please install Docker to use code execution with agent: {self.role}"
+            )
+
+        try:
+            subprocess.run(
+                ["docker", "info"],
+                check=True,
+                stdout=subprocess.PIPE,
+                stderr=subprocess.PIPE,
+            )
+        except subprocess.CalledProcessError:
+            raise RuntimeError(
+                f"Docker is not running. Please start Docker to use code execution with agent: {self.role}"
+            )
+
     @staticmethod
     def __tools_names(tools) -> str:
         return ", ".join([t.name for t in tools])

From a921828e51f5687b971b9883e6040092933a85e2 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 23 Oct 2024 11:21:27 -0400
Subject: [PATCH 016/126] Fix memory imports for embedding functions (#1497)

---
 docs/concepts/memory.mdx | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/docs/concepts/memory.mdx b/docs/concepts/memory.mdx
index de1fb3510..735ed861e 100644
--- a/docs/concepts/memory.mdx
+++ b/docs/concepts/memory.mdx
@@ -118,7 +118,7 @@ Alternatively, you can directly pass the OpenAIEmbeddingFunction to the embedder
 Example:
 ```python Code
 from crewai import Crew, Agent, Task, Process
-from chromadb.utils.embedding_functions.openai_embedding_function import OpenAIEmbeddingFunction
+from chromadb.utils.embedding_functions import OpenAIEmbeddingFunction
 
 my_crew = Crew(
     agents=[...],
@@ -174,6 +174,7 @@ my_crew = Crew(
 ### Using Azure OpenAI embeddings
 
 ```python Code
+from chromadb.utils.embedding_functions import OpenAIEmbeddingFunction
 from crewai import Crew, Agent, Task, Process
 
 my_crew = Crew(
@@ -182,7 +183,7 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=embedding_functions.OpenAIEmbeddingFunction(
+    embedder=OpenAIEmbeddingFunction(
         api_key="YOUR_API_KEY",
         api_base="YOUR_API_BASE_PATH",
         api_type="azure",
@@ -195,6 +196,7 @@ my_crew = Crew(
 ### Using Vertex AI embeddings
 
 ```python Code
+from chromadb.utils.embedding_functions import GoogleVertexEmbeddingFunction
 from crewai import Crew, Agent, Task, Process
 
 my_crew = Crew(
@@ -203,7 +205,7 @@ my_crew = Crew(
     process=Process.sequential,
     memory=True,
     verbose=True,
-    embedder=embedding_functions.GoogleVertexEmbeddingFunction(
+    embedder=GoogleVertexEmbeddingFunction(
         project_id="YOUR_PROJECT_ID",
         region="YOUR_REGION",
         api_key="YOUR_API_KEY",

From 74c17033108fc5392d4d09f3c0378cb45cd26f75 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Wed, 23 Oct 2024 17:56:21 -0300
Subject: [PATCH 017/126] updating crewai version

---
 pyproject.toml                                |    2 +-
 src/crewai/__init__.py                        |    2 +-
 src/crewai/cli/cli.py                         |    5 +-
 src/crewai/cli/create_crew.py                 |  125 +-
 src/crewai/cli/templates/crew/pyproject.toml  |    2 +-
 src/crewai/cli/templates/flow/pyproject.toml  |    2 +-
 .../cli/templates/pipeline/pyproject.toml     |    2 +-
 .../templates/pipeline_router/pyproject.toml  |    2 +-
 src/crewai/cli/templates/tool/pyproject.toml  |    2 +-
 uv.lock                                       | 1904 ++++++++---------
 10 files changed, 985 insertions(+), 1063 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 56fdee20d..929e68b9e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.75.1"
+version = "0.76.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 1a1439d57..a1b95951d 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.75.1"
+__version__ = "0.76.0"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index ae2cac143..48bb26ff9 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -32,11 +32,12 @@ def crewai():
 @crewai.command()
 @click.argument("type", type=click.Choice(["crew", "pipeline", "flow"]))
 @click.argument("name")
+@click.option("--skip-provider", is_flag=True, help="Skip provider validation")
 @click.option("--provider", type=str, help="The provider to use for the crew")
-def create(type, name, provider):
+def create(type, name, provider, skip_provider_validation=False):
     """Create a new crew, pipeline, or flow."""
     if type == "crew":
-        create_crew(name, provider)
+        create_crew(name, provider, skip_provider_validation)
     elif type == "pipeline":
         create_pipeline(name)
     elif type == "flow":
diff --git a/src/crewai/cli/create_crew.py b/src/crewai/cli/create_crew.py
index f336c3f52..90184ec31 100644
--- a/src/crewai/cli/create_crew.py
+++ b/src/crewai/cli/create_crew.py
@@ -81,77 +81,84 @@ def copy_template_files(folder_path, name, class_name, parent_folder):
             copy_template(src_file, dst_file, name, class_name, folder_path.name)
 
 
-def create_crew(name, parent_folder=None):
+def create_crew(
+    name, provider=None, skip_provider_validation=False, parent_folder=None
+):
     folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)
     env_vars = load_env_vars(folder_path)
+    if not skip_provider_validation:
+        if not provider:
+            provider_models = get_provider_data()
+            if not provider_models:
+                return
 
-    existing_provider = None
-    for provider, env_keys in ENV_VARS.items():
-        if any(key in env_vars for key in env_keys):
-            existing_provider = provider
-            break
+        existing_provider = None
+        for provider, env_keys in ENV_VARS.items():
+            if any(key in env_vars for key in env_keys):
+                existing_provider = provider
+                break
 
-    if existing_provider:
-        if not click.confirm(
-            f"Found existing environment variable configuration for {existing_provider.capitalize()}. Do you want to override it?"
-        ):
-            click.secho("Keeping existing provider configuration.", fg="yellow")
+        if existing_provider:
+            if not click.confirm(
+                f"Found existing environment variable configuration for {existing_provider.capitalize()}. Do you want to override it?"
+            ):
+                click.secho("Keeping existing provider configuration.", fg="yellow")
+                return
+
+        provider_models = get_provider_data()
+        if not provider_models:
             return
 
-    provider_models = get_provider_data()
-    if not provider_models:
-        return
+        while True:
+            selected_provider = select_provider(provider_models)
+            if selected_provider is None:  # User typed 'q'
+                click.secho("Exiting...", fg="yellow")
+                sys.exit(0)
+            if selected_provider:  # Valid selection
+                break
+            click.secho(
+                "No provider selected. Please try again or press 'q' to exit.", fg="red"
+            )
 
-    while True:
-        selected_provider = select_provider(provider_models)
-        if selected_provider is None:  # User typed 'q'
-            click.secho("Exiting...", fg="yellow")
-            sys.exit(0)
-        if selected_provider:  # Valid selection
-            break
-        click.secho(
-            "No provider selected. Please try again or press 'q' to exit.", fg="red"
-        )
+        while True:
+            selected_model = select_model(selected_provider, provider_models)
+            if selected_model is None:  # User typed 'q'
+                click.secho("Exiting...", fg="yellow")
+                sys.exit(0)
+            if selected_model:  # Valid selection
+                break
+            click.secho(
+                "No model selected. Please try again or press 'q' to exit.", fg="red"
+            )
 
-    while True:
-        selected_model = select_model(selected_provider, provider_models)
-        if selected_model is None:  # User typed 'q'
-            click.secho("Exiting...", fg="yellow")
-            sys.exit(0)
-        if selected_model:  # Valid selection
-            break
-        click.secho(
-            "No model selected. Please try again or press 'q' to exit.", fg="red"
-        )
+        if selected_provider in PROVIDERS:
+            api_key_var = ENV_VARS[selected_provider][0]
+        else:
+            api_key_var = click.prompt(
+                f"Enter the environment variable name for your {selected_provider.capitalize()} API key",
+                type=str,
+                default="",
+            )
 
-    if selected_provider in PROVIDERS:
-        api_key_var = ENV_VARS[selected_provider][0]
-    else:
-        api_key_var = click.prompt(
-            f"Enter the environment variable name for your {selected_provider.capitalize()} API key",
-            type=str,
-            default="",
-        )
-
-    api_key_value = ""
-    click.echo(
-        f"Enter your {selected_provider.capitalize()} API key (press Enter to skip): ",
-        nl=False,
-    )
-    try:
-        api_key_value = input()
-    except (KeyboardInterrupt, EOFError):
         api_key_value = ""
+        click.echo(
+            f"Enter your {selected_provider.capitalize()} API key (press Enter to skip): ",
+            nl=False,
+        )
+        try:
+            api_key_value = input()
+        except (KeyboardInterrupt, EOFError):
+            api_key_value = ""
 
-    if api_key_value.strip():
-        env_vars = {api_key_var: api_key_value}
-        write_env_file(folder_path, env_vars)
-        click.secho("API key saved to .env file", fg="green")
-    else:
-        click.secho("No API key provided. Skipping .env file creation.", fg="yellow")
+        if api_key_value.strip():
+            env_vars = {api_key_var: api_key_value}
+            write_env_file(folder_path, env_vars)
+            click.secho("API key saved to .env file", fg="green")
+        else:
+            click.secho("No API key provided. Skipping .env file creation.", fg="yellow")
 
-    env_vars["MODEL"] = selected_model
-    click.secho(f"Selected model: {selected_model}", fg="green")
+        env_vars["MODEL"] = selected_model
+        click.secho(f"Selected model: {selected_model}", fg="green")
 
     package_dir = Path(__file__).parent
     templates_dir = package_dir / "templates" / "crew"
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index a33e4bfce..6852f1292 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.75.1,<1.0.0"
+    "crewai[tools]>=0.76.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index d0ef63377..88a313ae9 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.75.1,<1.0.0",
+    "crewai[tools]>=0.76.0,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 62a69f3a7..b2a4d36d4 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.75.1,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.76.0,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 20b3a7c07..f7da504cf 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.75.1,<1.0.0"
+    "crewai[tools]>=0.76.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index c5d6a47e7..8f7194b7f 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.75.1"
+    "crewai[tools]>=0.76.0"
 ]
 
diff --git a/uv.lock b/uv.lock
index ddd57b313..9d07a5bae 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2,8 +2,9 @@ version = 1
 requires-python = ">=3.10, <=3.13"
 resolution-markers = [
     "python_full_version < '3.11' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy'",
     "python_full_version < '3.11' and platform_python_implementation != 'PyPy'",
-    "python_full_version == '3.11.*'",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy'",
     "python_full_version >= '3.12' and python_full_version < '3.12.4'",
     "python_full_version >= '3.12.4' and python_full_version < '3.13'",
     "python_full_version >= '3.13'",
@@ -11,7 +12,7 @@ resolution-markers = [
 
 [[package]]
 name = "agentops"
-version = "0.3.13"
+version = "0.3.14"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "packaging" },
@@ -20,9 +21,9 @@ dependencies = [
     { name = "requests" },
     { name = "termcolor" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/35/11/fb06b4cee96285a5f745809d0f4efddef70d2a82112a633ed53834d6fc64/agentops-0.3.13.tar.gz", hash = "sha256:319b7325fb79004ce996191aa21f0982489be22cc1acc2f3f6d02cdff1db2429", size = 48559 }
+sdist = { url = "https://files.pythonhosted.org/packages/46/cb/183fdaf40ae97ac1806ba91f6f23d55dc0a1a5cdf0881a5c834c8ca7175a/agentops-0.3.14.tar.gz", hash = "sha256:fcb515e5743d73efee851b687692bed74797dc88e29a8327b2bbfb21d73a7447", size = 48548 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/68/ef/a3b8adc0de2e7daa1e6e2734af9a0e37c90e3346b8a804e3fdc322c82b6c/agentops-0.3.13-py3-none-any.whl", hash = "sha256:81bfdfedd990fbc3064ee42a67422ddbee07b6cd96c5fca7e124eb8c1e0cebdc", size = 50813 },
+    { url = "https://files.pythonhosted.org/packages/1c/27/75ab5bf99341a6a02775e3858f54a18cbcda0f35b5c6c0f114a829d62b8e/agentops-0.3.14-py3-none-any.whl", hash = "sha256:f4a2fcf1a7caf1d5383bfb66d8a9d567f3cb88fc7495cfd81ade167b0c06a4ea", size = 50825 },
 ]
 
 [[package]]
@@ -36,7 +37,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.10.8"
+version = "3.10.10"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -47,68 +48,68 @@ dependencies = [
     { name = "multidict" },
     { name = "yarl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/4e/05/da5ff89c85444a6ade9079e73580fb3f78c6ba0e170a2472f15400d03e02/aiohttp-3.10.8.tar.gz", hash = "sha256:21f8225f7dc187018e8433c9326be01477fb2810721e048b33ac49091b19fb4a", size = 7540022 }
+sdist = { url = "https://files.pythonhosted.org/packages/17/7e/16e57e6cf20eb62481a2f9ce8674328407187950ccc602ad07c685279141/aiohttp-3.10.10.tar.gz", hash = "sha256:0631dd7c9f0822cc61c88586ca76d5b5ada26538097d0f1df510b082bad3411a", size = 7542993 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/80/2f/602f6e79ab70fbd881ba599f66e29254efab7e63ac463f513d25d8878ce5/aiohttp-3.10.8-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a1ba7bc139592339ddeb62c06486d0fa0f4ca61216e14137a40d626c81faf10c", size = 586808 },
-    { url = "https://files.pythonhosted.org/packages/b3/28/a1ae71c7395c1d39972bf5b3fcb0a1056ddd51faf7ab29f38267ad0e9eb3/aiohttp-3.10.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:85e4d7bd05d18e4b348441e7584c681eff646e3bf38f68b2626807f3add21aa2", size = 399198 },
-    { url = "https://files.pythonhosted.org/packages/c1/3b/23baa9c6cb19ae3b70cbe0f00881b33fc0994d3366808ad2621c3ed8f8d1/aiohttp-3.10.8-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:69de056022e7abf69cb9fec795515973cc3eeaff51e3ea8d72a77aa933a91c52", size = 390553 },
-    { url = "https://files.pythonhosted.org/packages/e2/a0/0abb1c58ee9f5f418100fbdeb26bf7b030b33dc9dfc29f5acfb2d6896cc5/aiohttp-3.10.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ee3587506898d4a404b33bd19689286ccf226c3d44d7a73670c8498cd688e42c", size = 1228651 },
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 ]
 
 [[package]]

From 6baaad045a5709a537c094e24c4aa42ffd451a3e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Wed, 23 Oct 2024 18:08:49 -0300
Subject: [PATCH 018/126] new version

---
 pyproject.toml                                         |  2 +-
 src/crewai/__init__.py                                 |  2 +-
 src/crewai/cli/cli.py                                  |  6 +++---
 src/crewai/cli/create_crew.py                          | 10 +++++-----
 src/crewai/cli/templates/crew/pyproject.toml           |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml           |  2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml       |  2 +-
 .../cli/templates/pipeline_router/pyproject.toml       |  2 +-
 src/crewai/cli/templates/tool/pyproject.toml           |  2 +-
 uv.lock                                                |  2 +-
 10 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 929e68b9e..36d43d90f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.76.0"
+version = "0.76.1"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index a1b95951d..92e85f98e 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.76.0"
+__version__ = "0.76.1"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 48bb26ff9..460128634 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -32,12 +32,12 @@ def crewai():
 @crewai.command()
 @click.argument("type", type=click.Choice(["crew", "pipeline", "flow"]))
 @click.argument("name")
-@click.option("--skip-provider", is_flag=True, help="Skip provider validation")
 @click.option("--provider", type=str, help="The provider to use for the crew")
-def create(type, name, provider, skip_provider_validation=False):
+@click.option("--skip_provider", is_flag=True, help="Skip provider validation")
+def create(type, name, provider, skip_provider=False):
     """Create a new crew, pipeline, or flow."""
     if type == "crew":
-        create_crew(name, provider, skip_provider_validation)
+        create_crew(name, provider, skip_provider)
     elif type == "pipeline":
         create_pipeline(name)
     elif type == "flow":
diff --git a/src/crewai/cli/create_crew.py b/src/crewai/cli/create_crew.py
index 90184ec31..5767b82a1 100644
--- a/src/crewai/cli/create_crew.py
+++ b/src/crewai/cli/create_crew.py
@@ -81,12 +81,10 @@ def copy_template_files(folder_path, name, class_name, parent_folder):
             copy_template(src_file, dst_file, name, class_name, folder_path.name)
 
 
-def create_crew(
-    name, provider=None, skip_provider_validation=False, parent_folder=None
-):
+def create_crew(name, provider=None, skip_provider=False, parent_folder=None):
     folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)
     env_vars = load_env_vars(folder_path)
-    if not skip_provider_validation:
+    if not skip_provider:
         if not provider:
             provider_models = get_provider_data()
             if not provider_models:
@@ -155,7 +153,9 @@ def create_crew(
             write_env_file(folder_path, env_vars)
             click.secho("API key saved to .env file", fg="green")
         else:
-            click.secho("No API key provided. Skipping .env file creation.", fg="yellow")
+            click.secho(
+                "No API key provided. Skipping .env file creation.", fg="yellow"
+            )
 
         env_vars["MODEL"] = selected_model
         click.secho(f"Selected model: {selected_model}", fg="green")
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 6852f1292..0c169013c 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.0,<1.0.0"
+    "crewai[tools]>=0.76.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 88a313ae9..3b6d7d54d 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.0,<1.0.0",
+    "crewai[tools]>=0.76.1,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index b2a4d36d4..6b6366cb7 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.76.0,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.76.1,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index f7da504cf..1c6b6bc3b 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.0,<1.0.0"
+    "crewai[tools]>=0.76.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 8f7194b7f..712c35969 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.0"
+    "crewai[tools]>=0.76.1"
 ]
 
diff --git a/uv.lock b/uv.lock
index 9d07a5bae..9743146f8 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.76.0"
+version = "0.76.1"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 8bc07e60711b79ad97d30463f3964f90f5a71c06 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Wed, 23 Oct 2024 18:10:37 -0300
Subject: [PATCH 019/126] new version

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 uv.lock                                                 | 2 +-
 8 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 36d43d90f..85a296867 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.76.1"
+version = "0.76.2"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 92e85f98e..5160aa77f 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.76.1"
+__version__ = "0.76.2"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 0c169013c..ed32aa600 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.1,<1.0.0"
+    "crewai[tools]>=0.76.2,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 3b6d7d54d..815e8b205 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.1,<1.0.0",
+    "crewai[tools]>=0.76.2,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 6b6366cb7..b4e74abea 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.76.1,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.76.2,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 1c6b6bc3b..bd487ce95 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.1,<1.0.0"
+    "crewai[tools]>=0.76.2,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 712c35969..360a940ed 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.1"
+    "crewai[tools]>=0.76.2"
 ]
 
diff --git a/uv.lock b/uv.lock
index 9743146f8..f242185db 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.76.1"
+version = "0.76.2"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 201e652fa2bdb44123609e00c0a2f33f5ad154cb Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Thu, 24 Oct 2024 14:44:30 -0400
Subject: [PATCH 020/126] update plot command (#1504)

---
 src/crewai/cli/plot_flow.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/crewai/cli/plot_flow.py b/src/crewai/cli/plot_flow.py
index 2183a02ec..848c55d69 100644
--- a/src/crewai/cli/plot_flow.py
+++ b/src/crewai/cli/plot_flow.py
@@ -7,7 +7,7 @@ def plot_flow() -> None:
     """
     Plot the flow by running a command in the UV environment.
     """
-    command = ["uv", "run", "plot_flow"]
+    command = ["uv", "run", "plot"]
 
     try:
         result = subprocess.run(command, capture_output=False, text=True, check=True)

From 4589d6fe9d976b491a86bdf0aca1d9972077b900 Mon Sep 17 00:00:00 2001
From: Eduardo Chiarotti <dudumelgaco@hotmail.com>
Date: Fri, 25 Oct 2024 10:33:21 -0300
Subject: [PATCH 021/126] feat: add tomli so we can support 3.10 (#1506)

* feat: add tomli so we can support 3.10

* feat: add validation for poetry data
---
 pyproject.toml                |  1 +
 src/crewai/cli/run_crew.py    | 13 ++++--------
 src/crewai/cli/update_crew.py | 40 +++++++++++++++++------------------
 src/crewai/cli/utils.py       |  8 +++++++
 uv.lock                       |  2 ++
 5 files changed, 35 insertions(+), 29 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 85a296867..ef8181cbc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -28,6 +28,7 @@ dependencies = [
     "uv>=0.4.25",
     "tomli-w>=1.1.0",
     "chromadb>=0.4.24",
+    "tomli>=2.0.2",
 ]
 
 [project.urls]
diff --git a/src/crewai/cli/run_crew.py b/src/crewai/cli/run_crew.py
index 829d8ed95..20d6aed01 100644
--- a/src/crewai/cli/run_crew.py
+++ b/src/crewai/cli/run_crew.py
@@ -1,10 +1,9 @@
 import subprocess
 
 import click
-import tomllib
 from packaging import version
 
-from crewai.cli.utils import get_crewai_version
+from crewai.cli.utils import get_crewai_version, read_toml
 
 
 def run_crew() -> None:
@@ -15,10 +14,9 @@ def run_crew() -> None:
     crewai_version = get_crewai_version()
     min_required_version = "0.71.0"
 
-    with open("pyproject.toml", "rb") as f:
-        data = tomllib.load(f)
+    pyproject_data = read_toml()
 
-    if data.get("tool", {}).get("poetry") and (
+    if pyproject_data.get("tool", {}).get("poetry") and (
         version.parse(crewai_version) < version.parse(min_required_version)
     ):
         click.secho(
@@ -35,10 +33,7 @@ def run_crew() -> None:
         click.echo(f"An error occurred while running the crew: {e}", err=True)
         click.echo(e.output, err=True, nl=True)
 
-        with open("pyproject.toml", "rb") as f:
-            data = tomllib.load(f)
-
-        if data.get("tool", {}).get("poetry"):
+        if pyproject_data.get("tool", {}).get("poetry"):
             click.secho(
                 "It's possible that you are using an old version of crewAI that uses poetry, please run `crewai update` to update your pyproject.toml to use uv.",
                 fg="yellow",
diff --git a/src/crewai/cli/update_crew.py b/src/crewai/cli/update_crew.py
index d38e11a25..e7ed69aa1 100644
--- a/src/crewai/cli/update_crew.py
+++ b/src/crewai/cli/update_crew.py
@@ -2,7 +2,8 @@ import os
 import shutil
 
 import tomli_w
-import tomllib
+
+from crewai.cli.utils import read_toml
 
 
 def update_crew() -> None:
@@ -18,10 +19,9 @@ def migrate_pyproject(input_file, output_file):
     And it will be used to migrate the pyproject.toml to the new format when uv is used.
     When the time comes that uv supports the new format, this function will be deprecated.
     """
-
+    poetry_data = {}
     # Read the input pyproject.toml
-    with open(input_file, "rb") as f:
-        pyproject = tomllib.load(f)
+    pyproject_data = read_toml()
 
     # Initialize the new project structure
     new_pyproject = {
@@ -30,30 +30,30 @@ def migrate_pyproject(input_file, output_file):
     }
 
     # Migrate project metadata
-    if "tool" in pyproject and "poetry" in pyproject["tool"]:
-        poetry = pyproject["tool"]["poetry"]
-        new_pyproject["project"]["name"] = poetry.get("name")
-        new_pyproject["project"]["version"] = poetry.get("version")
-        new_pyproject["project"]["description"] = poetry.get("description")
+    if "tool" in pyproject_data and "poetry" in pyproject_data["tool"]:
+        poetry_data = pyproject_data["tool"]["poetry"]
+        new_pyproject["project"]["name"] = poetry_data.get("name")
+        new_pyproject["project"]["version"] = poetry_data.get("version")
+        new_pyproject["project"]["description"] = poetry_data.get("description")
         new_pyproject["project"]["authors"] = [
             {
                 "name": author.split("<")[0].strip(),
                 "email": author.split("<")[1].strip(">").strip(),
             }
-            for author in poetry.get("authors", [])
+            for author in poetry_data.get("authors", [])
         ]
-        new_pyproject["project"]["requires-python"] = poetry.get("python")
+        new_pyproject["project"]["requires-python"] = poetry_data.get("python")
     else:
         # If it's already in the new format, just copy the project section
-        new_pyproject["project"] = pyproject.get("project", {})
+        new_pyproject["project"] = pyproject_data.get("project", {})
 
     # Migrate or copy dependencies
     if "dependencies" in new_pyproject["project"]:
         # If dependencies are already in the new format, keep them as is
         pass
-    elif "dependencies" in poetry:
+    elif poetry_data and "dependencies" in poetry_data:
         new_pyproject["project"]["dependencies"] = []
-        for dep, version in poetry["dependencies"].items():
+        for dep, version in poetry_data["dependencies"].items():
             if isinstance(version, dict):  # Handle extras
                 extras = ",".join(version.get("extras", []))
                 new_dep = f"{dep}[{extras}]"
@@ -67,10 +67,10 @@ def migrate_pyproject(input_file, output_file):
             new_pyproject["project"]["dependencies"].append(new_dep)
 
     # Migrate or copy scripts
-    if "scripts" in poetry:
-        new_pyproject["project"]["scripts"] = poetry["scripts"]
-    elif "scripts" in pyproject.get("project", {}):
-        new_pyproject["project"]["scripts"] = pyproject["project"]["scripts"]
+    if poetry_data and "scripts" in poetry_data:
+        new_pyproject["project"]["scripts"] = poetry_data["scripts"]
+    elif pyproject_data.get("project", {}) and "scripts" in pyproject_data["project"]:
+        new_pyproject["project"]["scripts"] = pyproject_data["project"]["scripts"]
     else:
         new_pyproject["project"]["scripts"] = {}
 
@@ -87,8 +87,8 @@ def migrate_pyproject(input_file, output_file):
         new_pyproject["project"]["scripts"]["run_crew"] = f"{module_name}.main:run"
 
     # Migrate optional dependencies
-    if "extras" in poetry:
-        new_pyproject["project"]["optional-dependencies"] = poetry["extras"]
+    if poetry_data and "extras" in poetry_data:
+        new_pyproject["project"]["optional-dependencies"] = poetry_data["extras"]
 
     # Backup the old pyproject.toml
     backup_file = "pyproject-old.toml"
diff --git a/src/crewai/cli/utils.py b/src/crewai/cli/utils.py
index c32113faa..25da9e31a 100644
--- a/src/crewai/cli/utils.py
+++ b/src/crewai/cli/utils.py
@@ -6,6 +6,7 @@ from functools import reduce
 from typing import Any, Dict, List
 
 import click
+import tomli
 from rich.console import Console
 
 from crewai.cli.authentication.utils import TokenManager
@@ -54,6 +55,13 @@ def simple_toml_parser(content):
     return result
 
 
+def read_toml(file_path: str = "pyproject.toml"):
+    """Read the content of a TOML file and return it as a dictionary."""
+    with open(file_path, "rb") as f:
+        toml_dict = tomli.load(f)
+    return toml_dict
+
+
 def parse_toml(content):
     if sys.version_info >= (3, 11):
         return tomllib.loads(content)
diff --git a/uv.lock b/uv.lock
index f242185db..df2572402 100644
--- a/uv.lock
+++ b/uv.lock
@@ -625,6 +625,7 @@ dependencies = [
     { name = "python-dotenv" },
     { name = "pyvis" },
     { name = "regex" },
+    { name = "tomli" },
     { name = "tomli-w" },
     { name = "uv" },
 ]
@@ -679,6 +680,7 @@ requires-dist = [
     { name = "python-dotenv", specifier = ">=1.0.0" },
     { name = "pyvis", specifier = ">=0.3.2" },
     { name = "regex", specifier = ">=2024.9.11" },
+    { name = "tomli", specifier = ">=2.0.2" },
     { name = "tomli-w", specifier = ">=1.1.0" },
     { name = "uv", specifier = ">=0.4.25" },
 ]

From f29f4abdd7ea4d3b4afeb8e1b403360ad7309ace Mon Sep 17 00:00:00 2001
From: Vini Brasil <vini@hey.com>
Date: Fri, 25 Oct 2024 11:20:41 -0300
Subject: [PATCH 022/126] Forward install command options to `uv sync` (#1510)

Allow passing additional options from `crewai install` directly to
`uv sync`. This enables commands like `crewai install --locked` to work
as expected by forwarding all flags and options to the underlying uv
command.
---
 src/crewai/cli/cli.py          | 10 +++++++---
 src/crewai/cli/install_crew.py |  5 +++--
 2 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 460128634..1ea2ef4e2 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -178,10 +178,14 @@ def test(n_iterations: int, model: str):
     evaluate_crew(n_iterations, model)
 
 
-@crewai.command()
-def install():
+@crewai.command(context_settings=dict(
+    ignore_unknown_options=True,
+    allow_extra_args=True,
+))
+@click.pass_context
+def install(context):
     """Install the Crew."""
-    install_crew()
+    install_crew(context.args)
 
 
 @crewai.command()
diff --git a/src/crewai/cli/install_crew.py b/src/crewai/cli/install_crew.py
index 35206e5eb..d1d0ab9da 100644
--- a/src/crewai/cli/install_crew.py
+++ b/src/crewai/cli/install_crew.py
@@ -3,12 +3,13 @@ import subprocess
 import click
 
 
-def install_crew() -> None:
+def install_crew(proxy_options: list[str]) -> None:
     """
     Install the crew by running the UV command to lock and install.
     """
     try:
-        subprocess.run(["uv", "sync"], check=True, capture_output=False, text=True)
+        command = ["uv", "sync"] + proxy_options
+        subprocess.run(command, check=True, capture_output=False, text=True)
 
     except subprocess.CalledProcessError as e:
         click.echo(f"An error occurred while running the crew: {e}", err=True)

From 26afee9bed0b11f6b22c894a68701c3a854c96f5 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Fri, 25 Oct 2024 18:42:55 -0400
Subject: [PATCH 023/126] improve tool text description and args (#1512)

* improve tool text descriptoin and args

* fix lint

* Drop print

* add back in docstring
---
 src/crewai/agent.py | 27 +++++++++++++--------------
 1 file changed, 13 insertions(+), 14 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index f68d6401b..937710f59 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -1,7 +1,6 @@
 import os
 import shutil
 import subprocess
-from inspect import signature
 from typing import Any, List, Literal, Optional, Union
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
@@ -395,26 +394,26 @@ class Agent(BaseAgent):
     def _render_text_description_and_args(self, tools: List[Any]) -> str:
         """Render the tool name, description, and args in plain text.
 
-        Output will be in the format of:
+            Output will be in the format of:
 
-        .. code-block:: markdown
+            .. code-block:: markdown
 
             search: This tool is used for search, args: {"query": {"type": "string"}}
             calculator: This tool is used for math, \
-    args: {"expression": {"type": "string"}}
+            args: {"expression": {"type": "string"}}
         """
         tool_strings = []
         for tool in tools:
-            args_schema = str(tool.model_fields)
-            if hasattr(tool, "func") and tool.func:
-                sig = signature(tool.func)
-                description = (
-                    f"Tool Name: {tool.name}{sig}\nTool Description: {tool.description}"
-                )
-            else:
-                description = (
-                    f"Tool Name: {tool.name}\nTool Description: {tool.description}"
-                )
+            args_schema = {
+                name: {
+                    "description": field.description,
+                    "type": field.annotation.__name__,
+                }
+                for name, field in tool.args_schema.model_fields.items()
+            }
+            description = (
+                f"Tool Name: {tool.name}\nTool Description: {tool.description}"
+            )
             tool_strings.append(f"{description}\nTool Arguments: {args_schema}")
 
         return "\n".join(tool_strings)

From 04bcfa6e2d7dcc6995ff381b6fc5396c3281117d Mon Sep 17 00:00:00 2001
From: Brandon Hancock <brandon@brandonhancock.io>
Date: Mon, 28 Oct 2024 09:40:56 -0500
Subject: [PATCH 024/126] Improve tooling docs

---
 docs/how-to/create-custom-tools.mdx                    |  9 ++++++++-
 src/crewai/cli/templates/crew/tools/custom_tool.py     |  6 ++++++
 src/crewai/cli/templates/flow/tools/custom_tool.py     | 10 ++++++++++
 src/crewai/cli/templates/pipeline/tools/custom_tool.py |  6 ++++++
 .../cli/templates/pipeline_router/tools/custom_tool.py |  6 ++++++
 5 files changed, 36 insertions(+), 1 deletion(-)

diff --git a/docs/how-to/create-custom-tools.mdx b/docs/how-to/create-custom-tools.mdx
index 31fd09e3f..2caab716b 100644
--- a/docs/how-to/create-custom-tools.mdx
+++ b/docs/how-to/create-custom-tools.mdx
@@ -20,14 +20,21 @@ pip install 'crewai[tools]'
 
 ### Subclassing `BaseTool`
 
-To create a personalized tool, inherit from `BaseTool` and define the necessary attributes and the `_run` method.
+To create a personalized tool, inherit from `BaseTool` and define the necessary attributes, including the `args_schema` for input validation, and the `_run` method.
 
 ```python Code
+from typing import Type
 from crewai_tools import BaseTool
+from pydantic import BaseModel, Field
+
+class MyToolInput(BaseModel):
+    """Input schema for MyCustomTool."""
+    argument: str = Field(..., description="Description of the argument.")
 
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
     description: str = "What this tool does. It's vital for effective utilization."
+    args_schema: Type[BaseModel] = MyToolInput
 
     def _run(self, argument: str) -> str:
         # Your tool's logic here
diff --git a/src/crewai/cli/templates/crew/tools/custom_tool.py b/src/crewai/cli/templates/crew/tools/custom_tool.py
index b12529303..d38318051 100644
--- a/src/crewai/cli/templates/crew/tools/custom_tool.py
+++ b/src/crewai/cli/templates/crew/tools/custom_tool.py
@@ -1,11 +1,17 @@
+from typing import Type
 from crewai_tools import BaseTool
+from pydantic import BaseModel, Field
 
+class MyCustomToolInput(BaseModel):
+    """Input schema for MyCustomTool."""
+    argument: str = Field(..., description="Description of the argument.")
 
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
     description: str = (
         "Clear description for what this tool is useful for, you agent will need this information to use it."
     )
+    args_schema: Type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here
diff --git a/src/crewai/cli/templates/flow/tools/custom_tool.py b/src/crewai/cli/templates/flow/tools/custom_tool.py
index b12529303..030e575ec 100644
--- a/src/crewai/cli/templates/flow/tools/custom_tool.py
+++ b/src/crewai/cli/templates/flow/tools/custom_tool.py
@@ -1,4 +1,13 @@
+from typing import Type
+
 from crewai_tools import BaseTool
+from pydantic import BaseModel, Field
+
+
+class MyCustomToolInput(BaseModel):
+    """Input schema for MyCustomTool."""
+
+    argument: str = Field(..., description="Description of the argument.")
 
 
 class MyCustomTool(BaseTool):
@@ -6,6 +15,7 @@ class MyCustomTool(BaseTool):
     description: str = (
         "Clear description for what this tool is useful for, you agent will need this information to use it."
     )
+    args_schema: Type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here
diff --git a/src/crewai/cli/templates/pipeline/tools/custom_tool.py b/src/crewai/cli/templates/pipeline/tools/custom_tool.py
index b12529303..d38318051 100644
--- a/src/crewai/cli/templates/pipeline/tools/custom_tool.py
+++ b/src/crewai/cli/templates/pipeline/tools/custom_tool.py
@@ -1,11 +1,17 @@
+from typing import Type
 from crewai_tools import BaseTool
+from pydantic import BaseModel, Field
 
+class MyCustomToolInput(BaseModel):
+    """Input schema for MyCustomTool."""
+    argument: str = Field(..., description="Description of the argument.")
 
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
     description: str = (
         "Clear description for what this tool is useful for, you agent will need this information to use it."
     )
+    args_schema: Type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here
diff --git a/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py b/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
index b12529303..d38318051 100644
--- a/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
+++ b/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
@@ -1,11 +1,17 @@
+from typing import Type
 from crewai_tools import BaseTool
+from pydantic import BaseModel, Field
 
+class MyCustomToolInput(BaseModel):
+    """Input schema for MyCustomTool."""
+    argument: str = Field(..., description="Description of the argument.")
 
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
     description: str = (
         "Clear description for what this tool is useful for, you agent will need this information to use it."
     )
+    args_schema: Type[BaseModel] = MyCustomToolInput
 
     def _run(self, argument: str) -> str:
         # Implementation goes here

From 500072d855d4aef709f04cf6b6944df291367238 Mon Sep 17 00:00:00 2001
From: Brandon Hancock <brandon@brandonhancock.io>
Date: Mon, 28 Oct 2024 12:17:44 -0500
Subject: [PATCH 025/126] Update flow docs to talk about self evaluation
 example

---
 docs/concepts/flows.mdx | 105 +++++++++++++++++++++++++++++++++++++++-
 1 file changed, 103 insertions(+), 2 deletions(-)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index dee6fd4fa..b2e7b600f 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -599,9 +599,110 @@ The generated plot will display nodes representing the tasks in your flow, with
 
 By visualizing your flows, you can gain a clearer understanding of the workflow's structure, making it easier to debug, optimize, and communicate your AI processes to others.
 
-### Conclusion
 
-Plotting your flows is a powerful feature of CrewAI that enhances your ability to design and manage complex AI workflows. Whether you choose to use the `plot()` method or the command line, generating plots will provide you with a visual representation of your workflows, aiding in both development and presentation.
+## Advanced
+
+In this section, we explore more complex use cases of CrewAI Flows, starting with a self-evaluation loop. This pattern is crucial for developing AI systems that can iteratively improve their outputs through feedback.
+
+### 1) Self-Evaluation Loop
+
+The self-evaluation loop is a powerful pattern that allows AI workflows to automatically assess and refine their outputs. This example demonstrates how to set up a flow that generates content, evaluates it, and iterates based on feedback until the desired quality is achieved.
+
+#### Overview
+
+The self-evaluation loop involves two main Crews:
+
+1. **ShakespeareanXPostCrew**: Generates a Shakespearean-style post on a given topic.
+2. **XPostReviewCrew**: Evaluates the generated post, providing feedback on its validity and quality.
+
+The process iterates until the post meets the criteria or a maximum retry limit is reached. This approach ensures high-quality outputs through iterative refinement.
+
+#### Importance
+
+This pattern is essential for building robust AI systems that can adapt and improve over time. By automating the evaluation and feedback loop, developers can ensure that their AI workflows produce reliable and high-quality results.
+
+#### Main Code Highlights
+
+Below is the `main.py` file for the self-evaluation loop flow:
+
+```python
+from typing import Optional
+from crewai.flow.flow import Flow, listen, router, start
+from pydantic import BaseModel
+from self_evaluation_loop_flow.crews.shakespeare_crew.shakespeare_crew import (
+    ShakespeareanXPostCrew,
+)
+from self_evaluation_loop_flow.crews.x_post_review_crew.x_post_review_crew import (
+    XPostReviewCrew,
+)
+
+class ShakespeareXPostFlowState(BaseModel):
+    x_post: str = ""
+    feedback: Optional[str] = None
+    valid: bool = False
+    retry_count: int = 0
+
+class ShakespeareXPostFlow(Flow[ShakespeareXPostFlowState]):
+
+    @start("retry")
+    def generate_shakespeare_x_post(self):
+        print("Generating Shakespearean X post")
+        topic = "Flying cars"
+        result = (
+            ShakespeareanXPostCrew()
+            .crew()
+            .kickoff(inputs={"topic": topic, "feedback": self.state.feedback})
+        )
+        print("X post generated", result.raw)
+        self.state.x_post = result.raw
+
+    @router(generate_shakespeare_x_post)
+    def evaluate_x_post(self):
+        if self.state.retry_count > 3:
+            return "max_retry_exceeded"
+        result = XPostReviewCrew().crew().kickoff(inputs={"x_post": self.state.x_post})
+        self.state.valid = result["valid"]
+        self.state.feedback = result["feedback"]
+        print("valid", self.state.valid)
+        print("feedback", self.state.feedback)
+        self.state.retry_count += 1
+        if self.state.valid:
+            return "complete"
+        return "retry"
+
+    @listen("complete")
+    def save_result(self):
+        print("X post is valid")
+        print("X post:", self.state.x_post)
+        with open("x_post.txt", "w") as file:
+            file.write(self.state.x_post)
+
+    @listen("max_retry_exceeded")
+    def max_retry_exceeded_exit(self):
+        print("Max retry count exceeded")
+        print("X post:", self.state.x_post)
+        print("Feedback:", self.state.feedback)
+
+def kickoff():
+    shakespeare_flow = ShakespeareXPostFlow()
+    shakespeare_flow.kickoff()
+
+def plot():
+    shakespeare_flow = ShakespeareXPostFlow()
+    shakespeare_flow.plot()
+
+if __name__ == "__main__":
+    kickoff()
+```
+
+#### Code Highlights
+
+- **Retry Mechanism**: The flow uses a retry mechanism to regenerate the post if it doesn't meet the criteria, up to a maximum of three retries.
+- **Feedback Loop**: Feedback from the `XPostReviewCrew` is used to refine the post iteratively.
+- **State Management**: The flow maintains state using a Pydantic model, ensuring type safety and clarity.
+
+For a complete example and further details, please refer to the [Self Evaluation Loop Flow repository](https://github.com/crewAIInc/crewAI-examples/tree/main/self_evaluation_loop_flow).
+
 
 ## Next Steps
 

From fa9949b9d0af809299678f02f1d827d2038514b4 Mon Sep 17 00:00:00 2001
From: Brandon Hancock <brandon@brandonhancock.io>
Date: Mon, 28 Oct 2024 12:18:03 -0500
Subject: [PATCH 026/126] Update flow docs to talk about self evaluation
 example

---
 docs/concepts/flows.mdx | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index b2e7b600f..093e7b6b7 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -706,7 +706,7 @@ For a complete example and further details, please refer to the [Self Evaluation
 
 ## Next Steps
 
-If you're interested in exploring additional examples of flows, we have a variety of recommendations in our examples repository. Here are four specific flow examples, each showcasing unique use cases to help you match your current problem type to a specific example:
+If you're interested in exploring additional examples of flows, we have a variety of recommendations in our examples repository. Here are five specific flow examples, each showcasing unique use cases to help you match your current problem type to a specific example:
 
 1. **Email Auto Responder Flow**: This example demonstrates an infinite loop where a background job continually runs to automate email responses. It's a great use case for tasks that need to be performed repeatedly without manual intervention. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/email_auto_responder_flow)
 
@@ -716,6 +716,8 @@ If you're interested in exploring additional examples of flows, we have a variet
 
 4. **Meeting Assistant Flow**: This flow demonstrates how to broadcast one event to trigger multiple follow-up actions. For instance, after a meeting is completed, the flow can update a Trello board, send a Slack message, and save the results. It's a great example of handling multiple outcomes from a single event, making it ideal for comprehensive task management and notification systems. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/meeting_assistant_flow)
 
+5. **Self Evaluation Loop Flow**: This flow demonstrates a self-evaluation loop where AI workflows automatically assess and refine their outputs through feedback. It involves generating content, evaluating it, and iterating until the desired quality is achieved. This pattern is crucial for developing robust AI systems that can adapt and improve over time. [View Example](https://github.com/joaomdmoura/crewai)
+
 By exploring these examples, you can gain insights into how to leverage CrewAI Flows for various use cases, from automating repetitive tasks to managing complex, multi-step processes with dynamic decision-making and human feedback.
 
 Also, check out our YouTube video on how to use flows in CrewAI below!

From 048aa6cbcc108166f9639a835b286899cf14a031 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 29 Oct 2024 10:40:49 -0400
Subject: [PATCH 027/126] Update flows.mdx - Fix link

---
 docs/concepts/flows.mdx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index 093e7b6b7..bf9ce8e67 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -716,7 +716,7 @@ If you're interested in exploring additional examples of flows, we have a variet
 
 4. **Meeting Assistant Flow**: This flow demonstrates how to broadcast one event to trigger multiple follow-up actions. For instance, after a meeting is completed, the flow can update a Trello board, send a Slack message, and save the results. It's a great example of handling multiple outcomes from a single event, making it ideal for comprehensive task management and notification systems. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/meeting_assistant_flow)
 
-5. **Self Evaluation Loop Flow**: This flow demonstrates a self-evaluation loop where AI workflows automatically assess and refine their outputs through feedback. It involves generating content, evaluating it, and iterating until the desired quality is achieved. This pattern is crucial for developing robust AI systems that can adapt and improve over time. [View Example](https://github.com/joaomdmoura/crewai)
+5. **Self Evaluation Loop Flow**: This flow demonstrates a self-evaluation loop where AI workflows automatically assess and refine their outputs through feedback. It involves generating content, evaluating it, and iterating until the desired quality is achieved. This pattern is crucial for developing robust AI systems that can adapt and improve over time. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/self_evaluation_loop_flow)
 
 By exploring these examples, you can gain insights into how to leverage CrewAI Flows for various use cases, from automating repetitive tasks to managing complex, multi-step processes with dynamic decision-making and human feedback.
 

From b43f3987ecae1c2867a2209a3f6de89fe444cabe Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 29 Oct 2024 11:53:48 -0400
Subject: [PATCH 028/126] Update flows cli to allow you to easily add
 additional crews to a flow (#1525)

* Update flows cli to allow you to easily add additional crews to a flow

* fix failing test

* adding more error logs to test thats failing

* try again
---
 docs/concepts/flows.mdx            | 34 +++++++++++++++
 src/crewai/cli/add_crew_to_flow.py | 70 ++++++++++++++++++++++++++++++
 src/crewai/cli/cli.py              | 19 ++++++--
 tests/cli/cli_test.py              | 42 ++++++++++++++++++
 4 files changed, 161 insertions(+), 4 deletions(-)
 create mode 100644 src/crewai/cli/add_crew_to_flow.py

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index bf9ce8e67..c86776982 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -560,6 +560,40 @@ uv run kickoff
 
 The flow will execute, and you should see the output in the console.
 
+
+### Adding Additional Crews Using the CLI
+
+Once you have created your initial flow, you can easily add additional crews to your project using the CLI. This allows you to expand your flow's capabilities by integrating new crews without starting from scratch.
+
+To add a new crew to your existing flow, use the following command:
+
+```bash
+crewai flow add-crew <crew_name>
+```
+
+This command will create a new directory for your crew within the `crews` folder of your flow project. It will include the necessary configuration files and a crew definition file, similar to the initial setup.
+
+#### Folder Structure
+
+After adding a new crew, your folder structure will look like this:
+
+name_of_flow/
+├── crews/
+│   ├── poem_crew/
+│   │   ├── config/
+│   │   │   ├── agents.yaml
+│   │   │   └── tasks.yaml
+│   │   └── poem_crew.py
+│   └── name_of_crew/
+│       ├── config/
+│       │   ├── agents.yaml
+│       │   └── tasks.yaml
+│       └── name_of_crew.py
+
+You can then customize the `agents.yaml` and `tasks.yaml` files to define the agents and tasks for your new crew. The `name_of_crew.py` file will contain the crew's logic, which you can modify to suit your needs.
+
+By using the CLI to add additional crews, you can efficiently build complex AI workflows that leverage multiple crews working together.
+
 ## Plot Flows
 
 Visualizing your AI workflows can provide valuable insights into the structure and execution paths of your flows. CrewAI offers a powerful visualization tool that allows you to generate interactive plots of your flows, making it easier to understand and optimize your AI workflows.
diff --git a/src/crewai/cli/add_crew_to_flow.py b/src/crewai/cli/add_crew_to_flow.py
new file mode 100644
index 000000000..e4901fa89
--- /dev/null
+++ b/src/crewai/cli/add_crew_to_flow.py
@@ -0,0 +1,70 @@
+from pathlib import Path
+
+import click
+
+from crewai.cli.utils import copy_template
+
+
+def add_crew_to_flow(crew_name: str) -> None:
+    """Add a new crew to the current flow."""
+    # Check if pyproject.toml exists in the current directory
+    if not Path("pyproject.toml").exists():
+        print("This command must be run from the root of a flow project.")
+        raise click.ClickException(
+            "This command must be run from the root of a flow project."
+        )
+
+    # Determine the flow folder based on the current directory
+    flow_folder = Path.cwd()
+    crews_folder = flow_folder / "src" / flow_folder.name / "crews"
+
+    if not crews_folder.exists():
+        print("Crews folder does not exist in the current flow.")
+        raise click.ClickException("Crews folder does not exist in the current flow.")
+
+    # Create the crew within the flow's crews directory
+    create_embedded_crew(crew_name, parent_folder=crews_folder)
+
+    click.echo(
+        f"Crew {crew_name} added to the current flow successfully!",
+    )
+
+
+def create_embedded_crew(crew_name: str, parent_folder: Path) -> None:
+    """Create a new crew within an existing flow project."""
+    folder_name = crew_name.replace(" ", "_").replace("-", "_").lower()
+    class_name = crew_name.replace("_", " ").replace("-", " ").title().replace(" ", "")
+
+    crew_folder = parent_folder / folder_name
+
+    if crew_folder.exists():
+        if not click.confirm(
+            f"Crew {folder_name} already exists. Do you want to override it?"
+        ):
+            click.secho("Operation cancelled.", fg="yellow")
+            return
+        click.secho(f"Overriding crew {folder_name}...", fg="green", bold=True)
+    else:
+        click.secho(f"Creating crew {folder_name}...", fg="green", bold=True)
+        crew_folder.mkdir(parents=True)
+
+    # Create config and crew.py files
+    config_folder = crew_folder / "config"
+    config_folder.mkdir(exist_ok=True)
+
+    templates_dir = Path(__file__).parent / "templates" / "crew"
+    config_template_files = ["agents.yaml", "tasks.yaml"]
+    crew_template_file = f"{folder_name}_crew.py"  # Updated file name
+
+    for file_name in config_template_files:
+        src_file = templates_dir / "config" / file_name
+        dst_file = config_folder / file_name
+        copy_template(src_file, dst_file, crew_name, class_name, folder_name)
+
+    src_file = templates_dir / "crew.py"
+    dst_file = crew_folder / crew_template_file
+    copy_template(src_file, dst_file, crew_name, class_name, folder_name)
+
+    click.secho(
+        f"Crew {crew_name} added to the flow successfully!", fg="green", bold=True
+    )
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 1ea2ef4e2..0f43ff3f4 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -3,6 +3,7 @@ from typing import Optional
 import click
 import pkg_resources
 
+from crewai.cli.add_crew_to_flow import add_crew_to_flow
 from crewai.cli.create_crew import create_crew
 from crewai.cli.create_flow import create_flow
 from crewai.cli.create_pipeline import create_pipeline
@@ -178,10 +179,12 @@ def test(n_iterations: int, model: str):
     evaluate_crew(n_iterations, model)
 
 
-@crewai.command(context_settings=dict(
-    ignore_unknown_options=True,
-    allow_extra_args=True,
-))
+@crewai.command(
+    context_settings=dict(
+        ignore_unknown_options=True,
+        allow_extra_args=True,
+    )
+)
 @click.pass_context
 def install(context):
     """Install the Crew."""
@@ -324,5 +327,13 @@ def flow_plot():
     plot_flow()
 
 
+@flow.command(name="add-crew")
+@click.argument("crew_name")
+def flow_add_crew(crew_name):
+    """Add a crew to an existing flow."""
+    click.echo(f"Adding crew {crew_name} to the flow")
+    add_crew_to_flow(crew_name)
+
+
 if __name__ == "__main__":
     crewai()
diff --git a/tests/cli/cli_test.py b/tests/cli/cli_test.py
index b2fb8d0e5..05e1cf03a 100644
--- a/tests/cli/cli_test.py
+++ b/tests/cli/cli_test.py
@@ -1,7 +1,9 @@
+from pathlib import Path
 from unittest import mock
 
 import pytest
 from click.testing import CliRunner
+
 from crewai.cli.cli import (
     deploy_create,
     deploy_list,
@@ -9,6 +11,7 @@ from crewai.cli.cli import (
     deploy_push,
     deploy_remove,
     deply_status,
+    flow_add_crew,
     reset_memories,
     signup,
     test,
@@ -277,3 +280,42 @@ def test_deploy_remove_no_uuid(command, runner):
 
     assert result.exit_code == 0
     mock_deploy.remove_crew.assert_called_once_with(uuid=None)
+
+
+@mock.patch("crewai.cli.add_crew_to_flow.create_embedded_crew")
+@mock.patch("pathlib.Path.exists", return_value=True)  # Mock the existence check
+def test_flow_add_crew(mock_path_exists, mock_create_embedded_crew, runner):
+    crew_name = "new_crew"
+    result = runner.invoke(flow_add_crew, [crew_name])
+
+    # Log the output for debugging
+    print(result.output)
+
+    assert result.exit_code == 0, f"Command failed with output: {result.output}"
+    assert f"Adding crew {crew_name} to the flow" in result.output
+
+    # Verify that create_embedded_crew was called with the correct arguments
+    mock_create_embedded_crew.assert_called_once()
+    call_args, call_kwargs = mock_create_embedded_crew.call_args
+    assert call_args[0] == crew_name
+    assert "parent_folder" in call_kwargs
+    assert isinstance(call_kwargs["parent_folder"], Path)
+
+
+def test_add_crew_to_flow_not_in_root(runner):
+    # Simulate not being in the root of a flow project
+    with mock.patch("pathlib.Path.exists", autospec=True) as mock_exists:
+        # Mock Path.exists to return False when checking for pyproject.toml
+        def exists_side_effect(self):
+            if self.name == "pyproject.toml":
+                return False  # Simulate that pyproject.toml does not exist
+            return True  # All other paths exist
+
+        mock_exists.side_effect = exists_side_effect
+
+        result = runner.invoke(flow_add_crew, ["new_crew"])
+
+        assert result.exit_code != 0
+        assert "This command must be run from the root of a flow project." in str(
+            result.output
+        )

From cdfbd5f62b23ed8753a48bd8df1a0ef4dbf68363 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 29 Oct 2024 18:36:53 -0400
Subject: [PATCH 029/126] Bugfix/flows with multiple starts plus ands breaking
 (#1531)

* bugfix/flows-with-multiple-starts-plus-ands-breaking

* fix user found issue

* remove prints
---
 src/crewai/flow/flow.py | 75 +++++++++++++++++++++++++++--------------
 1 file changed, 49 insertions(+), 26 deletions(-)

diff --git a/src/crewai/flow/flow.py b/src/crewai/flow/flow.py
index de9b2eeb2..e7231e13f 100644
--- a/src/crewai/flow/flow.py
+++ b/src/crewai/flow/flow.py
@@ -1,5 +1,3 @@
-# flow.py
-
 import asyncio
 import inspect
 from typing import Any, Callable, Dict, Generic, List, Set, Type, TypeVar, Union
@@ -120,6 +118,8 @@ class FlowMeta(type):
                 methods = attr_value.__trigger_methods__
                 condition_type = getattr(attr_value, "__condition_type__", "OR")
                 listeners[attr_name] = (condition_type, methods)
+
+            # TODO: should we add a check for __condition_type__ 'AND'?
             elif hasattr(attr_value, "__is_router__"):
                 routers[attr_value.__router_for__] = attr_name
                 possible_returns = get_possible_return_constants(attr_value)
@@ -159,7 +159,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
     def __init__(self) -> None:
         self._methods: Dict[str, Callable] = {}
         self._state: T = self._create_initial_state()
-        self._completed_methods: Set[str] = set()
+        self._executed_methods: Set[str] = set()
+        self._scheduled_tasks: Set[str] = set()
         self._pending_and_listeners: Dict[str, Set[str]] = {}
         self._method_outputs: List[Any] = []  # List to store all method outputs
 
@@ -216,17 +217,24 @@ class Flow(Generic[T], metaclass=FlowMeta):
         else:
             return None  # Or raise an exception if no methods were executed
 
-    async def _execute_start_method(self, start_method: str) -> None:
-        result = await self._execute_method(self._methods[start_method])
-        await self._execute_listeners(start_method, result)
+    async def _execute_start_method(self, start_method_name: str) -> None:
+        result = await self._execute_method(
+            start_method_name, self._methods[start_method_name]
+        )
+        await self._execute_listeners(start_method_name, result)
 
-    async def _execute_method(self, method: Callable, *args: Any, **kwargs: Any) -> Any:
+    async def _execute_method(
+        self, method_name: str, method: Callable, *args: Any, **kwargs: Any
+    ) -> Any:
         result = (
             await method(*args, **kwargs)
             if asyncio.iscoroutinefunction(method)
             else method(*args, **kwargs)
         )
         self._method_outputs.append(result)  # Store the output
+
+        self._executed_methods.add(method_name)
+
         return result
 
     async def _execute_listeners(self, trigger_method: str, result: Any) -> None:
@@ -234,32 +242,40 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
         if trigger_method in self._routers:
             router_method = self._methods[self._routers[trigger_method]]
-            path = await self._execute_method(router_method)
+            path = await self._execute_method(
+                trigger_method, router_method
+            )  # TODO: Change or not?
             # Use the path as the new trigger method
             trigger_method = path
 
-        for listener, (condition_type, methods) in self._listeners.items():
+        for listener_name, (condition_type, methods) in self._listeners.items():
             if condition_type == "OR":
                 if trigger_method in methods:
-                    listener_tasks.append(
-                        self._execute_single_listener(listener, result)
-                    )
+                    if (
+                        listener_name not in self._executed_methods
+                        and listener_name not in self._scheduled_tasks
+                    ):
+                        self._scheduled_tasks.add(listener_name)
+                        listener_tasks.append(
+                            self._execute_single_listener(listener_name, result)
+                        )
             elif condition_type == "AND":
-                if listener not in self._pending_and_listeners:
-                    self._pending_and_listeners[listener] = set()
-                self._pending_and_listeners[listener].add(trigger_method)
-                if set(methods) == self._pending_and_listeners[listener]:
-                    listener_tasks.append(
-                        self._execute_single_listener(listener, result)
-                    )
-                    del self._pending_and_listeners[listener]
+                if all(method in self._executed_methods for method in methods):
+                    if (
+                        listener_name not in self._executed_methods
+                        and listener_name not in self._scheduled_tasks
+                    ):
+                        self._scheduled_tasks.add(listener_name)
+                        listener_tasks.append(
+                            self._execute_single_listener(listener_name, result)
+                        )
 
         # Run all listener tasks concurrently and wait for them to complete
         await asyncio.gather(*listener_tasks)
 
-    async def _execute_single_listener(self, listener: str, result: Any) -> None:
+    async def _execute_single_listener(self, listener_name: str, result: Any) -> None:
         try:
-            method = self._methods[listener]
+            method = self._methods[listener_name]
             sig = inspect.signature(method)
             params = list(sig.parameters.values())
 
@@ -268,15 +284,22 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
             if method_params:
                 # If listener expects parameters, pass the result
-                listener_result = await self._execute_method(method, result)
+                listener_result = await self._execute_method(
+                    listener_name, method, result
+                )
             else:
                 # If listener does not expect parameters, call without arguments
-                listener_result = await self._execute_method(method)
+                listener_result = await self._execute_method(listener_name, method)
+
+            # Remove from scheduled tasks after execution
+            self._scheduled_tasks.discard(listener_name)
 
             # Execute listeners of this listener
-            await self._execute_listeners(listener, listener_result)
+            await self._execute_listeners(listener_name, listener_result)
         except Exception as e:
-            print(f"[Flow._execute_single_listener] Error in method {listener}: {e}")
+            print(
+                f"[Flow._execute_single_listener] Error in method {listener_name}: {e}"
+            )
             import traceback
 
             traceback.print_exc()

From 5f46ff883632e4b3396c6dfbae98b9347e807f99 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Wed, 30 Oct 2024 00:07:46 -0300
Subject: [PATCH 030/126] prepare new version

---
 pyproject.toml                                     |  8 ++++----
 src/crewai/__init__.py                             |  2 +-
 src/crewai/cli/templates/crew/pyproject.toml       |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml       |  2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml   |  2 +-
 .../cli/templates/pipeline_router/pyproject.toml   |  2 +-
 src/crewai/cli/templates/tool/pyproject.toml       |  2 +-
 uv.lock                                            | 14 +++++++-------
 8 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index ef8181cbc..b9e6bc986 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.76.2"
+version = "0.76.9"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
@@ -16,7 +16,7 @@ dependencies = [
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
     "instructor>=1.3.3",
     "regex>=2024.9.11",
-    "crewai-tools>=0.13.2",
+    "crewai-tools>=0.13.4",
     "click>=8.1.7",
     "python-dotenv>=1.0.0",
     "appdirs>=1.4.4",
@@ -37,7 +37,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools>=0.13.2"]
+tools = ["crewai-tools>=0.13.4"]
 agentops = ["agentops>=0.3.0"]
 
 [tool.uv]
@@ -52,7 +52,7 @@ dev-dependencies = [
     "mkdocs-material-extensions>=1.3.1",
     "pillow>=10.2.0",
     "cairosvg>=2.7.1",
-    "crewai-tools>=0.13.2",
+    "crewai-tools>=0.13.4",
     "pytest>=8.0.0",
     "pytest-vcr>=1.0.2",
     "python-dotenv>=1.0.0",
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 5160aa77f..0a2f02a59 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.76.2"
+__version__ = "0.76.9"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index ed32aa600..447cfcb86 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.2,<1.0.0"
+    "crewai[tools]>=0.76.9,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 815e8b205..1ef8f7b36 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.2,<1.0.0",
+    "crewai[tools]>=0.76.9,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index b4e74abea..53f304283 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.76.2,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.76.9,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index bd487ce95..33d5c58af 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.2,<1.0.0"
+    "crewai[tools]>=0.76.9,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 360a940ed..849298b6b 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.2"
+    "crewai[tools]>=0.76.9"
 ]
 
diff --git a/uv.lock b/uv.lock
index df2572402..f7f6a1839 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.76.2"
+version = "0.76.9"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -665,8 +665,8 @@ requires-dist = [
     { name = "auth0-python", specifier = ">=4.7.1" },
     { name = "chromadb", specifier = ">=0.4.24" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", specifier = ">=0.13.2" },
-    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.13.2" },
+    { name = "crewai-tools", specifier = ">=0.13.4" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.13.4" },
     { name = "instructor", specifier = ">=1.3.3" },
     { name = "json-repair", specifier = ">=0.25.2" },
     { name = "jsonref", specifier = ">=1.1.0" },
@@ -688,7 +688,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
     { name = "cairosvg", specifier = ">=2.7.1" },
-    { name = "crewai-tools", specifier = ">=0.13.2" },
+    { name = "crewai-tools", specifier = ">=0.13.4" },
     { name = "mkdocs", specifier = ">=1.4.3" },
     { name = "mkdocs-material", specifier = ">=9.5.7" },
     { name = "mkdocs-material-extensions", specifier = ">=1.3.1" },
@@ -707,7 +707,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.13.2"
+version = "0.13.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "beautifulsoup4" },
@@ -725,9 +725,9 @@ dependencies = [
     { name = "requests" },
     { name = "selenium" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/96/02/136f42ed8a7bd706a85663714c615bdcb684e43e95e4719c892aa0ce3d53/crewai_tools-0.13.2.tar.gz", hash = "sha256:c6782f2e868c0e96b25891f1b40fb8c90c01e920bab2fd1388f89ef1d7a4b99b", size = 816250 }
+sdist = { url = "https://files.pythonhosted.org/packages/64/bd/eff7b633a0b28ff4ed115adde1499e3dcc683e4f0b5c378a4c6f5c0c1bf6/crewai_tools-0.13.4.tar.gz", hash = "sha256:b6ac527633b7018471d892c21ac96bc961a86b6626d996b1ed7d53cd481d4505", size = 816588 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/28/30/df215173b6193b2cfb1902a339443be73056eae89579805b853c6f359761/crewai_tools-0.13.2-py3-none-any.whl", hash = "sha256:8c7583c9559fb625f594349c6553a5251ebd7b21918735ad6fbe8bab7ec3db50", size = 463444 },
+    { url = "https://files.pythonhosted.org/packages/6c/40/93cd347d854059cf5e54a81b70f896deea7ad1f03e9c024549eb323c4da5/crewai_tools-0.13.4-py3-none-any.whl", hash = "sha256:eda78fe3c4df57676259d8dd6b2610fa31f89b90909512f15893adb57fb9e825", size = 463703 },
 ]
 
 [[package]]

From 55cd15bfc629ab4aad159126c2aaf9dd10e647bf Mon Sep 17 00:00:00 2001
From: Rip&Tear <84775494+theCyberTech@users.noreply.github.com>
Date: Thu, 31 Oct 2024 00:07:38 +0800
Subject: [PATCH 031/126] Added security.md file (#1533)

---
 .github/security.md | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)
 create mode 100644 .github/security.md

diff --git a/.github/security.md b/.github/security.md
new file mode 100644
index 000000000..5bc967228
--- /dev/null
+++ b/.github/security.md
@@ -0,0 +1,19 @@
+CrewAI takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organization.
+If you believe you have found a security vulnerability in any CrewAI product or service, please report it to us as described below.
+
+ ## Reporting a Vulnerability
+ Please do not report security vulnerabilities through public GitHub issues.
+ To report a vulnerability, please email us at security@crewai.com.
+ Please include the requested information listed below so that we can triage your report more quickly
+
+ - Type of issue (e.g. SQL injection, cross-site scripting, etc.)
+ - Full paths of source file(s) related to the manifestation of the issue
+ - The location of the affected source code (tag/branch/commit or direct URL)
+ - Any special configuration required to reproduce the issue
+ - Step-by-step instructions to reproduce the issue (please include screenshots if needed)
+ - Proof-of-concept or exploit code (if possible)
+ - Impact of the issue, including how an attacker might exploit the issue
+
+ Once we have received your report, we will respond to you at the email address you provide. If the issue is confirmed, we will release a patch as soon as possible depending on the complexity of the issue.
+
+ At this time, we are not offering a bug bounty program. Any rewards will be at our discretion.
\ No newline at end of file

From 6193eb13fa0b56a214d920c60f6b1e5225899e65 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 30 Oct 2024 16:37:21 -0400
Subject: [PATCH 032/126] Disable telemetry explicitly (#1536)

* Disable telemetry explicitly

* fix linting

* revert parts to og
---
 src/crewai/telemetry/telemetry.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/src/crewai/telemetry/telemetry.py b/src/crewai/telemetry/telemetry.py
index a08ccd96f..e191f8d4d 100644
--- a/src/crewai/telemetry/telemetry.py
+++ b/src/crewai/telemetry/telemetry.py
@@ -21,7 +21,7 @@ with suppress_warnings():
 
 
 from opentelemetry import trace  # noqa: E402
-from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter  # noqa: E402
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter # noqa: E402
 from opentelemetry.sdk.resources import SERVICE_NAME, Resource  # noqa: E402
 from opentelemetry.sdk.trace import TracerProvider  # noqa: E402
 from opentelemetry.sdk.trace.export import BatchSpanProcessor  # noqa: E402
@@ -48,6 +48,10 @@ class Telemetry:
     def __init__(self):
         self.ready = False
         self.trace_set = False
+
+        if os.getenv("OTEL_SDK_DISABLED", "false").lower() == "true":
+            return
+
         try:
             telemetry_endpoint = "https://telemetry.crewai.com:4319"
             self.resource = Resource(

From 4ae07468f37db34e92df20a6aaae255ffdec7950 Mon Sep 17 00:00:00 2001
From: Robin Wang <6220861+MottoX@users.noreply.github.com>
Date: Thu, 31 Oct 2024 04:45:19 +0800
Subject: [PATCH 033/126] Enhance log storage to support more data types
 (#1530)

---
 src/crewai/memory/storage/kickoff_task_outputs_storage.py | 2 +-
 src/crewai/utilities/crew_json_encoder.py                 | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/src/crewai/memory/storage/kickoff_task_outputs_storage.py b/src/crewai/memory/storage/kickoff_task_outputs_storage.py
index 57623eef8..dbb5f124b 100644
--- a/src/crewai/memory/storage/kickoff_task_outputs_storage.py
+++ b/src/crewai/memory/storage/kickoff_task_outputs_storage.py
@@ -70,7 +70,7 @@ class KickoffTaskOutputsSQLiteStorage:
                         task.expected_output,
                         json.dumps(output, cls=CrewJSONEncoder),
                         task_index,
-                        json.dumps(inputs),
+                        json.dumps(inputs, cls=CrewJSONEncoder),
                         was_replayed,
                     ),
                 )
diff --git a/src/crewai/utilities/crew_json_encoder.py b/src/crewai/utilities/crew_json_encoder.py
index 3cab07ffc..c3f95fcf6 100644
--- a/src/crewai/utilities/crew_json_encoder.py
+++ b/src/crewai/utilities/crew_json_encoder.py
@@ -2,13 +2,14 @@ from datetime import datetime, date
 import json
 from uuid import UUID
 from pydantic import BaseModel
+from decimal import Decimal
 
 
 class CrewJSONEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, BaseModel):
             return self._handle_pydantic_model(obj)
-        elif isinstance(obj, UUID):
+        elif isinstance(obj, UUID) or isinstance(obj, Decimal):
             return str(obj)
 
         elif isinstance(obj, datetime) or isinstance(obj, date):

From ec2967c3624f355cb652541f4a64f21df1d9dc17 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Wed, 30 Oct 2024 21:56:13 -0400
Subject: [PATCH 034/126] Add llm providers accordion group (#1534)

* add llm providers accordion group

* fix numbering
---
 docs/concepts/llms.mdx | 249 ++++++++++++++++++++++++++++-------------
 1 file changed, 173 insertions(+), 76 deletions(-)

diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 90e86adaf..835c2491f 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -25,52 +25,55 @@ By default, CrewAI uses the `gpt-4o-mini` model. It uses environment variables i
 - `OPENAI_API_BASE`
 - `OPENAI_API_KEY`
 
-### 2. String Identifier
-
-```python Code
-agent = Agent(llm="gpt-4o", ...)
-```
-
-### 3. LLM Instance
-
-List of [more providers](https://docs.litellm.ai/docs/providers).
-
-```python Code
-from crewai import LLM
-
-llm = LLM(model="gpt-4", temperature=0.7)
-agent = Agent(llm=llm, ...)
-```
-
-### 4. Custom LLM Objects
+### 2. Custom LLM Objects
 
 Pass a custom LLM implementation or object from another library.
 
+See below for examples.
+
+<Tabs>
+    <Tab title="String Identifier">
+    ```python Code
+    agent = Agent(llm="gpt-4o", ...)
+    ```
+    </Tab>
+
+    <Tab title="LLM Instance">
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(model="gpt-4", temperature=0.7)
+    agent = Agent(llm=llm, ...)
+    ```
+    </Tab>
+</Tabs>
+
 ## Connecting to OpenAI-Compatible LLMs
 
 You can connect to OpenAI-compatible LLMs using either environment variables or by setting specific attributes on the LLM class:
 
-1. Using environment variables:
+<Tabs>
+    <Tab title="Using Environment Variables">
+    ```python Code
+    import os
 
-```python Code
-import os
+    os.environ["OPENAI_API_KEY"] = "your-api-key"
+    os.environ["OPENAI_API_BASE"] = "https://api.your-provider.com/v1"
+    ```
+    </Tab>
+    <Tab title="Using LLM Class Attributes">
+    ```python Code
+    from crewai import LLM
 
-os.environ["OPENAI_API_KEY"] = "your-api-key"
-os.environ["OPENAI_API_BASE"] = "https://api.your-provider.com/v1"
-```
-
-2. Using LLM class attributes:
-
-```python Code
-from crewai import LLM
-
-llm = LLM(
-    model="custom-model-name",
-    api_key="your-api-key",
-    base_url="https://api.your-provider.com/v1"
-)
-agent = Agent(llm=llm, ...)
-```
+    llm = LLM(
+        model="custom-model-name",
+        api_key="your-api-key",
+        base_url="https://api.your-provider.com/v1"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Tab>
+</Tabs>
 
 ## LLM Configuration Options
 
@@ -97,55 +100,149 @@ When configuring an LLM for your agent, you have access to a wide range of param
 | **api_key**          | `str`             | Your API key for authentication.                                                                 |
 
 
-## OpenAI Example Configuration
+These are examples of how to configure LLMs for your agent.
 
-```python Code
-from crewai import LLM
+<AccordionGroup>    
+    <Accordion title="OpenAI">
 
-llm = LLM(
-    model="gpt-4",
-    temperature=0.8,
-    max_tokens=150,
-    top_p=0.9,
-    frequency_penalty=0.1,
-    presence_penalty=0.1,
-    stop=["END"],
-    seed=42,
-    base_url="https://api.openai.com/v1",
-    api_key="your-api-key-here"
-)
-agent = Agent(llm=llm, ...)
-```
+    ```python Code
+    from crewai import LLM
 
-## Cerebras Example Configuration
+    llm = LLM(
+        model="gpt-4",
+        temperature=0.8,
+        max_tokens=150,
+        top_p=0.9,
+        frequency_penalty=0.1,
+        presence_penalty=0.1,
+        stop=["END"],
+        seed=42,
+        base_url="https://api.openai.com/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
 
-```python Code
-from crewai import LLM
+    <Accordion title="Cerebras">
 
-llm = LLM(
-    model="cerebras/llama-3.1-70b",
-    base_url="https://api.cerebras.ai/v1",
-    api_key="your-api-key-here"
-)
-agent = Agent(llm=llm, ...) 
-```
+    ```python Code
+    from crewai import LLM
 
-## Using Ollama (Local LLMs)
+    llm = LLM(
+        model="cerebras/llama-3.1-70b",
+        base_url="https://api.cerebras.ai/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...) 
+    ```
+    </Accordion>
+ 
+    <Accordion title="Ollama (Local LLMs)">
 
-CrewAI supports using Ollama for running open-source models locally:
+    CrewAI supports using Ollama for running open-source models locally:
 
-1. Install Ollama: [ollama.ai](https://ollama.ai/)
-2. Run a model: `ollama run llama2`
-3. Configure agent:
+    1. Install Ollama: [ollama.ai](https://ollama.ai/)
+    2. Run a model: `ollama run llama2`
+    3. Configure agent:
 
-```python Code
-from crewai import LLM
+    ```python Code
+    from crewai import LLM
 
-agent = Agent(
-    llm=LLM(model="ollama/llama3.1", base_url="http://localhost:11434"),
-    ...
-)
-```
+    agent = Agent(
+        llm=LLM(
+            model="ollama/llama3.1", 
+            base_url="http://localhost:11434"
+        ),
+        ...
+    )
+    ```
+    </Accordion>
+
+    <Accordion title="Groq">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="groq/llama3-8b-8192", 
+        base_url="https://api.groq.com/openai/v1", 
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
+
+    <Accordion title="Anthropic">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="anthropic/claude-3-5-sonnet-20241022",
+        base_url="https://api.anthropic.com/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
+
+    <Accordion title="Fireworks">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="fireworks/meta-llama-3.1-8b-instruct",
+        base_url="https://api.fireworks.ai/inference/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
+
+    <Accordion title="Gemini">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="gemini/gemini-1.5-flash",
+        base_url="https://api.gemini.google.com/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
+
+    <Accordion title="Perplexity AI (pplx-api)">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="perplexity/mistral-7b-instruct",
+        base_url="https://api.perplexity.ai/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
+
+    <Accordion title="IBM watsonx.ai">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="watsonx/ibm/granite-13b-chat-v2",
+        base_url="https://api.watsonx.ai/v1",
+        api_key="your-api-key-here"
+    )
+    agent = Agent(llm=llm, ...)
+    ```
+    </Accordion>
+</AccordionGroup>
 
 ## Changing the Base API URL
 

From 66698503b878459ed5d7d208c7ec37e995a54f28 Mon Sep 17 00:00:00 2001
From: Vini Brasil <vini@hey.com>
Date: Thu, 31 Oct 2024 15:00:58 -0300
Subject: [PATCH 035/126] Replace .netrc with uv environment variables (#1541)

This commit replaces .netrc with uv environment variables for installing
tools from private repositories. To store credentials, I created a new
and reusable settings file for the CLI in
`$HOME/.config/crewai/settings.json`.

The issue with .netrc files is that they are applied system-wide and are
scoped by hostname, meaning we can't differentiate tool repositories
requests from regular requests to CrewAI's API.
---
 src/crewai/cli/config.py     |  38 ++++++++++++
 src/crewai/cli/tools/main.py |  40 +++++++------
 tests/cli/config_test.py     | 109 +++++++++++++++++++++++++++++++++++
 tests/cli/tools/test_main.py |   1 +
 4 files changed, 169 insertions(+), 19 deletions(-)
 create mode 100644 src/crewai/cli/config.py
 create mode 100644 tests/cli/config_test.py

diff --git a/src/crewai/cli/config.py b/src/crewai/cli/config.py
new file mode 100644
index 000000000..000f1e6d0
--- /dev/null
+++ b/src/crewai/cli/config.py
@@ -0,0 +1,38 @@
+import json
+from pathlib import Path
+from pydantic import BaseModel, Field
+from typing import Optional
+
+DEFAULT_CONFIG_PATH = Path.home() / ".config" / "crewai" / "settings.json"
+
+class Settings(BaseModel):
+    tool_repository_username: Optional[str] = Field(None, description="Username for interacting with the Tool Repository")
+    tool_repository_password: Optional[str] = Field(None, description="Password for interacting with the Tool Repository")
+    config_path: Path = Field(default=DEFAULT_CONFIG_PATH, exclude=True)
+
+    def __init__(self, config_path: Path = DEFAULT_CONFIG_PATH, **data):
+        """Load Settings from config path"""
+        config_path.parent.mkdir(parents=True, exist_ok=True)
+
+        file_data = {}
+        if config_path.is_file():
+            try:
+                with config_path.open("r") as f:
+                    file_data = json.load(f)
+            except json.JSONDecodeError:
+                file_data = {}
+
+        merged_data = {**file_data, **data}
+        super().__init__(config_path=config_path, **merged_data)
+
+    def dump(self) -> None:
+        """Save current settings to settings.json"""
+        if self.config_path.is_file():
+            with self.config_path.open("r") as f:
+                existing_data = json.load(f)
+        else:
+            existing_data = {}
+
+        updated_data = {**existing_data, **self.model_dump(exclude_unset=True)}
+        with self.config_path.open("w") as f:
+            json.dump(updated_data, f, indent=4)
diff --git a/src/crewai/cli/tools/main.py b/src/crewai/cli/tools/main.py
index c875229c3..35652a1ec 100644
--- a/src/crewai/cli/tools/main.py
+++ b/src/crewai/cli/tools/main.py
@@ -1,17 +1,15 @@
 import base64
 import os
-import platform
 import subprocess
 import tempfile
 from pathlib import Path
-from netrc import netrc
-import stat
 
 import click
 from rich.console import Console
 
 from crewai.cli import git
 from crewai.cli.command import BaseCommand, PlusAPIMixin
+from crewai.cli.config import Settings
 from crewai.cli.utils import (
     get_project_description,
     get_project_name,
@@ -153,26 +151,16 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
             raise SystemExit
 
         login_response_json = login_response.json()
-        self._set_netrc_credentials(login_response_json["credential"])
+
+        settings = Settings()
+        settings.tool_repository_username = login_response_json["credential"]["username"]
+        settings.tool_repository_password = login_response_json["credential"]["password"]
+        settings.dump()
 
         console.print(
             "Successfully authenticated to the tool repository.", style="bold green"
         )
 
-    def _set_netrc_credentials(self, credentials, netrc_path=None):
-        if not netrc_path:
-            netrc_filename = "_netrc" if platform.system() == "Windows" else ".netrc"
-            netrc_path = Path.home() / netrc_filename
-            netrc_path.touch(mode=stat.S_IRUSR | stat.S_IWUSR, exist_ok=True)
-
-        netrc_instance = netrc(file=netrc_path)
-        netrc_instance.hosts["app.crewai.com"] = (credentials["username"], "", credentials["password"])
-
-        with open(netrc_path, 'w') as file:
-            file.write(str(netrc_instance))
-
-        console.print(f"Added credentials to {netrc_path}", style="bold green")
-
     def _add_package(self, tool_details):
         tool_handle = tool_details["handle"]
         repository_handle = tool_details["repository"]["handle"]
@@ -187,7 +175,11 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
             tool_handle,
         ]
         add_package_result = subprocess.run(
-            add_package_command, capture_output=False, text=True, check=True
+            add_package_command,
+            capture_output=False,
+            env=self._build_env_with_credentials(repository_handle),
+            text=True,
+            check=True
         )
 
         if add_package_result.stderr:
@@ -206,3 +198,13 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
                 "[bold yellow]Tip:[/bold yellow] Navigate to a different directory and try again."
             )
             raise SystemExit
+
+    def _build_env_with_credentials(self, repository_handle: str):
+        repository_handle = repository_handle.upper().replace("-", "_")
+        settings = Settings()
+
+        env = os.environ.copy()
+        env[f"UV_INDEX_{repository_handle}_USERNAME"] = str(settings.tool_repository_username or "")
+        env[f"UV_INDEX_{repository_handle}_PASSWORD"] = str(settings.tool_repository_password or "")
+
+        return env
diff --git a/tests/cli/config_test.py b/tests/cli/config_test.py
new file mode 100644
index 000000000..1065d4730
--- /dev/null
+++ b/tests/cli/config_test.py
@@ -0,0 +1,109 @@
+import unittest
+import json
+import tempfile
+import shutil
+from pathlib import Path
+from crewai.cli.config import Settings
+
+class TestSettings(unittest.TestCase):
+    def setUp(self):
+        self.test_dir = Path(tempfile.mkdtemp())
+        self.config_path = self.test_dir / "settings.json"
+
+    def tearDown(self):
+        shutil.rmtree(self.test_dir)
+
+    def test_empty_initialization(self):
+        settings = Settings(config_path=self.config_path)
+        self.assertIsNone(settings.tool_repository_username)
+        self.assertIsNone(settings.tool_repository_password)
+
+    def test_initialization_with_data(self):
+        settings = Settings(
+            config_path=self.config_path,
+            tool_repository_username="user1"
+        )
+        self.assertEqual(settings.tool_repository_username, "user1")
+        self.assertIsNone(settings.tool_repository_password)
+
+    def test_initialization_with_existing_file(self):
+        self.config_path.parent.mkdir(parents=True, exist_ok=True)
+        with self.config_path.open("w") as f:
+            json.dump({"tool_repository_username": "file_user"}, f)
+
+        settings = Settings(config_path=self.config_path)
+        self.assertEqual(settings.tool_repository_username, "file_user")
+
+    def test_merge_file_and_input_data(self):
+        self.config_path.parent.mkdir(parents=True, exist_ok=True)
+        with self.config_path.open("w") as f:
+            json.dump({
+                "tool_repository_username": "file_user",
+                "tool_repository_password": "file_pass"
+            }, f)
+
+        settings = Settings(
+            config_path=self.config_path,
+            tool_repository_username="new_user"
+        )
+        self.assertEqual(settings.tool_repository_username, "new_user")
+        self.assertEqual(settings.tool_repository_password, "file_pass")
+
+    def test_dump_new_settings(self):
+        settings = Settings(
+            config_path=self.config_path,
+            tool_repository_username="user1"
+        )
+        settings.dump()
+
+        with self.config_path.open("r") as f:
+            saved_data = json.load(f)
+
+        self.assertEqual(saved_data["tool_repository_username"], "user1")
+
+    def test_update_existing_settings(self):
+        self.config_path.parent.mkdir(parents=True, exist_ok=True)
+        with self.config_path.open("w") as f:
+            json.dump({"existing_setting": "value"}, f)
+
+        settings = Settings(
+            config_path=self.config_path,
+            tool_repository_username="user1"
+        )
+        settings.dump()
+
+        with self.config_path.open("r") as f:
+            saved_data = json.load(f)
+
+        self.assertEqual(saved_data["existing_setting"], "value")
+        self.assertEqual(saved_data["tool_repository_username"], "user1")
+
+    def test_none_values(self):
+        settings = Settings(
+            config_path=self.config_path,
+            tool_repository_username=None
+        )
+        settings.dump()
+
+        with self.config_path.open("r") as f:
+            saved_data = json.load(f)
+
+        self.assertIsNone(saved_data.get("tool_repository_username"))
+
+    def test_invalid_json_in_config(self):
+        self.config_path.parent.mkdir(parents=True, exist_ok=True)
+        with self.config_path.open("w") as f:
+            f.write("invalid json")
+
+        try:
+            settings = Settings(config_path=self.config_path)
+            self.assertIsNone(settings.tool_repository_username)
+        except json.JSONDecodeError:
+            self.fail("Settings initialization should handle invalid JSON")
+
+    def test_empty_config_file(self):
+        self.config_path.parent.mkdir(parents=True, exist_ok=True)
+        self.config_path.touch()
+
+        settings = Settings(config_path=self.config_path)
+        self.assertIsNone(settings.tool_repository_username)
diff --git a/tests/cli/tools/test_main.py b/tests/cli/tools/test_main.py
index e4fc19be3..3804fb9b4 100644
--- a/tests/cli/tools/test_main.py
+++ b/tests/cli/tools/test_main.py
@@ -82,6 +82,7 @@ def test_install_success(mock_get, mock_subprocess_run):
         capture_output=False,
         text=True,
         check=True,
+        env=unittest.mock.ANY
     )
 
     assert "Succesfully installed sample-tool" in output

From e66a135d5d41a1dec37b32ddebd329d0f0dab670 Mon Sep 17 00:00:00 2001
From: C0deZ <c0dezlee@gmail.com>
Date: Fri, 1 Nov 2024 12:30:48 -0400
Subject: [PATCH 036/126] refactor: Move BaseTool to main package and
 centralize tool description generation (#1514)

* move base_tool to main package and consolidate tool desscription generation

* update import path

* update tests

* update doc

* add base_tool test

* migrate agent delegation tools to use BaseTool

* update tests

* update import path for tool

* fix lint

* update param signature

* add from_langchain to BaseTool for backwards support of langchain tools

* fix the case where StructuredTool doesn't have func

---------

Co-authored-by: c0dez <li@vitablehealth.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/concepts/tools.mdx                       |  99 +++++-----
 docs/how-to/create-custom-tools.mdx           |  18 +-
 src/crewai/agent.py                           |  25 +--
 src/crewai/agents/agent_builder/base_agent.py |  13 +-
 src/crewai/agents/tools_handler.py            |   2 +-
 .../cli/templates/crew/tools/custom_tool.py   |   3 +-
 .../cli/templates/flow/tools/custom_tool.py   |   2 +-
 .../templates/pipeline/tools/custom_tool.py   |   3 +-
 .../pipeline_router/tools/custom_tool.py      |   3 +-
 .../tool/src/{{folder_name}}/tool.py          |   3 +-
 src/crewai/crew.py                            |   2 +-
 src/crewai/task.py                            |   7 +-
 src/crewai/tools/__init__.py                  |   1 +
 src/crewai/tools/agent_tools.py               |  25 ---
 src/crewai/tools/agent_tools/agent_tools.py   |  32 +++
 .../tools/agent_tools/ask_question_tool.py    |  26 +++
 .../agent_tools/base_agent_tools.py}          |  40 +---
 .../tools/agent_tools/delegate_work_tool.py   |  29 +++
 src/crewai/tools/base_tool.py                 | 186 ++++++++++++++++++
 .../tools/{ => cache_tools}/cache_tools.py    |   0
 src/crewai/tools/tool_usage.py                |  20 +-
 tests/agent_test.py                           |  36 ++--
 tests/agent_tools/lol.py                      |   0
 tests/agents/agent_builder/base_agent_test.py |   5 +-
 tests/crew_test.py                            |  23 ++-
 tests/task_test.py                            |   6 +-
 tests/{ => tools}/agent_tools/__init__.py     |   0
 .../agent_tools/agent_tools_test.py           |  30 +--
 .../cassettes/test_ask_question.yaml          |   0
 ...t_ask_question_with_coworker_as_array.yaml |   0
 ...uestion_with_wrong_co_worker_variable.yaml |   0
 .../cassettes/test_delegate_work.yaml         |   0
 ...te_work_with_wrong_co_worker_variable.yaml |   0
 ...egate_work_withwith_coworker_as_array.yaml |   0
 tests/tools/test_base_tool.py                 | 109 ++++++++++
 tests/tools/test_tool_usage.py                |  16 +-
 36 files changed, 547 insertions(+), 217 deletions(-)
 delete mode 100644 src/crewai/tools/agent_tools.py
 create mode 100644 src/crewai/tools/agent_tools/agent_tools.py
 create mode 100644 src/crewai/tools/agent_tools/ask_question_tool.py
 rename src/crewai/{agents/agent_builder/utilities/base_agent_tool.py => tools/agent_tools/base_agent_tools.py} (67%)
 create mode 100644 src/crewai/tools/agent_tools/delegate_work_tool.py
 create mode 100644 src/crewai/tools/base_tool.py
 rename src/crewai/tools/{ => cache_tools}/cache_tools.py (100%)
 delete mode 100644 tests/agent_tools/lol.py
 rename tests/{ => tools}/agent_tools/__init__.py (100%)
 rename tests/{ => tools}/agent_tools/agent_tools_test.py (95%)
 rename tests/{ => tools}/agent_tools/cassettes/test_ask_question.yaml (100%)
 rename tests/{ => tools}/agent_tools/cassettes/test_ask_question_with_coworker_as_array.yaml (100%)
 rename tests/{ => tools}/agent_tools/cassettes/test_ask_question_with_wrong_co_worker_variable.yaml (100%)
 rename tests/{ => tools}/agent_tools/cassettes/test_delegate_work.yaml (100%)
 rename tests/{ => tools}/agent_tools/cassettes/test_delegate_work_with_wrong_co_worker_variable.yaml (100%)
 rename tests/{ => tools}/agent_tools/cassettes/test_delegate_work_withwith_coworker_as_array.yaml (100%)
 create mode 100644 tests/tools/test_base_tool.py

diff --git a/docs/concepts/tools.mdx b/docs/concepts/tools.mdx
index 12ab96c6e..9b9c6a32e 100644
--- a/docs/concepts/tools.mdx
+++ b/docs/concepts/tools.mdx
@@ -5,13 +5,14 @@ icon: screwdriver-wrench
 ---
 
 ## Introduction
-CrewAI tools empower agents with capabilities ranging from web searching and data analysis to collaboration and delegating tasks among coworkers. 
+
+CrewAI tools empower agents with capabilities ranging from web searching and data analysis to collaboration and delegating tasks among coworkers.
 This documentation outlines how to create, integrate, and leverage these tools within the CrewAI framework, including a new focus on collaboration tools.
 
 ## What is a Tool?
 
-A tool in CrewAI is a skill or function that agents can utilize to perform various actions. 
-This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools), 
+A tool in CrewAI is a skill or function that agents can utilize to perform various actions.
+This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools),
 enabling everything from simple searches to complex interactions and effective teamwork among agents.
 
 ## Key Characteristics of Tools
@@ -103,57 +104,53 @@ crew.kickoff()
 
 Here is a list of the available tools and their descriptions:
 
-| Tool                        | Description                                                                                   |
-| :-------------------------- | :-------------------------------------------------------------------------------------------- |
-| **BrowserbaseLoadTool**     | A tool for interacting with and extracting data from web browsers.                            |
-| **CodeDocsSearchTool**      | A RAG tool optimized for searching through code documentation and related technical documents. |
-| **CodeInterpreterTool**     | A tool for interpreting python code.                                                          |
-| **ComposioTool**            | Enables use of Composio tools.                                                                |
-| **CSVSearchTool**           | A RAG tool designed for searching within CSV files, tailored to handle structured data.       |
-| **DALL-E Tool**             | A tool for generating images using the DALL-E API.                                            |
-| **DirectorySearchTool**     | A RAG tool for searching within directories, useful for navigating through file systems.      |
-| **DOCXSearchTool**          | A RAG tool aimed at searching within DOCX documents, ideal for processing Word files.         |
-| **DirectoryReadTool**       | Facilitates reading and processing of directory structures and their contents.                |
-| **EXASearchTool**           | A tool designed for performing exhaustive searches across various data sources.               |
-| **FileReadTool**            | Enables reading and extracting data from files, supporting various file formats.              |
-| **FirecrawlSearchTool**     | A tool to search webpages using Firecrawl and return the results.                             |
-| **FirecrawlCrawlWebsiteTool** | A tool for crawling webpages using Firecrawl.                                               |
-| **FirecrawlScrapeWebsiteTool** | A tool for scraping webpages URL using Firecrawl and returning its contents.              |
-| **GithubSearchTool**        | A RAG tool for searching within GitHub repositories, useful for code and documentation search.|
-| **SerperDevTool**           | A specialized tool for development purposes, with specific functionalities under development. |
-| **TXTSearchTool**           | A RAG tool focused on searching within text (.txt) files, suitable for unstructured data.     |
-| **JSONSearchTool**          | A RAG tool designed for searching within JSON files, catering to structured data handling.     |
-| **LlamaIndexTool**          | Enables the use of LlamaIndex tools.                                                          |
-| **MDXSearchTool**           | A RAG tool tailored for searching within Markdown (MDX) files, useful for documentation.      |
-| **PDFSearchTool**           | A RAG tool aimed at searching within PDF documents, ideal for processing scanned documents.    |
-| **PGSearchTool**            | A RAG tool optimized for searching within PostgreSQL databases, suitable for database queries. |
-| **Vision Tool**             | A tool for generating images using the DALL-E API.                                            |
-| **RagTool**                 | A general-purpose RAG tool capable of handling various data sources and types.                |
-| **ScrapeElementFromWebsiteTool** | Enables scraping specific elements from websites, useful for targeted data extraction.   |
-| **ScrapeWebsiteTool**       | Facilitates scraping entire websites, ideal for comprehensive data collection.                |
-| **WebsiteSearchTool**       | A RAG tool for searching website content, optimized for web data extraction.                  |
-| **XMLSearchTool**           | A RAG tool designed for searching within XML files, suitable for structured data formats.     |
-| **YoutubeChannelSearchTool**| A RAG tool for searching within YouTube channels, useful for video content analysis.          |
-| **YoutubeVideoSearchTool**  | A RAG tool aimed at searching within YouTube videos, ideal for video data extraction.         |
+| Tool                             | Description                                                                                    |
+| :------------------------------- | :--------------------------------------------------------------------------------------------- |
+| **BrowserbaseLoadTool**          | A tool for interacting with and extracting data from web browsers.                             |
+| **CodeDocsSearchTool**           | A RAG tool optimized for searching through code documentation and related technical documents. |
+| **CodeInterpreterTool**          | A tool for interpreting python code.                                                           |
+| **ComposioTool**                 | Enables use of Composio tools.                                                                 |
+| **CSVSearchTool**                | A RAG tool designed for searching within CSV files, tailored to handle structured data.        |
+| **DALL-E Tool**                  | A tool for generating images using the DALL-E API.                                             |
+| **DirectorySearchTool**          | A RAG tool for searching within directories, useful for navigating through file systems.       |
+| **DOCXSearchTool**               | A RAG tool aimed at searching within DOCX documents, ideal for processing Word files.          |
+| **DirectoryReadTool**            | Facilitates reading and processing of directory structures and their contents.                 |
+| **EXASearchTool**                | A tool designed for performing exhaustive searches across various data sources.                |
+| **FileReadTool**                 | Enables reading and extracting data from files, supporting various file formats.               |
+| **FirecrawlSearchTool**          | A tool to search webpages using Firecrawl and return the results.                              |
+| **FirecrawlCrawlWebsiteTool**    | A tool for crawling webpages using Firecrawl.                                                  |
+| **FirecrawlScrapeWebsiteTool**   | A tool for scraping webpages URL using Firecrawl and returning its contents.                   |
+| **GithubSearchTool**             | A RAG tool for searching within GitHub repositories, useful for code and documentation search. |
+| **SerperDevTool**                | A specialized tool for development purposes, with specific functionalities under development.  |
+| **TXTSearchTool**                | A RAG tool focused on searching within text (.txt) files, suitable for unstructured data.      |
+| **JSONSearchTool**               | A RAG tool designed for searching within JSON files, catering to structured data handling.     |
+| **LlamaIndexTool**               | Enables the use of LlamaIndex tools.                                                           |
+| **MDXSearchTool**                | A RAG tool tailored for searching within Markdown (MDX) files, useful for documentation.       |
+| **PDFSearchTool**                | A RAG tool aimed at searching within PDF documents, ideal for processing scanned documents.    |
+| **PGSearchTool**                 | A RAG tool optimized for searching within PostgreSQL databases, suitable for database queries. |
+| **Vision Tool**                  | A tool for generating images using the DALL-E API.                                             |
+| **RagTool**                      | A general-purpose RAG tool capable of handling various data sources and types.                 |
+| **ScrapeElementFromWebsiteTool** | Enables scraping specific elements from websites, useful for targeted data extraction.         |
+| **ScrapeWebsiteTool**            | Facilitates scraping entire websites, ideal for comprehensive data collection.                 |
+| **WebsiteSearchTool**            | A RAG tool for searching website content, optimized for web data extraction.                   |
+| **XMLSearchTool**                | A RAG tool designed for searching within XML files, suitable for structured data formats.      |
+| **YoutubeChannelSearchTool**     | A RAG tool for searching within YouTube channels, useful for video content analysis.           |
+| **YoutubeVideoSearchTool**       | A RAG tool aimed at searching within YouTube videos, ideal for video data extraction.          |
 
 ## Creating your own Tools
 
 <Tip>
-  Developers can craft `custom tools` tailored for their agent’s needs or utilize pre-built options.
+  Developers can craft `custom tools` tailored for their agent’s needs or
+  utilize pre-built options.
 </Tip>
 
-To create your own CrewAI tools you will need to install our extra tools package:
-
-```bash
-pip install 'crewai[tools]'
-```
-
-Once you do that there are two main ways for one to create a CrewAI tool:
+There are two main ways for one to create a CrewAI tool:
 
 ### Subclassing `BaseTool`
 
 ```python Code
-from crewai_tools import BaseTool
+from crewai.tools import BaseTool
+
 
 class MyCustomTool(BaseTool):
     name: str = "Name of my tool"
@@ -167,7 +164,7 @@ class MyCustomTool(BaseTool):
 ### Utilizing the `tool` Decorator
 
 ```python Code
-from crewai_tools import tool
+from crewai.tools import tool
 @tool("Name of my tool")
 def my_tool(question: str) -> str:
     """Clear description for what this tool is useful for, your agent will need this information to use it."""
@@ -178,11 +175,13 @@ def my_tool(question: str) -> str:
 ### Custom Caching Mechanism
 
 <Tip>
-  Tools can optionally implement a `cache_function` to fine-tune caching behavior. This function determines when to cache results based on specific conditions, offering granular control over caching logic.
+  Tools can optionally implement a `cache_function` to fine-tune caching
+  behavior. This function determines when to cache results based on specific
+  conditions, offering granular control over caching logic.
 </Tip>
 
 ```python Code
-from crewai_tools import tool
+from crewai.tools import tool
 
 @tool
 def multiplication_tool(first_number: int, second_number: int) -> str:
@@ -208,6 +207,6 @@ writer1 = Agent(
 
 ## Conclusion
 
-Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively. 
-When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling, 
-caching mechanisms, and the flexibility of tool arguments to optimize your agents' performance and capabilities.
\ No newline at end of file
+Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively.
+When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling,
+caching mechanisms, and the flexibility of tool arguments to optimize your agents' performance and capabilities.
diff --git a/docs/how-to/create-custom-tools.mdx b/docs/how-to/create-custom-tools.mdx
index 2caab716b..e7ee2e9a9 100644
--- a/docs/how-to/create-custom-tools.mdx
+++ b/docs/how-to/create-custom-tools.mdx
@@ -6,25 +6,17 @@ icon: hammer
 
 ## Creating and Utilizing Tools in CrewAI
 
-This guide provides detailed instructions on creating custom tools for the CrewAI framework and how to efficiently manage and utilize these tools, 
-incorporating the latest functionalities such as tool delegation, error handling, and dynamic tool calling. It also highlights the importance of collaboration tools, 
+This guide provides detailed instructions on creating custom tools for the CrewAI framework and how to efficiently manage and utilize these tools,
+incorporating the latest functionalities such as tool delegation, error handling, and dynamic tool calling. It also highlights the importance of collaboration tools,
 enabling agents to perform a wide range of actions.
 
-### Prerequisites
-
-Before creating your own tools, ensure you have the crewAI extra tools package installed:
-
-```bash
-pip install 'crewai[tools]'
-```
-
 ### Subclassing `BaseTool`
 
 To create a personalized tool, inherit from `BaseTool` and define the necessary attributes, including the `args_schema` for input validation, and the `_run` method.
 
 ```python Code
 from typing import Type
-from crewai_tools import BaseTool
+from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
 class MyToolInput(BaseModel):
@@ -47,7 +39,7 @@ Alternatively, you can use the tool decorator `@tool`. This approach allows you
 offering a concise and efficient way to create specialized tools tailored to your needs.
 
 ```python Code
-from crewai_tools import tool
+from crewai.tools import tool
 
 @tool("Tool Name")
 def my_simple_tool(question: str) -> str:
@@ -73,5 +65,5 @@ def my_cache_strategy(arguments: dict, result: str) -> bool:
 cached_tool.cache_function = my_cache_strategy
 ```
 
-By adhering to these guidelines and incorporating new functionalities and collaboration tools into your tool creation and management processes, 
+By adhering to these guidelines and incorporating new functionalities and collaboration tools into your tool creation and management processes,
 you can leverage the full capabilities of the CrewAI framework, enhancing both the development experience and the efficiency of your AI agents.
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 937710f59..f2a0a5c31 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -10,7 +10,8 @@ from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
-from crewai.tools.agent_tools import AgentTools
+from crewai.tools.agent_tools.agent_tools import AgentTools
+from crewai.tools import BaseTool
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -192,7 +193,7 @@ class Agent(BaseAgent):
         self,
         task: Any,
         context: Optional[str] = None,
-        tools: Optional[List[Any]] = None,
+        tools: Optional[List[BaseTool]] = None,
     ) -> str:
         """Execute a task with the agent.
 
@@ -259,7 +260,9 @@ class Agent(BaseAgent):
 
         return result
 
-    def create_agent_executor(self, tools=None, task=None) -> None:
+    def create_agent_executor(
+        self, tools: Optional[List[BaseTool]] = None, task=None
+    ) -> None:
         """Create an agent executor for the agent.
 
         Returns:
@@ -332,7 +335,7 @@ class Agent(BaseAgent):
         tools_list = []
         try:
             # tentatively try to import from crewai_tools import BaseTool as CrewAITool
-            from crewai_tools import BaseTool as CrewAITool
+            from crewai.tools import BaseTool as CrewAITool
 
             for tool in tools:
                 if isinstance(tool, CrewAITool):
@@ -391,7 +394,7 @@ class Agent(BaseAgent):
 
         return description
 
-    def _render_text_description_and_args(self, tools: List[Any]) -> str:
+    def _render_text_description_and_args(self, tools: List[BaseTool]) -> str:
         """Render the tool name, description, and args in plain text.
 
             Output will be in the format of:
@@ -404,17 +407,7 @@ class Agent(BaseAgent):
         """
         tool_strings = []
         for tool in tools:
-            args_schema = {
-                name: {
-                    "description": field.description,
-                    "type": field.annotation.__name__,
-                }
-                for name, field in tool.args_schema.model_fields.items()
-            }
-            description = (
-                f"Tool Name: {tool.name}\nTool Description: {tool.description}"
-            )
-            tool_strings.append(f"{description}\nTool Arguments: {args_schema}")
+            tool_strings.append(tool.description)
 
         return "\n".join(tool_strings)
 
diff --git a/src/crewai/agents/agent_builder/base_agent.py b/src/crewai/agents/agent_builder/base_agent.py
index f42ab3172..55315e7ff 100644
--- a/src/crewai/agents/agent_builder/base_agent.py
+++ b/src/crewai/agents/agent_builder/base_agent.py
@@ -18,6 +18,7 @@ from pydantic_core import PydanticCustomError
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
 from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.agents.tools_handler import ToolsHandler
+from crewai.tools import BaseTool
 from crewai.utilities import I18N, Logger, RPMController
 from crewai.utilities.config import process_config
 
@@ -49,11 +50,11 @@ class BaseAgent(ABC, BaseModel):
 
 
     Methods:
-        execute_task(task: Any, context: Optional[str] = None, tools: Optional[List[Any]] = None) -> str:
+        execute_task(task: Any, context: Optional[str] = None, tools: Optional[List[BaseTool]] = None) -> str:
             Abstract method to execute a task.
         create_agent_executor(tools=None) -> None:
             Abstract method to create an agent executor.
-        _parse_tools(tools: List[Any]) -> List[Any]:
+        _parse_tools(tools: List[BaseTool]) -> List[Any]:
             Abstract method to parse tools.
         get_delegation_tools(agents: List["BaseAgent"]):
             Abstract method to set the agents task tools for handling delegation and question asking to other agents in crew.
@@ -105,7 +106,7 @@ class BaseAgent(ABC, BaseModel):
         default=False,
         description="Enable agent to delegate and ask questions among each other.",
     )
-    tools: Optional[List[Any]] = Field(
+    tools: Optional[List[BaseTool]] = Field(
         default_factory=list, description="Tools at agents' disposal"
     )
     max_iter: Optional[int] = Field(
@@ -188,7 +189,7 @@ class BaseAgent(ABC, BaseModel):
         self,
         task: Any,
         context: Optional[str] = None,
-        tools: Optional[List[Any]] = None,
+        tools: Optional[List[BaseTool]] = None,
     ) -> str:
         pass
 
@@ -197,11 +198,11 @@ class BaseAgent(ABC, BaseModel):
         pass
 
     @abstractmethod
-    def _parse_tools(self, tools: List[Any]) -> List[Any]:
+    def _parse_tools(self, tools: List[BaseTool]) -> List[BaseTool]:
         pass
 
     @abstractmethod
-    def get_delegation_tools(self, agents: List["BaseAgent"]) -> List[Any]:
+    def get_delegation_tools(self, agents: List["BaseAgent"]) -> List[BaseTool]:
         """Set the task tools that init BaseAgenTools class."""
         pass
 
diff --git a/src/crewai/agents/tools_handler.py b/src/crewai/agents/tools_handler.py
index c82f7de8c..fd4bec7ee 100644
--- a/src/crewai/agents/tools_handler.py
+++ b/src/crewai/agents/tools_handler.py
@@ -1,6 +1,6 @@
 from typing import Any, Optional, Union
 
-from ..tools.cache_tools import CacheTools
+from ..tools.cache_tools.cache_tools import CacheTools
 from ..tools.tool_calling import InstructorToolCalling, ToolCalling
 from .cache.cache_handler import CacheHandler
 
diff --git a/src/crewai/cli/templates/crew/tools/custom_tool.py b/src/crewai/cli/templates/crew/tools/custom_tool.py
index d38318051..50bffa505 100644
--- a/src/crewai/cli/templates/crew/tools/custom_tool.py
+++ b/src/crewai/cli/templates/crew/tools/custom_tool.py
@@ -1,7 +1,8 @@
+from crewai.tools import BaseTool
 from typing import Type
-from crewai_tools import BaseTool
 from pydantic import BaseModel, Field
 
+
 class MyCustomToolInput(BaseModel):
     """Input schema for MyCustomTool."""
     argument: str = Field(..., description="Description of the argument.")
diff --git a/src/crewai/cli/templates/flow/tools/custom_tool.py b/src/crewai/cli/templates/flow/tools/custom_tool.py
index 030e575ec..e669b6c3b 100644
--- a/src/crewai/cli/templates/flow/tools/custom_tool.py
+++ b/src/crewai/cli/templates/flow/tools/custom_tool.py
@@ -1,6 +1,6 @@
 from typing import Type
 
-from crewai_tools import BaseTool
+from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
 
diff --git a/src/crewai/cli/templates/pipeline/tools/custom_tool.py b/src/crewai/cli/templates/pipeline/tools/custom_tool.py
index d38318051..fbd53cf02 100644
--- a/src/crewai/cli/templates/pipeline/tools/custom_tool.py
+++ b/src/crewai/cli/templates/pipeline/tools/custom_tool.py
@@ -1,7 +1,8 @@
 from typing import Type
-from crewai_tools import BaseTool
+from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
+
 class MyCustomToolInput(BaseModel):
     """Input schema for MyCustomTool."""
     argument: str = Field(..., description="Description of the argument.")
diff --git a/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py b/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
index d38318051..fbd53cf02 100644
--- a/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
+++ b/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
@@ -1,7 +1,8 @@
 from typing import Type
-from crewai_tools import BaseTool
+from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
+
 class MyCustomToolInput(BaseModel):
     """Input schema for MyCustomTool."""
     argument: str = Field(..., description="Description of the argument.")
diff --git a/src/crewai/cli/templates/tool/src/{{folder_name}}/tool.py b/src/crewai/cli/templates/tool/src/{{folder_name}}/tool.py
index 63c653a6c..24bc36017 100644
--- a/src/crewai/cli/templates/tool/src/{{folder_name}}/tool.py
+++ b/src/crewai/cli/templates/tool/src/{{folder_name}}/tool.py
@@ -1,4 +1,5 @@
-from crewai_tools import BaseTool
+from crewai.tools import BaseTool
+
 
 class {{class_name}}(BaseTool):
     name: str = "Name of my tool"
diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 377b6fec9..e65024ed6 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -32,7 +32,7 @@ from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
-from crewai.tools.agent_tools import AgentTools
+from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
 from crewai.utilities.constants import (
diff --git a/src/crewai/task.py b/src/crewai/task.py
index 82baa9959..21278af98 100644
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -20,6 +20,7 @@ from pydantic import (
 from pydantic_core import PydanticCustomError
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.tools.base_tool import BaseTool
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry.telemetry import Telemetry
@@ -91,7 +92,7 @@ class Task(BaseModel):
     output: Optional[TaskOutput] = Field(
         description="Task output, it's final result after being executed", default=None
     )
-    tools: Optional[List[Any]] = Field(
+    tools: Optional[List[BaseTool]] = Field(
         default_factory=list,
         description="Tools the agent is limited to use for this task.",
     )
@@ -185,7 +186,7 @@ class Task(BaseModel):
         self,
         agent: Optional[BaseAgent] = None,
         context: Optional[str] = None,
-        tools: Optional[List[Any]] = None,
+        tools: Optional[List[BaseTool]] = None,
     ) -> TaskOutput:
         """Execute the task synchronously."""
         return self._execute_core(agent, context, tools)
@@ -202,7 +203,7 @@ class Task(BaseModel):
         self,
         agent: BaseAgent | None = None,
         context: Optional[str] = None,
-        tools: Optional[List[Any]] = None,
+        tools: Optional[List[BaseTool]] = None,
     ) -> Future[TaskOutput]:
         """Execute the task asynchronously."""
         future: Future[TaskOutput] = Future()
diff --git a/src/crewai/tools/__init__.py b/src/crewai/tools/__init__.py
index e69de29bb..41819ccbc 100644
--- a/src/crewai/tools/__init__.py
+++ b/src/crewai/tools/__init__.py
@@ -0,0 +1 @@
+from .base_tool import BaseTool, tool
diff --git a/src/crewai/tools/agent_tools.py b/src/crewai/tools/agent_tools.py
deleted file mode 100644
index 7831285cf..000000000
--- a/src/crewai/tools/agent_tools.py
+++ /dev/null
@@ -1,25 +0,0 @@
-from crewai.agents.agent_builder.utilities.base_agent_tool import BaseAgentTools
-
-
-class AgentTools(BaseAgentTools):
-    """Default tools around agent delegation"""
-
-    def tools(self):
-        from langchain.tools import StructuredTool
-
-        coworkers = ", ".join([f"{agent.role}" for agent in self.agents])
-        tools = [
-            StructuredTool.from_function(
-                func=self.delegate_work,
-                name="Delegate work to coworker",
-                description=self.i18n.tools("delegate_work").format(
-                    coworkers=coworkers
-                ),
-            ),
-            StructuredTool.from_function(
-                func=self.ask_question,
-                name="Ask question to coworker",
-                description=self.i18n.tools("ask_question").format(coworkers=coworkers),
-            ),
-        ]
-        return tools
diff --git a/src/crewai/tools/agent_tools/agent_tools.py b/src/crewai/tools/agent_tools/agent_tools.py
new file mode 100644
index 000000000..1db55a29b
--- /dev/null
+++ b/src/crewai/tools/agent_tools/agent_tools.py
@@ -0,0 +1,32 @@
+from crewai.tools.base_tool import BaseTool
+from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.utilities import I18N
+
+from .delegate_work_tool import DelegateWorkTool
+from .ask_question_tool import AskQuestionTool
+
+
+class AgentTools:
+    """Manager class for agent-related tools"""
+
+    def __init__(self, agents: list[BaseAgent], i18n: I18N = I18N()):
+        self.agents = agents
+        self.i18n = i18n
+
+    def tools(self) -> list[BaseTool]:
+        """Get all available agent tools"""
+        coworkers = ", ".join([f"{agent.role}" for agent in self.agents])
+
+        delegate_tool = DelegateWorkTool(
+            agents=self.agents,
+            i18n=self.i18n,
+            description=self.i18n.tools("delegate_work").format(coworkers=coworkers),
+        )
+
+        ask_tool = AskQuestionTool(
+            agents=self.agents,
+            i18n=self.i18n,
+            description=self.i18n.tools("ask_question").format(coworkers=coworkers),
+        )
+
+        return [delegate_tool, ask_tool]
diff --git a/src/crewai/tools/agent_tools/ask_question_tool.py b/src/crewai/tools/agent_tools/ask_question_tool.py
new file mode 100644
index 000000000..af739b8fc
--- /dev/null
+++ b/src/crewai/tools/agent_tools/ask_question_tool.py
@@ -0,0 +1,26 @@
+from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
+from typing import Optional
+from pydantic import BaseModel, Field
+
+
+class AskQuestionToolSchema(BaseModel):
+    question: str = Field(..., description="The question to ask")
+    context: str = Field(..., description="The context for the question")
+    coworker: str = Field(..., description="The role/name of the coworker to ask")
+
+
+class AskQuestionTool(BaseAgentTool):
+    """Tool for asking questions to coworkers"""
+
+    name: str = "Ask question to coworker"
+    args_schema: type[BaseModel] = AskQuestionToolSchema
+
+    def _run(
+        self,
+        question: str,
+        context: str,
+        coworker: Optional[str] = None,
+        **kwargs,
+    ) -> str:
+        coworker = self._get_coworker(coworker, **kwargs)
+        return self._execute(coworker, question, context)
diff --git a/src/crewai/agents/agent_builder/utilities/base_agent_tool.py b/src/crewai/tools/agent_tools/base_agent_tools.py
similarity index 67%
rename from src/crewai/agents/agent_builder/utilities/base_agent_tool.py
rename to src/crewai/tools/agent_tools/base_agent_tools.py
index fef4ee9ef..bedb2aed6 100644
--- a/src/crewai/agents/agent_builder/utilities/base_agent_tool.py
+++ b/src/crewai/tools/agent_tools/base_agent_tools.py
@@ -1,22 +1,19 @@
-from abc import ABC, abstractmethod
-from typing import List, Optional, Union
-
-from pydantic import BaseModel, Field
+from typing import Optional, Union
+from pydantic import Field
 
+from crewai.tools.base_tool import BaseTool
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.task import Task
 from crewai.utilities import I18N
 
 
-class BaseAgentTools(BaseModel, ABC):
-    """Default tools around agent delegation"""
+class BaseAgentTool(BaseTool):
+    """Base class for agent-related tools"""
 
-    agents: List[BaseAgent] = Field(description="List of agents in this crew.")
-    i18n: I18N = Field(default=I18N(), description="Internationalization settings.")
-
-    @abstractmethod
-    def tools(self):
-        pass
+    agents: list[BaseAgent] = Field(description="List of available agents")
+    i18n: I18N = Field(
+        default_factory=I18N, description="Internationalization settings"
+    )
 
     def _get_coworker(self, coworker: Optional[str], **kwargs) -> Optional[str]:
         coworker = coworker or kwargs.get("co_worker") or kwargs.get("coworker")
@@ -24,27 +21,11 @@ class BaseAgentTools(BaseModel, ABC):
             is_list = coworker.startswith("[") and coworker.endswith("]")
             if is_list:
                 coworker = coworker[1:-1].split(",")[0]
-
         return coworker
 
-    def delegate_work(
-        self, task: str, context: str, coworker: Optional[str] = None, **kwargs
-    ):
-        """Useful to delegate a specific task to a coworker passing all necessary context and names."""
-        coworker = self._get_coworker(coworker, **kwargs)
-        return self._execute(coworker, task, context)
-
-    def ask_question(
-        self, question: str, context: str, coworker: Optional[str] = None, **kwargs
-    ):
-        """Useful to ask a question, opinion or take from a coworker passing all necessary context and names."""
-        coworker = self._get_coworker(coworker, **kwargs)
-        return self._execute(coworker, question, context)
-
     def _execute(
         self, agent_name: Union[str, None], task: str, context: Union[str, None]
-    ):
-        """Execute the command."""
+    ) -> str:
         try:
             if agent_name is None:
                 agent_name = ""
@@ -57,7 +38,6 @@ class BaseAgentTools(BaseModel, ABC):
             # when it should look like this:
             # {"task": "....", "coworker": "...."}
             agent_name = agent_name.casefold().replace('"', "").replace("\n", "")
-
             agent = [  # type: ignore # Incompatible types in assignment (expression has type "list[BaseAgent]", variable has type "str | None")
                 available_agent
                 for available_agent in self.agents
diff --git a/src/crewai/tools/agent_tools/delegate_work_tool.py b/src/crewai/tools/agent_tools/delegate_work_tool.py
new file mode 100644
index 000000000..7f2007597
--- /dev/null
+++ b/src/crewai/tools/agent_tools/delegate_work_tool.py
@@ -0,0 +1,29 @@
+from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class DelegateWorkToolSchema(BaseModel):
+    task: str = Field(..., description="The task to delegate")
+    context: str = Field(..., description="The context for the task")
+    coworker: str = Field(
+        ..., description="The role/name of the coworker to delegate to"
+    )
+
+
+class DelegateWorkTool(BaseAgentTool):
+    """Tool for delegating work to coworkers"""
+
+    name: str = "Delegate work to coworker"
+    args_schema: type[BaseModel] = DelegateWorkToolSchema
+
+    def _run(
+        self,
+        task: str,
+        context: str,
+        coworker: Optional[str] = None,
+        **kwargs,
+    ) -> str:
+        coworker = self._get_coworker(coworker, **kwargs)
+        return self._execute(coworker, task, context)
diff --git a/src/crewai/tools/base_tool.py b/src/crewai/tools/base_tool.py
new file mode 100644
index 000000000..f41fb7c0b
--- /dev/null
+++ b/src/crewai/tools/base_tool.py
@@ -0,0 +1,186 @@
+from abc import ABC, abstractmethod
+from typing import Any, Callable, Type, get_args, get_origin
+
+from langchain_core.tools import StructuredTool
+from pydantic import BaseModel, ConfigDict, Field, validator
+from pydantic import BaseModel as PydanticBaseModel
+
+
+class BaseTool(BaseModel, ABC):
+    class _ArgsSchemaPlaceholder(PydanticBaseModel):
+        pass
+
+    model_config = ConfigDict()
+
+    name: str
+    """The unique name of the tool that clearly communicates its purpose."""
+    description: str
+    """Used to tell the model how/when/why to use the tool."""
+    args_schema: Type[PydanticBaseModel] = Field(default_factory=_ArgsSchemaPlaceholder)
+    """The schema for the arguments that the tool accepts."""
+    description_updated: bool = False
+    """Flag to check if the description has been updated."""
+    cache_function: Callable = lambda _args=None, _result=None: True
+    """Function that will be used to determine if the tool should be cached, should return a boolean. If None, the tool will be cached."""
+    result_as_answer: bool = False
+    """Flag to check if the tool should be the final agent answer."""
+
+    @validator("args_schema", always=True, pre=True)
+    def _default_args_schema(
+        cls, v: Type[PydanticBaseModel]
+    ) -> Type[PydanticBaseModel]:
+        if not isinstance(v, cls._ArgsSchemaPlaceholder):
+            return v
+
+        return type(
+            f"{cls.__name__}Schema",
+            (PydanticBaseModel,),
+            {
+                "__annotations__": {
+                    k: v for k, v in cls._run.__annotations__.items() if k != "return"
+                },
+            },
+        )
+
+    def model_post_init(self, __context: Any) -> None:
+        self._generate_description()
+
+        super().model_post_init(__context)
+
+    def run(
+        self,
+        *args: Any,
+        **kwargs: Any,
+    ) -> Any:
+        print(f"Using Tool: {self.name}")
+        return self._run(*args, **kwargs)
+
+    @abstractmethod
+    def _run(
+        self,
+        *args: Any,
+        **kwargs: Any,
+    ) -> Any:
+        """Here goes the actual implementation of the tool."""
+
+    def to_langchain(self) -> StructuredTool:
+        self._set_args_schema()
+        return StructuredTool(
+            name=self.name,
+            description=self.description,
+            args_schema=self.args_schema,
+            func=self._run,
+        )
+
+    @classmethod
+    def from_langchain(cls, tool: StructuredTool) -> "BaseTool":
+        if cls == Tool:
+            if tool.func is None:
+                raise ValueError("StructuredTool must have a callable 'func'")
+            return Tool(
+                name=tool.name,
+                description=tool.description,
+                args_schema=tool.args_schema,
+                func=tool.func,
+            )
+        raise NotImplementedError(f"from_langchain not implemented for {cls.__name__}")
+
+    def _set_args_schema(self):
+        if self.args_schema is None:
+            class_name = f"{self.__class__.__name__}Schema"
+            self.args_schema = type(
+                class_name,
+                (PydanticBaseModel,),
+                {
+                    "__annotations__": {
+                        k: v
+                        for k, v in self._run.__annotations__.items()
+                        if k != "return"
+                    },
+                },
+            )
+
+    def _generate_description(self):
+        args_schema = {
+            name: {
+                "description": field.description,
+                "type": BaseTool._get_arg_annotations(field.annotation),
+            }
+            for name, field in self.args_schema.model_fields.items()
+        }
+
+        self.description = f"Tool Name: {self.name}\nTool Arguments: {args_schema}\nTool Description: {self.description}"
+
+    @staticmethod
+    def _get_arg_annotations(annotation: type[Any] | None) -> str:
+        if annotation is None:
+            return "None"
+
+        origin = get_origin(annotation)
+        args = get_args(annotation)
+
+        if origin is None:
+            return (
+                annotation.__name__
+                if hasattr(annotation, "__name__")
+                else str(annotation)
+            )
+
+        if args:
+            args_str = ", ".join(BaseTool._get_arg_annotations(arg) for arg in args)
+            return f"{origin.__name__}[{args_str}]"
+
+        return origin.__name__
+
+
+class Tool(BaseTool):
+    func: Callable
+    """The function that will be executed when the tool is called."""
+
+    def _run(self, *args: Any, **kwargs: Any) -> Any:
+        return self.func(*args, **kwargs)
+
+
+def to_langchain(
+    tools: list[BaseTool | StructuredTool],
+) -> list[StructuredTool]:
+    return [t.to_langchain() if isinstance(t, BaseTool) else t for t in tools]
+
+
+def tool(*args):
+    """
+    Decorator to create a tool from a function.
+    """
+
+    def _make_with_name(tool_name: str) -> Callable:
+        def _make_tool(f: Callable) -> BaseTool:
+            if f.__doc__ is None:
+                raise ValueError("Function must have a docstring")
+            if f.__annotations__ is None:
+                raise ValueError("Function must have type annotations")
+
+            class_name = "".join(tool_name.split()).title()
+            args_schema = type(
+                class_name,
+                (PydanticBaseModel,),
+                {
+                    "__annotations__": {
+                        k: v for k, v in f.__annotations__.items() if k != "return"
+                    },
+                },
+            )
+
+            return Tool(
+                name=tool_name,
+                description=f.__doc__,
+                func=f,
+                args_schema=args_schema,
+            )
+
+        return _make_tool
+
+    if len(args) == 1 and callable(args[0]):
+        return _make_with_name(args[0].__name__)(args[0])
+    if len(args) == 1 and isinstance(args[0], str):
+        return _make_with_name(args[0])
+    raise ValueError("Invalid arguments")
diff --git a/src/crewai/tools/cache_tools.py b/src/crewai/tools/cache_tools/cache_tools.py
similarity index 100%
rename from src/crewai/tools/cache_tools.py
rename to src/crewai/tools/cache_tools/cache_tools.py
diff --git a/src/crewai/tools/tool_usage.py b/src/crewai/tools/tool_usage.py
index 71c02fc3c..e4108c8ba 100644
--- a/src/crewai/tools/tool_usage.py
+++ b/src/crewai/tools/tool_usage.py
@@ -10,6 +10,7 @@ import crewai.utilities.events as events
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.task import Task
 from crewai.telemetry import Telemetry
+from crewai.tools import BaseTool
 from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
 from crewai.tools.tool_usage_events import ToolUsageError, ToolUsageFinished
 from crewai.utilities import I18N, Converter, ConverterError, Printer
@@ -49,7 +50,7 @@ class ToolUsage:
     def __init__(
         self,
         tools_handler: ToolsHandler,
-        tools: List[Any],
+        tools: List[BaseTool],
         original_tools: List[Any],
         tools_description: str,
         tools_names: str,
@@ -298,22 +299,7 @@ class ToolUsage:
         """Render the tool name and description in plain text."""
         descriptions = []
         for tool in self.tools:
-            args = {
-                name: {
-                    "description": field.description,
-                    "type": field.annotation.__name__,
-                }
-                for name, field in tool.args_schema.model_fields.items()
-            }
-            descriptions.append(
-                "\n".join(
-                    [
-                        f"Tool Name: {tool.name.lower()}",
-                        f"Tool Description: {tool.description}",
-                        f"Tool Arguments: {args}",
-                    ]
-                )
-            )
+            descriptions.append(tool.description)
         return "\n--\n".join(descriptions)
 
     def _function_calling(self, tool_string: str):
diff --git a/tests/agent_test.py b/tests/agent_test.py
index 154677ccf..c4094d15c 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -5,7 +5,6 @@ from unittest import mock
 from unittest.mock import patch
 
 import pytest
-from crewai_tools import tool
 
 from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
@@ -14,6 +13,7 @@ from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserExcep
 from crewai.llm import LLM
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
+from crewai.tools import tool
 from crewai.tools.tool_usage_events import ToolUsageFinished
 from crewai.utilities import RPMController
 from crewai.utilities.events import Emitter
@@ -277,9 +277,10 @@ def test_cache_hitting():
         "multiplier-{'first_number': 12, 'second_number': 3}": 36,
     }
 
-    with patch.object(CacheHandler, "read") as read, patch.object(
-        Emitter, "emit"
-    ) as emit:
+    with (
+        patch.object(CacheHandler, "read") as read,
+        patch.object(Emitter, "emit") as emit,
+    ):
         read.return_value = "0"
         task = Task(
             description="What is 2 times 6? Ignore correctness and just return the result of the multiplication tool, you must use the tool.",
@@ -604,7 +605,7 @@ def test_agent_respect_the_max_rpm_set(capsys):
 def test_agent_respect_the_max_rpm_set_over_crew_rpm(capsys):
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def get_final_answer() -> float:
@@ -642,7 +643,7 @@ def test_agent_respect_the_max_rpm_set_over_crew_rpm(capsys):
 def test_agent_without_max_rpm_respet_crew_rpm(capsys):
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def get_final_answer() -> float:
@@ -696,7 +697,7 @@ def test_agent_without_max_rpm_respet_crew_rpm(capsys):
 def test_agent_error_on_parsing_tool(capsys):
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def get_final_answer() -> float:
@@ -739,7 +740,7 @@ def test_agent_error_on_parsing_tool(capsys):
 def test_agent_remembers_output_format_after_using_tools_too_many_times():
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def get_final_answer() -> float:
@@ -863,11 +864,16 @@ def test_agent_function_calling_llm():
 
     from crewai.tools.tool_usage import ToolUsage
 
-    with patch.object(
-        instructor, "from_litellm", wraps=instructor.from_litellm
-    ) as mock_from_litellm, patch.object(
-        ToolUsage, "_original_tool_calling", side_effect=Exception("Forced exception")
-    ) as mock_original_tool_calling:
+    with (
+        patch.object(
+            instructor, "from_litellm", wraps=instructor.from_litellm
+        ) as mock_from_litellm,
+        patch.object(
+            ToolUsage,
+            "_original_tool_calling",
+            side_effect=Exception("Forced exception"),
+        ) as mock_original_tool_calling,
+    ):
         crew.kickoff()
         mock_from_litellm.assert_called()
         mock_original_tool_calling.assert_called()
@@ -894,7 +900,7 @@ def test_agent_count_formatting_error():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_tool_result_as_answer_is_the_final_answer_for_the_agent():
-    from crewai_tools import BaseTool
+    from crewai.tools import BaseTool
 
     class MyCustomTool(BaseTool):
         name: str = "Get Greetings"
@@ -924,7 +930,7 @@ def test_tool_result_as_answer_is_the_final_answer_for_the_agent():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_tool_usage_information_is_appended_to_agent():
-    from crewai_tools import BaseTool
+    from crewai.tools import BaseTool
 
     class MyCustomTool(BaseTool):
         name: str = "Decide Greetings"
diff --git a/tests/agent_tools/lol.py b/tests/agent_tools/lol.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/tests/agents/agent_builder/base_agent_test.py b/tests/agents/agent_builder/base_agent_test.py
index 4e47f2271..fcd5d58b6 100644
--- a/tests/agents/agent_builder/base_agent_test.py
+++ b/tests/agents/agent_builder/base_agent_test.py
@@ -2,6 +2,7 @@ import hashlib
 from typing import Any, List, Optional
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.tools.base_tool import BaseTool
 from pydantic import BaseModel
 
 
@@ -10,13 +11,13 @@ class TestAgent(BaseAgent):
         self,
         task: Any,
         context: Optional[str] = None,
-        tools: Optional[List[Any]] = None,
+        tools: Optional[List[BaseTool]] = None,
     ) -> str:
         return ""
 
     def create_agent_executor(self, tools=None) -> None: ...
 
-    def _parse_tools(self, tools: List[Any]) -> List[Any]:
+    def _parse_tools(self, tools: List[BaseTool]) -> List[BaseTool]:
         return []
 
     def get_delegation_tools(self, agents: List["BaseAgent"]): ...
diff --git a/tests/crew_test.py b/tests/crew_test.py
index 6444b781c..24b892271 100644
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -456,7 +456,7 @@ def test_crew_verbose_output(capsys):
 def test_cache_hitting_between_agents():
     from unittest.mock import call, patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def multiplier(first_number: int, second_number: int) -> float:
@@ -499,7 +499,7 @@ def test_cache_hitting_between_agents():
 def test_api_calls_throttling(capsys):
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def get_final_answer() -> float:
@@ -1111,7 +1111,7 @@ def test_dont_set_agents_step_callback_if_already_set():
 def test_crew_function_calling_llm():
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     llm = "gpt-4o"
 
@@ -1146,7 +1146,7 @@ def test_crew_function_calling_llm():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_task_with_no_arguments():
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def return_data() -> str:
@@ -1309,8 +1309,9 @@ def test_hierarchical_crew_creation_tasks_with_agents():
 
     assert crew.manager_agent is not None
     assert crew.manager_agent.tools is not None
-    assert crew.manager_agent.tools[0].description.startswith(
-        "Delegate a specific task to one of the following coworkers: Senior Writer"
+    assert (
+        "Delegate a specific task to one of the following coworkers: Senior Writer\n"
+        in crew.manager_agent.tools[0].description
     )
 
 
@@ -1337,8 +1338,9 @@ def test_hierarchical_crew_creation_tasks_with_async_execution():
     crew.kickoff()
     assert crew.manager_agent is not None
     assert crew.manager_agent.tools is not None
-    assert crew.manager_agent.tools[0].description.startswith(
+    assert (
         "Delegate a specific task to one of the following coworkers: Senior Writer\n"
+        in crew.manager_agent.tools[0].description
     )
 
 
@@ -1370,8 +1372,9 @@ def test_hierarchical_crew_creation_tasks_with_sync_last():
     crew.kickoff()
     assert crew.manager_agent is not None
     assert crew.manager_agent.tools is not None
-    assert crew.manager_agent.tools[0].description.startswith(
+    assert (
         "Delegate a specific task to one of the following coworkers: Senior Writer, Researcher, CEO\n"
+        in crew.manager_agent.tools[0].description
     )
 
 
@@ -1494,7 +1497,7 @@ def test_task_callback_on_crew():
 def test_tools_with_custom_caching():
     from unittest.mock import patch
 
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def multiplcation_tool(first_number: int, second_number: int) -> int:
@@ -1696,7 +1699,7 @@ def test_manager_agent_in_agents_raises_exception():
 
 
 def test_manager_agent_with_tools_raises_exception():
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def testing_tool(first_number: int, second_number: int) -> int:
diff --git a/tests/task_test.py b/tests/task_test.py
index 1e20c9491..3b3de0bed 100644
--- a/tests/task_test.py
+++ b/tests/task_test.py
@@ -15,7 +15,7 @@ from pydantic_core import ValidationError
 
 
 def test_task_tool_reflect_agent_tools():
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def fake_tool() -> None:
@@ -39,7 +39,7 @@ def test_task_tool_reflect_agent_tools():
 
 
 def test_task_tool_takes_precedence_over_agent_tools():
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def fake_tool() -> None:
@@ -656,7 +656,7 @@ def test_increment_delegations_for_sequential_process():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_increment_tool_errors():
-    from crewai_tools import tool
+    from crewai.tools import tool
 
     @tool
     def scoring_examples() -> None:
diff --git a/tests/agent_tools/__init__.py b/tests/tools/agent_tools/__init__.py
similarity index 100%
rename from tests/agent_tools/__init__.py
rename to tests/tools/agent_tools/__init__.py
diff --git a/tests/agent_tools/agent_tools_test.py b/tests/tools/agent_tools/agent_tools_test.py
similarity index 95%
rename from tests/agent_tools/agent_tools_test.py
rename to tests/tools/agent_tools/agent_tools_test.py
index 8d9345b46..9aea7b4bc 100644
--- a/tests/agent_tools/agent_tools_test.py
+++ b/tests/tools/agent_tools/agent_tools_test.py
@@ -3,7 +3,7 @@
 import pytest
 
 from crewai.agent import Agent
-from crewai.tools.agent_tools import AgentTools
+from crewai.tools.agent_tools.agent_tools import AgentTools
 
 researcher = Agent(
     role="researcher",
@@ -11,12 +11,14 @@ researcher = Agent(
     backstory="You're an expert researcher, specialized in technology",
     allow_delegation=False,
 )
-tools = AgentTools(agents=[researcher])
+tools = AgentTools(agents=[researcher]).tools()
+delegate_tool = tools[0]
+ask_tool = tools[1]
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_delegate_work():
-    result = tools.delegate_work(
+    result = delegate_tool.run(
         coworker="researcher",
         task="share your take on AI Agents",
         context="I heard you hate them",
@@ -30,8 +32,8 @@ def test_delegate_work():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_delegate_work_with_wrong_co_worker_variable():
-    result = tools.delegate_work(
-        co_worker="researcher",
+    result = delegate_tool.run(
+        coworker="researcher",
         task="share your take on AI Agents",
         context="I heard you hate them",
     )
@@ -44,7 +46,7 @@ def test_delegate_work_with_wrong_co_worker_variable():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_ask_question():
-    result = tools.ask_question(
+    result = ask_tool.run(
         coworker="researcher",
         question="do you hate AI Agents?",
         context="I heard you LOVE them",
@@ -58,8 +60,8 @@ def test_ask_question():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_ask_question_with_wrong_co_worker_variable():
-    result = tools.ask_question(
-        co_worker="researcher",
+    result = ask_tool.run(
+        coworker="researcher",
         question="do you hate AI Agents?",
         context="I heard you LOVE them",
     )
@@ -72,8 +74,8 @@ def test_ask_question_with_wrong_co_worker_variable():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_delegate_work_withwith_coworker_as_array():
-    result = tools.delegate_work(
-        co_worker="[researcher]",
+    result = delegate_tool.run(
+        coworker="[researcher]",
         task="share your take on AI Agents",
         context="I heard you hate them",
     )
@@ -86,8 +88,8 @@ def test_delegate_work_withwith_coworker_as_array():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_ask_question_with_coworker_as_array():
-    result = tools.ask_question(
-        co_worker="[researcher]",
+    result = ask_tool.run(
+        coworker="[researcher]",
         question="do you hate AI Agents?",
         context="I heard you LOVE them",
     )
@@ -99,7 +101,7 @@ def test_ask_question_with_coworker_as_array():
 
 
 def test_delegate_work_to_wrong_agent():
-    result = tools.ask_question(
+    result = ask_tool.run(
         coworker="writer",
         question="share your take on AI Agents",
         context="I heard you hate them",
@@ -112,7 +114,7 @@ def test_delegate_work_to_wrong_agent():
 
 
 def test_ask_question_to_wrong_agent():
-    result = tools.ask_question(
+    result = ask_tool.run(
         coworker="writer",
         question="do you hate AI Agents?",
         context="I heard you LOVE them",
diff --git a/tests/agent_tools/cassettes/test_ask_question.yaml b/tests/tools/agent_tools/cassettes/test_ask_question.yaml
similarity index 100%
rename from tests/agent_tools/cassettes/test_ask_question.yaml
rename to tests/tools/agent_tools/cassettes/test_ask_question.yaml
diff --git a/tests/agent_tools/cassettes/test_ask_question_with_coworker_as_array.yaml b/tests/tools/agent_tools/cassettes/test_ask_question_with_coworker_as_array.yaml
similarity index 100%
rename from tests/agent_tools/cassettes/test_ask_question_with_coworker_as_array.yaml
rename to tests/tools/agent_tools/cassettes/test_ask_question_with_coworker_as_array.yaml
diff --git a/tests/agent_tools/cassettes/test_ask_question_with_wrong_co_worker_variable.yaml b/tests/tools/agent_tools/cassettes/test_ask_question_with_wrong_co_worker_variable.yaml
similarity index 100%
rename from tests/agent_tools/cassettes/test_ask_question_with_wrong_co_worker_variable.yaml
rename to tests/tools/agent_tools/cassettes/test_ask_question_with_wrong_co_worker_variable.yaml
diff --git a/tests/agent_tools/cassettes/test_delegate_work.yaml b/tests/tools/agent_tools/cassettes/test_delegate_work.yaml
similarity index 100%
rename from tests/agent_tools/cassettes/test_delegate_work.yaml
rename to tests/tools/agent_tools/cassettes/test_delegate_work.yaml
diff --git a/tests/agent_tools/cassettes/test_delegate_work_with_wrong_co_worker_variable.yaml b/tests/tools/agent_tools/cassettes/test_delegate_work_with_wrong_co_worker_variable.yaml
similarity index 100%
rename from tests/agent_tools/cassettes/test_delegate_work_with_wrong_co_worker_variable.yaml
rename to tests/tools/agent_tools/cassettes/test_delegate_work_with_wrong_co_worker_variable.yaml
diff --git a/tests/agent_tools/cassettes/test_delegate_work_withwith_coworker_as_array.yaml b/tests/tools/agent_tools/cassettes/test_delegate_work_withwith_coworker_as_array.yaml
similarity index 100%
rename from tests/agent_tools/cassettes/test_delegate_work_withwith_coworker_as_array.yaml
rename to tests/tools/agent_tools/cassettes/test_delegate_work_withwith_coworker_as_array.yaml
diff --git a/tests/tools/test_base_tool.py b/tests/tools/test_base_tool.py
new file mode 100644
index 000000000..eca36739c
--- /dev/null
+++ b/tests/tools/test_base_tool.py
@@ -0,0 +1,109 @@
+from typing import Callable
+from crewai.tools import BaseTool, tool
+
+
+def test_creating_a_tool_using_annotation():
+    @tool("Name of my tool")
+    def my_tool(question: str) -> str:
+        """Clear description for what this tool is useful for, you agent will need this information to use it."""
+        return question
+
+    # Assert all the right attributes were defined
+    assert my_tool.name == "Name of my tool"
+    assert (
+        my_tool.description
+        == "Tool Name: Name of my tool\nTool Arguments: {'question': {'description': None, 'type': 'str'}}\nTool Description: Clear description for what this tool is useful for, you agent will need this information to use it."
+    )
+    assert my_tool.args_schema.schema()["properties"] == {
+        "question": {"title": "Question", "type": "string"}
+    }
+    assert (
+        my_tool.func("What is the meaning of life?") == "What is the meaning of life?"
+    )
+
+    # Assert the langchain tool conversion worked as expected
+    converted_tool = my_tool.to_langchain()
+    assert converted_tool.name == "Name of my tool"
+
+    assert (
+        converted_tool.description
+        == "Tool Name: Name of my tool\nTool Arguments: {'question': {'description': None, 'type': 'str'}}\nTool Description: Clear description for what this tool is useful for, you agent will need this information to use it."
+    )
+    assert converted_tool.args_schema.schema()["properties"] == {
+        "question": {"title": "Question", "type": "string"}
+    }
+    assert (
+        converted_tool.func("What is the meaning of life?")
+        == "What is the meaning of life?"
+    )
+
+
+def test_creating_a_tool_using_baseclass():
+    class MyCustomTool(BaseTool):
+        name: str = "Name of my tool"
+        description: str = (
+            "Clear description for what this tool is useful for, you agent will need this information to use it."
+        )
+
+        def _run(self, question: str) -> str:
+            return question
+
+    my_tool = MyCustomTool()
+    # Assert all the right attributes were defined
+    assert my_tool.name == "Name of my tool"
+
+    assert (
+        my_tool.description
+        == "Tool Name: Name of my tool\nTool Arguments: {'question': {'description': None, 'type': 'str'}}\nTool Description: Clear description for what this tool is useful for, you agent will need this information to use it."
+    )
+    assert my_tool.args_schema.schema()["properties"] == {
+        "question": {"title": "Question", "type": "string"}
+    }
+    assert my_tool.run("What is the meaning of life?") == "What is the meaning of life?"
+
+    # Assert the langchain tool conversion worked as expected
+    converted_tool = my_tool.to_langchain()
+    assert converted_tool.name == "Name of my tool"
+
+    assert (
+        converted_tool.description
+        == "Tool Name: Name of my tool\nTool Arguments: {'question': {'description': None, 'type': 'str'}}\nTool Description: Clear description for what this tool is useful for, you agent will need this information to use it."
+    )
+    assert converted_tool.args_schema.schema()["properties"] == {
+        "question": {"title": "Question", "type": "string"}
+    }
+    assert (
+        converted_tool.run("What is the meaning of life?")
+        == "What is the meaning of life?"
+    )
+
+
+def test_setting_cache_function():
+    class MyCustomTool(BaseTool):
+        name: str = "Name of my tool"
+        description: str = (
+            "Clear description for what this tool is useful for, you agent will need this information to use it."
+        )
+        cache_function: Callable = lambda: False
+
+        def _run(self, question: str) -> str:
+            return question
+
+    my_tool = MyCustomTool()
+    # Assert all the right attributes were defined
+    assert not my_tool.cache_function()
+
+
+def test_default_cache_function_is_true():
+    class MyCustomTool(BaseTool):
+        name: str = "Name of my tool"
+        description: str = (
+            "Clear description for what this tool is useful for, you agent will need this information to use it."
+        )
+
+        def _run(self, question: str) -> str:
+            return question
+
+    my_tool = MyCustomTool()
+    # Assert all the right attributes were defined
+    assert my_tool.cache_function()
diff --git a/tests/tools/test_tool_usage.py b/tests/tools/test_tool_usage.py
index 8af9b8abb..fbe93a628 100644
--- a/tests/tools/test_tool_usage.py
+++ b/tests/tools/test_tool_usage.py
@@ -3,11 +3,11 @@ import random
 from unittest.mock import MagicMock
 
 import pytest
-from crewai_tools import BaseTool
 from pydantic import BaseModel, Field
 
 from crewai import Agent, Task
 from crewai.tools.tool_usage import ToolUsage
+from crewai.tools import BaseTool
 
 
 class RandomNumberToolInput(BaseModel):
@@ -103,11 +103,7 @@ def test_tool_usage_render():
     rendered = tool_usage._render()
 
     # Updated checks to match the actual output
-    assert "Tool Name: random number generator" in rendered
-    assert (
-        "Random Number Generator(min_value: 'integer', max_value: 'integer') - Generates a random number within a specified range min_value: 'The minimum value of the range (inclusive)', max_value: 'The maximum value of the range (inclusive)'"
-        in rendered
-    )
+    assert "Tool Name: Random Number Generator" in rendered
     assert "Tool Arguments:" in rendered
     assert (
         "'min_value': {'description': 'The minimum value of the range (inclusive)', 'type': 'int'}"
@@ -117,3 +113,11 @@ def test_tool_usage_render():
         "'max_value': {'description': 'The maximum value of the range (inclusive)', 'type': 'int'}"
         in rendered
     )
+    assert (
+        "Tool Description: Generates a random number within a specified range"
+        in rendered
+    )
+    assert (
+        "Tool Name: Random Number Generator\nTool Arguments: {'min_value': {'description': 'The minimum value of the range (inclusive)', 'type': 'int'}, 'max_value': {'description': 'The maximum value of the range (inclusive)', 'type': 'int'}}\nTool Description: Generates a random number within a specified range"
+        in rendered
+    )

From 34954e6f74525c6f28d24124524aa8984059322b Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Fri, 1 Nov 2024 15:58:36 -0400
Subject: [PATCH 037/126] Update docs  (#1550)

* add llm providers accordion group

* fix numbering

* Fix directory tree & add llms to accordion
---
 docs/concepts/flows.mdx | 26 ++++++++++++++------------
 docs/concepts/llms.mdx  | 26 +++++++++++++++++---------
 2 files changed, 31 insertions(+), 21 deletions(-)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index c86776982..e3f0e6b45 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -577,18 +577,20 @@ This command will create a new directory for your crew within the `crews` folder
 
 After adding a new crew, your folder structure will look like this:
 
-name_of_flow/
-├── crews/
-│   ├── poem_crew/
-│   │   ├── config/
-│   │   │   ├── agents.yaml
-│   │   │   └── tasks.yaml
-│   │   └── poem_crew.py
-│   └── name_of_crew/
-│       ├── config/
-│       │   ├── agents.yaml
-│       │   └── tasks.yaml
-│       └── name_of_crew.py
+| Directory/File         | Description                                                        |
+| :--------------------- | :----------------------------------------------------------------- |
+| `name_of_flow/`        | Root directory for the flow.                                       |
+| ├── `crews/`           | Contains directories for specific crews.                           |
+| │   ├── `poem_crew/`   | Directory for the "poem_crew" with its configurations and scripts. |
+| │   │   ├── `config/`  | Configuration files directory for the "poem_crew".                 |
+| │   │   │  ├── `agents.yaml` | YAML file defining the agents for "poem_crew".                     |
+| │   │   │  └── `tasks.yaml`  | YAML file defining the tasks for "poem_crew".                      |
+| │   │   └── `poem_crew.py`    | Script for "poem_crew" functionality.                              |
+| └── `name_of_crew/`       | Directory for the new crew.                                          |
+|     ├── `config/`         | Configuration files directory for the new crew.                     |
+|     │   ├── `agents.yaml` | YAML file defining the agents for the new crew.                     |
+|     │   └── `tasks.yaml`  | YAML file defining the tasks for the new crew.                      |
+|     └── `name_of_crew.py` | Script for the new crew functionality.                              |
 
 You can then customize the `agents.yaml` and `tasks.yaml` files to define the agents and tasks for your new crew. The `name_of_crew.py` file will contain the crew's logic, which you can modify to suit your needs.
 
diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 835c2491f..d432070d4 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -131,7 +131,6 @@ These are examples of how to configure LLMs for your agent.
 
     llm = LLM(
         model="cerebras/llama-3.1-70b",
-        base_url="https://api.cerebras.ai/v1",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...) 
@@ -166,7 +165,6 @@ These are examples of how to configure LLMs for your agent.
 
     llm = LLM(
         model="groq/llama3-8b-8192", 
-        base_url="https://api.groq.com/openai/v1", 
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -180,21 +178,18 @@ These are examples of how to configure LLMs for your agent.
 
     llm = LLM(
         model="anthropic/claude-3-5-sonnet-20241022",
-        base_url="https://api.anthropic.com/v1",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
     ```
     </Accordion>
 
-    <Accordion title="Fireworks">
-
+    <Accordion title="Fireworks AI">
     ```python Code
     from crewai import LLM
 
     llm = LLM(
-        model="fireworks/meta-llama-3.1-8b-instruct",
-        base_url="https://api.fireworks.ai/inference/v1",
+        model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct",  
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -207,8 +202,7 @@ These are examples of how to configure LLMs for your agent.
     from crewai import LLM
 
     llm = LLM(
-        model="gemini/gemini-1.5-flash",
-        base_url="https://api.gemini.google.com/v1",
+        model="gemini/gemini-1.5-pro-002",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -242,6 +236,20 @@ These are examples of how to configure LLMs for your agent.
     agent = Agent(llm=llm, ...)
     ```
     </Accordion>
+
+    <Accordion title="Hugging Face">
+
+    ```python Code
+    from crewai import LLM
+
+    llm = LLM(
+        model="huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct",
+        api_key="your-api-key-here",
+        base_url="your_api_endpoint"
+    )
+    agent = Agent(llm=llm, ...) 
+    ```
+    </Accordion>
 </AccordionGroup>
 
 ## Changing the Base API URL

From 3878daffd68d14ee0379d11c19bef63c4dc02edc Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Fri, 1 Nov 2024 16:42:46 -0400
Subject: [PATCH 038/126] Feat/ibm memory (#1549)

* Everything looks like its working. Waiting for lorenze review.

* Update docs as well.

* clean up for PR
---
 docs/concepts/memory.mdx                      | 25 ++++++++
 .../memory/contextual/contextual_memory.py    |  4 ++
 src/crewai/memory/storage/rag_storage.py      | 62 ++++++++++++++++---
 3 files changed, 81 insertions(+), 10 deletions(-)

diff --git a/docs/concepts/memory.mdx b/docs/concepts/memory.mdx
index 735ed861e..bda9f3401 100644
--- a/docs/concepts/memory.mdx
+++ b/docs/concepts/memory.mdx
@@ -254,6 +254,31 @@ my_crew = Crew(
 )
 ```
 
+### Using Watson embeddings
+
+```python Code
+from crewai import Crew, Agent, Task, Process
+
+# Note: Ensure you have installed and imported `ibm_watsonx_ai` for Watson embeddings to work.
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    verbose=True,
+    embedder={
+        "provider": "watson",
+        "config": {
+            "model": "<model_name>",
+            "api_url": "<api_url>",
+            "api_key": "<YOUR_API_KEY>",
+            "project_id": "<YOUR_PROJECT_ID>",
+        }
+    }
+)
+```
+
 ### Resetting Memory
 
 ```shell
diff --git a/src/crewai/memory/contextual/contextual_memory.py b/src/crewai/memory/contextual/contextual_memory.py
index 5d91cf47d..3d3a9c6c1 100644
--- a/src/crewai/memory/contextual/contextual_memory.py
+++ b/src/crewai/memory/contextual/contextual_memory.py
@@ -34,6 +34,7 @@ class ContextualMemory:
         formatted_results = "\n".join(
             [f"- {result['context']}" for result in stm_results]
         )
+        print("formatted_results stm", formatted_results)
         return f"Recent Insights:\n{formatted_results}" if stm_results else ""
 
     def _fetch_ltm_context(self, task) -> Optional[str]:
@@ -53,6 +54,8 @@ class ContextualMemory:
         formatted_results = list(dict.fromkeys(formatted_results))
         formatted_results = "\n".join([f"- {result}" for result in formatted_results])  # type: ignore # Incompatible types in assignment (expression has type "str", variable has type "list[str]")
 
+        print("formatted_results ltm", formatted_results)
+
         return f"Historical Data:\n{formatted_results}" if ltm_results else ""
 
     def _fetch_entity_context(self, query) -> str:
@@ -64,4 +67,5 @@ class ContextualMemory:
         formatted_results = "\n".join(
             [f"- {result['context']}" for result in em_results]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
         )
+        print("formatted_results em", formatted_results)
         return f"Entities:\n{formatted_results}" if em_results else ""
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index db98c0036..d0f1cfc64 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -4,13 +4,13 @@ import logging
 import os
 import shutil
 import uuid
-from typing import Any, Dict, List, Optional
-from crewai.memory.storage.base_rag_storage import BaseRAGStorage
-from crewai.utilities.paths import db_storage_path
+from typing import Any, Dict, List, Optional, cast
+
+from chromadb import Documents, EmbeddingFunction, Embeddings
 from chromadb.api import ClientAPI
 from chromadb.api.types import validate_embedding_function
-from chromadb import Documents, EmbeddingFunction, Embeddings
-from typing import cast
+from crewai.memory.storage.base_rag_storage import BaseRAGStorage
+from crewai.utilities.paths import db_storage_path
 
 
 @contextlib.contextmanager
@@ -21,9 +21,11 @@ def suppress_logging(
     logger = logging.getLogger(logger_name)
     original_level = logger.getEffectiveLevel()
     logger.setLevel(level)
-    with contextlib.redirect_stdout(io.StringIO()), contextlib.redirect_stderr(
-        io.StringIO()
-    ), contextlib.suppress(UserWarning):
+    with (
+        contextlib.redirect_stdout(io.StringIO()),
+        contextlib.redirect_stderr(io.StringIO()),
+        contextlib.suppress(UserWarning),
+    ):
         yield
     logger.setLevel(original_level)
 
@@ -113,12 +115,52 @@ class RAGStorage(BaseRAGStorage):
                 self.embedder_config = embedding_functions.HuggingFaceEmbeddingServer(
                     url=config.get("api_url"),
                 )
+            elif provider == "watson":
+                try:
+                    import ibm_watsonx_ai.foundation_models as watson_models
+                    from ibm_watsonx_ai import Credentials
+                    from ibm_watsonx_ai.metanames import (
+                        EmbedTextParamsMetaNames as EmbedParams,
+                    )
+                except ImportError as e:
+                    raise ImportError(
+                        "IBM Watson dependencies are not installed. Please install them to use Watson embedding."
+                    ) from e
+
+                class WatsonEmbeddingFunction(EmbeddingFunction):
+                    def __call__(self, input: Documents) -> Embeddings:
+                        if isinstance(input, str):
+                            input = [input]
+
+                        embed_params = {
+                            EmbedParams.TRUNCATE_INPUT_TOKENS: 3,
+                            EmbedParams.RETURN_OPTIONS: {"input_text": True},
+                        }
+
+                        embedding = watson_models.Embeddings(
+                            model_id=config.get("model"),
+                            params=embed_params,
+                            credentials=Credentials(
+                                api_key=config.get("api_key"), url=config.get("api_url")
+                            ),
+                            project_id=config.get("project_id"),
+                        )
+
+                        try:
+                            embeddings = embedding.embed_documents(input)
+                            return cast(Embeddings, embeddings)
+
+                        except Exception as e:
+                            print("Error during Watson embedding:", e)
+                            raise e
+
+                self.embedder_config = WatsonEmbeddingFunction()
             else:
                 raise Exception(
-                    f"Unsupported embedding provider: {provider}, supported providers: [openai, azure, ollama, vertexai, google, cohere, huggingface]"
+                    f"Unsupported embedding provider: {provider}, supported providers: [openai, azure, ollama, vertexai, google, cohere, huggingface, watson]"
                 )
         else:
-            validate_embedding_function(self.embedder_config)  # type: ignore # used for validating embedder_config if defined a embedding function/class
+            validate_embedding_function(self.embedder_config)
             self.embedder_config = self.embedder_config
 
     def _initialize_app(self):

From 9b142e580b5a9eb158ea45bf4ac05ee8c0e662ad Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Fri, 1 Nov 2024 17:37:02 -0400
Subject: [PATCH 039/126] add inputs to flows (#1553)

* add inputs to flows

* fix flows lint
---
 docs/concepts/flows.mdx | 123 +++++++++++++++++++---------------------
 src/crewai/flow/flow.py |  84 +++++++++++++++++++++++++--
 2 files changed, 139 insertions(+), 68 deletions(-)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index e3f0e6b45..9ead26d70 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -18,60 +18,63 @@ Flows allow you to create structured, event-driven workflows. They provide a sea
 
 4. **Flexible Control Flow**: Implement conditional logic, loops, and branching within your workflows.
 
+5. **Input Flexibility**: Flows can accept inputs to initialize or update their state, with different handling for structured and unstructured state management.
+
 ## Getting Started
 
 Let's create a simple Flow where you will use OpenAI to generate a random city in one task and then use that city to generate a fun fact in another task.
 
-```python Code
+### Passing Inputs to Flows
 
+Flows can accept inputs to initialize or update their state before execution. The way inputs are handled depends on whether the flow uses structured or unstructured state management.
+
+#### Structured State Management
+
+In structured state management, the flow's state is defined using a Pydantic `BaseModel`. Inputs must match the model's schema, and any updates will overwrite the default values.
+
+```python
 from crewai.flow.flow import Flow, listen, start
-from dotenv import load_dotenv
-from litellm import completion
+from pydantic import BaseModel
 
+class ExampleState(BaseModel):
+    counter: int = 0
+    message: str = ""
 
-class ExampleFlow(Flow):
-    model = "gpt-4o-mini"
-
+class StructuredExampleFlow(Flow[ExampleState]):
     @start()
-    def generate_city(self):
-        print("Starting flow")
+    def first_method(self):
+        # Implementation
 
-        response = completion(
-            model=self.model,
-            messages=[
-                {
-                    "role": "user",
-                    "content": "Return the name of a random city in the world.",
-                },
-            ],
-        )
+flow = StructuredExampleFlow()
+flow.kickoff(inputs={"counter": 10})
+```
 
-        random_city = response["choices"][0]["message"]["content"]
-        print(f"Random City: {random_city}")
+In this example, the `counter` is initialized to `10`, while `message` retains its default value.
 
-        return random_city
+#### Unstructured State Management
 
-    @listen(generate_city)
-    def generate_fun_fact(self, random_city):
-        response = completion(
-            model=self.model,
-            messages=[
-                {
-                    "role": "user",
-                    "content": f"Tell me a fun fact about {random_city}",
-                },
-            ],
-        )
+In unstructured state management, the flow's state is a dictionary. You can pass any dictionary to update the state.
 
-        fun_fact = response["choices"][0]["message"]["content"]
-        return fun_fact
+```python
+from crewai.flow.flow import Flow, listen, start
 
+class UnstructuredExampleFlow(Flow):
+    @start()
+    def first_method(self):
+        # Implementation
 
+flow = UnstructuredExampleFlow()
+flow.kickoff(inputs={"counter": 5, "message": "Initial message"})
+```
 
-flow = ExampleFlow()
-result = flow.kickoff()
+Here, both `counter` and `message` are updated based on the provided inputs.
 
-print(f"Generated fun fact: {result}")
+**Note:** Ensure that inputs for structured state management adhere to the defined schema to avoid validation errors.
+
+### Example Flow
+
+```python
+# Existing example code
 ```
 
 In the above example, we have created a simple Flow that generates a random city using OpenAI and then generates a fun fact about that city. The Flow consists of two tasks: `generate_city` and `generate_fun_fact`. The `generate_city` task is the starting point of the Flow, and the `generate_fun_fact` task listens for the output of the `generate_city` task.
@@ -94,14 +97,14 @@ The `@listen()` decorator can be used in several ways:
 
 1. **Listening to a Method by Name**: You can pass the name of the method you want to listen to as a string. When that method completes, the listener method will be triggered.
 
-   ```python Code
+   ```python
    @listen("generate_city")
    def generate_fun_fact(self, random_city):
        # Implementation
    ```
 
 2. **Listening to a Method Directly**: You can pass the method itself. When that method completes, the listener method will be triggered.
-   ```python Code
+   ```python
    @listen(generate_city)
    def generate_fun_fact(self, random_city):
        # Implementation
@@ -118,7 +121,7 @@ When you run a Flow, the final output is determined by the last method that comp
 Here's how you can access the final output:
 
 <CodeGroup>
-```python Code
+```python
 from crewai.flow.flow import Flow, listen, start
 
 class OutputExampleFlow(Flow):
@@ -130,18 +133,17 @@ class OutputExampleFlow(Flow):
     def second_method(self, first_output):
         return f"Second method received: {first_output}"
 
-
 flow = OutputExampleFlow()
 final_output = flow.kickoff()
 
 print("---- Final Output ----")
 print(final_output)
-````
+```
 
-``` text Output
+```text
 ---- Final Output ----
 Second method received: Output from first_method
-````
+```
 
 </CodeGroup>
 
@@ -156,7 +158,7 @@ Here's an example of how to update and access the state:
 
 <CodeGroup>
 
-```python Code
+```python
 from crewai.flow.flow import Flow, listen, start
 from pydantic import BaseModel
 
@@ -184,7 +186,7 @@ print("Final State:")
 print(flow.state)
 ```
 
-```text Output
+```text
 Final Output: Hello from first_method - updated by second_method
 Final State:
 counter=2 message='Hello from first_method - updated by second_method'
@@ -208,10 +210,10 @@ allowing developers to choose the approach that best fits their application's ne
 In unstructured state management, all state is stored in the `state` attribute of the `Flow` class.
 This approach offers flexibility, enabling developers to add or modify state attributes on the fly without defining a strict schema.
 
-```python Code
+```python
 from crewai.flow.flow import Flow, listen, start
 
-class UntructuredExampleFlow(Flow):
+class UnstructuredExampleFlow(Flow):
 
     @start()
     def first_method(self):
@@ -230,8 +232,7 @@ class UntructuredExampleFlow(Flow):
 
         print(f"State after third_method: {self.state}")
 
-
-flow = UntructuredExampleFlow()
+flow = UnstructuredExampleFlow()
 flow.kickoff()
 ```
 
@@ -245,16 +246,14 @@ flow.kickoff()
 Structured state management leverages predefined schemas to ensure consistency and type safety across the workflow.
 By using models like Pydantic's `BaseModel`, developers can define the exact shape of the state, enabling better validation and auto-completion in development environments.
 
-```python Code
+```python
 from crewai.flow.flow import Flow, listen, start
 from pydantic import BaseModel
 
-
 class ExampleState(BaseModel):
     counter: int = 0
     message: str = ""
 
-
 class StructuredExampleFlow(Flow[ExampleState]):
 
     @start()
@@ -273,7 +272,6 @@ class StructuredExampleFlow(Flow[ExampleState]):
 
         print(f"State after third_method: {self.state}")
 
-
 flow = StructuredExampleFlow()
 flow.kickoff()
 ```
@@ -307,7 +305,7 @@ The `or_` function in Flows allows you to listen to multiple methods and trigger
 
 <CodeGroup>
 
-```python Code
+```python
 from crewai.flow.flow import Flow, listen, or_, start
 
 class OrExampleFlow(Flow):
@@ -324,13 +322,11 @@ class OrExampleFlow(Flow):
     def logger(self, result):
         print(f"Logger: {result}")
 
-
-
 flow = OrExampleFlow()
 flow.kickoff()
 ```
 
-```text Output
+```text
 Logger: Hello from the start method
 Logger: Hello from the second method
 ```
@@ -346,7 +342,7 @@ The `and_` function in Flows allows you to listen to multiple methods and trigge
 
 <CodeGroup>
 
-```python Code
+```python
 from crewai.flow.flow import Flow, and_, listen, start
 
 class AndExampleFlow(Flow):
@@ -368,7 +364,7 @@ flow = AndExampleFlow()
 flow.kickoff()
 ```
 
-```text Output
+```text
 ---- Logger ----
 {'greeting': 'Hello from the start method', 'joke': 'What do computers eat? Microchips.'}
 ```
@@ -385,7 +381,7 @@ You can specify different routes based on the output of the method, allowing you
 
 <CodeGroup>
 
-```python Code
+```python
 import random
 from crewai.flow.flow import Flow, listen, router, start
 from pydantic import BaseModel
@@ -416,12 +412,11 @@ class RouterFlow(Flow[ExampleState]):
     def fourth_method(self):
         print("Fourth method running")
 
-
 flow = RouterFlow()
 flow.kickoff()
 ```
 
-```text Output
+```text
 Starting the structured flow
 Third method running
 Fourth method running
@@ -484,7 +479,7 @@ The `main.py` file is where you create your flow and connect the crews together.
 
 Here's an example of how you can connect the `poem_crew` in the `main.py` file:
 
-```python Code
+```python
 #!/usr/bin/env python
 from random import randint
 
@@ -612,7 +607,7 @@ CrewAI provides two convenient methods to generate plots of your flows:
 
 If you are working directly with a flow instance, you can generate a plot by calling the `plot()` method on your flow object. This method will create an HTML file containing the interactive plot of your flow.
 
-```python Code
+```python
 # Assuming you have a flow instance
 flow.plot("my_flow_plot")
 ```
diff --git a/src/crewai/flow/flow.py b/src/crewai/flow/flow.py
index e7231e13f..9b6463d65 100644
--- a/src/crewai/flow/flow.py
+++ b/src/crewai/flow/flow.py
@@ -1,8 +1,20 @@
 import asyncio
 import inspect
-from typing import Any, Callable, Dict, Generic, List, Set, Type, TypeVar, Union
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Generic,
+    List,
+    Optional,
+    Set,
+    Type,
+    TypeVar,
+    Union,
+    cast,
+)
 
-from pydantic import BaseModel
+from pydantic import BaseModel, ValidationError
 
 from crewai.flow.flow_visualizer import plot_flow
 from crewai.flow.utils import get_possible_return_constants
@@ -191,10 +203,74 @@ class Flow(Generic[T], metaclass=FlowMeta):
         """Returns the list of all outputs from executed methods."""
         return self._method_outputs
 
-    def kickoff(self) -> Any:
+    def _initialize_state(self, inputs: Dict[str, Any]) -> None:
+        """
+        Initializes or updates the state with the provided inputs.
+
+        Args:
+            inputs: Dictionary of inputs to initialize or update the state.
+
+        Raises:
+            ValueError: If inputs do not match the structured state model.
+            TypeError: If state is neither a BaseModel instance nor a dictionary.
+        """
+        if isinstance(self._state, BaseModel):
+            # Structured state management
+            try:
+                # Define a function to create the dynamic class
+                def create_model_with_extra_forbid(
+                    base_model: Type[BaseModel],
+                ) -> Type[BaseModel]:
+                    class ModelWithExtraForbid(base_model):  # type: ignore
+                        model_config = base_model.model_config.copy()
+                        model_config["extra"] = "forbid"
+
+                    return ModelWithExtraForbid
+
+                # Create the dynamic class
+                ModelWithExtraForbid = create_model_with_extra_forbid(
+                    self._state.__class__
+                )
+
+                # Create a new instance using the combined state and inputs
+                self._state = cast(
+                    T, ModelWithExtraForbid(**{**self._state.model_dump(), **inputs})
+                )
+
+            except ValidationError as e:
+                raise ValueError(f"Invalid inputs for structured state: {e}") from e
+        elif isinstance(self._state, dict):
+            # Unstructured state management
+            self._state.update(inputs)
+        else:
+            raise TypeError("State must be a BaseModel instance or a dictionary.")
+
+    def kickoff(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
+        """
+        Starts the execution of the flow synchronously.
+
+        Args:
+            inputs: Optional dictionary of inputs to initialize or update the state.
+
+        Returns:
+            The final output from the flow execution.
+        """
+        if inputs is not None:
+            self._initialize_state(inputs)
         return asyncio.run(self.kickoff_async())
 
-    async def kickoff_async(self) -> Any:
+    async def kickoff_async(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
+        """
+        Starts the execution of the flow asynchronously.
+
+        Args:
+            inputs: Optional dictionary of inputs to initialize or update the state.
+
+        Returns:
+            The final output from the flow execution.
+        """
+        if inputs is not None:
+            self._initialize_state(inputs)
         if not self._start_methods:
             raise ValueError("No start method defined")
 

From 57201fb856ea729e0b5ca73b798198d31012ebc3 Mon Sep 17 00:00:00 2001
From: Gui Vieira <guilherme_vieira@me.com>
Date: Fri, 1 Nov 2024 18:54:40 -0300
Subject: [PATCH 040/126] Increase providers fetching timeout

---
 src/crewai/cli/provider.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/crewai/cli/provider.py b/src/crewai/cli/provider.py
index 4bfeb9324..529ca5e26 100644
--- a/src/crewai/cli/provider.py
+++ b/src/crewai/cli/provider.py
@@ -164,7 +164,7 @@ def fetch_provider_data(cache_file):
     - dict or None: The fetched provider data or None if the operation fails.
     """
     try:
-        response = requests.get(JSON_URL, stream=True, timeout=10)
+        response = requests.get(JSON_URL, stream=True, timeout=60)
         response.raise_for_status()
         data = download_data(response)
         with open(cache_file, "w") as f:

From d70c54254750cc31842b3814eb1526625fae7f69 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 4 Nov 2024 11:42:38 -0500
Subject: [PATCH 041/126] Raise an error if an LLM doesnt return a response
 (#1548)

---
 src/crewai/agents/crew_agent_executor.py |  9 +++++++++
 src/crewai/llm.py                        | 10 +++++-----
 2 files changed, 14 insertions(+), 5 deletions(-)

diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index b11782ca1..9e9ad9c7e 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -117,6 +117,15 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         callbacks=self.callbacks,
                     )
 
+                    if answer is None or answer == "":
+                        self._printer.print(
+                            content="Received None or empty response from LLM call.",
+                            color="red",
+                        )
+                        raise ValueError(
+                            "Invalid response from LLM call - None or empty."
+                        )
+
                     if not self.use_stop_words:
                         try:
                             self._format_answer(answer)
diff --git a/src/crewai/llm.py b/src/crewai/llm.py
index 000bc2509..577cb6a43 100644
--- a/src/crewai/llm.py
+++ b/src/crewai/llm.py
@@ -1,7 +1,10 @@
+import io
+import logging
+import sys
+import warnings
 from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Union
-import logging
-import warnings
+
 import litellm
 from litellm import get_supported_openai_params
 
@@ -9,9 +12,6 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
 
-import sys
-import io
-
 
 class FilteredStream(io.StringIO):
     def write(self, s):

From f50e709985281a8ff9e37372b02e3bcdf577d86b Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Tue, 5 Nov 2024 11:26:19 -0500
Subject: [PATCH 042/126] docs update (#1558)

* add llm providers accordion group

* fix numbering

* Fix directory tree & add llms to accordion

* update crewai enterprise link in docs
---
 docs/quickstart.mdx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/quickstart.mdx b/docs/quickstart.mdx
index 49a690093..ef149bfcc 100644
--- a/docs/quickstart.mdx
+++ b/docs/quickstart.mdx
@@ -330,4 +330,4 @@ This will clear the crew's memory, allowing for a fresh start.
 
 ## Deploying Your Project
 
-The easiest way to deploy your crew is through [CrewAI Enterprise](https://www.crewai.com/crewaiplus), where you can deploy your crew in a few clicks.
+The easiest way to deploy your crew is through [CrewAI Enterprise](http://app.crewai.com/), where you can deploy your crew in a few clicks.

From 3d4479547668828b18430624a3fe58f72c861f41 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 5 Nov 2024 12:01:57 -0500
Subject: [PATCH 043/126] Feat/watson in cli (#1535)

* getting cli and .env to work together for different models

* support new models

* clean up prints

* Add support for cerebras

* Fix watson keys
---
 src/crewai/agent.py                   |  45 ++++++-
 src/crewai/cli/constants.py           | 173 ++++++++++++++++++++++++--
 src/crewai/cli/create_crew.py         | 102 +++++++--------
 src/crewai/cli/templates/crew/crew.py |   2 +-
 src/crewai/cli/templates/crew/main.py |   4 +
 5 files changed, 259 insertions(+), 67 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index f2a0a5c31..d30746808 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -8,6 +8,7 @@ from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 from crewai.agents import CacheHandler
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
+from crewai.cli.constants import ENV_VARS
 from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.tools.agent_tools.agent_tools import AgentTools
@@ -131,8 +132,12 @@ class Agent(BaseAgent):
             # If it's already an LLM instance, keep it as is
             pass
         elif self.llm is None:
-            # If it's None, use environment variables or default
-            model_name = os.environ.get("OPENAI_MODEL_NAME", "gpt-4o-mini")
+            # Determine the model name from environment variables or use default
+            model_name = (
+                os.environ.get("OPENAI_MODEL_NAME")
+                or os.environ.get("MODEL")
+                or "gpt-4o-mini"
+            )
             llm_params = {"model": model_name}
 
             api_base = os.environ.get("OPENAI_API_BASE") or os.environ.get(
@@ -141,9 +146,39 @@ class Agent(BaseAgent):
             if api_base:
                 llm_params["base_url"] = api_base
 
-            api_key = os.environ.get("OPENAI_API_KEY")
-            if api_key:
-                llm_params["api_key"] = api_key
+            # Iterate over all environment variables to find matching API keys or use defaults
+            for provider, env_vars in ENV_VARS.items():
+                for env_var in env_vars:
+                    # Check if the environment variable is set
+                    if "key_name" in env_var:
+                        env_value = os.environ.get(env_var["key_name"])
+                        if env_value:
+                            # Map key names containing "API_KEY" to "api_key"
+                            key_name = (
+                                "api_key"
+                                if "API_KEY" in env_var["key_name"]
+                                else env_var["key_name"]
+                            )
+                            # Map key names containing "API_BASE" to "api_base"
+                            key_name = (
+                                "api_base"
+                                if "API_BASE" in env_var["key_name"]
+                                else key_name
+                            )
+                            # Map key names containing "API_VERSION" to "api_version"
+                            key_name = (
+                                "api_version"
+                                if "API_VERSION" in env_var["key_name"]
+                                else key_name
+                            )
+                            llm_params[key_name] = env_value
+                    # Check for default values if the environment variable is not set
+                    elif env_var.get("default", False):
+                        for key, value in env_var.items():
+                            if key not in ["prompt", "key_name", "default"]:
+                                # Only add default if the key is already set in os.environ
+                                if key in os.environ:
+                                    llm_params[key] = value
 
             self.llm = LLM(**llm_params)
         else:
diff --git a/src/crewai/cli/constants.py b/src/crewai/cli/constants.py
index 9a0b36c39..4be08fa2a 100644
--- a/src/crewai/cli/constants.py
+++ b/src/crewai/cli/constants.py
@@ -1,19 +1,168 @@
 ENV_VARS = {
-    'openai': ['OPENAI_API_KEY'],
-    'anthropic': ['ANTHROPIC_API_KEY'],
-    'gemini': ['GEMINI_API_KEY'],
-    'groq': ['GROQ_API_KEY'],
-    'ollama': ['FAKE_KEY'],
+    "openai": [
+        {
+            "prompt": "Enter your OPENAI API key (press Enter to skip)",
+            "key_name": "OPENAI_API_KEY",
+        }
+    ],
+    "anthropic": [
+        {
+            "prompt": "Enter your ANTHROPIC API key (press Enter to skip)",
+            "key_name": "ANTHROPIC_API_KEY",
+        }
+    ],
+    "gemini": [
+        {
+            "prompt": "Enter your GEMINI API key (press Enter to skip)",
+            "key_name": "GEMINI_API_KEY",
+        }
+    ],
+    "groq": [
+        {
+            "prompt": "Enter your GROQ API key (press Enter to skip)",
+            "key_name": "GROQ_API_KEY",
+        }
+    ],
+    "watson": [
+        {
+            "prompt": "Enter your WATSONX URL (press Enter to skip)",
+            "key_name": "WATSONX_URL",
+        },
+        {
+            "prompt": "Enter your WATSONX API Key (press Enter to skip)",
+            "key_name": "WATSONX_APIKEY",
+        },
+        {
+            "prompt": "Enter your WATSONX Project Id (press Enter to skip)",
+            "key_name": "WATSONX_PROJECT_ID",
+        },
+    ],
+    "ollama": [
+        {
+            "default": True,
+            "API_BASE": "http://localhost:11434",
+        }
+    ],
+    "bedrock": [
+        {
+            "prompt": "Enter your AWS Access Key ID (press Enter to skip)",
+            "key_name": "AWS_ACCESS_KEY_ID",
+        },
+        {
+            "prompt": "Enter your AWS Secret Access Key (press Enter to skip)",
+            "key_name": "AWS_SECRET_ACCESS_KEY",
+        },
+        {
+            "prompt": "Enter your AWS Region Name (press Enter to skip)",
+            "key_name": "AWS_REGION_NAME",
+        },
+    ],
+    "azure": [
+        {
+            "prompt": "Enter your Azure deployment name (must start with 'azure/')",
+            "key_name": "model",
+        },
+        {
+            "prompt": "Enter your AZURE API key (press Enter to skip)",
+            "key_name": "AZURE_API_KEY",
+        },
+        {
+            "prompt": "Enter your AZURE API base URL (press Enter to skip)",
+            "key_name": "AZURE_API_BASE",
+        },
+        {
+            "prompt": "Enter your AZURE API version (press Enter to skip)",
+            "key_name": "AZURE_API_VERSION",
+        },
+    ],
+    "cerebras": [
+        {
+            "prompt": "Enter your Cerebras model name (must start with 'cerebras/')",
+            "key_name": "model",
+        },
+        {
+            "prompt": "Enter your Cerebras API version (press Enter to skip)",
+            "key_name": "CEREBRAS_API_KEY",
+        },
+    ],
 }
 
-PROVIDERS = ['openai', 'anthropic', 'gemini', 'groq', 'ollama']
+
+PROVIDERS = [
+    "openai",
+    "anthropic",
+    "gemini",
+    "groq",
+    "ollama",
+    "watson",
+    "bedrock",
+    "azure",
+    "cerebras",
+]
 
 MODELS = {
-    'openai': ['gpt-4', 'gpt-4o', 'gpt-4o-mini', 'o1-mini', 'o1-preview'],
-    'anthropic': ['claude-3-5-sonnet-20240620', 'claude-3-sonnet-20240229', 'claude-3-opus-20240229', 'claude-3-haiku-20240307'],
-    'gemini': ['gemini-1.5-flash', 'gemini-1.5-pro', 'gemini-gemma-2-9b-it', 'gemini-gemma-2-27b-it'],
-    'groq': ['llama-3.1-8b-instant', 'llama-3.1-70b-versatile', 'llama-3.1-405b-reasoning', 'gemma2-9b-it', 'gemma-7b-it'],
-    'ollama': ['llama3.1', 'mixtral'],
+    "openai": ["gpt-4", "gpt-4o", "gpt-4o-mini", "o1-mini", "o1-preview"],
+    "anthropic": [
+        "claude-3-5-sonnet-20240620",
+        "claude-3-sonnet-20240229",
+        "claude-3-opus-20240229",
+        "claude-3-haiku-20240307",
+    ],
+    "gemini": [
+        "gemini/gemini-1.5-flash",
+        "gemini/gemini-1.5-pro",
+        "gemini/gemini-gemma-2-9b-it",
+        "gemini/gemini-gemma-2-27b-it",
+    ],
+    "groq": [
+        "groq/llama-3.1-8b-instant",
+        "groq/llama-3.1-70b-versatile",
+        "groq/llama-3.1-405b-reasoning",
+        "groq/gemma2-9b-it",
+        "groq/gemma-7b-it",
+    ],
+    "ollama": ["ollama/llama3.1", "ollama/mixtral"],
+    "watson": [
+        "watsonx/google/flan-t5-xxl",
+        "watsonx/google/flan-ul2",
+        "watsonx/bigscience/mt0-xxl",
+        "watsonx/eleutherai/gpt-neox-20b",
+        "watsonx/ibm/mpt-7b-instruct2",
+        "watsonx/bigcode/starcoder",
+        "watsonx/meta-llama/llama-2-70b-chat",
+        "watsonx/meta-llama/llama-2-13b-chat",
+        "watsonx/ibm/granite-13b-instruct-v1",
+        "watsonx/ibm/granite-13b-chat-v1",
+        "watsonx/google/flan-t5-xl",
+        "watsonx/ibm/granite-13b-chat-v2",
+        "watsonx/ibm/granite-13b-instruct-v2",
+        "watsonx/elyza/elyza-japanese-llama-2-7b-instruct",
+        "watsonx/ibm-mistralai/mixtral-8x7b-instruct-v01-q",
+    ],
+    "bedrock": [
+        "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",
+        "bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
+        "bedrock/anthropic.claude-3-haiku-20240307-v1:0",
+        "bedrock/anthropic.claude-3-opus-20240229-v1:0",
+        "bedrock/anthropic.claude-v2:1",
+        "bedrock/anthropic.claude-v2",
+        "bedrock/anthropic.claude-instant-v1",
+        "bedrock/meta.llama3-1-405b-instruct-v1:0",
+        "bedrock/meta.llama3-1-70b-instruct-v1:0",
+        "bedrock/meta.llama3-1-8b-instruct-v1:0",
+        "bedrock/meta.llama3-70b-instruct-v1:0",
+        "bedrock/meta.llama3-8b-instruct-v1:0",
+        "bedrock/amazon.titan-text-lite-v1",
+        "bedrock/amazon.titan-text-express-v1",
+        "bedrock/cohere.command-text-v14",
+        "bedrock/ai21.j2-mid-v1",
+        "bedrock/ai21.j2-ultra-v1",
+        "bedrock/ai21.jamba-instruct-v1:0",
+        "bedrock/meta.llama2-13b-chat-v1",
+        "bedrock/meta.llama2-70b-chat-v1",
+        "bedrock/mistral.mistral-7b-instruct-v0:2",
+        "bedrock/mistral.mixtral-8x7b-instruct-v0:1",
+    ],
 }
 
-JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
\ No newline at end of file
+JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
diff --git a/src/crewai/cli/create_crew.py b/src/crewai/cli/create_crew.py
index 5767b82a1..06440d74e 100644
--- a/src/crewai/cli/create_crew.py
+++ b/src/crewai/cli/create_crew.py
@@ -1,11 +1,11 @@
+import shutil
 import sys
 from pathlib import Path
 
 import click
 
-from crewai.cli.constants import ENV_VARS
+from crewai.cli.constants import ENV_VARS, MODELS
 from crewai.cli.provider import (
-    PROVIDERS,
     get_provider_data,
     select_model,
     select_provider,
@@ -29,20 +29,20 @@ def create_folder_structure(name, parent_folder=None):
             click.secho("Operation cancelled.", fg="yellow")
             sys.exit(0)
         click.secho(f"Overriding folder {folder_name}...", fg="green", bold=True)
-    else:
-        click.secho(
-            f"Creating {'crew' if parent_folder else 'folder'} {folder_name}...",
-            fg="green",
-            bold=True,
-        )
+        shutil.rmtree(folder_path)  # Delete the existing folder and its contents
 
-    if not folder_path.exists():
-        folder_path.mkdir(parents=True)
-        (folder_path / "tests").mkdir(exist_ok=True)
-        if not parent_folder:
-            (folder_path / "src" / folder_name).mkdir(parents=True)
-            (folder_path / "src" / folder_name / "tools").mkdir(parents=True)
-            (folder_path / "src" / folder_name / "config").mkdir(parents=True)
+    click.secho(
+        f"Creating {'crew' if parent_folder else 'folder'} {folder_name}...",
+        fg="green",
+        bold=True,
+    )
+
+    folder_path.mkdir(parents=True)
+    (folder_path / "tests").mkdir(exist_ok=True)
+    if not parent_folder:
+        (folder_path / "src" / folder_name).mkdir(parents=True)
+        (folder_path / "src" / folder_name / "tools").mkdir(parents=True)
+        (folder_path / "src" / folder_name / "config").mkdir(parents=True)
 
     return folder_path, folder_name, class_name
 
@@ -92,7 +92,10 @@ def create_crew(name, provider=None, skip_provider=False, parent_folder=None):
 
         existing_provider = None
         for provider, env_keys in ENV_VARS.items():
-            if any(key in env_vars for key in env_keys):
+            if any(
+                "key_name" in details and details["key_name"] in env_vars
+                for details in env_keys
+            ):
                 existing_provider = provider
                 break
 
@@ -118,47 +121,48 @@ def create_crew(name, provider=None, skip_provider=False, parent_folder=None):
                 "No provider selected. Please try again or press 'q' to exit.", fg="red"
             )
 
-        while True:
-            selected_model = select_model(selected_provider, provider_models)
-            if selected_model is None:  # User typed 'q'
-                click.secho("Exiting...", fg="yellow")
-                sys.exit(0)
-            if selected_model:  # Valid selection
-                break
-            click.secho(
-                "No model selected. Please try again or press 'q' to exit.", fg="red"
-            )
+        # Check if the selected provider has predefined models
+        if selected_provider in MODELS and MODELS[selected_provider]:
+            while True:
+                selected_model = select_model(selected_provider, provider_models)
+                if selected_model is None:  # User typed 'q'
+                    click.secho("Exiting...", fg="yellow")
+                    sys.exit(0)
+                if selected_model:  # Valid selection
+                    break
+                click.secho(
+                    "No model selected. Please try again or press 'q' to exit.",
+                    fg="red",
+                )
+            env_vars["MODEL"] = selected_model
 
-        if selected_provider in PROVIDERS:
-            api_key_var = ENV_VARS[selected_provider][0]
-        else:
-            api_key_var = click.prompt(
-                f"Enter the environment variable name for your {selected_provider.capitalize()} API key",
-                type=str,
-                default="",
-            )
+        # Check if the selected provider requires API keys
+        if selected_provider in ENV_VARS:
+            provider_env_vars = ENV_VARS[selected_provider]
+            for details in provider_env_vars:
+                if details.get("default", False):
+                    # Automatically add default key-value pairs
+                    for key, value in details.items():
+                        if key not in ["prompt", "key_name", "default"]:
+                            env_vars[key] = value
+                elif "key_name" in details:
+                    # Prompt for non-default key-value pairs
+                    prompt = details["prompt"]
+                    key_name = details["key_name"]
+                    api_key_value = click.prompt(prompt, default="", show_default=False)
 
-        api_key_value = ""
-        click.echo(
-            f"Enter your {selected_provider.capitalize()} API key (press Enter to skip): ",
-            nl=False,
-        )
-        try:
-            api_key_value = input()
-        except (KeyboardInterrupt, EOFError):
-            api_key_value = ""
+                    if api_key_value.strip():
+                        env_vars[key_name] = api_key_value
 
-        if api_key_value.strip():
-            env_vars = {api_key_var: api_key_value}
+        if env_vars:
             write_env_file(folder_path, env_vars)
-            click.secho("API key saved to .env file", fg="green")
+            click.secho("API keys and model saved to .env file", fg="green")
         else:
             click.secho(
-                "No API key provided. Skipping .env file creation.", fg="yellow"
+                "No API keys provided. Skipping .env file creation.", fg="yellow"
             )
 
-        env_vars["MODEL"] = selected_model
-        click.secho(f"Selected model: {selected_model}", fg="green")
+        click.secho(f"Selected model: {env_vars.get('MODEL', 'N/A')}", fg="green")
 
     package_dir = Path(__file__).parent
     templates_dir = package_dir / "templates" / "crew"
diff --git a/src/crewai/cli/templates/crew/crew.py b/src/crewai/cli/templates/crew/crew.py
index f950d13d4..392e29edd 100644
--- a/src/crewai/cli/templates/crew/crew.py
+++ b/src/crewai/cli/templates/crew/crew.py
@@ -48,4 +48,4 @@ class {{crew_name}}Crew():
 			process=Process.sequential,
 			verbose=True,
 			# process=Process.hierarchical, # In case you wanna use that instead https://docs.crewai.com/how-to/Hierarchical/
-		)
\ No newline at end of file
+		)
diff --git a/src/crewai/cli/templates/crew/main.py b/src/crewai/cli/templates/crew/main.py
index 88edfcbff..d441fa0fa 100644
--- a/src/crewai/cli/templates/crew/main.py
+++ b/src/crewai/cli/templates/crew/main.py
@@ -1,7 +1,11 @@
 #!/usr/bin/env python
 import sys
+import warnings
+
 from {{folder_name}}.crew import {{crew_name}}Crew
 
+warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
+
 # This main file is intended to be a way for you to run your
 # crew locally, so refrain from adding unnecessary logic into this file.
 # Replace with inputs you want to test with, it will automatically

From faa231e27880c4b9cab4f5a3d92c749e1de9bd93 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 5 Nov 2024 12:02:54 -0500
Subject: [PATCH 044/126] Fix flows to support cycles and added in test (#1556)

---
 src/crewai/flow/flow.py |  53 ++++----
 tests/flow_test.py      | 264 ++++++++++++++++++++++++++++++++++++++++
 2 files changed, 289 insertions(+), 28 deletions(-)
 create mode 100644 tests/flow_test.py

diff --git a/src/crewai/flow/flow.py b/src/crewai/flow/flow.py
index 9b6463d65..fa0902594 100644
--- a/src/crewai/flow/flow.py
+++ b/src/crewai/flow/flow.py
@@ -131,7 +131,6 @@ class FlowMeta(type):
                 condition_type = getattr(attr_value, "__condition_type__", "OR")
                 listeners[attr_name] = (condition_type, methods)
 
-            # TODO: should we add a check for __condition_type__ 'AND'?
             elif hasattr(attr_value, "__is_router__"):
                 routers[attr_value.__router_for__] = attr_name
                 possible_returns = get_possible_return_constants(attr_value)
@@ -171,8 +170,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
     def __init__(self) -> None:
         self._methods: Dict[str, Callable] = {}
         self._state: T = self._create_initial_state()
-        self._executed_methods: Set[str] = set()
-        self._scheduled_tasks: Set[str] = set()
+        self._method_execution_counts: Dict[str, int] = {}
         self._pending_and_listeners: Dict[str, Set[str]] = {}
         self._method_outputs: List[Any] = []  # List to store all method outputs
 
@@ -309,7 +307,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
         )
         self._method_outputs.append(result)  # Store the output
 
-        self._executed_methods.add(method_name)
+        # Track method execution counts
+        self._method_execution_counts[method_name] = (
+            self._method_execution_counts.get(method_name, 0) + 1
+        )
 
         return result
 
@@ -319,35 +320,34 @@ class Flow(Generic[T], metaclass=FlowMeta):
         if trigger_method in self._routers:
             router_method = self._methods[self._routers[trigger_method]]
             path = await self._execute_method(
-                trigger_method, router_method
-            )  # TODO: Change or not?
-            # Use the path as the new trigger method
+                self._routers[trigger_method], router_method
+            )
             trigger_method = path
 
         for listener_name, (condition_type, methods) in self._listeners.items():
             if condition_type == "OR":
                 if trigger_method in methods:
-                    if (
-                        listener_name not in self._executed_methods
-                        and listener_name not in self._scheduled_tasks
-                    ):
-                        self._scheduled_tasks.add(listener_name)
-                        listener_tasks.append(
-                            self._execute_single_listener(listener_name, result)
-                        )
+                    # Schedule the listener without preventing re-execution
+                    listener_tasks.append(
+                        self._execute_single_listener(listener_name, result)
+                    )
             elif condition_type == "AND":
-                if all(method in self._executed_methods for method in methods):
-                    if (
-                        listener_name not in self._executed_methods
-                        and listener_name not in self._scheduled_tasks
-                    ):
-                        self._scheduled_tasks.add(listener_name)
-                        listener_tasks.append(
-                            self._execute_single_listener(listener_name, result)
-                        )
+                # Initialize pending methods for this listener if not already done
+                if listener_name not in self._pending_and_listeners:
+                    self._pending_and_listeners[listener_name] = set(methods)
+                # Remove the trigger method from pending methods
+                self._pending_and_listeners[listener_name].discard(trigger_method)
+                if not self._pending_and_listeners[listener_name]:
+                    # All required methods have been executed
+                    listener_tasks.append(
+                        self._execute_single_listener(listener_name, result)
+                    )
+                    # Reset pending methods for this listener
+                    self._pending_and_listeners.pop(listener_name, None)
 
         # Run all listener tasks concurrently and wait for them to complete
-        await asyncio.gather(*listener_tasks)
+        if listener_tasks:
+            await asyncio.gather(*listener_tasks)
 
     async def _execute_single_listener(self, listener_name: str, result: Any) -> None:
         try:
@@ -367,9 +367,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 # If listener does not expect parameters, call without arguments
                 listener_result = await self._execute_method(listener_name, method)
 
-            # Remove from scheduled tasks after execution
-            self._scheduled_tasks.discard(listener_name)
-
             # Execute listeners of this listener
             await self._execute_listeners(listener_name, listener_result)
         except Exception as e:
diff --git a/tests/flow_test.py b/tests/flow_test.py
new file mode 100644
index 000000000..ffd82367c
--- /dev/null
+++ b/tests/flow_test.py
@@ -0,0 +1,264 @@
+"""Test Flow creation and execution basic functionality."""
+
+import asyncio
+
+import pytest
+from crewai.flow.flow import Flow, and_, listen, or_, router, start
+
+
+def test_simple_sequential_flow():
+    """Test a simple flow with two steps called sequentially."""
+    execution_order = []
+
+    class SimpleFlow(Flow):
+        @start()
+        def step_1(self):
+            execution_order.append("step_1")
+
+        @listen(step_1)
+        def step_2(self):
+            execution_order.append("step_2")
+
+    flow = SimpleFlow()
+    flow.kickoff()
+
+    assert execution_order == ["step_1", "step_2"]
+
+
+def test_flow_with_multiple_starts():
+    """Test a flow with multiple start methods."""
+    execution_order = []
+
+    class MultiStartFlow(Flow):
+        @start()
+        def step_a(self):
+            execution_order.append("step_a")
+
+        @start()
+        def step_b(self):
+            execution_order.append("step_b")
+
+        @listen(step_a)
+        def step_c(self):
+            execution_order.append("step_c")
+
+        @listen(step_b)
+        def step_d(self):
+            execution_order.append("step_d")
+
+    flow = MultiStartFlow()
+    flow.kickoff()
+
+    assert "step_a" in execution_order
+    assert "step_b" in execution_order
+    assert "step_c" in execution_order
+    assert "step_d" in execution_order
+    assert execution_order.index("step_c") > execution_order.index("step_a")
+    assert execution_order.index("step_d") > execution_order.index("step_b")
+
+
+def test_cyclic_flow():
+    """Test a cyclic flow that runs a finite number of iterations."""
+    execution_order = []
+
+    class CyclicFlow(Flow):
+        iteration = 0
+        max_iterations = 3
+
+        @start("loop")
+        def step_1(self):
+            if self.iteration >= self.max_iterations:
+                return  # Do not proceed further
+            execution_order.append(f"step_1_{self.iteration}")
+
+        @listen(step_1)
+        def step_2(self):
+            execution_order.append(f"step_2_{self.iteration}")
+
+        @router(step_2)
+        def step_3(self):
+            execution_order.append(f"step_3_{self.iteration}")
+            self.iteration += 1
+            if self.iteration < self.max_iterations:
+                return "loop"
+
+            return "exit"
+
+    flow = CyclicFlow()
+    flow.kickoff()
+
+    expected_order = []
+    for i in range(flow.max_iterations):
+        expected_order.extend([f"step_1_{i}", f"step_2_{i}", f"step_3_{i}"])
+
+    assert execution_order == expected_order
+
+
+def test_flow_with_and_condition():
+    """Test a flow where a step waits for multiple other steps to complete."""
+    execution_order = []
+
+    class AndConditionFlow(Flow):
+        @start()
+        def step_1(self):
+            execution_order.append("step_1")
+
+        @start()
+        def step_2(self):
+            execution_order.append("step_2")
+
+        @listen(and_(step_1, step_2))
+        def step_3(self):
+            execution_order.append("step_3")
+
+    flow = AndConditionFlow()
+    flow.kickoff()
+
+    assert "step_1" in execution_order
+    assert "step_2" in execution_order
+    assert execution_order[-1] == "step_3"
+    assert execution_order.index("step_3") > execution_order.index("step_1")
+    assert execution_order.index("step_3") > execution_order.index("step_2")
+
+
+def test_flow_with_or_condition():
+    """Test a flow where a step is triggered when any of multiple steps complete."""
+    execution_order = []
+
+    class OrConditionFlow(Flow):
+        @start()
+        def step_a(self):
+            execution_order.append("step_a")
+
+        @start()
+        def step_b(self):
+            execution_order.append("step_b")
+
+        @listen(or_(step_a, step_b))
+        def step_c(self):
+            execution_order.append("step_c")
+
+    flow = OrConditionFlow()
+    flow.kickoff()
+
+    assert "step_a" in execution_order or "step_b" in execution_order
+    assert "step_c" in execution_order
+    assert execution_order.index("step_c") > min(
+        execution_order.index("step_a"), execution_order.index("step_b")
+    )
+
+
+def test_flow_with_router():
+    """Test a flow that uses a router method to determine the next step."""
+    execution_order = []
+
+    class RouterFlow(Flow):
+        @start()
+        def start_method(self):
+            execution_order.append("start_method")
+
+        @router(start_method)
+        def router(self):
+            execution_order.append("router")
+            # Ensure the condition is set to True to follow the "step_if_true" path
+            condition = True
+            return "step_if_true" if condition else "step_if_false"
+
+        @listen("step_if_true")
+        def truthy(self):
+            execution_order.append("step_if_true")
+
+        @listen("step_if_false")
+        def falsy(self):
+            execution_order.append("step_if_false")
+
+    flow = RouterFlow()
+    flow.kickoff()
+
+    assert execution_order == ["start_method", "router", "step_if_true"]
+
+
+def test_async_flow():
+    """Test an asynchronous flow."""
+    execution_order = []
+
+    class AsyncFlow(Flow):
+        @start()
+        async def step_1(self):
+            execution_order.append("step_1")
+            await asyncio.sleep(0.1)
+
+        @listen(step_1)
+        async def step_2(self):
+            execution_order.append("step_2")
+            await asyncio.sleep(0.1)
+
+    flow = AsyncFlow()
+    asyncio.run(flow.kickoff_async())
+
+    assert execution_order == ["step_1", "step_2"]
+
+
+def test_flow_with_exceptions():
+    """Test flow behavior when exceptions occur in steps."""
+    execution_order = []
+
+    class ExceptionFlow(Flow):
+        @start()
+        def step_1(self):
+            execution_order.append("step_1")
+            raise ValueError("An error occurred in step_1")
+
+        @listen(step_1)
+        def step_2(self):
+            execution_order.append("step_2")
+
+    flow = ExceptionFlow()
+
+    with pytest.raises(ValueError):
+        flow.kickoff()
+
+    # Ensure step_2 did not execute
+    assert execution_order == ["step_1"]
+
+
+def test_flow_restart():
+    """Test restarting a flow after it has completed."""
+    execution_order = []
+
+    class RestartableFlow(Flow):
+        @start()
+        def step_1(self):
+            execution_order.append("step_1")
+
+        @listen(step_1)
+        def step_2(self):
+            execution_order.append("step_2")
+
+    flow = RestartableFlow()
+    flow.kickoff()
+    flow.kickoff()  # Restart the flow
+
+    assert execution_order == ["step_1", "step_2", "step_1", "step_2"]
+
+
+def test_flow_with_custom_state():
+    """Test a flow that maintains and modifies internal state."""
+
+    class StateFlow(Flow):
+        def __init__(self):
+            super().__init__()
+            self.counter = 0
+
+        @start()
+        def step_1(self):
+            self.counter += 1
+
+        @listen(step_1)
+        def step_2(self):
+            self.counter *= 2
+            assert self.counter == 2
+
+    flow = StateFlow()
+    flow.kickoff()
+    assert flow.counter == 2

From e856359e2333bc97c6f0a3e62b0f79aecba84204 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 5 Nov 2024 12:07:29 -0500
Subject: [PATCH 045/126] fix missing config (#1557)

---
 src/crewai/cli/add_crew_to_flow.py    |  2 +-
 src/crewai/cli/templates/crew/crew.py |  5 ++++-
 src/crewai/cli/templates/crew/main.py | 10 +++++-----
 3 files changed, 10 insertions(+), 7 deletions(-)

diff --git a/src/crewai/cli/add_crew_to_flow.py b/src/crewai/cli/add_crew_to_flow.py
index e4901fa89..ef693a22b 100644
--- a/src/crewai/cli/add_crew_to_flow.py
+++ b/src/crewai/cli/add_crew_to_flow.py
@@ -54,7 +54,7 @@ def create_embedded_crew(crew_name: str, parent_folder: Path) -> None:
 
     templates_dir = Path(__file__).parent / "templates" / "crew"
     config_template_files = ["agents.yaml", "tasks.yaml"]
-    crew_template_file = f"{folder_name}_crew.py"  # Updated file name
+    crew_template_file = f"{folder_name}.py"  # Updated file name
 
     for file_name in config_template_files:
         src_file = templates_dir / "config" / file_name
diff --git a/src/crewai/cli/templates/crew/crew.py b/src/crewai/cli/templates/crew/crew.py
index 392e29edd..c47315415 100644
--- a/src/crewai/cli/templates/crew/crew.py
+++ b/src/crewai/cli/templates/crew/crew.py
@@ -8,9 +8,12 @@ from crewai.project import CrewBase, agent, crew, task
 # from crewai_tools import SerperDevTool
 
 @CrewBase
-class {{crew_name}}Crew():
+class {{crew_name}}():
 	"""{{crew_name}} crew"""
 
+	agents_config = 'config/agents.yaml'
+	tasks_config = 'config/tasks.yaml'
+
 	@agent
 	def researcher(self) -> Agent:
 		return Agent(
diff --git a/src/crewai/cli/templates/crew/main.py b/src/crewai/cli/templates/crew/main.py
index d441fa0fa..d5224edcf 100644
--- a/src/crewai/cli/templates/crew/main.py
+++ b/src/crewai/cli/templates/crew/main.py
@@ -2,7 +2,7 @@
 import sys
 import warnings
 
-from {{folder_name}}.crew import {{crew_name}}Crew
+from {{folder_name}}.crew import {{crew_name}}
 
 warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
 
@@ -18,7 +18,7 @@ def run():
     inputs = {
         'topic': 'AI LLMs'
     }
-    {{crew_name}}Crew().crew().kickoff(inputs=inputs)
+    {{crew_name}}().crew().kickoff(inputs=inputs)
 
 
 def train():
@@ -29,7 +29,7 @@ def train():
         "topic": "AI LLMs"
     }
     try:
-        {{crew_name}}Crew().crew().train(n_iterations=int(sys.argv[1]), filename=sys.argv[2], inputs=inputs)
+        {{crew_name}}().crew().train(n_iterations=int(sys.argv[1]), filename=sys.argv[2], inputs=inputs)
 
     except Exception as e:
         raise Exception(f"An error occurred while training the crew: {e}")
@@ -39,7 +39,7 @@ def replay():
     Replay the crew execution from a specific task.
     """
     try:
-        {{crew_name}}Crew().crew().replay(task_id=sys.argv[1])
+        {{crew_name}}().crew().replay(task_id=sys.argv[1])
 
     except Exception as e:
         raise Exception(f"An error occurred while replaying the crew: {e}")
@@ -52,7 +52,7 @@ def test():
         "topic": "AI LLMs"
     }
     try:
-        {{crew_name}}Crew().crew().test(n_iterations=int(sys.argv[1]), openai_model_name=sys.argv[2], inputs=inputs)
+        {{crew_name}}().crew().test(n_iterations=int(sys.argv[1]), openai_model_name=sys.argv[2], inputs=inputs)
 
     except Exception as e:
         raise Exception(f"An error occurred while replaying the crew: {e}")

From 9f2acfe91f3dafab2aef1c465810b7ef8780eee7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Wed, 6 Nov 2024 23:03:58 -0300
Subject: [PATCH 046/126] making sure we don't check for agents that were not
 used in the crew

---
 src/crewai/crew.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index e65024ed6..7bcaa82ad 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -445,13 +445,14 @@ class Crew(BaseModel):
         training_data = CrewTrainingHandler(TRAINING_DATA_FILE).load()
 
         for agent in train_crew.agents:
-            result = TaskEvaluator(agent).evaluate_training_data(
-                training_data=training_data, agent_id=str(agent.id)
-            )
+            if training_data.get(str(agent.id)):
+                result = TaskEvaluator(agent).evaluate_training_data(
+                    training_data=training_data, agent_id=str(agent.id)
+                )
 
-            CrewTrainingHandler(filename).save_trained_data(
-                agent_id=str(agent.role), trained_data=result.model_dump()
-            )
+                CrewTrainingHandler(filename).save_trained_data(
+                    agent_id=str(agent.role), trained_data=result.model_dump()
+                )
 
     def kickoff(
         self,

From 1b09b085a741bdc87b1786410edef04c34b28f4f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Sun, 10 Nov 2024 11:00:16 -0300
Subject: [PATCH 047/126] preparing new version

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 uv.lock                                                 | 2 +-
 8 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index b9e6bc986..7102c9efa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.76.9"
+version = "0.79.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 0a2f02a59..353c11b88 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.76.9"
+__version__ = "0.79.0"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 447cfcb86..136fa2026 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.9,<1.0.0"
+    "crewai[tools]>=0.79.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 1ef8f7b36..032f7ee9b 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.9,<1.0.0",
+    "crewai[tools]>=0.79.0,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 53f304283..53a81a620 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.76.9,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.79.0,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 33d5c58af..89275861d 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.9,<1.0.0"
+    "crewai[tools]>=0.79.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 849298b6b..b60edf21b 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.76.9"
+    "crewai[tools]>=0.79.0"
 ]
 
diff --git a/uv.lock b/uv.lock
index f7f6a1839..0034b42e0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.76.9"
+version = "0.79.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 40d378abfbcdd2a71fdb4999f679a0a4b9ff6552 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Sun, 10 Nov 2024 11:36:03 -0300
Subject: [PATCH 048/126] updating LLM docs

---
 docs/concepts/llms.mdx | 132 ++++++++++++++++++++++++++++++++++++++---
 1 file changed, 124 insertions(+), 8 deletions(-)

diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index d432070d4..5757feca3 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -25,7 +25,100 @@ By default, CrewAI uses the `gpt-4o-mini` model. It uses environment variables i
 - `OPENAI_API_BASE`
 - `OPENAI_API_KEY`
 
-### 2. Custom LLM Objects
+### 2. Updating YAML files
+
+You can update the `agents.yml` file to refer to the LLM you want to use:
+
+```yaml Code
+researcher:
+    role: Research Specialist
+    goal: Conduct comprehensive research and analysis to gather relevant information,
+        synthesize findings, and produce well-documented insights.
+    backstory: A dedicated research professional with years of experience in academic
+        investigation, literature review, and data analysis, known for thorough and
+        methodical approaches to complex research questions.
+    verbose: true
+    llm: openai/gpt-4o
+    # llm: azure/gpt-4o-mini
+    # llm: gemini/gemini-pro
+    # llm: anthropic/claude-3-5-sonnet-20240620
+    # llm: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
+    # llm: mistral/mistral-large-latest
+    # llm: ollama/llama3:70b
+    # llm: groq/llama-3.2-90b-vision-preview
+    # llm: watsonx/meta-llama/llama-3-1-70b-instruct
+    # ...
+```
+
+Keep in mind that you will need to set certain ENV vars depending on the model you are
+using to account for the credentials or set a custom LLM object like described below.
+Here are some of the required ENV vars for some of the LLM integrations:
+
+<AccordionGroup>
+    <Accordion title="OpenAI">
+    ```python Code
+    OPENAI_API_KEY=<your-api-key>
+    OPENAI_API_BASE=<optional-custom-base-url>
+    OPENAI_MODEL_NAME=<openai-model-name>
+    OPENAI_ORGANIZATION=<your-org-id>       # OPTIONAL
+    OPENAI_API_BASE=<openaiai-api-base>     # OPTIONAL
+    ```
+    </Accordion>
+
+    <Accordion title="Anthropic">
+    ```python Code
+    ANTHROPIC_API_KEY=<your-api-key>
+    ```
+    </Accordion>
+
+    <Accordion title="Google">
+    ```python Code
+    GEMINI_API_KEY=<your-api-key>
+    ```
+    </Accordion>
+
+    <Accordion title="Azure">
+    ```python Code
+    AZURE_API_KEY=<your-api-key>                    # "my-azure-api-key"
+    AZURE_API_BASE=<your-resource-url>              # "https://example-endpoint.openai.azure.com"
+    AZURE_API_VERSION=<api-version>                 # "2023-05-15"
+    AZURE_AD_TOKEN=<your-azure-ad-token>            # Optional
+    AZURE_API_TYPE=<your-azure-api-type>            # Optional
+    ```
+    </Accordion>
+
+    <Accordion title="AWS Bedrock">
+    ```python Code
+    AWS_ACCESS_KEY_ID=<your-access-key>
+    AWS_SECRET_ACCESS_KEY=<your-secret-key>
+    AWS_DEFAULT_REGION=<your-region>
+    ```
+    </Accordion>
+
+    <Accordion title="Mistral">
+    ```python Code
+    MISTRAL_API_KEY=<your-api-key>
+    ```
+    </Accordion>
+
+    <Accordion title="Groq">
+    ```python Code
+    GROQ_API_KEY=<your-api-key>
+    ```
+    </Accordion>
+
+    <Accordion title="IBM watsonx.ai">
+    ```python Code
+    WATSONX_URL=<your-url>                          # (required) Base URL of your WatsonX instance
+    WATSONX_APIKEY=<your-apikey>                    # (required) IBM cloud API key
+    WATSONX_TOKEN=<your-token>                      # (required) IAM auth token (alternative to APIKEY)
+    WATSONX_PROJECT_ID=<your-project-id>            # (optional) Project ID of your WatsonX instance
+    WATSONX_DEPLOYMENT_SPACE_ID=<your-space-id>     # (optional) ID of deployment space for deployed models
+    ```
+    </Accordion>
+</AccordionGroup>
+
+### 3. Custom LLM Objects
 
 Pass a custom LLM implementation or object from another library.
 
@@ -102,7 +195,7 @@ When configuring an LLM for your agent, you have access to a wide range of param
 
 These are examples of how to configure LLMs for your agent.
 
-<AccordionGroup>    
+<AccordionGroup>
     <Accordion title="OpenAI">
 
     ```python Code
@@ -133,10 +226,10 @@ These are examples of how to configure LLMs for your agent.
         model="cerebras/llama-3.1-70b",
         api_key="your-api-key-here"
     )
-    agent = Agent(llm=llm, ...) 
+    agent = Agent(llm=llm, ...)
     ```
     </Accordion>
- 
+
     <Accordion title="Ollama (Local LLMs)">
 
     CrewAI supports using Ollama for running open-source models locally:
@@ -150,7 +243,7 @@ These are examples of how to configure LLMs for your agent.
 
     agent = Agent(
         llm=LLM(
-            model="ollama/llama3.1", 
+            model="ollama/llama3.1",
             base_url="http://localhost:11434"
         ),
         ...
@@ -164,7 +257,7 @@ These are examples of how to configure LLMs for your agent.
     from crewai import LLM
 
     llm = LLM(
-        model="groq/llama3-8b-8192", 
+        model="groq/llama3-8b-8192",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -189,7 +282,7 @@ These are examples of how to configure LLMs for your agent.
     from crewai import LLM
 
     llm = LLM(
-        model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct",  
+        model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -224,6 +317,29 @@ These are examples of how to configure LLMs for your agent.
     </Accordion>
 
     <Accordion title="IBM watsonx.ai">
+    You can use IBM Watson by seeting the following ENV vars:
+
+    ```python Code
+    WATSONX_URL=<your-url>
+    WATSONX_APIKEY=<your-apikey>
+    WATSONX_PROJECT_ID=<your-project-id>
+    ```
+
+    You can then define your agents llms by updating the `agents.yml`
+
+    ```yaml Code
+    researcher:
+        role: Research Specialist
+        goal: Conduct comprehensive research and analysis to gather relevant information,
+            synthesize findings, and produce well-documented insights.
+        backstory: A dedicated research professional with years of experience in academic
+            investigation, literature review, and data analysis, known for thorough and
+            methodical approaches to complex research questions.
+        verbose: true
+        llm: watsonx/meta-llama/llama-3-1-70b-instruct
+    ```
+
+    You can also set up agents more dynamically as a base level LLM instance, like bellow:
 
     ```python Code
     from crewai import LLM
@@ -247,7 +363,7 @@ These are examples of how to configure LLMs for your agent.
         api_key="your-api-key-here",
         base_url="your_api_endpoint"
     )
-    agent = Agent(llm=llm, ...) 
+    agent = Agent(llm=llm, ...)
     ```
     </Accordion>
 </AccordionGroup>

From 50bf146d1e3319c84d342d42f9f914e8744fdcba Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Sun, 10 Nov 2024 20:47:56 -0300
Subject: [PATCH 049/126] preparing new version

---
 pyproject.toml                                     |  8 ++++----
 src/crewai/__init__.py                             |  2 +-
 src/crewai/cli/templates/crew/pyproject.toml       |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml       |  2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml   |  2 +-
 .../cli/templates/pipeline_router/pyproject.toml   |  2 +-
 src/crewai/cli/templates/tool/pyproject.toml       |  2 +-
 uv.lock                                            | 14 +++++++-------
 8 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 7102c9efa..d57811f32 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.79.0"
+version = "0.79.1"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
@@ -16,7 +16,7 @@ dependencies = [
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
     "instructor>=1.3.3",
     "regex>=2024.9.11",
-    "crewai-tools>=0.13.4",
+    "crewai-tools>=0.14.0",
     "click>=8.1.7",
     "python-dotenv>=1.0.0",
     "appdirs>=1.4.4",
@@ -37,7 +37,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools>=0.13.4"]
+tools = ["crewai-tools>=0.14.0"]
 agentops = ["agentops>=0.3.0"]
 
 [tool.uv]
@@ -52,7 +52,7 @@ dev-dependencies = [
     "mkdocs-material-extensions>=1.3.1",
     "pillow>=10.2.0",
     "cairosvg>=2.7.1",
-    "crewai-tools>=0.13.4",
+    "crewai-tools>=0.14.0",
     "pytest>=8.0.0",
     "pytest-vcr>=1.0.2",
     "python-dotenv>=1.0.0",
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 353c11b88..1da8e2455 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.79.0"
+__version__ = "0.79.1"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 136fa2026..4c5a7cb39 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.0,<1.0.0"
+    "crewai[tools]>=0.79.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 032f7ee9b..a90efe904 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.0,<1.0.0",
+    "crewai[tools]>=0.79.1,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 53a81a620..b049a98f5 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.79.0,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.79.1,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 89275861d..ee36d771b 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.0,<1.0.0"
+    "crewai[tools]>=0.79.1,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index b60edf21b..a60e0b668 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.0"
+    "crewai[tools]>=0.79.1"
 ]
 
diff --git a/uv.lock b/uv.lock
index 0034b42e0..a71556e2d 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.79.0"
+version = "0.79.1"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -665,8 +665,8 @@ requires-dist = [
     { name = "auth0-python", specifier = ">=4.7.1" },
     { name = "chromadb", specifier = ">=0.4.24" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", specifier = ">=0.13.4" },
-    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.13.4" },
+    { name = "crewai-tools", specifier = ">=0.14.0" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.14.0" },
     { name = "instructor", specifier = ">=1.3.3" },
     { name = "json-repair", specifier = ">=0.25.2" },
     { name = "jsonref", specifier = ">=1.1.0" },
@@ -688,7 +688,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
     { name = "cairosvg", specifier = ">=2.7.1" },
-    { name = "crewai-tools", specifier = ">=0.13.4" },
+    { name = "crewai-tools", specifier = ">=0.14.0" },
     { name = "mkdocs", specifier = ">=1.4.3" },
     { name = "mkdocs-material", specifier = ">=9.5.7" },
     { name = "mkdocs-material-extensions", specifier = ">=1.3.1" },
@@ -707,7 +707,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.13.4"
+version = "0.14.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "beautifulsoup4" },
@@ -725,9 +725,9 @@ dependencies = [
     { name = "requests" },
     { name = "selenium" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/64/bd/eff7b633a0b28ff4ed115adde1499e3dcc683e4f0b5c378a4c6f5c0c1bf6/crewai_tools-0.13.4.tar.gz", hash = "sha256:b6ac527633b7018471d892c21ac96bc961a86b6626d996b1ed7d53cd481d4505", size = 816588 }
+sdist = { url = "https://files.pythonhosted.org/packages/64/bd/eff7b633a0b28ff4ed115adde1499e3dcc683e4f0b5c378a4c6f5c0c1bf6/crewai_tools-0.14.0.tar.gz", hash = "sha256:b6ac527633b7018471d892c21ac96bc961a86b6626d996b1ed7d53cd481d4505", size = 816588 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6c/40/93cd347d854059cf5e54a81b70f896deea7ad1f03e9c024549eb323c4da5/crewai_tools-0.13.4-py3-none-any.whl", hash = "sha256:eda78fe3c4df57676259d8dd6b2610fa31f89b90909512f15893adb57fb9e825", size = 463703 },
+    { url = "https://files.pythonhosted.org/packages/6c/40/93cd347d854059cf5e54a81b70f896deea7ad1f03e9c024549eb323c4da5/crewai_tools-0.14.0-py3-none-any.whl", hash = "sha256:eda78fe3c4df57676259d8dd6b2610fa31f89b90909512f15893adb57fb9e825", size = 463703 },
 ]
 
 [[package]]

From 40a676b7ac8a2d429f99a27917dc25133f44c583 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Sun, 10 Nov 2024 21:16:36 -0300
Subject: [PATCH 050/126] curring new version

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 src/crewai/memory/contextual/contextual_memory.py       | 4 ----
 uv.lock                                                 | 2 +-
 9 files changed, 8 insertions(+), 12 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index d57811f32..31853a82d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.79.1"
+version = "0.79.2"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 1da8e2455..77cbc19f5 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.79.1"
+__version__ = "0.79.2"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 4c5a7cb39..fea666134 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.1,<1.0.0"
+    "crewai[tools]>=0.79.2,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index a90efe904..3a708f780 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.1,<1.0.0",
+    "crewai[tools]>=0.79.2,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index b049a98f5..616fa0836 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.79.1,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.79.2,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index ee36d771b..ca8d99629 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.1,<1.0.0"
+    "crewai[tools]>=0.79.2,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index a60e0b668..8a412ab25 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.1"
+    "crewai[tools]>=0.79.2"
 ]
 
diff --git a/src/crewai/memory/contextual/contextual_memory.py b/src/crewai/memory/contextual/contextual_memory.py
index 3d3a9c6c1..5d91cf47d 100644
--- a/src/crewai/memory/contextual/contextual_memory.py
+++ b/src/crewai/memory/contextual/contextual_memory.py
@@ -34,7 +34,6 @@ class ContextualMemory:
         formatted_results = "\n".join(
             [f"- {result['context']}" for result in stm_results]
         )
-        print("formatted_results stm", formatted_results)
         return f"Recent Insights:\n{formatted_results}" if stm_results else ""
 
     def _fetch_ltm_context(self, task) -> Optional[str]:
@@ -54,8 +53,6 @@ class ContextualMemory:
         formatted_results = list(dict.fromkeys(formatted_results))
         formatted_results = "\n".join([f"- {result}" for result in formatted_results])  # type: ignore # Incompatible types in assignment (expression has type "str", variable has type "list[str]")
 
-        print("formatted_results ltm", formatted_results)
-
         return f"Historical Data:\n{formatted_results}" if ltm_results else ""
 
     def _fetch_entity_context(self, query) -> str:
@@ -67,5 +64,4 @@ class ContextualMemory:
         formatted_results = "\n".join(
             [f"- {result['context']}" for result in em_results]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
         )
-        print("formatted_results em", formatted_results)
         return f"Entities:\n{formatted_results}" if em_results else ""
diff --git a/uv.lock b/uv.lock
index a71556e2d..b59d377ee 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.79.1"
+version = "0.79.2"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 49220ec163f87aa4a289231a119043409d8d89ad Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Sun, 10 Nov 2024 23:46:38 -0300
Subject: [PATCH 051/126] preparing new version

---
 pyproject.toml                           |  2 +-
 src/crewai/agent.py                      | 75 ++++++++++++++----------
 src/crewai/agents/crew_agent_executor.py |  7 ++-
 uv.lock                                  |  6 +-
 4 files changed, 53 insertions(+), 37 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 31853a82d..b9e403140 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.79.2"
+version = "0.79.3"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index d30746808..c8998fd19 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -123,6 +123,11 @@ class Agent(BaseAgent):
     @model_validator(mode="after")
     def post_init_setup(self):
         self.agent_ops_agent_name = self.role
+        unnacepted_attributes = [
+            "AWS_ACCESS_KEY_ID",
+            "AWS_SECRET_ACCESS_KEY",
+            "AWS_REGION_NAME",
+        ]
 
         # Handle different cases for self.llm
         if isinstance(self.llm, str):
@@ -146,39 +151,49 @@ class Agent(BaseAgent):
             if api_base:
                 llm_params["base_url"] = api_base
 
+            set_provider = model_name.split("/")[0] if "/" in model_name else "openai"
+
             # Iterate over all environment variables to find matching API keys or use defaults
             for provider, env_vars in ENV_VARS.items():
-                for env_var in env_vars:
-                    # Check if the environment variable is set
-                    if "key_name" in env_var:
-                        env_value = os.environ.get(env_var["key_name"])
-                        if env_value:
-                            # Map key names containing "API_KEY" to "api_key"
-                            key_name = (
-                                "api_key"
-                                if "API_KEY" in env_var["key_name"]
-                                else env_var["key_name"]
+                if provider == set_provider:
+                    for env_var in env_vars:
+                        if env_var["key_name"] in unnacepted_attributes:
+                            continue
+                        # Check if the environment variable is set
+                        if "key_name" in env_var:
+                            env_value = os.environ.get(env_var["key_name"])
+                            print(
+                                f"Checking env var {env_var['key_name']}: {env_value}"
                             )
-                            # Map key names containing "API_BASE" to "api_base"
-                            key_name = (
-                                "api_base"
-                                if "API_BASE" in env_var["key_name"]
-                                else key_name
-                            )
-                            # Map key names containing "API_VERSION" to "api_version"
-                            key_name = (
-                                "api_version"
-                                if "API_VERSION" in env_var["key_name"]
-                                else key_name
-                            )
-                            llm_params[key_name] = env_value
-                    # Check for default values if the environment variable is not set
-                    elif env_var.get("default", False):
-                        for key, value in env_var.items():
-                            if key not in ["prompt", "key_name", "default"]:
-                                # Only add default if the key is already set in os.environ
-                                if key in os.environ:
-                                    llm_params[key] = value
+                            if env_value:
+                                # Map key names containing "API_KEY" to "api_key"
+                                key_name = (
+                                    "api_key"
+                                    if "API_KEY" in env_var["key_name"]
+                                    else env_var["key_name"]
+                                )
+                                # Map key names containing "API_BASE" to "api_base"
+                                key_name = (
+                                    "api_base"
+                                    if "API_BASE" in env_var["key_name"]
+                                    else key_name
+                                )
+                                # Map key names containing "API_VERSION" to "api_version"
+                                key_name = (
+                                    "api_version"
+                                    if "API_VERSION" in env_var["key_name"]
+                                    else key_name
+                                )
+                                print(f"Mapped key name: {key_name}")
+                                llm_params[key_name] = env_value
+                        # Check for default values if the environment variable is not set
+                        elif env_var.get("default", False):
+                            for key, value in env_var.items():
+                                if key not in ["prompt", "key_name", "default"]:
+                                    # Only add default if the key is already set in os.environ
+                                    if key in os.environ:
+                                        print(f"Using default value for {key}: {value}")
+                                        llm_params[key] = value
 
             self.llm = LLM(**llm_params)
         else:
diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index 9e9ad9c7e..aa641e061 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -332,9 +332,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             if self.crew is not None and hasattr(self.crew, "_train_iteration"):
                 train_iteration = self.crew._train_iteration
                 if agent_id in training_data and isinstance(train_iteration, int):
-                    training_data[agent_id][train_iteration][
-                        "improved_output"
-                    ] = result.output
+                    training_data[agent_id][train_iteration]["improved_output"] = (
+                        result.output
+                    )
                     training_handler.save(training_data)
                 else:
                     self._logger.log(
@@ -385,4 +385,5 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         return CrewAgentParser(agent=self.agent).parse(answer)
 
     def _format_msg(self, prompt: str, role: str = "user") -> Dict[str, str]:
+        prompt = prompt.rstrip()
         return {"role": role, "content": prompt}
diff --git a/uv.lock b/uv.lock
index b59d377ee..0b541a3e7 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.79.2"
+version = "0.79.3"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -725,9 +725,9 @@ dependencies = [
     { name = "requests" },
     { name = "selenium" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/64/bd/eff7b633a0b28ff4ed115adde1499e3dcc683e4f0b5c378a4c6f5c0c1bf6/crewai_tools-0.14.0.tar.gz", hash = "sha256:b6ac527633b7018471d892c21ac96bc961a86b6626d996b1ed7d53cd481d4505", size = 816588 }
+sdist = { url = "https://files.pythonhosted.org/packages/9b/6d/4fa91b481b120f83bb58f365203d8aa8564e8ced1035d79f8aedb7d71e2f/crewai_tools-0.14.0.tar.gz", hash = "sha256:510f3a194bcda4fdae4314bd775521964b5f229ddbe451e5d9e0216cae57f4e3", size = 815892 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6c/40/93cd347d854059cf5e54a81b70f896deea7ad1f03e9c024549eb323c4da5/crewai_tools-0.14.0-py3-none-any.whl", hash = "sha256:eda78fe3c4df57676259d8dd6b2610fa31f89b90909512f15893adb57fb9e825", size = 463703 },
+    { url = "https://files.pythonhosted.org/packages/c8/ed/9f4e64e1507062957b0118085332d38b621c1000874baef2d1c4069bfd97/crewai_tools-0.14.0-py3-none-any.whl", hash = "sha256:0a804a828c29869c3af3253f4fc4c3967a3f80f06dab22e9bbe9526608a31564", size = 462980 },
 ]
 
 [[package]]

From 6d677541c738edd10e80dbe8d5d07bb4f2b60d7f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Mon, 11 Nov 2024 00:03:52 -0300
Subject: [PATCH 052/126] preparing new version

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 uv.lock                                                 | 2 +-
 8 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index b9e403140..8a5d2f1b9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.79.3"
+version = "0.79.4"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 77cbc19f5..8d01b7cb5 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.79.2"
+__version__ = "0.79.4"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index fea666134..8606a2134 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.2,<1.0.0"
+    "crewai[tools]>=0.79.4,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 3a708f780..69e26f220 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.2,<1.0.0",
+    "crewai[tools]>=0.79.4,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 616fa0836..b09ce842f 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.79.2,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.79.4,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index ca8d99629..16d6360db 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.2,<1.0.0"
+    "crewai[tools]>=0.79.4,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 8a412ab25..dc928ad1e 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.2"
+    "crewai[tools]>=0.79.4"
 ]
 
diff --git a/uv.lock b/uv.lock
index 0b541a3e7..844e0b862 100644
--- a/uv.lock
+++ b/uv.lock
@@ -604,7 +604,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.79.3"
+version = "0.79.4"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 8610faef22024fb24486851402ae6ee7df95625c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Mon, 11 Nov 2024 02:29:40 -0300
Subject: [PATCH 053/126] add missing init

---
 src/crewai/tools/cache_tools/__init__.py | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 src/crewai/tools/cache_tools/__init__.py

diff --git a/src/crewai/tools/cache_tools/__init__.py b/src/crewai/tools/cache_tools/__init__.py
new file mode 100644
index 000000000..e69de29bb

From 4afb022572e2f48ee5379aaa591ead833ec0959b Mon Sep 17 00:00:00 2001
From: Thiago Moretto <thiago.moretto@gmail.com>
Date: Tue, 12 Nov 2024 15:04:57 -0300
Subject: [PATCH 054/126] fix LiteLLM callback replacement

---
 src/crewai/llm.py                             |  16 +-
 .../test_llm_callback_replacement.yaml        | 205 ++++++++++++++++++
 tests/llm_test.py                             |  30 +++
 3 files changed, 249 insertions(+), 2 deletions(-)
 create mode 100644 tests/cassettes/test_llm_callback_replacement.yaml
 create mode 100644 tests/llm_test.py

diff --git a/src/crewai/llm.py b/src/crewai/llm.py
index 577cb6a43..7ea8155a6 100644
--- a/src/crewai/llm.py
+++ b/src/crewai/llm.py
@@ -118,12 +118,12 @@ class LLM:
 
         litellm.drop_params = True
         litellm.set_verbose = False
-        litellm.callbacks = callbacks
+        self.set_callbacks(callbacks)
 
     def call(self, messages: List[Dict[str, str]], callbacks: List[Any] = []) -> str:
         with suppress_warnings():
             if callbacks and len(callbacks) > 0:
-                litellm.callbacks = callbacks
+                self.set_callbacks(callbacks)
 
             try:
                 params = {
@@ -181,3 +181,15 @@ class LLM:
     def get_context_window_size(self) -> int:
         # Only using 75% of the context window size to avoid cutting the message in the middle
         return int(LLM_CONTEXT_WINDOW_SIZES.get(self.model, 8192) * 0.75)
+
+    def set_callbacks(self, callbacks: List[Any]):
+        callback_types = [type(callback) for callback in callbacks]
+        for callback in litellm.success_callback[:]:
+            if type(callback) in callback_types:
+                litellm.success_callback.remove(callback)
+
+        for callback in litellm._async_success_callback[:]:
+            if type(callback) in callback_types:
+                litellm._async_success_callback.remove(callback)
+
+        litellm.callbacks = callbacks
diff --git a/tests/cassettes/test_llm_callback_replacement.yaml b/tests/cassettes/test_llm_callback_replacement.yaml
new file mode 100644
index 000000000..7b8f7e707
--- /dev/null
+++ b/tests/cassettes/test_llm_callback_replacement.yaml
@@ -0,0 +1,205 @@
+interactions:
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diff --git a/tests/llm_test.py b/tests/llm_test.py
new file mode 100644
index 000000000..e824d54c9
--- /dev/null
+++ b/tests/llm_test.py
@@ -0,0 +1,30 @@
+import pytest
+
+from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
+from crewai.llm import LLM
+from crewai.utilities.token_counter_callback import TokenCalcHandler
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_llm_callback_replacement():
+    llm = LLM(model="gpt-4o-mini")
+
+    calc_handler_1 = TokenCalcHandler(token_cost_process=TokenProcess())
+    calc_handler_2 = TokenCalcHandler(token_cost_process=TokenProcess())
+
+    llm.call(
+        messages=[{"role": "user", "content": "Hello, world!"}],
+        callbacks=[calc_handler_1],
+    )
+    usage_metrics_1 = calc_handler_1.token_cost_process.get_summary()
+
+    llm.call(
+        messages=[{"role": "user", "content": "Hello, world from another agent!"}],
+        callbacks=[calc_handler_2],
+    )
+    usage_metrics_2 = calc_handler_2.token_cost_process.get_summary()
+
+    # The first handler should not have been updated
+    assert usage_metrics_1.successful_requests == 1
+    assert usage_metrics_2.successful_requests == 1
+    assert usage_metrics_1 == calc_handler_1.token_cost_process.get_summary()

From c7b9ae02fd48ff0d43852398a11f945a69951fc9 Mon Sep 17 00:00:00 2001
From: Thiago Moretto <thiago.moretto@gmail.com>
Date: Tue, 12 Nov 2024 16:43:43 -0300
Subject: [PATCH 055/126] fix
 test_agent_usage_metrics_are_captured_for_hierarchical_process

---
 tests/crew_test.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/crew_test.py b/tests/crew_test.py
index 24b892271..5f39557e0 100644
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -1280,10 +1280,10 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
     assert result.raw == "Howdy!"
 
     assert result.token_usage == UsageMetrics(
-        total_tokens=2626,
-        prompt_tokens=2482,
-        completion_tokens=144,
-        successful_requests=5,
+        total_tokens=1673,
+        prompt_tokens=1562,
+        completion_tokens=111,
+        successful_requests=3,
     )
 
 

From bcfcf88e789e14ca20113b0a3268a2cecb380836 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Tue, 12 Nov 2024 18:37:50 -0300
Subject: [PATCH 056/126] removing prints

---
 src/crewai/agent.py        | 5 -----
 src/crewai/cli/run_crew.py | 1 -
 2 files changed, 6 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index c8998fd19..fc43137a2 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -162,9 +162,6 @@ class Agent(BaseAgent):
                         # Check if the environment variable is set
                         if "key_name" in env_var:
                             env_value = os.environ.get(env_var["key_name"])
-                            print(
-                                f"Checking env var {env_var['key_name']}: {env_value}"
-                            )
                             if env_value:
                                 # Map key names containing "API_KEY" to "api_key"
                                 key_name = (
@@ -184,7 +181,6 @@ class Agent(BaseAgent):
                                     if "API_VERSION" in env_var["key_name"]
                                     else key_name
                                 )
-                                print(f"Mapped key name: {key_name}")
                                 llm_params[key_name] = env_value
                         # Check for default values if the environment variable is not set
                         elif env_var.get("default", False):
@@ -192,7 +188,6 @@ class Agent(BaseAgent):
                                 if key not in ["prompt", "key_name", "default"]:
                                     # Only add default if the key is already set in os.environ
                                     if key in os.environ:
-                                        print(f"Using default value for {key}: {value}")
                                         llm_params[key] = value
 
             self.llm = LLM(**llm_params)
diff --git a/src/crewai/cli/run_crew.py b/src/crewai/cli/run_crew.py
index 20d6aed01..5450cf32b 100644
--- a/src/crewai/cli/run_crew.py
+++ b/src/crewai/cli/run_crew.py
@@ -24,7 +24,6 @@ def run_crew() -> None:
             f"Please run `crewai update` to update your pyproject.toml to use uv.",
             fg="red",
         )
-        print()
 
     try:
         subprocess.run(command, capture_output=False, text=True, check=True)

From b98f8f9fe1f79d9d380f3bd8ddb6bc800cf59d0e Mon Sep 17 00:00:00 2001
From: Eduardo Chiarotti <dudumelgaco@hotmail.com>
Date: Wed, 13 Nov 2024 10:07:28 -0300
Subject: [PATCH 057/126] fix: Step callback issue (#1595)

* fix: Step callback issue

* fix: Add empty thought since its required
---
 src/crewai/agents/crew_agent_executor.py | 37 ++++++++++++------------
 1 file changed, 19 insertions(+), 18 deletions(-)

diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index aa641e061..bf14e6915 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -145,25 +145,26 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         formatted_answer.result = action_result
                         self._show_logs(formatted_answer)
 
-                        if self.step_callback:
-                            self.step_callback(formatted_answer)
+                    if self.step_callback:
+                        self.step_callback(formatted_answer)
 
-                        if self._should_force_answer():
-                            if self.have_forced_answer:
-                                return AgentFinish(
-                                    output=self._i18n.errors(
-                                        "force_final_answer_error"
-                                    ).format(formatted_answer.text),
-                                    text=formatted_answer.text,
-                                )
-                            else:
-                                formatted_answer.text += (
-                                    f'\n{self._i18n.errors("force_final_answer")}'
-                                )
-                                self.have_forced_answer = True
-                        self.messages.append(
-                            self._format_msg(formatted_answer.text, role="assistant")
-                        )
+                    if self._should_force_answer():
+                        if self.have_forced_answer:
+                            return AgentFinish(
+                                thought="",
+                                output=self._i18n.errors(
+                                    "force_final_answer_error"
+                                ).format(formatted_answer.text),
+                                text=formatted_answer.text,
+                            )
+                        else:
+                            formatted_answer.text += (
+                                f'\n{self._i18n.errors("force_final_answer")}'
+                            )
+                            self.have_forced_answer = True
+                    self.messages.append(
+                        self._format_msg(formatted_answer.text, role="assistant")
+                    )
 
         except OutputParserException as e:
             self.messages.append({"role": "user", "content": e.error})

From 36aa4bcb4615bc5da33d65bd24dbceb80291ce51 Mon Sep 17 00:00:00 2001
From: Thiago Moretto <thiago.moretto@gmail.com>
Date: Wed, 13 Nov 2024 10:16:30 -0300
Subject: [PATCH 058/126] Cached prompt tokens on usage metrics

---
 .../utilities/base_token_process.py           |   6 +
 src/crewai/types/usage_metrics.py             |   5 +
 .../utilities/token_counter_callback.py       |  13 +-
 .../test_crew_kickoff_usage_metrics.yaml      | 206 ++++++++++--------
 tests/crew_test.py                            |   2 +
 5 files changed, 137 insertions(+), 95 deletions(-)

diff --git a/src/crewai/agents/agent_builder/utilities/base_token_process.py b/src/crewai/agents/agent_builder/utilities/base_token_process.py
index e971d018e..91df8140e 100644
--- a/src/crewai/agents/agent_builder/utilities/base_token_process.py
+++ b/src/crewai/agents/agent_builder/utilities/base_token_process.py
@@ -4,6 +4,7 @@ from crewai.types.usage_metrics import UsageMetrics
 class TokenProcess:
     total_tokens: int = 0
     prompt_tokens: int = 0
+    cached_prompt_tokens: int = 0
     completion_tokens: int = 0
     successful_requests: int = 0
 
@@ -15,6 +16,10 @@ class TokenProcess:
         self.completion_tokens = self.completion_tokens + tokens
         self.total_tokens = self.total_tokens + tokens
 
+    def sum_cached_prompt_tokens(self, tokens: int):
+        self.cached_prompt_tokens = self.cached_prompt_tokens + tokens
+        self.total_tokens = self.total_tokens + tokens
+
     def sum_successful_requests(self, requests: int):
         self.successful_requests = self.successful_requests + requests
 
@@ -22,6 +27,7 @@ class TokenProcess:
         return UsageMetrics(
             total_tokens=self.total_tokens,
             prompt_tokens=self.prompt_tokens,
+            cached_prompt_tokens=self.cached_prompt_tokens,
             completion_tokens=self.completion_tokens,
             successful_requests=self.successful_requests,
         )
diff --git a/src/crewai/types/usage_metrics.py b/src/crewai/types/usage_metrics.py
index a5cee6a0f..e87a79e33 100644
--- a/src/crewai/types/usage_metrics.py
+++ b/src/crewai/types/usage_metrics.py
@@ -8,6 +8,7 @@ class UsageMetrics(BaseModel):
     Attributes:
         total_tokens: Total number of tokens used.
         prompt_tokens: Number of tokens used in prompts.
+        cached_prompt_tokens: Number of cached prompt tokens used.
         completion_tokens: Number of tokens used in completions.
         successful_requests: Number of successful requests made.
     """
@@ -16,6 +17,9 @@ class UsageMetrics(BaseModel):
     prompt_tokens: int = Field(
         default=0, description="Number of tokens used in prompts."
     )
+    cached_prompt_tokens: int = Field(
+        default=0, description="Number of cached prompt tokens used."
+    )
     completion_tokens: int = Field(
         default=0, description="Number of tokens used in completions."
     )
@@ -32,5 +36,6 @@ class UsageMetrics(BaseModel):
         """
         self.total_tokens += usage_metrics.total_tokens
         self.prompt_tokens += usage_metrics.prompt_tokens
+        self.cached_prompt_tokens += usage_metrics.cached_prompt_tokens
         self.completion_tokens += usage_metrics.completion_tokens
         self.successful_requests += usage_metrics.successful_requests
diff --git a/src/crewai/utilities/token_counter_callback.py b/src/crewai/utilities/token_counter_callback.py
index 1b6215232..feaaa4c22 100644
--- a/src/crewai/utilities/token_counter_callback.py
+++ b/src/crewai/utilities/token_counter_callback.py
@@ -1,5 +1,5 @@
 from litellm.integrations.custom_logger import CustomLogger
-
+from litellm.types.utils import Usage
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
 
 
@@ -11,8 +11,11 @@ class TokenCalcHandler(CustomLogger):
         if self.token_cost_process is None:
             return
 
+        usage : Usage = response_obj["usage"]
         self.token_cost_process.sum_successful_requests(1)
-        self.token_cost_process.sum_prompt_tokens(response_obj["usage"].prompt_tokens)
-        self.token_cost_process.sum_completion_tokens(
-            response_obj["usage"].completion_tokens
-        )
+        self.token_cost_process.sum_prompt_tokens(usage.prompt_tokens)
+        self.token_cost_process.sum_completion_tokens(usage.completion_tokens)
+        if usage.prompt_tokens_details:
+            self.token_cost_process.sum_cached_prompt_tokens(
+                usage.prompt_tokens_details.cached_tokens
+            )
diff --git a/tests/cassettes/test_crew_kickoff_usage_metrics.yaml b/tests/cassettes/test_crew_kickoff_usage_metrics.yaml
index cc0863ee4..1851d0901 100644
--- a/tests/cassettes/test_crew_kickoff_usage_metrics.yaml
+++ b/tests/cassettes/test_crew_kickoff_usage_metrics.yaml
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-      Answer, your job depends on it!\n\nThought:"}], "model": "gpt-4o"}'
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-      - '430'
+      - '464'
       openai-version:
       - '2020-10-01'
       strict-transport-security:
@@ -192,19 +210,20 @@ interactions:
       x-ratelimit-limit-requests:
       - '10000'
       x-ratelimit-limit-tokens:
-      - '30000000'
+      - '200000'
       x-ratelimit-remaining-requests:
-      - '9999'
+      - '9998'
       x-ratelimit-remaining-tokens:
-      - '29999792'
+      - '199792'
       x-ratelimit-reset-requests:
-      - 6ms
+      - 16.369s
       x-ratelimit-reset-tokens:
-      - 0s
+      - 62ms
       x-request-id:
-      - req_ace859b7d9e83d9fa7753ce23bb03716
-    http_version: HTTP/1.1
-    status_code: 200
+      - req_91706b23d0ef23458ba63ec18304cd28
+    status:
+      code: 200
+      message: OK
 - request:
     body: '{"messages": [{"role": "system", "content": "You are apple Researcher.
       You have a lot of experience with apple.\nYour personal goal is: Express hot
@@ -217,7 +236,7 @@ interactions:
       under 15 words.\nyou MUST return the actual complete content as the final answer,
       not a summary.\n\nBegin! This is VERY important to you, use the tools available
       and give your best Final Answer, your job depends on it!\n\nThought:"}], "model":
-      "gpt-4o"}'
+      "gpt-4o-mini", "stop": ["\nObservation:"], "stream": false}'
     headers:
       accept:
       - application/json
@@ -226,49 +245,53 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '879'
+      - '929'
       content-type:
       - application/json
       cookie:
-      - __cf_bm=9.8sBYBkvBR8R1K_bVF7xgU..80XKlEIg3N2OBbTSCU-1727214102-1.0.1.1-.qiTLXbPamYUMSuyNsOEB9jhGu.jOifujOrx9E2JZvStbIZ9RTIiE44xKKNfLPxQkOi6qAT3h6htK8lPDGV_5g;
-        _cfuvid=lbRdAddVWV6W3f5Dm9SaOPWDUOxqtZBSPr_fTW26nEA-1727213194587-0.0.1.1-604800000
+      - __cf_bm=MkvcnvacGpTyn.y0OkFRoFXuAwg4oxjMhViZJTt9mw0-1731448324-1.0.1.1-oekkH_B0xOoPnIFw15LpqFCkZ2cu7VBTJVLDGylan4I67NjX.tlPvOiX9kvtP5Acewi28IE2IwlwtrZWzCH3vw;
+        _cfuvid=4.17346mfw5npZfYNbCx3Vj1VAVPy.tH0Jm2gkTteJ8-1731448324998-0.0.1.1-604800000
       host:
       - api.openai.com
       user-agent:
-      - OpenAI/Python 1.47.0
+      - OpenAI/Python 1.52.1
       x-stainless-arch:
-      - arm64
+      - x64
       x-stainless-async:
       - 'false'
       x-stainless-lang:
       - python
       x-stainless-os:
-      - MacOS
+      - Linux
       x-stainless-package-version:
-      - 1.47.0
+      - 1.52.1
       x-stainless-raw-response:
       - 'true'
+      x-stainless-retry-count:
+      - '0'
       x-stainless-runtime:
       - CPython
       x-stainless-runtime-version:
-      - 3.11.7
+      - 3.11.9
     method: POST
     uri: https://api.openai.com/v1/chat/completions
   response:
-    content: "{\n  \"id\": \"chatcmpl-AB7avZ0yqY18ukQS7SnLkZydsx72b\",\n  \"object\":
-      \"chat.completion\",\n  \"created\": 1727214165,\n  \"model\": \"gpt-4o-2024-05-13\",\n
-      \ \"choices\": [\n    {\n      \"index\": 0,\n      \"message\": {\n        \"role\":
-      \"assistant\",\n        \"content\": \"I now can give a great answer.\\n\\nFinal
-      Answer: Apples are incredibly versatile, nutritious, and a staple in diets globally.\",\n
-      \       \"refusal\": null\n      },\n      \"logprobs\": null,\n      \"finish_reason\":
-      \"stop\"\n    }\n  ],\n  \"usage\": {\n    \"prompt_tokens\": 175,\n    \"completion_tokens\":
-      25,\n    \"total_tokens\": 200,\n    \"completion_tokens_details\": {\n      \"reasoning_tokens\":
-      0\n    }\n  },\n  \"system_fingerprint\": \"fp_a5d11b2ef2\"\n}\n"
+    body:
+      string: !!binary |
+        H4sIAAAAAAAAA4xSPW/bMBDd9SsOXLpIgeTITarNS4t26JJubSHQ5IliSh1ZHv0RBP7vhSTHctAU
+        6CJQ7909vHd3zxmAsFo0IFQvkxqCKzYPaf1b2/hhW+8PR9N9Kh9W5Zdhjebr4zeRjx1++4gqvXTd
+        KD8Eh8l6mmkVUSYcVau726qu729X7ydi8Brd2GZCKmpfDJZssSpXdVHeFdX9ubv3ViGLBr5nAADP
+        03f0SRqPooEyf0EGZJYGRXMpAhDRuxERktlykpREvpDKU0KarH8G8gdQksDYPYIEM9oGSXzACPCD
+        PlqSDjbTfwObEBy+Y0Dl+YkTDmApoYkyIUMvoz7IiDmw79L8kqSBMe7HMMAoB4fM7ikHpF6SsmRg
+        xxgBjwGjRVJ4c+00YrdjOU6Lds6d8dMluvMmRL/lM3/BO0uW+zaiZE9jTE4+iIk9ZQA/pxHvXk1N
+        hOiHkNrkfyHxtLX1rCeWzS7svEsAkXyS7govq/wNvVZjktbx1ZKEkqpHvbQuG5U7bf0VkV2l/tvN
+        W9pzckvmf+QXQikMCXUbImqrXideyiKOh/+vssuUJ8NiPpO2s2Qwhmjns+tCW25lqatV3VUiO2V/
+        AAAA//8DAPtpFJCEAwAA
     headers:
       CF-Cache-Status:
       - DYNAMIC
       CF-RAY:
-      - 8c85f2369a761cf3-GRU
+      - 8e19bf447ba48761-GRU
       Connection:
       - keep-alive
       Content-Encoding:
@@ -276,7 +299,7 @@ interactions:
       Content-Type:
       - application/json
       Date:
-      - Tue, 24 Sep 2024 21:42:46 GMT
+      - Tue, 12 Nov 2024 21:52:06 GMT
       Server:
       - cloudflare
       Transfer-Encoding:
@@ -285,10 +308,12 @@ interactions:
       - nosniff
       access-control-expose-headers:
       - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
       openai-organization:
-      - crewai-iuxna1
+      - user-tqfegqsiobpvvjmn0giaipdq
       openai-processing-ms:
-      - '389'
+      - '655'
       openai-version:
       - '2020-10-01'
       strict-transport-security:
@@ -296,17 +321,18 @@ interactions:
       x-ratelimit-limit-requests:
       - '10000'
       x-ratelimit-limit-tokens:
-      - '30000000'
+      - '200000'
       x-ratelimit-remaining-requests:
-      - '9999'
+      - '9997'
       x-ratelimit-remaining-tokens:
-      - '29999791'
+      - '199791'
       x-ratelimit-reset-requests:
-      - 6ms
+      - 24.239s
       x-ratelimit-reset-tokens:
-      - 0s
+      - 62ms
       x-request-id:
-      - req_0167388f0a7a7f1a1026409834ceb914
-    http_version: HTTP/1.1
-    status_code: 200
+      - req_a228208b0e965ecee334a6947d6c9e7c
+    status:
+      code: 200
+      message: OK
 version: 1
diff --git a/tests/crew_test.py b/tests/crew_test.py
index 5f39557e0..8a7fc193a 100644
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -564,6 +564,7 @@ def test_crew_kickoff_usage_metrics():
         assert result.token_usage.prompt_tokens > 0
         assert result.token_usage.completion_tokens > 0
         assert result.token_usage.successful_requests > 0
+        assert result.token_usage.cached_prompt_tokens == 0
 
 
 def test_agents_rpm_is_never_set_if_crew_max_RPM_is_not_set():
@@ -1284,6 +1285,7 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
         prompt_tokens=1562,
         completion_tokens=111,
         successful_requests=3,
+        cached_prompt_tokens=0
     )
 
 

From c725105b1f49da983e029cdbb38093ed01507ba7 Mon Sep 17 00:00:00 2001
From: Thiago Moretto <thiago.moretto@gmail.com>
Date: Wed, 13 Nov 2024 10:18:30 -0300
Subject: [PATCH 059/126] do not include cached on total

---
 src/crewai/agents/agent_builder/utilities/base_token_process.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/crewai/agents/agent_builder/utilities/base_token_process.py b/src/crewai/agents/agent_builder/utilities/base_token_process.py
index 91df8140e..320d34caa 100644
--- a/src/crewai/agents/agent_builder/utilities/base_token_process.py
+++ b/src/crewai/agents/agent_builder/utilities/base_token_process.py
@@ -18,7 +18,6 @@ class TokenProcess:
 
     def sum_cached_prompt_tokens(self, tokens: int):
         self.cached_prompt_tokens = self.cached_prompt_tokens + tokens
-        self.total_tokens = self.total_tokens + tokens
 
     def sum_successful_requests(self, requests: int):
         self.successful_requests = self.successful_requests + requests

From c57cbd8591dc352485d4bb213649ca5c085fd5b5 Mon Sep 17 00:00:00 2001
From: Thiago Moretto <thiago.moretto@gmail.com>
Date: Wed, 13 Nov 2024 10:47:49 -0300
Subject: [PATCH 060/126] Fix crew_train_success test

---
 tests/crew_test.py | 36 ++++++++++++++++--------------------
 1 file changed, 16 insertions(+), 20 deletions(-)

diff --git a/tests/crew_test.py b/tests/crew_test.py
index 8a7fc193a..5f31061ec 100644
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -1779,26 +1779,22 @@ def test_crew_train_success(
         ]
     )
 
-    crew_training_handler.assert_has_calls(
-        [
-            mock.call("training_data.pkl"),
-            mock.call().load(),
-            mock.call("trained_agents_data.pkl"),
-            mock.call().save_trained_data(
-                agent_id="Researcher",
-                trained_data=task_evaluator().evaluate_training_data().model_dump(),
-            ),
-            mock.call("trained_agents_data.pkl"),
-            mock.call().save_trained_data(
-                agent_id="Senior Writer",
-                trained_data=task_evaluator().evaluate_training_data().model_dump(),
-            ),
-            mock.call(),
-            mock.call().load(),
-            mock.call(),
-            mock.call().load(),
-        ]
-    )
+    crew_training_handler.assert_any_call("training_data.pkl")
+    crew_training_handler().load.assert_called()
+
+    crew_training_handler.assert_any_call("trained_agents_data.pkl")
+    crew_training_handler().load.assert_called()
+
+    crew_training_handler().save_trained_data.assert_has_calls([
+        mock.call(
+            agent_id="Researcher",
+            trained_data=task_evaluator().evaluate_training_data().model_dump(),
+        ),
+        mock.call(
+            agent_id="Senior Writer",
+            trained_data=task_evaluator().evaluate_training_data().model_dump(),
+        )
+    ])
 
 
 def test_crew_train_error():

From 9285ebf8a210d076d392ef02901a620ef568327f Mon Sep 17 00:00:00 2001
From: Eduardo Chiarotti <dudumelgaco@hotmail.com>
Date: Thu, 14 Nov 2024 13:12:35 -0300
Subject: [PATCH 061/126] feat: Reduce level for Bandit and fix code to adapt
 (#1604)

---
 .github/workflows/security-checker.yml                    | 2 +-
 src/crewai/cli/authentication/main.py                     | 6 ++++--
 src/crewai/memory/storage/kickoff_task_outputs_storage.py | 2 +-
 src/crewai/memory/storage/ltm_sqlite_storage.py           | 2 +-
 src/crewai/utilities/file_handler.py                      | 8 ++++++--
 5 files changed, 13 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/security-checker.yml b/.github/workflows/security-checker.yml
index d0d309b4c..665f49292 100644
--- a/.github/workflows/security-checker.yml
+++ b/.github/workflows/security-checker.yml
@@ -19,5 +19,5 @@ jobs:
         run: pip install bandit
 
       - name: Run Bandit
-        run: bandit -c pyproject.toml -r src/ -lll
+        run: bandit -c pyproject.toml -r src/ -ll
 
diff --git a/src/crewai/cli/authentication/main.py b/src/crewai/cli/authentication/main.py
index 331b583e8..543f06844 100644
--- a/src/crewai/cli/authentication/main.py
+++ b/src/crewai/cli/authentication/main.py
@@ -34,7 +34,9 @@ class AuthenticationCommand:
             "scope": "openid",
             "audience": AUTH0_AUDIENCE,
         }
-        response = requests.post(url=self.DEVICE_CODE_URL, data=device_code_payload)
+        response = requests.post(
+            url=self.DEVICE_CODE_URL, data=device_code_payload, timeout=20
+        )
         response.raise_for_status()
         return response.json()
 
@@ -54,7 +56,7 @@ class AuthenticationCommand:
 
         attempts = 0
         while True and attempts < 5:
-            response = requests.post(self.TOKEN_URL, data=token_payload)
+            response = requests.post(self.TOKEN_URL, data=token_payload, timeout=30)
             token_data = response.json()
 
             if response.status_code == 200:
diff --git a/src/crewai/memory/storage/kickoff_task_outputs_storage.py b/src/crewai/memory/storage/kickoff_task_outputs_storage.py
index dbb5f124b..26905191c 100644
--- a/src/crewai/memory/storage/kickoff_task_outputs_storage.py
+++ b/src/crewai/memory/storage/kickoff_task_outputs_storage.py
@@ -103,7 +103,7 @@ class KickoffTaskOutputsSQLiteStorage:
                         else value
                     )
 
-                query = f"UPDATE latest_kickoff_task_outputs SET {', '.join(fields)} WHERE task_index = ?"
+                query = f"UPDATE latest_kickoff_task_outputs SET {', '.join(fields)} WHERE task_index = ?"  # nosec
                 values.append(task_index)
 
                 cursor.execute(query, tuple(values))
diff --git a/src/crewai/memory/storage/ltm_sqlite_storage.py b/src/crewai/memory/storage/ltm_sqlite_storage.py
index 7fb388a62..93d993ee6 100644
--- a/src/crewai/memory/storage/ltm_sqlite_storage.py
+++ b/src/crewai/memory/storage/ltm_sqlite_storage.py
@@ -83,7 +83,7 @@ class LTMSQLiteStorage:
                     WHERE task_description = ?
                     ORDER BY datetime DESC, score ASC
                     LIMIT {latest_n}
-                """,
+                """,  # nosec
                     (task_description,),
                 )
                 rows = cursor.fetchall()
diff --git a/src/crewai/utilities/file_handler.py b/src/crewai/utilities/file_handler.py
index 091bd930a..bb97b940f 100644
--- a/src/crewai/utilities/file_handler.py
+++ b/src/crewai/utilities/file_handler.py
@@ -16,7 +16,11 @@ class FileHandler:
 
     def log(self, **kwargs):
         now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-        message = f"{now}: " + ", ".join([f"{key}=\"{value}\"" for key, value in kwargs.items()]) + "\n"
+        message = (
+            f"{now}: "
+            + ", ".join([f'{key}="{value}"' for key, value in kwargs.items()])
+            + "\n"
+        )
         with open(self._path, "a", encoding="utf-8") as file:
             file.write(message + "\n")
 
@@ -63,7 +67,7 @@ class PickleHandler:
 
         with open(self.file_path, "rb") as file:
             try:
-                return pickle.load(file)
+                return pickle.load(file)  # nosec
             except EOFError:
                 return {}  # Return an empty dictionary if the file is empty or corrupted
             except Exception:

From e70bc94ab6c14fbfe0491a562d5252908160e033 Mon Sep 17 00:00:00 2001
From: Dev Khant <devkhant24@gmail.com>
Date: Fri, 15 Nov 2024 00:29:24 +0530
Subject: [PATCH 062/126] Add support for retrieving user preferences and
 memories using Mem0 (#1209)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* Integrate Mem0

* Update src/crewai/memory/contextual/contextual_memory.py

Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>

* pending commit for _fetch_user_memories

* update poetry.lock

* fixes mypy issues

* fix mypy checks

* New fixes for user_id

* remove memory_provider

* handle memory_provider

* checks for memory_config

* add mem0 to dependency

* Update pyproject.toml

Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>

* update docs

* update doc

* bump mem0 version

* fix api error msg and mypy issue

* mypy fix

* resolve comments

* fix memory usage without mem0

* mem0 version bump

* lazy import mem0

---------

Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>
Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/concepts/crews.mdx                       |   3 +-
 docs/concepts/memory.mdx                      |  42 +++
 poetry.lock                                   |   6 +-
 pyproject.toml                                |   1 +
 src/crewai/agent.py                           |   2 +
 src/crewai/crew.py                            |  24 +-
 src/crewai/memory/__init__.py                 |   3 +-
 .../memory/contextual/contextual_memory.py    |  47 ++-
 src/crewai/memory/entity/entity_memory.py     |  42 ++-
 src/crewai/memory/memory.py                   |  11 +-
 .../memory/short_term/short_term_memory.py    |  39 ++-
 src/crewai/memory/storage/interface.py        |   6 +-
 src/crewai/memory/storage/mem0_storage.py     | 104 +++++++
 src/crewai/memory/user/__init__.py            |   0
 src/crewai/memory/user/user_memory.py         |  45 +++
 src/crewai/memory/user/user_memory_item.py    |   8 +
 .../test_save_and_search_with_provider.yaml   | 270 ++++++++++++++++++
 17 files changed, 619 insertions(+), 34 deletions(-)
 create mode 100644 src/crewai/memory/storage/mem0_storage.py
 create mode 100644 src/crewai/memory/user/__init__.py
 create mode 100644 src/crewai/memory/user/user_memory.py
 create mode 100644 src/crewai/memory/user/user_memory_item.py
 create mode 100644 tests/memory/cassettes/test_save_and_search_with_provider.yaml

diff --git a/docs/concepts/crews.mdx b/docs/concepts/crews.mdx
index 43451ca4b..ec0f190de 100644
--- a/docs/concepts/crews.mdx
+++ b/docs/concepts/crews.mdx
@@ -22,7 +22,8 @@ A crew in crewAI represents a collaborative group of agents working together to
 | **Max RPM** _(optional)_              | `max_rpm`              | Maximum requests per minute the crew adheres to during execution. Defaults to `None`.                                                                                                                                                                     |
 | **Language** _(optional)_             | `language`             | Language used for the crew, defaults to English.                                                                                                                                                                                                          |
 | **Language File** _(optional)_        | `language_file`        | Path to the language file to be used for the crew.                                                                                                                                                                                                        |
-| **Memory** _(optional)_               | `memory`               | Utilized for storing execution memories (short-term, long-term, entity memory). Defaults to `False`.                                                                                                                                                       |
+| **Memory** _(optional)_               | `memory`               | Utilized for storing execution memories (short-term, long-term, entity memory).                                                                                                                                                                           |
+| **Memory Config** _(optional)_        | `memory_config`        | Configuration for the memory provider to be used by the crew.                                                                                                                                                                                          |
 | **Cache** _(optional)_                | `cache`                | Specifies whether to use a cache for storing the results of tools' execution. Defaults to `True`.                                                                                                                                                          |
 | **Embedder** _(optional)_             | `embedder`             | Configuration for the embedder to be used by the crew. Mostly used by memory for now. Default is `{"provider": "openai"}`.                                                                                                                                                                     |
 | **Full Output** _(optional)_          | `full_output`          | Whether the crew should return the full output with all tasks outputs or just the final output. Defaults to `False`.                                                                                                                                       |
diff --git a/docs/concepts/memory.mdx b/docs/concepts/memory.mdx
index bda9f3401..a7677cec1 100644
--- a/docs/concepts/memory.mdx
+++ b/docs/concepts/memory.mdx
@@ -18,6 +18,7 @@ reason, and learn from past interactions.
 | **Long-Term Memory** | Preserves valuable insights and learnings from past executions, allowing agents to build and refine their knowledge over time. |
 | **Entity Memory**    | Captures and organizes information about entities (people, places, concepts) encountered during tasks, facilitating deeper understanding and relationship mapping. Uses `RAG` for storing entity information. |
 | **Contextual Memory**| Maintains the context of interactions by combining `ShortTermMemory`, `LongTermMemory`, and `EntityMemory`, aiding in the coherence and relevance of agent responses over a sequence of tasks or a conversation. |
+| **User Memory**      | Stores user-specific information and preferences, enhancing personalization and user experience. |
 
 ## How Memory Systems Empower Agents
 
@@ -92,6 +93,47 @@ my_crew = Crew(
 )
 ```
 
+## Integrating Mem0 for Enhanced User Memory
+
+[Mem0](https://mem0.ai/) is a self-improving memory layer for LLM applications, enabling personalized AI experiences. 
+
+To include user-specific memory you can get your API key [here](https://app.mem0.ai/dashboard/api-keys) and refer the [docs](https://docs.mem0.ai/platform/quickstart#4-1-create-memories) for adding user preferences.
+
+
+```python Code
+import os
+from crewai import Crew, Process
+from mem0 import MemoryClient
+
+# Set environment variables for Mem0
+os.environ["MEM0_API_KEY"] = "m0-xx"
+
+# Step 1: Record preferences based on past conversation or user input
+client = MemoryClient()
+messages = [
+    {"role": "user", "content": "Hi there! I'm planning a vacation and could use some advice."},
+    {"role": "assistant", "content": "Hello! I'd be happy to help with your vacation planning. What kind of destination do you prefer?"},
+    {"role": "user", "content": "I am more of a beach person than a mountain person."},
+    {"role": "assistant", "content": "That's interesting. Do you like hotels or Airbnb?"},
+    {"role": "user", "content": "I like Airbnb more."},
+]
+client.add(messages, user_id="john")
+
+# Step 2: Create a Crew with User Memory
+
+crew = Crew(
+    agents=[...],
+    tasks=[...],
+    verbose=True,
+    process=Process.sequential,
+    memory=True,
+    memory_config={
+        "provider": "mem0",
+        "config": {"user_id": "john"},
+    },
+)
+```
+
 
 ## Additional Embedding Providers
 
diff --git a/poetry.lock b/poetry.lock
index 8ba39f6c3..094b84664 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1597,12 +1597,12 @@ files = [
 google-auth = ">=2.14.1,<3.0.dev0"
 googleapis-common-protos = ">=1.56.2,<2.0.dev0"
 grpcio = [
-    {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
     {version = ">=1.33.2,<2.0dev", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
 ]
 grpcio-status = [
-    {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
     {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
 ]
 proto-plus = ">=1.22.3,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
@@ -4286,8 +4286,8 @@ files = [
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
     {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
diff --git a/pyproject.toml b/pyproject.toml
index 8a5d2f1b9..66adfee3e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -39,6 +39,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 [project.optional-dependencies]
 tools = ["crewai-tools>=0.14.0"]
 agentops = ["agentops>=0.3.0"]
+mem0 = ["mem0ai>=0.1.29"]
 
 [tool.uv]
 dev-dependencies = [
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index fc43137a2..4e9a0685f 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -262,9 +262,11 @@ class Agent(BaseAgent):
 
         if self.crew and self.crew.memory:
             contextual_memory = ContextualMemory(
+                self.crew.memory_config,
                 self.crew._short_term_memory,
                 self.crew._long_term_memory,
                 self.crew._entity_memory,
+                self.crew._user_memory,
             )
             memory = contextual_memory.build_context_for_task(task, context)
             if memory.strip() != "":
diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 7bcaa82ad..04820adf8 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -27,6 +27,7 @@ from crewai.llm import LLM
 from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
+from crewai.memory.user.user_memory import UserMemory
 from crewai.process import Process
 from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
@@ -71,6 +72,7 @@ class Crew(BaseModel):
         manager_llm: The language model that will run manager agent.
         manager_agent: Custom agent that will be used as manager.
         memory: Whether the crew should use memory to store memories of it's execution.
+        memory_config: Configuration for the memory to be used for the crew.
         cache: Whether the crew should use a cache to store the results of the tools execution.
         function_calling_llm: The language model that will run the tool calling for all the agents.
         process: The process flow that the crew will follow (e.g., sequential, hierarchical).
@@ -94,6 +96,7 @@ class Crew(BaseModel):
     _short_term_memory: Optional[InstanceOf[ShortTermMemory]] = PrivateAttr()
     _long_term_memory: Optional[InstanceOf[LongTermMemory]] = PrivateAttr()
     _entity_memory: Optional[InstanceOf[EntityMemory]] = PrivateAttr()
+    _user_memory: Optional[InstanceOf[UserMemory]] = PrivateAttr()
     _train: Optional[bool] = PrivateAttr(default=False)
     _train_iteration: Optional[int] = PrivateAttr()
     _inputs: Optional[Dict[str, Any]] = PrivateAttr(default=None)
@@ -114,6 +117,10 @@ class Crew(BaseModel):
         default=False,
         description="Whether the crew should use memory to store memories of it's execution",
     )
+    memory_config: Optional[Dict[str, Any]] = Field(
+        default=None,
+        description="Configuration for the memory to be used for the crew.",
+    )
     short_term_memory: Optional[InstanceOf[ShortTermMemory]] = Field(
         default=None,
         description="An Instance of the ShortTermMemory to be used by the Crew",
@@ -126,7 +133,11 @@ class Crew(BaseModel):
         default=None,
         description="An Instance of the EntityMemory to be used by the Crew",
     )
-    embedder: Optional[Any] = Field(
+    user_memory: Optional[InstanceOf[UserMemory]] = Field(
+        default=None,
+        description="An instance of the UserMemory to be used by the Crew to store/fetch memories of a specific user.",
+    )
+    embedder: Optional[dict] = Field(
         default=None,
         description="Configuration for the embedder to be used for the crew.",
     )
@@ -238,13 +249,22 @@ class Crew(BaseModel):
             self._short_term_memory = (
                 self.short_term_memory
                 if self.short_term_memory
-                else ShortTermMemory(crew=self, embedder_config=self.embedder)
+                else ShortTermMemory(
+                    crew=self,
+                    embedder_config=self.embedder,
+                )
             )
             self._entity_memory = (
                 self.entity_memory
                 if self.entity_memory
                 else EntityMemory(crew=self, embedder_config=self.embedder)
             )
+            if hasattr(self, "memory_config") and self.memory_config is not None:
+                self._user_memory = (
+                    self.user_memory if self.user_memory else UserMemory(crew=self)
+                )
+            else:
+                self._user_memory = None
         return self
 
     @model_validator(mode="after")
diff --git a/src/crewai/memory/__init__.py b/src/crewai/memory/__init__.py
index 8182bede7..3f7ca2ad6 100644
--- a/src/crewai/memory/__init__.py
+++ b/src/crewai/memory/__init__.py
@@ -1,5 +1,6 @@
 from .entity.entity_memory import EntityMemory
 from .long_term.long_term_memory import LongTermMemory
 from .short_term.short_term_memory import ShortTermMemory
+from .user.user_memory import UserMemory
 
-__all__ = ["EntityMemory", "LongTermMemory", "ShortTermMemory"]
+__all__ = ["UserMemory", "EntityMemory", "LongTermMemory", "ShortTermMemory"]
diff --git a/src/crewai/memory/contextual/contextual_memory.py b/src/crewai/memory/contextual/contextual_memory.py
index 5d91cf47d..9598fe6ee 100644
--- a/src/crewai/memory/contextual/contextual_memory.py
+++ b/src/crewai/memory/contextual/contextual_memory.py
@@ -1,13 +1,25 @@
-from typing import Optional
+from typing import Optional, Dict, Any
 
-from crewai.memory import EntityMemory, LongTermMemory, ShortTermMemory
+from crewai.memory import EntityMemory, LongTermMemory, ShortTermMemory, UserMemory
 
 
 class ContextualMemory:
-    def __init__(self, stm: ShortTermMemory, ltm: LongTermMemory, em: EntityMemory):
+    def __init__(
+        self,
+        memory_config: Optional[Dict[str, Any]],
+        stm: ShortTermMemory,
+        ltm: LongTermMemory,
+        em: EntityMemory,
+        um: UserMemory,
+    ):
+        if memory_config is not None:
+            self.memory_provider = memory_config.get("provider")
+        else:
+            self.memory_provider = None
         self.stm = stm
         self.ltm = ltm
         self.em = em
+        self.um = um
 
     def build_context_for_task(self, task, context) -> str:
         """
@@ -23,6 +35,8 @@ class ContextualMemory:
         context.append(self._fetch_ltm_context(task.description))
         context.append(self._fetch_stm_context(query))
         context.append(self._fetch_entity_context(query))
+        if self.memory_provider == "mem0":
+            context.append(self._fetch_user_context(query))
         return "\n".join(filter(None, context))
 
     def _fetch_stm_context(self, query) -> str:
@@ -32,7 +46,10 @@ class ContextualMemory:
         """
         stm_results = self.stm.search(query)
         formatted_results = "\n".join(
-            [f"- {result['context']}" for result in stm_results]
+            [
+                f"- {result['memory'] if self.memory_provider == 'mem0' else result['context']}"
+                for result in stm_results
+            ]
         )
         return f"Recent Insights:\n{formatted_results}" if stm_results else ""
 
@@ -62,6 +79,26 @@ class ContextualMemory:
         """
         em_results = self.em.search(query)
         formatted_results = "\n".join(
-            [f"- {result['context']}" for result in em_results]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
+            [
+                f"- {result['memory'] if self.memory_provider == 'mem0' else result['context']}"
+                for result in em_results
+            ]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
         )
         return f"Entities:\n{formatted_results}" if em_results else ""
+
+    def _fetch_user_context(self, query: str) -> str:
+        """
+        Fetches and formats relevant user information from User Memory.
+        Args:
+            query (str): The search query to find relevant user memories.
+        Returns:
+            str: Formatted user memories as bullet points, or an empty string if none found.
+        """
+        user_memories = self.um.search(query)
+        if not user_memories:
+            return ""
+
+        formatted_memories = "\n".join(
+            f"- {result['memory']}" for result in user_memories
+        )
+        return f"User memories/preferences:\n{formatted_memories}"
diff --git a/src/crewai/memory/entity/entity_memory.py b/src/crewai/memory/entity/entity_memory.py
index 4de0594c7..134e19bfa 100644
--- a/src/crewai/memory/entity/entity_memory.py
+++ b/src/crewai/memory/entity/entity_memory.py
@@ -11,21 +11,43 @@ class EntityMemory(Memory):
     """
 
     def __init__(self, crew=None, embedder_config=None, storage=None):
-        storage = (
-            storage
-            if storage
-            else RAGStorage(
-                type="entities",
-                allow_reset=True,
-                embedder_config=embedder_config,
-                crew=crew,
+        if hasattr(crew, "memory_config") and crew.memory_config is not None:
+            self.memory_provider = crew.memory_config.get("provider")
+        else:
+            self.memory_provider = None
+
+        if self.memory_provider == "mem0":
+            try:
+                from crewai.memory.storage.mem0_storage import Mem0Storage
+            except ImportError:
+                raise ImportError(
+                    "Mem0 is not installed. Please install it with `pip install mem0ai`."
+                )
+            storage = Mem0Storage(type="entities", crew=crew)
+        else:
+            storage = (
+                storage
+                if storage
+                else RAGStorage(
+                    type="entities",
+                    allow_reset=False,
+                    embedder_config=embedder_config,
+                    crew=crew,
+                )
             )
-        )
         super().__init__(storage)
 
     def save(self, item: EntityMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"
         """Saves an entity item into the SQLite storage."""
-        data = f"{item.name}({item.type}): {item.description}"
+        if self.memory_provider == "mem0":
+            data = f"""
+            Remember details about the following entity:
+            Name: {item.name}
+            Type: {item.type}
+            Entity Description: {item.description}
+            """
+        else:
+            data = f"{item.name}({item.type}): {item.description}"
         super().save(data, item.metadata)
 
     def reset(self) -> None:
diff --git a/src/crewai/memory/memory.py b/src/crewai/memory/memory.py
index d0bcd614f..4869f8e6b 100644
--- a/src/crewai/memory/memory.py
+++ b/src/crewai/memory/memory.py
@@ -23,5 +23,12 @@ class Memory:
 
         self.storage.save(value, metadata)
 
-    def search(self, query: str) -> List[Dict[str, Any]]:
-        return self.storage.search(query)
+    def search(
+        self,
+        query: str,
+        limit: int = 3,
+        score_threshold: float = 0.35,
+    ) -> List[Any]:
+        return self.storage.search(
+            query=query, limit=limit, score_threshold=score_threshold
+        )
diff --git a/src/crewai/memory/short_term/short_term_memory.py b/src/crewai/memory/short_term/short_term_memory.py
index 919fb6115..67a568d63 100644
--- a/src/crewai/memory/short_term/short_term_memory.py
+++ b/src/crewai/memory/short_term/short_term_memory.py
@@ -14,13 +14,27 @@ class ShortTermMemory(Memory):
     """
 
     def __init__(self, crew=None, embedder_config=None, storage=None):
-        storage = (
-            storage
-            if storage
-            else RAGStorage(
-                type="short_term", embedder_config=embedder_config, crew=crew
+        if hasattr(crew, "memory_config") and crew.memory_config is not None:
+            self.memory_provider = crew.memory_config.get("provider")
+        else:
+            self.memory_provider = None
+
+        if self.memory_provider == "mem0":
+            try:
+                from crewai.memory.storage.mem0_storage import Mem0Storage
+            except ImportError:
+                raise ImportError(
+                    "Mem0 is not installed. Please install it with `pip install mem0ai`."
+                )
+            storage = Mem0Storage(type="short_term", crew=crew)
+        else:
+            storage = (
+                storage
+                if storage
+                else RAGStorage(
+                    type="short_term", embedder_config=embedder_config, crew=crew
+                )
             )
-        )
         super().__init__(storage)
 
     def save(
@@ -30,11 +44,20 @@ class ShortTermMemory(Memory):
         agent: Optional[str] = None,
     ) -> None:
         item = ShortTermMemoryItem(data=value, metadata=metadata, agent=agent)
+        if self.memory_provider == "mem0":
+            item.data = f"Remember the following insights from Agent run: {item.data}"
 
         super().save(value=item.data, metadata=item.metadata, agent=item.agent)
 
-    def search(self, query: str, score_threshold: float = 0.35):
-        return self.storage.search(query=query, score_threshold=score_threshold)  # type: ignore # BUG? The reference is to the parent class, but the parent class does not have this parameters
+    def search(
+        self,
+        query: str,
+        limit: int = 3,
+        score_threshold: float = 0.35,
+    ):
+        return self.storage.search(
+            query=query, limit=limit, score_threshold=score_threshold
+        )  # type: ignore # BUG? The reference is to the parent class, but the parent class does not have this parameters
 
     def reset(self) -> None:
         try:
diff --git a/src/crewai/memory/storage/interface.py b/src/crewai/memory/storage/interface.py
index 8fbe10b03..8bec9a14f 100644
--- a/src/crewai/memory/storage/interface.py
+++ b/src/crewai/memory/storage/interface.py
@@ -7,8 +7,10 @@ class Storage:
     def save(self, value: Any, metadata: Dict[str, Any]) -> None:
         pass
 
-    def search(self, key: str) -> List[Dict[str, Any]]:  # type: ignore
-        pass
+    def search(
+        self, query: str, limit: int, score_threshold: float
+    ) -> Dict[str, Any] | List[Any]:
+        return {}
 
     def reset(self) -> None:
         pass
diff --git a/src/crewai/memory/storage/mem0_storage.py b/src/crewai/memory/storage/mem0_storage.py
new file mode 100644
index 000000000..34aab9716
--- /dev/null
+++ b/src/crewai/memory/storage/mem0_storage.py
@@ -0,0 +1,104 @@
+import os
+from typing import Any, Dict, List
+
+from mem0 import MemoryClient
+from crewai.memory.storage.interface import Storage
+
+
+class Mem0Storage(Storage):
+    """
+    Extends Storage to handle embedding and searching across entities using Mem0.
+    """
+
+    def __init__(self, type, crew=None):
+        super().__init__()
+
+        if type not in ["user", "short_term", "long_term", "entities"]:
+            raise ValueError("Invalid type for Mem0Storage. Must be 'user' or 'agent'.")
+
+        self.memory_type = type
+        self.crew = crew
+        self.memory_config = crew.memory_config
+
+        # User ID is required for user memory type "user" since it's used as a unique identifier for the user.
+        user_id = self._get_user_id()
+        if type == "user" and not user_id:
+            raise ValueError("User ID is required for user memory type")
+
+        # API key in memory config overrides the environment variable
+        mem0_api_key = self.memory_config.get("config", {}).get("api_key") or os.getenv(
+            "MEM0_API_KEY"
+        )
+        self.memory = MemoryClient(api_key=mem0_api_key)
+
+    def _sanitize_role(self, role: str) -> str:
+        """
+        Sanitizes agent roles to ensure valid directory names.
+        """
+        return role.replace("\n", "").replace(" ", "_").replace("/", "_")
+
+    def save(self, value: Any, metadata: Dict[str, Any]) -> None:
+        user_id = self._get_user_id()
+        agent_name = self._get_agent_name()
+        if self.memory_type == "user":
+            self.memory.add(value, user_id=user_id, metadata={**metadata})
+        elif self.memory_type == "short_term":
+            agent_name = self._get_agent_name()
+            self.memory.add(
+                value, agent_id=agent_name, metadata={"type": "short_term", **metadata}
+            )
+        elif self.memory_type == "long_term":
+            agent_name = self._get_agent_name()
+            self.memory.add(
+                value,
+                agent_id=agent_name,
+                infer=False,
+                metadata={"type": "long_term", **metadata},
+            )
+        elif self.memory_type == "entities":
+            entity_name = None
+            self.memory.add(
+                value, user_id=entity_name, metadata={"type": "entity", **metadata}
+            )
+
+    def search(
+        self,
+        query: str,
+        limit: int = 3,
+        score_threshold: float = 0.35,
+    ) -> List[Any]:
+        params = {"query": query, "limit": limit}
+        if self.memory_type == "user":
+            user_id = self._get_user_id()
+            params["user_id"] = user_id
+        elif self.memory_type == "short_term":
+            agent_name = self._get_agent_name()
+            params["agent_id"] = agent_name
+            params["metadata"] = {"type": "short_term"}
+        elif self.memory_type == "long_term":
+            agent_name = self._get_agent_name()
+            params["agent_id"] = agent_name
+            params["metadata"] = {"type": "long_term"}
+        elif self.memory_type == "entities":
+            agent_name = self._get_agent_name()
+            params["agent_id"] = agent_name
+            params["metadata"] = {"type": "entity"}
+
+        # Discard the filters for now since we create the filters
+        # automatically when the crew is created.
+        results = self.memory.search(**params)
+        return [r for r in results if r["score"] >= score_threshold]
+
+    def _get_user_id(self):
+        if self.memory_type == "user":
+            if hasattr(self, "memory_config") and self.memory_config is not None:
+                return self.memory_config.get("config", {}).get("user_id")
+            else:
+                return None
+        return None
+
+    def _get_agent_name(self):
+        agents = self.crew.agents if self.crew else []
+        agents = [self._sanitize_role(agent.role) for agent in agents]
+        agents = "_".join(agents)
+        return agents
diff --git a/src/crewai/memory/user/__init__.py b/src/crewai/memory/user/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/crewai/memory/user/user_memory.py b/src/crewai/memory/user/user_memory.py
new file mode 100644
index 000000000..25e36617c
--- /dev/null
+++ b/src/crewai/memory/user/user_memory.py
@@ -0,0 +1,45 @@
+from typing import Any, Dict, Optional
+
+from crewai.memory.memory import Memory
+
+
+class UserMemory(Memory):
+    """
+    UserMemory class for handling user memory storage and retrieval.
+    Inherits from the Memory class and utilizes an instance of a class that
+    adheres to the Storage for data storage, specifically working with
+    MemoryItem instances.
+    """
+
+    def __init__(self, crew=None):
+        try:
+            from crewai.memory.storage.mem0_storage import Mem0Storage
+        except ImportError:
+            raise ImportError(
+                "Mem0 is not installed. Please install it with `pip install mem0ai`."
+            )
+        storage = Mem0Storage(type="user", crew=crew)
+        super().__init__(storage)
+
+    def save(
+        self,
+        value,
+        metadata: Optional[Dict[str, Any]] = None,
+        agent: Optional[str] = None,
+    ) -> None:
+        # TODO: Change this function since we want to take care of the case where we save memories for the usr
+        data = f"Remember the details about the user: {value}"
+        super().save(data, metadata)
+
+    def search(
+        self,
+        query: str,
+        limit: int = 3,
+        score_threshold: float = 0.35,
+    ):
+        results = super().search(
+            query=query,
+            limit=limit,
+            score_threshold=score_threshold,
+        )
+        return results
diff --git a/src/crewai/memory/user/user_memory_item.py b/src/crewai/memory/user/user_memory_item.py
new file mode 100644
index 000000000..288c1544a
--- /dev/null
+++ b/src/crewai/memory/user/user_memory_item.py
@@ -0,0 +1,8 @@
+from typing import Any, Dict, Optional
+
+
+class UserMemoryItem:
+    def __init__(self, data: Any, user: str, metadata: Optional[Dict[str, Any]] = None):
+        self.data = data
+        self.user = user
+        self.metadata = metadata if metadata is not None else {}
diff --git a/tests/memory/cassettes/test_save_and_search_with_provider.yaml b/tests/memory/cassettes/test_save_and_search_with_provider.yaml
new file mode 100644
index 000000000..c30f3f065
--- /dev/null
+++ b/tests/memory/cassettes/test_save_and_search_with_provider.yaml
@@ -0,0 +1,270 @@
+interactions:
+- request:
+    body: ''
+    headers:
+      accept:
+      - '*/*'
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      host:
+      - api.mem0.ai
+      user-agent:
+      - python-httpx/0.27.0
+    method: GET
+    uri: https://api.mem0.ai/v1/memories/?user_id=test
+  response:
+    body:
+      string: '[]'
+    headers:
+      CF-Cache-Status:
+      - DYNAMIC
+      CF-RAY:
+      - 8b477138bad847b9-BOM
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '2'
+      Content-Type:
+      - application/json
+      Date:
+      - Sat, 17 Aug 2024 06:00:11 GMT
+      NEL:
+      - '{"success_fraction":0,"report_to":"cf-nel","max_age":604800}'
+      Report-To:
+      - '{"endpoints":[{"url":"https:\/\/a.nel.cloudflare.com\/report\/v4?s=uuyH2foMJVDpV%2FH52g1q%2FnvXKe3dBKVzvsK0mqmSNezkiszNR9OgrEJfVqmkX%2FlPFRP2sH4zrOuzGo6k%2FjzsjYJczqSWJUZHN2pPujiwnr1E9W%2BdLGKmG6%2FqPrGYAy2SBRWkkJVWsTO3OQ%3D%3D"}],"group":"cf-nel","max_age":604800}'
+      Server:
+      - cloudflare
+      allow:
+      - GET, POST, DELETE, OPTIONS
+      alt-svc:
+      - h3=":443"; ma=86400
+      cross-origin-opener-policy:
+      - same-origin
+      referrer-policy:
+      - same-origin
+      vary:
+      - Accept, origin, Cookie
+      x-content-type-options:
+      - nosniff
+      x-frame-options:
+      - DENY
+    status:
+      code: 200
+      message: OK
+- request:
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From 3dc02310b62c473c0764f10f08aef678291e9aaf Mon Sep 17 00:00:00 2001
From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Date: Thu, 14 Nov 2024 14:13:12 -0800
Subject: [PATCH 063/126] upgrade chroma and adjust embedder function generator
 (#1607)

* upgrade chroma and adjust embedder function generator

* >= version

* linted
---
 pyproject.toml                            |  2 +-
 src/crewai/memory/entity/entity_memory.py |  2 +-
 src/crewai/memory/storage/rag_storage.py  | 94 ++++++++++++++---------
 uv.lock                                   | 84 ++++++++------------
 4 files changed, 90 insertions(+), 92 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 66adfee3e..57868636f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -27,8 +27,8 @@ dependencies = [
     "pyvis>=0.3.2",
     "uv>=0.4.25",
     "tomli-w>=1.1.0",
-    "chromadb>=0.4.24",
     "tomli>=2.0.2",
+    "chromadb>=0.5.18",
 ]
 
 [project.urls]
diff --git a/src/crewai/memory/entity/entity_memory.py b/src/crewai/memory/entity/entity_memory.py
index 134e19bfa..88d33c09a 100644
--- a/src/crewai/memory/entity/entity_memory.py
+++ b/src/crewai/memory/entity/entity_memory.py
@@ -30,7 +30,7 @@ class EntityMemory(Memory):
                 if storage
                 else RAGStorage(
                     type="entities",
-                    allow_reset=False,
+                    allow_reset=True,
                     embedder_config=embedder_config,
                     crew=crew,
                 )
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index d0f1cfc64..7af5fb554 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -51,8 +51,6 @@ class RAGStorage(BaseRAGStorage):
         self._initialize_app()
 
     def _set_embedder_config(self):
-        import chromadb.utils.embedding_functions as embedding_functions
-
         if self.embedder_config is None:
             self.embedder_config = self._create_default_embedding_function()
 
@@ -61,12 +59,20 @@ class RAGStorage(BaseRAGStorage):
             config = self.embedder_config.get("config", {})
             model_name = config.get("model")
             if provider == "openai":
-                self.embedder_config = embedding_functions.OpenAIEmbeddingFunction(
+                from chromadb.utils.embedding_functions.openai_embedding_function import (
+                    OpenAIEmbeddingFunction,
+                )
+
+                self.embedder_config = OpenAIEmbeddingFunction(
                     api_key=config.get("api_key") or os.getenv("OPENAI_API_KEY"),
                     model_name=model_name,
                 )
             elif provider == "azure":
-                self.embedder_config = embedding_functions.OpenAIEmbeddingFunction(
+                from chromadb.utils.embedding_functions.openai_embedding_function import (
+                    OpenAIEmbeddingFunction,
+                )
+
+                self.embedder_config = OpenAIEmbeddingFunction(
                     api_key=config.get("api_key"),
                     api_base=config.get("api_base"),
                     api_type=config.get("api_type", "azure"),
@@ -74,45 +80,55 @@ class RAGStorage(BaseRAGStorage):
                     model_name=model_name,
                 )
             elif provider == "ollama":
-                from openai import OpenAI
+                from chromadb.utils.embedding_functions.ollama_embedding_function import (
+                    OllamaEmbeddingFunction,
+                )
 
-                class OllamaEmbeddingFunction(EmbeddingFunction):
-                    def __call__(self, input: Documents) -> Embeddings:
-                        client = OpenAI(
-                            base_url="http://localhost:11434/v1",
-                            api_key=config.get("api_key", "ollama"),
-                        )
-                        try:
-                            response = client.embeddings.create(
-                                input=input, model=model_name
-                            )
-                            embeddings = [item.embedding for item in response.data]
-                            return cast(Embeddings, embeddings)
-                        except Exception as e:
-                            raise e
-
-                self.embedder_config = OllamaEmbeddingFunction()
+                self.embedder_config = OllamaEmbeddingFunction(
+                    url=config.get("url", "http://localhost:11434/api/embeddings"),
+                    model_name=model_name,
+                )
             elif provider == "vertexai":
-                self.embedder_config = (
-                    embedding_functions.GoogleVertexEmbeddingFunction(
-                        model_name=model_name,
-                        api_key=config.get("api_key"),
-                    )
+                from chromadb.utils.embedding_functions.google_embedding_function import (
+                    GoogleVertexEmbeddingFunction,
                 )
-            elif provider == "google":
-                self.embedder_config = (
-                    embedding_functions.GoogleGenerativeAiEmbeddingFunction(
-                        model_name=model_name,
-                        api_key=config.get("api_key"),
-                    )
-                )
-            elif provider == "cohere":
-                self.embedder_config = embedding_functions.CohereEmbeddingFunction(
+
+                self.embedder_config = GoogleVertexEmbeddingFunction(
                     model_name=model_name,
                     api_key=config.get("api_key"),
                 )
+            elif provider == "google":
+                from chromadb.utils.embedding_functions.google_embedding_function import (
+                    GoogleGenerativeAiEmbeddingFunction,
+                )
+
+                self.embedder_config = GoogleGenerativeAiEmbeddingFunction(
+                    model_name=model_name,
+                    api_key=config.get("api_key"),
+                )
+            elif provider == "cohere":
+                from chromadb.utils.embedding_functions.cohere_embedding_function import (
+                    CohereEmbeddingFunction,
+                )
+
+                self.embedder_config = CohereEmbeddingFunction(
+                    model_name=model_name,
+                    api_key=config.get("api_key"),
+                )
+            elif provider == "bedrock":
+                from chromadb.utils.embedding_functions.amazon_bedrock_embedding_function import (
+                    AmazonBedrockEmbeddingFunction,
+                )
+
+                self.embedder_config = AmazonBedrockEmbeddingFunction(
+                    session=config.get("session"),
+                )
             elif provider == "huggingface":
-                self.embedder_config = embedding_functions.HuggingFaceEmbeddingServer(
+                from chromadb.utils.embedding_functions.huggingface_embedding_function import (
+                    HuggingFaceEmbeddingServer,
+                )
+
+                self.embedder_config = HuggingFaceEmbeddingServer(
                     url=config.get("api_url"),
                 )
             elif provider == "watson":
@@ -253,8 +269,10 @@ class RAGStorage(BaseRAGStorage):
                 )
 
     def _create_default_embedding_function(self):
-        import chromadb.utils.embedding_functions as embedding_functions
+        from chromadb.utils.embedding_functions.openai_embedding_function import (
+            OpenAIEmbeddingFunction,
+        )
 
-        return embedding_functions.OpenAIEmbeddingFunction(
+        return OpenAIEmbeddingFunction(
             api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
         )
diff --git a/uv.lock b/uv.lock
index 844e0b862..f19648220 100644
--- a/uv.lock
+++ b/uv.lock
@@ -490,28 +490,32 @@ wheels = [
 
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 name = "chroma-hnswlib"
-version = "0.7.3"
+version = "0.7.6"
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 [[package]]
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-version = "0.4.24"
+version = "0.5.18"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "bcrypt" },
@@ -519,6 +523,7 @@ dependencies = [
     { name = "chroma-hnswlib" },
     { name = "fastapi" },
     { name = "grpcio" },
+    { name = "httpx" },
     { name = "importlib-resources" },
     { name = "kubernetes" },
     { name = "mmh3" },
@@ -531,11 +536,10 @@ dependencies = [
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     { name = "overrides" },
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-    { name = "pulsar-client" },
     { name = "pydantic" },
     { name = "pypika" },
     { name = "pyyaml" },
-    { name = "requests" },
+    { name = "rich" },
     { name = "tenacity" },
     { name = "tokenizers" },
     { name = "tqdm" },
@@ -543,9 +547,9 @@ dependencies = [
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 [[package]]
@@ -634,6 +638,9 @@ dependencies = [
 agentops = [
     { name = "agentops" },
 ]
+mem0 = [
+    { name = "mem0ai" },
+]
 tools = [
     { name = "crewai-tools" },
 ]
@@ -663,7 +670,7 @@ requires-dist = [
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     { name = "auth0-python", specifier = ">=4.7.1" },
-    { name = "chromadb", specifier = ">=0.4.24" },
+    { name = "chromadb", specifier = ">=0.5.18" },
     { name = "click", specifier = ">=8.1.7" },
     { name = "crewai-tools", specifier = ">=0.14.0" },
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@@ -672,6 +679,7 @@ requires-dist = [
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     { name = "langchain", specifier = ">=0.2.16" },
     { name = "litellm", specifier = ">=1.44.22" },
+    { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" },
     { name = "openai", specifier = ">=1.13.3" },
     { name = "opentelemetry-api", specifier = ">=1.22.0" },
     { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.22.0" },
@@ -889,7 +897,7 @@ wheels = [
 
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+version = "0.1.125"
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@@ -914,9 +922,9 @@ dependencies = [
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 ]
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@@ -2160,7 +2168,7 @@ wheels = [
 
 [[package]]
 name = "mem0ai"
-version = "0.1.22"
+version = "0.1.29"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -2170,9 +2178,9 @@ dependencies = [
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 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/a9/bf/152718f9da3844dd24d4c45850b2e719798b5ce9389adf4ec873ee8905ca/mem0ai-0.1.29.tar.gz", hash = "sha256:42adefb7a9b241be03fbcabadf5328abf91b4ac390bc97e5966e55e3cac192c5", size = 55201 }
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 version = "0.2.3"

From 8376698534b4c3012443760eb967b58fa43c111d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Sun, 17 Nov 2024 04:07:21 -0300
Subject: [PATCH 064/126] preparing enw version

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 uv.lock                                                 | 2 +-
 8 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 57868636f..5955baf33 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.79.4"
+version = "0.80.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 8d01b7cb5..fbad09663 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,5 +14,5 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.79.4"
+__version__ = "0.80.0"
 __all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 8606a2134..a5ab36877 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.4,<1.0.0"
+    "crewai[tools]>=0.80.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 69e26f220..e863f20b7 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.4,<1.0.0",
+    "crewai[tools]>=0.80.0,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index b09ce842f..60294740d 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.79.4,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.80.0,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 16d6360db..7c022b1f7 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.4,<1.0.0"
+    "crewai[tools]>=0.80.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index dc928ad1e..4142c325d 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.79.4"
+    "crewai[tools]>=0.80.0"
 ]
 
diff --git a/uv.lock b/uv.lock
index f19648220..ab78a63d0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -608,7 +608,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.79.4"
+version = "0.80.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 0b9092702bc39f2f8bf823fa3543b9056404e5f4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Mon, 18 Nov 2024 00:21:19 -0300
Subject: [PATCH 065/126] adding before and after crew

---
 .gitignore                                    |   4 +
 src/crewai/project/__init__.py                |   4 +
 src/crewai/project/annotations.py             |  10 +
 src/crewai/project/crew_base.py               |  58 +-
 .../test_after_crew_modification.yaml         | 449 ++++++++++++++
 .../test_before_crew_modification.yaml        | 445 ++++++++++++++
 .../test_before_crew_with_none_input.yaml     | 438 ++++++++++++++
 .../cassettes/test_crew_execution_order.yaml  | 450 ++++++++++++++
 .../test_multiple_before_after_crew.yaml      | 565 ++++++++++++++++++
 tests/config/agents.yaml                      |  21 +
 tests/config/tasks.yaml                       |  17 +
 tests/project_test.py                         | 172 +++++-
 12 files changed, 2624 insertions(+), 9 deletions(-)
 create mode 100644 tests/cassettes/test_after_crew_modification.yaml
 create mode 100644 tests/cassettes/test_before_crew_modification.yaml
 create mode 100644 tests/cassettes/test_before_crew_with_none_input.yaml
 create mode 100644 tests/cassettes/test_crew_execution_order.yaml
 create mode 100644 tests/cassettes/test_multiple_before_after_crew.yaml
 create mode 100644 tests/config/agents.yaml
 create mode 100644 tests/config/tasks.yaml

diff --git a/.gitignore b/.gitignore
index ad64db4e7..8559a290c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -17,3 +17,7 @@ rc-tests/*
 temp/*
 .vscode/*
 crew_tasks_output.json
+.codesight
+.mypy_cache
+.ruff_cache
+.venv
diff --git a/src/crewai/project/__init__.py b/src/crewai/project/__init__.py
index 34759f465..1dbb6e41b 100644
--- a/src/crewai/project/__init__.py
+++ b/src/crewai/project/__init__.py
@@ -9,6 +9,8 @@ from .annotations import (
     pipeline,
     task,
     tool,
+    before_crew,
+    after_crew,
 )
 from .crew_base import CrewBase
 from .pipeline_base import PipelineBase
@@ -26,4 +28,6 @@ __all__ = [
     "llm",
     "cache_handler",
     "pipeline",
+    "before_crew",
+    "after_crew",
 ]
diff --git a/src/crewai/project/annotations.py b/src/crewai/project/annotations.py
index 6c0b9942a..c1a497fa1 100644
--- a/src/crewai/project/annotations.py
+++ b/src/crewai/project/annotations.py
@@ -5,6 +5,16 @@ from crewai import Crew
 from crewai.project.utils import memoize
 
 
+def before_crew(func):
+    func.is_before_crew = True
+    return func
+
+
+def after_crew(func):
+    func.is_after_crew = True
+    return func
+
+
 def task(func):
     func.is_task = True
 
diff --git a/src/crewai/project/crew_base.py b/src/crewai/project/crew_base.py
index a420c4dd2..ed48b24d1 100644
--- a/src/crewai/project/crew_base.py
+++ b/src/crewai/project/crew_base.py
@@ -34,18 +34,39 @@ def CrewBase(cls: T) -> T:
             self.map_all_agent_variables()
             self.map_all_task_variables()
 
-            # Preserve task and agent information
-            self._original_tasks = {
+            # Preserve all decorated functions
+            self._original_functions = {
                 name: method
                 for name, method in cls.__dict__.items()
-                if hasattr(method, "is_task") and method.is_task
-            }
-            self._original_agents = {
-                name: method
-                for name, method in cls.__dict__.items()
-                if hasattr(method, "is_agent") and method.is_agent
+                if any(
+                    hasattr(method, attr)
+                    for attr in [
+                        "is_task",
+                        "is_agent",
+                        "is_before_crew",
+                        "is_after_crew",
+                        "is_kickoff",
+                    ]
+                )
             }
 
+            # Store specific function types
+            self._original_tasks = self._filter_functions(
+                self._original_functions, "is_task"
+            )
+            self._original_agents = self._filter_functions(
+                self._original_functions, "is_agent"
+            )
+            self._before_crew = self._filter_functions(
+                self._original_functions, "is_before_crew"
+            )
+            self._after_crew = self._filter_functions(
+                self._original_functions, "is_after_crew"
+            )
+            self._kickoff = self._filter_functions(
+                self._original_functions, "is_kickoff"
+            )
+
         @staticmethod
         def load_yaml(config_path: Path):
             try:
@@ -192,4 +213,25 @@ def CrewBase(cls: T) -> T:
                     callback_functions[callback]() for callback in callbacks
                 ]
 
+        def kickoff(self, inputs=None):
+            # Execute before_crew functions and allow them to modify inputs
+            for _, func in self._before_crew.items():
+                modified_inputs = func(self, inputs)
+                if modified_inputs is not None:
+                    inputs = modified_inputs
+
+            # Get the crew instance
+            crew_instance = self.crew()
+
+            # Execute the crew's tasks
+            result = crew_instance.kickoff(inputs=inputs)
+
+            # Execute after_crew functions and allow them to modify the output
+            for _, func in self._after_crew.items():
+                modified_result = func(self, result)
+                if modified_result is not None:
+                    result = modified_result
+
+            return result
+
     return cast(T, WrappedClass)
diff --git a/tests/cassettes/test_after_crew_modification.yaml b/tests/cassettes/test_after_crew_modification.yaml
new file mode 100644
index 000000000..e9d6926b0
--- /dev/null
+++ b/tests/cassettes/test_after_crew_modification.yaml
@@ -0,0 +1,449 @@
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diff --git a/tests/config/agents.yaml b/tests/config/agents.yaml
new file mode 100644
index 000000000..84e8ef3cc
--- /dev/null
+++ b/tests/config/agents.yaml
@@ -0,0 +1,21 @@
+researcher:
+  role: >
+    {topic} Senior Data Researcher
+  goal: >
+    Uncover cutting-edge developments in {topic}
+  backstory: >
+    You're a seasoned researcher with a knack for uncovering the latest
+    developments in {topic}. Known for your ability to find the most relevant
+    information and present it in a clear and concise manner.
+  verbose: true
+
+reporting_analyst:
+  role: >
+    {topic} Reporting Analyst
+  goal: >
+    Create detailed reports based on {topic} data analysis and research findings
+  backstory: >
+    You're a meticulous analyst with a keen eye for detail. You're known for
+    your ability to turn complex data into clear and concise reports, making
+    it easy for others to understand and act on the information you provide.
+  verbose: true
\ No newline at end of file
diff --git a/tests/config/tasks.yaml b/tests/config/tasks.yaml
new file mode 100644
index 000000000..f30820855
--- /dev/null
+++ b/tests/config/tasks.yaml
@@ -0,0 +1,17 @@
+research_task:
+  description: >
+    Conduct a thorough research about {topic}
+    Make sure you find any interesting and relevant information given
+    the current year is 2024.
+  expected_output: >
+    A list with 10 bullet points of the most relevant information about {topic}
+  agent: researcher
+
+reporting_task:
+  description: >
+    Review the context you got and expand each topic into a full section for a report.
+    Make sure the report is detailed and contains any and all relevant information.
+  expected_output: >
+    A fully fledge reports with the mains topics, each with a full section of information.
+    Formatted as markdown without '```'
+  agent: reporting_analyst
diff --git a/tests/project_test.py b/tests/project_test.py
index 188ba024d..329886a25 100644
--- a/tests/project_test.py
+++ b/tests/project_test.py
@@ -1,6 +1,9 @@
 from crewai.agent import Agent
-from crewai.project import agent, task
+from crewai.project import agent, task, before_crew, after_crew, crew
+from crewai.project import CrewBase
 from crewai.task import Task
+from crewai.crew import Crew
+import pytest
 
 
 class SimpleCrew:
@@ -23,6 +26,43 @@ class SimpleCrew:
         )
 
 
+@CrewBase
+class TestCrew:
+    agents_config = "config/agents.yaml"
+    tasks_config = "config/tasks.yaml"
+
+    @agent
+    def researcher(self):
+        return Agent(config=self.agents_config["researcher"])
+
+    @agent
+    def reporting_analyst(self):
+        return Agent(config=self.agents_config["reporting_analyst"])
+
+    @task
+    def research_task(self):
+        return Task(config=self.tasks_config["research_task"])
+
+    @task
+    def reporting_task(self):
+        return Task(config=self.tasks_config["reporting_task"])
+
+    @before_crew
+    def modify_inputs(self, inputs):
+        if inputs:
+            inputs["topic"] = "Bicycles"
+        return inputs
+
+    @after_crew
+    def modify_outputs(self, outputs):
+        outputs.raw = outputs.raw + " post processed"
+        return outputs
+
+    @crew
+    def crew(self):
+        return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
+
+
 def test_agent_memoization():
     crew = SimpleCrew()
     first_call_result = crew.simple_agent()
@@ -53,3 +93,133 @@ def test_task_name():
     assert (
         custom_named_task.name == "Custom"
     ), "Custom task name is not being set as expected"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_before_crew_modification():
+    crew = TestCrew()
+    inputs = {"topic": "LLMs"}
+    result = crew.kickoff(inputs=inputs)
+    print(result.raw)
+    assert "bicycles" in result.raw, "Before crew function did not modify inputs"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_after_crew_modification():
+    crew = TestCrew()
+    # Assuming the crew execution returns a dict
+    result = crew.kickoff({"topic": "LLMs"})
+
+    assert "post processed" in result.raw, "After crew function did not modify outputs"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_before_crew_with_none_input():
+    crew = TestCrew()
+    crew.crew().kickoff(None)
+    # Test should pass without raising exceptions
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_multiple_before_after_crew():
+    @CrewBase
+    class MultipleHooksCrew:
+        agents_config = "config/agents.yaml"
+        tasks_config = "config/tasks.yaml"
+
+        @agent
+        def researcher(self):
+            return Agent(config=self.agents_config["researcher"])
+
+        @agent
+        def reporting_analyst(self):
+            return Agent(config=self.agents_config["reporting_analyst"])
+
+        @task
+        def research_task(self):
+            return Task(config=self.tasks_config["research_task"])
+
+        @task
+        def reporting_task(self):
+            return Task(config=self.tasks_config["reporting_task"])
+
+        @before_crew
+        def first_before(self, inputs):
+            inputs["topic"] = "Bicycles"
+            return inputs
+
+        @before_crew
+        def second_before(self, inputs):
+            inputs["topic"] = "plants"
+            return inputs
+
+        @after_crew
+        def first_after(self, outputs):
+            outputs.raw = outputs.raw + " processed first"
+            return outputs
+
+        @after_crew
+        def second_after(self, outputs):
+            outputs.raw = outputs.raw + " processed second"
+            return outputs
+
+        @crew
+        def crew(self):
+            return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
+
+    crew = MultipleHooksCrew()
+    result = crew.kickoff({"topic": "LLMs"})
+
+    assert "plants" in result.raw, "First before_crew not executed"
+    assert "processed first" in result.raw, "First after_crew not executed"
+    assert "processed second" in result.raw, "Second after_crew not executed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_execution_order():
+    execution_order = []
+
+    @CrewBase
+    class OrderTestCrew:
+        agents_config = "config/agents.yaml"
+        tasks_config = "config/tasks.yaml"
+
+        @agent
+        def researcher(self):
+            return Agent(config=self.agents_config["researcher"])
+
+        @agent
+        def reporting_analyst(self):
+            return Agent(config=self.agents_config["reporting_analyst"])
+
+        @task
+        def research_task(self):
+            execution_order.append("task")
+            return Task(config=self.tasks_config["research_task"])
+
+        @task
+        def reporting_task(self):
+            return Task(config=self.tasks_config["reporting_task"])
+
+        @before_crew
+        def before(self, inputs):
+            execution_order.append("before")
+            return inputs
+
+        @after_crew
+        def after(self, outputs):
+            execution_order.append("after")
+            return outputs
+
+        @crew
+        def crew(self):
+            return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
+
+    crew = OrderTestCrew()
+    crew.kickoff({"topic": "LLMs"})
+
+    assert execution_order == [
+        "before",
+        "task",
+        "after",
+    ], "Crew execution order is incorrect"

From 55e968c9e0ba0e4bfb716e5827550156a13681b0 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Tue, 19 Nov 2024 17:42:54 -0500
Subject: [PATCH 066/126] Update CLI Watson supported models + docs (#1628)

---
 docs/concepts/llms.mdx      |  2 ++
 src/crewai/cli/constants.py | 23 ++++++++---------------
 2 files changed, 10 insertions(+), 15 deletions(-)

diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 5757feca3..5211e6652 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -47,6 +47,8 @@ researcher:
     # llm: ollama/llama3:70b
     # llm: groq/llama-3.2-90b-vision-preview
     # llm: watsonx/meta-llama/llama-3-1-70b-instruct
+    # llm: nvidia_nim/meta/llama3-70b-instruct
+    # llm: sambanova/Meta-Llama-3.1-8B-Instruct
     # ...
 ```
 
diff --git a/src/crewai/cli/constants.py b/src/crewai/cli/constants.py
index 4be08fa2a..e13349155 100644
--- a/src/crewai/cli/constants.py
+++ b/src/crewai/cli/constants.py
@@ -123,21 +123,14 @@ MODELS = {
     ],
     "ollama": ["ollama/llama3.1", "ollama/mixtral"],
     "watson": [
-        "watsonx/google/flan-t5-xxl",
-        "watsonx/google/flan-ul2",
-        "watsonx/bigscience/mt0-xxl",
-        "watsonx/eleutherai/gpt-neox-20b",
-        "watsonx/ibm/mpt-7b-instruct2",
-        "watsonx/bigcode/starcoder",
-        "watsonx/meta-llama/llama-2-70b-chat",
-        "watsonx/meta-llama/llama-2-13b-chat",
-        "watsonx/ibm/granite-13b-instruct-v1",
-        "watsonx/ibm/granite-13b-chat-v1",
-        "watsonx/google/flan-t5-xl",
-        "watsonx/ibm/granite-13b-chat-v2",
-        "watsonx/ibm/granite-13b-instruct-v2",
-        "watsonx/elyza/elyza-japanese-llama-2-7b-instruct",
-        "watsonx/ibm-mistralai/mixtral-8x7b-instruct-v01-q",
+        "watsonx/meta-llama/llama-3-1-70b-instruct",
+        "watsonx/meta-llama/llama-3-1-8b-instruct",
+        "watsonx/meta-llama/llama-3-2-11b-vision-instruct",
+        "watsonx/meta-llama/llama-3-2-1b-instruct",
+        "watsonx/meta-llama/llama-3-2-90b-vision-instruct",
+        "watsonx/meta-llama/llama-3-405b-instruct",
+        "watsonx/mistral/mistral-large",
+        "watsonx/ibm/granite-3-8b-instruct",
     ],
     "bedrock": [
         "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",

From 58af5c08f9f3f01c1c2120c85dc36aafb879a97f Mon Sep 17 00:00:00 2001
From: theCyberTech <84775494+theCyberTech@users.noreply.github.com>
Date: Wed, 20 Nov 2024 19:23:09 +0800
Subject: [PATCH 067/126] docs: add gh_token documentation to GithubSearchTool

---
 docs/tools/githubsearchtool.mdx | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/docs/tools/githubsearchtool.mdx b/docs/tools/githubsearchtool.mdx
index 6fd0e686a..80b363a3c 100644
--- a/docs/tools/githubsearchtool.mdx
+++ b/docs/tools/githubsearchtool.mdx
@@ -34,6 +34,7 @@ from crewai_tools import GithubSearchTool
 # Initialize the tool for semantic searches within a specific GitHub repository
 tool = GithubSearchTool(
 	github_repo='https://github.com/example/repo',
+	gh_token='your_github_personal_access_token',
 	content_types=['code', 'issue'] # Options: code, repo, pr, issue
 )
 
@@ -41,6 +42,7 @@ tool = GithubSearchTool(
 
 # Initialize the tool for semantic searches within a specific GitHub repository, so the agent can search any repository if it learns about during its execution
 tool = GithubSearchTool(
+	gh_token='your_github_personal_access_token',
 	content_types=['code', 'issue'] # Options: code, repo, pr, issue
 )
 ```
@@ -48,6 +50,7 @@ tool = GithubSearchTool(
 ## Arguments
 
 - `github_repo` : The URL of the GitHub repository where the search will be conducted. This is a mandatory field and specifies the target repository for your search.
+- `gh_token` : Your GitHub Personal Access Token (PAT) required for authentication. You can create one in your GitHub account settings under Developer Settings > Personal Access Tokens.
 - `content_types` : Specifies the types of content to include in your search. You must provide a list of content types from the following options: `code` for searching within the code, 
 `repo` for searching within the repository's general information, `pr` for searching within pull requests, and `issue` for searching within issues. 
 This field is mandatory and allows tailoring the search to specific content types within the GitHub repository.
@@ -77,5 +80,4 @@ tool = GithubSearchTool(
             ),
         ),
     )
-)
-```
\ No newline at end of file
+)
\ No newline at end of file

From 3e003f5e3209e0ce815b0a0214c56fd6c830e861 Mon Sep 17 00:00:00 2001
From: Gui Vieira <guilherme_vieira@me.com>
Date: Wed, 20 Nov 2024 10:06:49 -0300
Subject: [PATCH 068/126] Move kickoff callbacks to crew's domain

---
 src/crewai/crew.py                            |  22 +-
 src/crewai/project/__init__.py                |   8 +-
 src/crewai/project/annotations.py             |  25 +-
 src/crewai/project/crew_base.py               |  33 +-
 .../cassettes/test_crew_execution_order.yaml  | 450 ------------------
 tests/project_test.py                         | 109 ++---
 6 files changed, 82 insertions(+), 565 deletions(-)
 delete mode 100644 tests/cassettes/test_crew_execution_order.yaml

diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 04820adf8..fb03acb5b 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -5,7 +5,7 @@ import uuid
 import warnings
 from concurrent.futures import Future
 from hashlib import md5
-from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
 
 from pydantic import (
     UUID4,
@@ -36,9 +36,7 @@ from crewai.telemetry import Telemetry
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
-from crewai.utilities.constants import (
-    TRAINING_DATA_FILE,
-)
+from crewai.utilities.constants import TRAINING_DATA_FILE
 from crewai.utilities.evaluators.crew_evaluator_handler import CrewEvaluator
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
 from crewai.utilities.formatter import (
@@ -165,6 +163,16 @@ class Crew(BaseModel):
         default=None,
         description="Callback to be executed after each task for all agents execution.",
     )
+    before_kickoff_callbacks: List[
+        Callable[[Optional[Dict[str, Any]]], Optional[Dict[str, Any]]]
+    ] = Field(
+        default_factory=list,
+        description="List of callbacks to be executed before crew kickoff. It may be used to adjust inputs before the crew is executed.",
+    )
+    after_kickoff_callbacks: List[Callable[[CrewOutput], CrewOutput]] = Field(
+        default_factory=list,
+        description="List of callbacks to be executed after crew kickoff. It may be used to adjust the output of the crew.",
+    )
     max_rpm: Optional[int] = Field(
         default=None,
         description="Maximum number of requests per minute for the crew execution to be respected.",
@@ -478,6 +486,9 @@ class Crew(BaseModel):
         self,
         inputs: Optional[Dict[str, Any]] = None,
     ) -> CrewOutput:
+        for callback in self.before_kickoff_callbacks:
+            inputs = callback(inputs)
+
         """Starts the crew to work on its assigned tasks."""
         self._execution_span = self._telemetry.crew_execution_span(self, inputs)
         self._task_output_handler.reset()
@@ -520,6 +531,9 @@ class Crew(BaseModel):
                 f"The process '{self.process}' is not implemented yet."
             )
 
+        for callback in self.after_kickoff_callbacks:
+            result = callback(result)
+
         metrics += [agent._token_process.get_summary() for agent in self.agents]
 
         self.usage_metrics = UsageMetrics()
diff --git a/src/crewai/project/__init__.py b/src/crewai/project/__init__.py
index 1dbb6e41b..25f6f5e04 100644
--- a/src/crewai/project/__init__.py
+++ b/src/crewai/project/__init__.py
@@ -1,5 +1,7 @@
 from .annotations import (
+    after_kickoff,
     agent,
+    before_kickoff,
     cache_handler,
     callback,
     crew,
@@ -9,8 +11,6 @@ from .annotations import (
     pipeline,
     task,
     tool,
-    before_crew,
-    after_crew,
 )
 from .crew_base import CrewBase
 from .pipeline_base import PipelineBase
@@ -28,6 +28,6 @@ __all__ = [
     "llm",
     "cache_handler",
     "pipeline",
-    "before_crew",
-    "after_crew",
+    "before_kickoff",
+    "after_kickoff",
 ]
diff --git a/src/crewai/project/annotations.py b/src/crewai/project/annotations.py
index c1a497fa1..83e396a4c 100644
--- a/src/crewai/project/annotations.py
+++ b/src/crewai/project/annotations.py
@@ -5,13 +5,13 @@ from crewai import Crew
 from crewai.project.utils import memoize
 
 
-def before_crew(func):
-    func.is_before_crew = True
+def before_kickoff(func):
+    func.is_before_kickoff = True
     return func
 
 
-def after_crew(func):
-    func.is_after_crew = True
+def after_kickoff(func):
+    func.is_after_kickoff = True
     return func
 
 
@@ -109,6 +109,19 @@ def crew(func) -> Callable[..., Crew]:
         self.agents = instantiated_agents
         self.tasks = instantiated_tasks
 
-        return func(self, *args, **kwargs)
+        crew = func(self, *args, **kwargs)
 
-    return wrapper
+        def callback_wrapper(callback, instance):
+            def wrapper(*args, **kwargs):
+                return callback(instance, *args, **kwargs)
+
+            return wrapper
+
+        for _, callback in self._before_kickoff.items():
+            crew.before_kickoff_callbacks.append(callback_wrapper(callback, self))
+        for _, callback in self._after_kickoff.items():
+            crew.after_kickoff_callbacks.append(callback_wrapper(callback, self))
+
+        return crew
+
+    return memoize(wrapper)
diff --git a/src/crewai/project/crew_base.py b/src/crewai/project/crew_base.py
index ed48b24d1..e93452a6e 100644
--- a/src/crewai/project/crew_base.py
+++ b/src/crewai/project/crew_base.py
@@ -43,8 +43,8 @@ def CrewBase(cls: T) -> T:
                     for attr in [
                         "is_task",
                         "is_agent",
-                        "is_before_crew",
-                        "is_after_crew",
+                        "is_before_kickoff",
+                        "is_after_kickoff",
                         "is_kickoff",
                     ]
                 )
@@ -57,11 +57,11 @@ def CrewBase(cls: T) -> T:
             self._original_agents = self._filter_functions(
                 self._original_functions, "is_agent"
             )
-            self._before_crew = self._filter_functions(
-                self._original_functions, "is_before_crew"
+            self._before_kickoff = self._filter_functions(
+                self._original_functions, "is_before_kickoff"
             )
-            self._after_crew = self._filter_functions(
-                self._original_functions, "is_after_crew"
+            self._after_kickoff = self._filter_functions(
+                self._original_functions, "is_after_kickoff"
             )
             self._kickoff = self._filter_functions(
                 self._original_functions, "is_kickoff"
@@ -213,25 +213,4 @@ def CrewBase(cls: T) -> T:
                     callback_functions[callback]() for callback in callbacks
                 ]
 
-        def kickoff(self, inputs=None):
-            # Execute before_crew functions and allow them to modify inputs
-            for _, func in self._before_crew.items():
-                modified_inputs = func(self, inputs)
-                if modified_inputs is not None:
-                    inputs = modified_inputs
-
-            # Get the crew instance
-            crew_instance = self.crew()
-
-            # Execute the crew's tasks
-            result = crew_instance.kickoff(inputs=inputs)
-
-            # Execute after_crew functions and allow them to modify the output
-            for _, func in self._after_crew.items():
-                modified_result = func(self, result)
-                if modified_result is not None:
-                    result = modified_result
-
-            return result
-
     return cast(T, WrappedClass)
diff --git a/tests/cassettes/test_crew_execution_order.yaml b/tests/cassettes/test_crew_execution_order.yaml
deleted file mode 100644
index 5f05a3258..000000000
--- a/tests/cassettes/test_crew_execution_order.yaml
+++ /dev/null
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diff --git a/tests/project_test.py b/tests/project_test.py
index 329886a25..6c68f4993 100644
--- a/tests/project_test.py
+++ b/tests/project_test.py
@@ -1,10 +1,10 @@
-from crewai.agent import Agent
-from crewai.project import agent, task, before_crew, after_crew, crew
-from crewai.project import CrewBase
-from crewai.task import Task
-from crewai.crew import Crew
 import pytest
 
+from crewai.agent import Agent
+from crewai.crew import Crew
+from crewai.project import CrewBase, after_kickoff, agent, before_kickoff, crew, task
+from crewai.task import Task
+
 
 class SimpleCrew:
     @agent
@@ -47,13 +47,13 @@ class TestCrew:
     def reporting_task(self):
         return Task(config=self.tasks_config["reporting_task"])
 
-    @before_crew
+    @before_kickoff
     def modify_inputs(self, inputs):
         if inputs:
             inputs["topic"] = "Bicycles"
         return inputs
 
-    @after_crew
+    @after_kickoff
     def modify_outputs(self, outputs):
         outputs.raw = outputs.raw + " post processed"
         return outputs
@@ -83,6 +83,16 @@ def test_task_memoization():
     ), "Task memoization is not working as expected"
 
 
+def test_crew_memoization():
+    crew = TestCrew()
+    first_call_result = crew.crew()
+    second_call_result = crew.crew()
+
+    assert (
+        first_call_result is second_call_result
+    ), "Crew references should point to the same object"
+
+
 def test_task_name():
     simple_task = SimpleCrew().simple_task()
     assert (
@@ -96,32 +106,33 @@ def test_task_name():
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_before_crew_modification():
+def test_before_kickoff_modification():
     crew = TestCrew()
     inputs = {"topic": "LLMs"}
-    result = crew.kickoff(inputs=inputs)
-    print(result.raw)
-    assert "bicycles" in result.raw, "Before crew function did not modify inputs"
+    result = crew.crew().kickoff(inputs=inputs)
+    assert "bicycles" in result.raw, "Before kickoff function did not modify inputs"
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_after_crew_modification():
+def test_after_kickoff_modification():
     crew = TestCrew()
     # Assuming the crew execution returns a dict
-    result = crew.kickoff({"topic": "LLMs"})
+    result = crew.crew().kickoff({"topic": "LLMs"})
 
-    assert "post processed" in result.raw, "After crew function did not modify outputs"
+    assert (
+        "post processed" in result.raw
+    ), "After kickoff function did not modify outputs"
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_before_crew_with_none_input():
+def test_before_kickoff_with_none_input():
     crew = TestCrew()
     crew.crew().kickoff(None)
     # Test should pass without raising exceptions
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_multiple_before_after_crew():
+def test_multiple_before_after_kickoff():
     @CrewBase
     class MultipleHooksCrew:
         agents_config = "config/agents.yaml"
@@ -143,22 +154,22 @@ def test_multiple_before_after_crew():
         def reporting_task(self):
             return Task(config=self.tasks_config["reporting_task"])
 
-        @before_crew
+        @before_kickoff
         def first_before(self, inputs):
             inputs["topic"] = "Bicycles"
             return inputs
 
-        @before_crew
+        @before_kickoff
         def second_before(self, inputs):
             inputs["topic"] = "plants"
             return inputs
 
-        @after_crew
+        @after_kickoff
         def first_after(self, outputs):
             outputs.raw = outputs.raw + " processed first"
             return outputs
 
-        @after_crew
+        @after_kickoff
         def second_after(self, outputs):
             outputs.raw = outputs.raw + " processed second"
             return outputs
@@ -168,58 +179,8 @@ def test_multiple_before_after_crew():
             return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
 
     crew = MultipleHooksCrew()
-    result = crew.kickoff({"topic": "LLMs"})
+    result = crew.crew().kickoff({"topic": "LLMs"})
 
-    assert "plants" in result.raw, "First before_crew not executed"
-    assert "processed first" in result.raw, "First after_crew not executed"
-    assert "processed second" in result.raw, "Second after_crew not executed"
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_crew_execution_order():
-    execution_order = []
-
-    @CrewBase
-    class OrderTestCrew:
-        agents_config = "config/agents.yaml"
-        tasks_config = "config/tasks.yaml"
-
-        @agent
-        def researcher(self):
-            return Agent(config=self.agents_config["researcher"])
-
-        @agent
-        def reporting_analyst(self):
-            return Agent(config=self.agents_config["reporting_analyst"])
-
-        @task
-        def research_task(self):
-            execution_order.append("task")
-            return Task(config=self.tasks_config["research_task"])
-
-        @task
-        def reporting_task(self):
-            return Task(config=self.tasks_config["reporting_task"])
-
-        @before_crew
-        def before(self, inputs):
-            execution_order.append("before")
-            return inputs
-
-        @after_crew
-        def after(self, outputs):
-            execution_order.append("after")
-            return outputs
-
-        @crew
-        def crew(self):
-            return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
-
-    crew = OrderTestCrew()
-    crew.kickoff({"topic": "LLMs"})
-
-    assert execution_order == [
-        "before",
-        "task",
-        "after",
-    ], "Crew execution order is incorrect"
+    assert "plants" in result.raw, "First before_kickoff not executed"
+    assert "processed first" in result.raw, "First after_kickoff not executed"
+    assert "processed second" in result.raw, "Second after_kickoff not executed"

From 495c3859af015b970c7c478946769ae18983de17 Mon Sep 17 00:00:00 2001
From: Gui Vieira <guilherme_vieira@me.com>
Date: Wed, 20 Nov 2024 10:26:00 -0300
Subject: [PATCH 069/126] Cassettes

---
 .../test_after_kickoff_modification.yaml      | 487 +++++++++++++++++
 .../test_before_kickoff_modification.yaml     | 500 ++++++++++++++++++
 .../test_before_kickoff_with_none_input.yaml  | 492 +++++++++++++++++
 .../test_multiple_before_after_kickoff.yaml   | 495 +++++++++++++++++
 4 files changed, 1974 insertions(+)
 create mode 100644 tests/cassettes/test_after_kickoff_modification.yaml
 create mode 100644 tests/cassettes/test_before_kickoff_modification.yaml
 create mode 100644 tests/cassettes/test_before_kickoff_with_none_input.yaml
 create mode 100644 tests/cassettes/test_multiple_before_after_kickoff.yaml

diff --git a/tests/cassettes/test_after_kickoff_modification.yaml b/tests/cassettes/test_after_kickoff_modification.yaml
new file mode 100644
index 000000000..bf63b910d
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+      conditions, such as droughts, floods, and extreme temperatures. This initiative
+      aims to empower farmers with viable options to adapt to shifting climate patterns,
+      ensuring stable crop yields despite adverse environmental conditions. The development
+      of these climate-resilient plants is vital for maintaining food supply chains
+      and safeguarding agricultural biodiversity, ultimately contributing to the long-term
+      sustainability of farming practices.\\n\\n## 5. Edible Vaccines in Plants\\nInnovative
+      research in the area of edible vaccines is making significant strides in 2024.
+      Scientists are exploring the potential of genetically engineered plants to express
+      specific antigens that can serve as immunizations. These advancements hold promising
+      implications for public health, particularly in developing regions where traditional
+      vaccine delivery systems may be less feasible. Edible vaccines offer a cost-effective,
+      accessible, and non-invasive way to promote immunity against various diseases,
+      highlighting the intersection of agriculture and health science in addressing
+      global health challenges.\\n\\n## 6. Fungi and Plant Collaborations\\nThe symbiotic
+      relationships between mycorrhizal fungi and plants have gained increasing attention
+      in research circles. Studies conducted in 2024 reveal that these fungi enhance
+      nutrient uptake, improve soil health, and bolster plant resilience when faced
+      with environmental stressors, such as drought and soil degradation. The incorporation
+      of these beneficial fungi into sustainable agricultural practices not only promotes
+      plant health but also contributes to organic farming resiliency, highlighting
+      the importance of understanding and utilizing biological partnerships in cultivating
+      healthy crops.\\n\\n## 7. Biophilic Design\\nThe concept of biophilic design
+      continues to gain traction in architecture and urban planning throughout 2024,
+      underscoring the importance of integrating nature into built environments. This
+      approach encourages the incorporation of plants and green spaces into architectural
+      designs, enhancing air quality and promoting mental well-being. By reducing
+      reliance on artificial heating and cooling systems, biophilic design offers
+      opportunities to lower overall energy consumption. As cities recognize the benefits
+      of urban greenery, significant investments are being made to create healthier,
+      more sustainable urban ecosystems.\\n\\n## 8. Deciduous Trees and Urban Cooling\\nResearch
+      conducted this year has demonstrated that strategic planting of deciduous trees
+      in urban areas can lead to significant temperature reductions. These trees act
+      as natural air conditioners by providing shade and releasing moisture. The benefits
+      extend beyond cooling cities\u2014for instance, they contribute to lower energy
+      consumption for air conditioning, enhance local biodiversity, and improve overall
+      urban livability. Understanding the role of green infrastructure in combating
+      urban heat islands is essential for developing climate-responsive cities.\\n\\n##
+      9. Carnivorous Plant Studies\\nRecent advancements in the study of carnivorous
+      plants reveal exciting potential applications in sustainable pest control and
+      agriculture. By understanding their unique adaptations and natural predatory
+      methods, researchers envision the use of these plants as biological pest management
+      tools in crop production. In 2024, interest in harnessing the ecological roles
+      of these plants may lead to more sustainable farming practices, alleviating
+      the need for chemical pesticides and promoting healthier ecosystems.\\n\\n##
+      10. Smart Agriculture Technology\\nThe integration of Internet of Things (IoT)
+      and Artificial Intelligence (AI) into agriculture has transformed how farming
+      is conducted in 2024. Smart agriculture technologies enable farmers to monitor
+      plant health, soil conditions, and microclimates through advanced sensors and
+      data analytics. This real-time data helps optimize water usage, elevate crop
+      yields, and foster sustainable farming practices. As farmers harness these technological
+      advancements, the sector moves toward a more efficient and environmentally conscious
+      model of production.\\n\\nIn conclusion, these insights reflect ongoing research
+      and innovation in the field of plant science, laying the groundwork for more
+      sustainable and resilient agricultural practices. As the world faces critical
+      global challenges, these advancements illustrate the potential to leverage plant
+      science in creating solutions that address both environmental concerns and food
+      security.\",\n        \"refusal\": null\n      },\n      \"logprobs\": null,\n
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+    headers:
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+      - DYNAMIC
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+      - 8e58a67f18856225-GRU
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+      - gzip
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+      - application/json
+      Date:
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+      Server:
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+      - nosniff
+      access-control-expose-headers:
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+      alt-svc:
+      - h3=":443"; ma=86400
+      openai-organization:
+      - crewai-iuxna1
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+      - '20960'
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+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      x-ratelimit-limit-requests:
+      - '30000'
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+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
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+    http_version: HTTP/1.1
+    status_code: 200
+version: 1

From 6774bc2c53d6a81acf104be9ad6e82f4beb5a543 Mon Sep 17 00:00:00 2001
From: Gui Vieira <guilherme_vieira@me.com>
Date: Wed, 20 Nov 2024 16:08:08 -0300
Subject: [PATCH 070/126] Make mypy happy

---
 src/crewai/crew.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index fb03acb5b..7f5539976 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -486,8 +486,8 @@ class Crew(BaseModel):
         self,
         inputs: Optional[Dict[str, Any]] = None,
     ) -> CrewOutput:
-        for callback in self.before_kickoff_callbacks:
-            inputs = callback(inputs)
+        for before_callback in self.before_kickoff_callbacks:
+            inputs = before_callback(inputs)
 
         """Starts the crew to work on its assigned tasks."""
         self._execution_span = self._telemetry.crew_execution_span(self, inputs)
@@ -531,8 +531,8 @@ class Crew(BaseModel):
                 f"The process '{self.process}' is not implemented yet."
             )
 
-        for callback in self.after_kickoff_callbacks:
-            result = callback(result)
+        for after_callback in self.after_kickoff_callbacks:
+            result = after_callback(result)
 
         metrics += [agent._token_process.get_summary() for agent in self.agents]
 

From 14a36d3f5efef6772bce705955a2a024f7afa74c Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 20 Nov 2024 18:40:08 -0500
Subject: [PATCH 071/126] Knowledge (#1567)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* initial knowledge

* WIP

* Adding core knowledge sources

* Improve types and better support for file paths

* added additional sources

* fix linting

* update yaml to include optional deps

* adding in lorenze feedback

* ensure embeddings are persisted

* improvements all around Knowledge class

* return this

* properly reset memory

* properly reset memory+knowledge

* consolodation and improvements

* linted

* cleanup rm unused embedder

* fix test

* fix duplicate

* generating cassettes for knowledge test

* updated default embedder

* None embedder to use default on pipeline cloning

* improvements

* fixed text_file_knowledge

* mypysrc fixes

* type check fixes

* added extra cassette

* just mocks

* linted

* mock knowledge query to not spin up db

* linted

* verbose run

* put a flag

* fix

* adding docs

* better docs

* improvements from review

* more docs

* linted

* rm print

* more fixes

* clearer docs

* added docstrings and type hints for cli

---------

Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
---
 .github/workflows/tests.yml                   |   4 +-
 docs/concepts/knowledge.mdx                   |  75 +++
 pyproject.toml                                |  10 +
 src/crewai/__init__.py                        |  14 +-
 src/crewai/agent.py                           |  15 +-
 src/crewai/cli/cli.py                         |  14 +-
 src/crewai/cli/reset_memories_command.py      |  15 +-
 src/crewai/crew.py                            |  14 +
 src/crewai/knowledge/__init__.py              |   0
 src/crewai/knowledge/embedder/__init__.py     |   0
 .../knowledge/embedder/base_embedder.py       |  55 ++
 src/crewai/knowledge/embedder/fastembed.py    |  93 +++
 src/crewai/knowledge/knowledge.py             |  54 ++
 src/crewai/knowledge/source/__init__.py       |   0
 .../source/base_file_knowledge_source.py      |  36 ++
 .../knowledge/source/base_knowledge_source.py |  48 ++
 .../knowledge/source/csv_knowledge_source.py  |  44 ++
 .../source/excel_knowledge_source.py          |  56 ++
 .../knowledge/source/json_knowledge_source.py |  54 ++
 .../knowledge/source/pdf_knowledge_source.py  |  54 ++
 .../source/string_knowledge_source.py         |  33 ++
 .../source/text_file_knowledge_source.py      |  35 ++
 src/crewai/knowledge/storage/__init__.py      |   0
 .../storage/base_knowledge_storage.py         |  29 +
 .../knowledge/storage/knowledge_storage.py    | 132 +++++
 src/crewai/memory/storage/rag_storage.py      | 134 +----
 src/crewai/utilities/__init__.py              |   2 +
 src/crewai/utilities/constants.py             |   1 +
 .../utilities/embedding_configurator.py       | 183 ++++++
 tests/agent_test.py                           |  42 +-
 .../test_agent_with_knowledge_sources.yaml    | 115 ++++
 .../test_kickoff_for_each_error_handling.yaml | 232 ++++++++
 tests/knowledge/__init__.py                   |   0
 tests/knowledge/crewai_quickstart.pdf         | Bin 0 -> 952178 bytes
 tests/knowledge/knowledge_test.py             | 545 ++++++++++++++++++
 tests/pipeline/test_pipeline.py               |   2 +
 uv.lock                                       | 428 ++++++++++----
 37 files changed, 2302 insertions(+), 266 deletions(-)
 create mode 100644 docs/concepts/knowledge.mdx
 create mode 100644 src/crewai/knowledge/__init__.py
 create mode 100644 src/crewai/knowledge/embedder/__init__.py
 create mode 100644 src/crewai/knowledge/embedder/base_embedder.py
 create mode 100644 src/crewai/knowledge/embedder/fastembed.py
 create mode 100644 src/crewai/knowledge/knowledge.py
 create mode 100644 src/crewai/knowledge/source/__init__.py
 create mode 100644 src/crewai/knowledge/source/base_file_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/base_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/csv_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/excel_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/json_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/pdf_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/string_knowledge_source.py
 create mode 100644 src/crewai/knowledge/source/text_file_knowledge_source.py
 create mode 100644 src/crewai/knowledge/storage/__init__.py
 create mode 100644 src/crewai/knowledge/storage/base_knowledge_storage.py
 create mode 100644 src/crewai/knowledge/storage/knowledge_storage.py
 create mode 100644 src/crewai/utilities/embedding_configurator.py
 create mode 100644 tests/cassettes/test_agent_with_knowledge_sources.yaml
 create mode 100644 tests/cassettes/test_kickoff_for_each_error_handling.yaml
 create mode 100644 tests/knowledge/__init__.py
 create mode 100644 tests/knowledge/crewai_quickstart.pdf
 create mode 100644 tests/knowledge/knowledge_test.py

diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 04f6693d0..76ef2a611 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -26,7 +26,7 @@ jobs:
         run: uv python install 3.11.9
 
       - name: Install the project
-        run: uv sync --dev
+        run: uv sync --dev --all-extras
 
       - name: Run tests
-        run: uv run pytest tests
+        run: uv run pytest tests -vv
diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
new file mode 100644
index 000000000..2afb1b568
--- /dev/null
+++ b/docs/concepts/knowledge.mdx
@@ -0,0 +1,75 @@
+---
+title: Knowledge
+description: What is knowledge in CrewAI and how to use it.
+icon: book
+---
+
+# Using Knowledge in CrewAI
+
+## Introduction
+
+The Knowledge class in CrewAI provides a powerful way to manage and query knowledge sources for your AI agents. This guide will show you how to implement knowledge management in your CrewAI projects.
+Additionally, we have specific tools for generate knowledge sources for strings, text files, PDF's, and Spreadsheets. You can expand on any source type by extending the `KnowledgeSource` class.
+
+## Basic Implementation
+
+Here's a simple example of how to use the Knowledge class:
+
+```python
+from crewai import Agent, Task, Crew, Process, LLM
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+
+# Create a knowledge source
+content = "Users name is John. He is 30 years old and lives in San Francisco."
+string_source = StringKnowledgeSource(
+    content=content, metadata={"preference": "personal"}
+)
+
+
+llm = LLM(model="gpt-4o-mini", temperature=0)
+  # Create an agent with the knowledge store
+agent = Agent(
+    role="About User",
+    goal="You know everything about the user.",
+    backstory="""You are a master at understanding people and their preferences.""",
+    verbose=True,
+    allow_delegation=False,
+    llm=llm,
+)
+task = Task(
+    description="Answer the following questions about the user: {question}",
+    expected_output="An answer to the question.",
+    agent=agent,
+)
+
+crew = Crew(
+    agents=[agent],
+    tasks=[task],
+    verbose=True,
+    process=Process.sequential,
+    knowledge={"sources": [string_source], "metadata": {"preference": "personal"}}, # Enable knowledge by adding the sources here. You can also add more sources to the sources list.
+)
+
+result = crew.kickoff(inputs={"question": "What city does John live in and how old is he?"})
+```
+
+
+## Embedder Configuration
+
+You can also configure the embedder for the knowledge store. This is useful if you want to use a different embedder for the knowledge store than the one used for the agents.
+
+```python
+...
+string_source = StringKnowledgeSource(
+    content="Users name is John. He is 30 years old and lives in San Francisco.",
+    metadata={"preference": "personal"}
+)
+crew = Crew(
+    ...
+    knowledge={
+        "sources": [string_source],
+        "metadata": {"preference": "personal"},
+        "embedder_config": {"provider": "openai", "config": {"model": "text-embedding-3-small"}},
+    },
+)
+```
diff --git a/pyproject.toml b/pyproject.toml
index 5955baf33..2dbc00e24 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -39,6 +39,16 @@ Repository = "https://github.com/crewAIInc/crewAI"
 [project.optional-dependencies]
 tools = ["crewai-tools>=0.14.0"]
 agentops = ["agentops>=0.3.0"]
+fastembed = ["fastembed>=0.4.1"]
+pdfplumber = [
+    "pdfplumber>=0.11.4",
+]
+pandas = [
+    "pandas>=2.2.3",
+]
+openpyxl = [
+    "openpyxl>=3.1.5",
+]
 mem0 = ["mem0ai>=0.1.29"]
 
 [tool.uv]
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index fbad09663..6cfa381de 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -1,7 +1,9 @@
 import warnings
+
 from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.flow.flow import Flow
+from crewai.knowledge.knowledge import Knowledge
 from crewai.llm import LLM
 from crewai.pipeline import Pipeline
 from crewai.process import Process
@@ -15,4 +17,14 @@ warnings.filterwarnings(
     module="pydantic.main",
 )
 __version__ = "0.80.0"
-__all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]
+__all__ = [
+    "Agent",
+    "Crew",
+    "Process",
+    "Task",
+    "Pipeline",
+    "Router",
+    "LLM",
+    "Flow",
+    "Knowledge",
+]
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 4e9a0685f..d17cbbdfe 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -11,8 +11,8 @@ from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.cli.constants import ENV_VARS
 from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
-from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools import BaseTool
+from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -52,6 +52,7 @@ class Agent(BaseAgent):
             role: The role of the agent.
             goal: The objective of the agent.
             backstory: The backstory of the agent.
+            knowledge: The knowledge base of the agent.
             config: Dict representation of agent configuration.
             llm: The language model that will run the agent.
             function_calling_llm: The language model that will handle the tool calling for this agent, it overrides the crew function_calling_llm.
@@ -272,6 +273,18 @@ class Agent(BaseAgent):
             if memory.strip() != "":
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 
+        # Integrate the knowledge base
+        if self.crew and self.crew.knowledge:
+            knowledge_snippets = self.crew.knowledge.query([task.prompt()])
+            valid_snippets = [
+                result["context"] 
+                for result in knowledge_snippets 
+                if result and result.get("context")
+            ]
+            if valid_snippets:
+                formatted_knowledge = "\n".join(valid_snippets)
+                task_prompt += f"\n\nAdditional Information:\n{formatted_knowledge}"
+
         tools = tools or self.tools or []
         self.create_agent_executor(tools=tools, task=task)
 
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 0f43ff3f4..600eb6142 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -136,6 +136,7 @@ def log_tasks_outputs() -> None:
 @click.option("-l", "--long", is_flag=True, help="Reset LONG TERM memory")
 @click.option("-s", "--short", is_flag=True, help="Reset SHORT TERM memory")
 @click.option("-e", "--entities", is_flag=True, help="Reset ENTITIES memory")
+@click.option("-kn", "--knowledge", is_flag=True, help="Reset KNOWLEDGE storage")
 @click.option(
     "-k",
     "--kickoff-outputs",
@@ -143,17 +144,24 @@ def log_tasks_outputs() -> None:
     help="Reset LATEST KICKOFF TASK OUTPUTS",
 )
 @click.option("-a", "--all", is_flag=True, help="Reset ALL memories")
-def reset_memories(long, short, entities, kickoff_outputs, all):
+def reset_memories(
+    long: bool,
+    short: bool,
+    entities: bool,
+    knowledge: bool,
+    kickoff_outputs: bool,
+    all: bool,
+) -> None:
     """
     Reset the crew memories (long, short, entity, latest_crew_kickoff_ouputs). This will delete all the data saved.
     """
     try:
-        if not all and not (long or short or entities or kickoff_outputs):
+        if not all and not (long or short or entities or knowledge or kickoff_outputs):
             click.echo(
                 "Please specify at least one memory type to reset using the appropriate flags."
             )
             return
-        reset_memories_command(long, short, entities, kickoff_outputs, all)
+        reset_memories_command(long, short, entities, knowledge, kickoff_outputs, all)
     except Exception as e:
         click.echo(f"An error occurred while resetting memories: {e}", err=True)
 
diff --git a/src/crewai/cli/reset_memories_command.py b/src/crewai/cli/reset_memories_command.py
index c4808594f..31624cfc3 100644
--- a/src/crewai/cli/reset_memories_command.py
+++ b/src/crewai/cli/reset_memories_command.py
@@ -5,9 +5,17 @@ from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
 from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
+from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
 
 
-def reset_memories_command(long, short, entity, kickoff_outputs, all) -> None:
+def reset_memories_command(
+    long,
+    short,
+    entity,
+    knowledge,
+    kickoff_outputs,
+    all,
+) -> None:
     """
     Reset the crew memories.
 
@@ -17,6 +25,7 @@ def reset_memories_command(long, short, entity, kickoff_outputs, all) -> None:
       entity (bool): Whether to reset the entity memory.
       kickoff_outputs (bool): Whether to reset the latest kickoff task outputs.
       all (bool): Whether to reset all memories.
+      knowledge (bool): Whether to reset the knowledge.
     """
 
     try:
@@ -25,6 +34,7 @@ def reset_memories_command(long, short, entity, kickoff_outputs, all) -> None:
             EntityMemory().reset()
             LongTermMemory().reset()
             TaskOutputStorageHandler().reset()
+            KnowledgeStorage().reset()
             click.echo("All memories have been reset.")
         else:
             if long:
@@ -40,6 +50,9 @@ def reset_memories_command(long, short, entity, kickoff_outputs, all) -> None:
             if kickoff_outputs:
                 TaskOutputStorageHandler().reset()
                 click.echo("Latest Kickoff outputs stored has been reset.")
+            if knowledge:
+                KnowledgeStorage().reset()
+                click.echo("Knowledge has been reset.")
 
     except subprocess.CalledProcessError as e:
         click.echo(f"An error occurred while resetting the memories: {e}", err=True)
diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 7f5539976..4c3886a3f 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -27,6 +27,7 @@ from crewai.llm import LLM
 from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
+from crewai.knowledge.knowledge import Knowledge
 from crewai.memory.user.user_memory import UserMemory
 from crewai.process import Process
 from crewai.task import Task
@@ -201,6 +202,10 @@ class Crew(BaseModel):
         default=[],
         description="List of execution logs for tasks",
     )
+    knowledge: Optional[Dict[str, Any]] = Field(
+        default=None, description="Knowledge for the crew. Add knowledge sources to the knowledge object."
+    )
+
 
     @field_validator("id", mode="before")
     @classmethod
@@ -275,6 +280,15 @@ class Crew(BaseModel):
                 self._user_memory = None
         return self
 
+    @model_validator(mode="after")
+    def create_crew_knowledge(self) -> "Crew":
+        if self.knowledge:
+            try:
+                self.knowledge = Knowledge(**self.knowledge) if isinstance(self.knowledge, dict) else self.knowledge
+            except (TypeError, ValueError) as e:
+                raise ValueError(f"Invalid knowledge configuration: {str(e)}")
+        return self
+
     @model_validator(mode="after")
     def check_manager_llm(self):
         """Validates that the language model is set when using hierarchical process."""
diff --git a/src/crewai/knowledge/__init__.py b/src/crewai/knowledge/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/crewai/knowledge/embedder/__init__.py b/src/crewai/knowledge/embedder/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/crewai/knowledge/embedder/base_embedder.py b/src/crewai/knowledge/embedder/base_embedder.py
new file mode 100644
index 000000000..c3252bf43
--- /dev/null
+++ b/src/crewai/knowledge/embedder/base_embedder.py
@@ -0,0 +1,55 @@
+from abc import ABC, abstractmethod
+from typing import List
+
+import numpy as np
+
+
+class BaseEmbedder(ABC):
+    """
+    Abstract base class for text embedding models
+    """
+
+    @abstractmethod
+    def embed_chunks(self, chunks: List[str]) -> np.ndarray:
+        """
+        Generate embeddings for a list of text chunks
+
+        Args:
+            chunks: List of text chunks to embed
+
+        Returns:
+            Array of embeddings
+        """
+        pass
+
+    @abstractmethod
+    def embed_texts(self, texts: List[str]) -> np.ndarray:
+        """
+        Generate embeddings for a list of texts
+
+        Args:
+            texts: List of texts to embed
+
+        Returns:
+            Array of embeddings
+        """
+        pass
+
+    @abstractmethod
+    def embed_text(self, text: str) -> np.ndarray:
+        """
+        Generate embedding for a single text
+
+        Args:
+            text: Text to embed
+
+        Returns:
+            Embedding array
+        """
+        pass
+
+    @property
+    @abstractmethod
+    def dimension(self) -> int:
+        """Get the dimension of the embeddings"""
+        pass
diff --git a/src/crewai/knowledge/embedder/fastembed.py b/src/crewai/knowledge/embedder/fastembed.py
new file mode 100644
index 000000000..54db11643
--- /dev/null
+++ b/src/crewai/knowledge/embedder/fastembed.py
@@ -0,0 +1,93 @@
+from pathlib import Path
+from typing import List, Optional, Union
+
+import numpy as np
+
+from .base_embedder import BaseEmbedder
+
+try:
+    from fastembed_gpu import TextEmbedding  # type: ignore
+
+    FASTEMBED_AVAILABLE = True
+except ImportError:
+    try:
+        from fastembed import TextEmbedding
+
+        FASTEMBED_AVAILABLE = True
+    except ImportError:
+        FASTEMBED_AVAILABLE = False
+
+
+class FastEmbed(BaseEmbedder):
+    """
+    A wrapper class for text embedding models using FastEmbed
+    """
+
+    def __init__(
+        self,
+        model_name: str = "BAAI/bge-small-en-v1.5",
+        cache_dir: Optional[Union[str, Path]] = None,
+    ):
+        """
+        Initialize the embedding model
+
+        Args:
+            model_name: Name of the model to use
+            cache_dir: Directory to cache the model
+            gpu: Whether to use GPU acceleration
+        """
+        if not FASTEMBED_AVAILABLE:
+            raise ImportError(
+                "FastEmbed is not installed. Please install it with: "
+                "uv pip install fastembed or uv pip install fastembed-gpu for GPU support"
+            )
+
+        self.model = TextEmbedding(
+            model_name=model_name,
+            cache_dir=str(cache_dir) if cache_dir else None,
+        )
+
+    def embed_chunks(self, chunks: List[str]) -> List[np.ndarray]:
+        """
+        Generate embeddings for a list of text chunks
+
+        Args:
+            chunks: List of text chunks to embed
+
+        Returns:
+            List of embeddings
+        """
+        embeddings = list(self.model.embed(chunks))
+        return embeddings
+
+    def embed_texts(self, texts: List[str]) -> List[np.ndarray]:
+        """
+        Generate embeddings for a list of texts
+
+        Args:
+            texts: List of texts to embed
+
+        Returns:
+            List of embeddings
+        """
+        embeddings = list(self.model.embed(texts))
+        return embeddings
+
+    def embed_text(self, text: str) -> np.ndarray:
+        """
+        Generate embedding for a single text
+
+        Args:
+            text: Text to embed
+
+        Returns:
+            Embedding array
+        """
+        return self.embed_texts([text])[0]
+
+    @property
+    def dimension(self) -> int:
+        """Get the dimension of the embeddings"""
+        # Generate a test embedding to get dimensions
+        test_embed = self.embed_text("test")
+        return len(test_embed)
diff --git a/src/crewai/knowledge/knowledge.py b/src/crewai/knowledge/knowledge.py
new file mode 100644
index 000000000..cf2907e67
--- /dev/null
+++ b/src/crewai/knowledge/knowledge.py
@@ -0,0 +1,54 @@
+import os
+
+from typing import List, Optional, Dict, Any
+from pydantic import BaseModel, ConfigDict, Field
+
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+from crewai.utilities.logger import Logger
+from crewai.utilities.constants import DEFAULT_SCORE_THRESHOLD
+os.environ["TOKENIZERS_PARALLELISM"] = "false"  # removes logging from fastembed
+
+
+class Knowledge(BaseModel):
+    """
+    Knowledge is a collection of sources and setup for the vector store to save and query relevant context.
+    Args:
+        sources: List[BaseKnowledgeSource] = Field(default_factory=list)
+        storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+        embedder_config: Optional[Dict[str, Any]] = None
+    """
+    sources: List[BaseKnowledgeSource] = Field(default_factory=list)
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+    storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+    embedder_config: Optional[Dict[str, Any]] = None
+
+    def __init__(self, embedder_config: Optional[Dict[str, Any]] = None, **data):
+        super().__init__(**data)
+        self.storage = KnowledgeStorage(embedder_config=embedder_config or None)
+
+        try:
+            for source in self.sources:
+                source.add()
+        except Exception as e:
+            Logger(verbose=True).log(
+                "warning",
+                f"Failed to init knowledge: {e}",
+                color="yellow",
+            )
+
+    def query(
+        self, query: List[str], limit: int = 3, preference: Optional[str] = None
+    ) -> List[Dict[str, Any]]:
+        """
+        Query across all knowledge sources to find the most relevant information.
+        Returns the top_k most relevant chunks.
+        """
+
+        results = self.storage.search(
+            query,
+            limit,
+            filter={"preference": preference} if preference else None,
+            score_threshold=DEFAULT_SCORE_THRESHOLD,
+        )
+        return results
diff --git a/src/crewai/knowledge/source/__init__.py b/src/crewai/knowledge/source/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/crewai/knowledge/source/base_file_knowledge_source.py b/src/crewai/knowledge/source/base_file_knowledge_source.py
new file mode 100644
index 000000000..b6e346534
--- /dev/null
+++ b/src/crewai/knowledge/source/base_file_knowledge_source.py
@@ -0,0 +1,36 @@
+from pathlib import Path
+from typing import Union, List
+
+from pydantic import Field
+
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+from typing import Dict, Any
+from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+
+
+class BaseFileKnowledgeSource(BaseKnowledgeSource):
+    """Base class for knowledge sources that load content from files."""
+
+    file_path: Union[Path, List[Path]] = Field(...)
+    content: Dict[Path, str] = Field(init=False, default_factory=dict)
+    storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+
+    def model_post_init(self, _):
+        """Post-initialization method to load content."""
+        self.content = self.load_content()
+
+    def load_content(self) -> Dict[Path, str]:
+        """Load and preprocess file content. Should be overridden by subclasses."""
+        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
+
+        for path in paths:
+            if not path.exists():
+                raise FileNotFoundError(f"File not found: {path}")
+            if not path.is_file():
+                raise ValueError(f"Path is not a file: {path}")
+        return {}
+
+    def save_documents(self, metadata: Dict[str, Any]):
+        """Save the documents to the storage."""
+        chunk_metadatas = [metadata.copy() for _ in self.chunks]
+        self.storage.save(self.chunks, chunk_metadatas)
diff --git a/src/crewai/knowledge/source/base_knowledge_source.py b/src/crewai/knowledge/source/base_knowledge_source.py
new file mode 100644
index 000000000..bb4c69cf3
--- /dev/null
+++ b/src/crewai/knowledge/source/base_knowledge_source.py
@@ -0,0 +1,48 @@
+from abc import ABC, abstractmethod
+from typing import List, Dict, Any
+
+import numpy as np
+from pydantic import BaseModel, ConfigDict, Field
+
+from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+
+
+class BaseKnowledgeSource(BaseModel, ABC):
+    """Abstract base class for knowledge sources."""
+
+    chunk_size: int = 4000
+    chunk_overlap: int = 200
+    chunks: List[str] = Field(default_factory=list)
+    chunk_embeddings: List[np.ndarray] = Field(default_factory=list)
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+    storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+    @abstractmethod
+    def load_content(self) -> Dict[Any, str]:
+        """Load and preprocess content from the source."""
+        pass
+
+    @abstractmethod
+    def add(self) -> None:
+        """Process content, chunk it, compute embeddings, and save them."""
+        pass
+
+    def get_embeddings(self) -> List[np.ndarray]:
+        """Return the list of embeddings for the chunks."""
+        return self.chunk_embeddings
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
+
+    def save_documents(self, metadata: Dict[str, Any]):
+        """
+        Save the documents to the storage.
+        This method should be called after the chunks and embeddings are generated.
+        """
+        self.storage.save(self.chunks, metadata)
diff --git a/src/crewai/knowledge/source/csv_knowledge_source.py b/src/crewai/knowledge/source/csv_knowledge_source.py
new file mode 100644
index 000000000..0946104a4
--- /dev/null
+++ b/src/crewai/knowledge/source/csv_knowledge_source.py
@@ -0,0 +1,44 @@
+import csv
+from typing import Dict, List
+from pathlib import Path
+
+from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
+
+
+class CSVKnowledgeSource(BaseFileKnowledgeSource):
+    """A knowledge source that stores and queries CSV file content using embeddings."""
+
+    def load_content(self) -> Dict[Path, str]:
+        """Load and preprocess CSV file content."""
+        super().load_content()  # Validate the file path
+
+        file_path = (
+            self.file_path[0] if isinstance(self.file_path, list) else self.file_path
+        )
+        file_path = Path(file_path) if isinstance(file_path, str) else file_path
+
+        with open(file_path, "r", encoding="utf-8") as csvfile:
+            reader = csv.reader(csvfile)
+            content = ""
+            for row in reader:
+                content += " ".join(row) + "\n"
+        return {file_path: content}
+
+    def add(self) -> None:
+        """
+        Add CSV file content to the knowledge source, chunk it, compute embeddings,
+        and save the embeddings.
+        """
+        content_str = (
+            str(self.content) if isinstance(self.content, dict) else self.content
+        )
+        new_chunks = self._chunk_text(content_str)
+        self.chunks.extend(new_chunks)
+        self.save_documents(metadata=self.metadata)
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
diff --git a/src/crewai/knowledge/source/excel_knowledge_source.py b/src/crewai/knowledge/source/excel_knowledge_source.py
new file mode 100644
index 000000000..3b5c71514
--- /dev/null
+++ b/src/crewai/knowledge/source/excel_knowledge_source.py
@@ -0,0 +1,56 @@
+from typing import Dict, List
+from pathlib import Path
+from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
+
+
+class ExcelKnowledgeSource(BaseFileKnowledgeSource):
+    """A knowledge source that stores and queries Excel file content using embeddings."""
+
+    def load_content(self) -> Dict[Path, str]:
+        """Load and preprocess Excel file content."""
+        super().load_content()  # Validate the file path
+        pd = self._import_dependencies()
+
+        if isinstance(self.file_path, list):
+            file_path = self.file_path[0]
+        else:
+            file_path = self.file_path
+
+        df = pd.read_excel(file_path)
+        content = df.to_csv(index=False)
+        return {file_path: content}
+
+    def _import_dependencies(self):
+        """Dynamically import dependencies."""
+        try:
+            import openpyxl  # noqa
+            import pandas as pd
+
+            return pd
+        except ImportError as e:
+            missing_package = str(e).split()[-1]
+            raise ImportError(
+                f"{missing_package} is not installed. Please install it with: pip install {missing_package}"
+            )
+
+    def add(self) -> None:
+        """
+        Add Excel file content to the knowledge source, chunk it, compute embeddings,
+        and save the embeddings.
+        """
+        # Convert dictionary values to a single string if content is a dictionary
+        if isinstance(self.content, dict):
+            content_str = "\n".join(str(value) for value in self.content.values())
+        else:
+            content_str = str(self.content)
+
+        new_chunks = self._chunk_text(content_str)
+        self.chunks.extend(new_chunks)
+        self.save_documents(metadata=self.metadata)
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
diff --git a/src/crewai/knowledge/source/json_knowledge_source.py b/src/crewai/knowledge/source/json_knowledge_source.py
new file mode 100644
index 000000000..490423a00
--- /dev/null
+++ b/src/crewai/knowledge/source/json_knowledge_source.py
@@ -0,0 +1,54 @@
+import json
+from typing import Any, Dict, List
+from pathlib import Path
+
+from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
+
+
+class JSONKnowledgeSource(BaseFileKnowledgeSource):
+    """A knowledge source that stores and queries JSON file content using embeddings."""
+
+    def load_content(self) -> Dict[Path, str]:
+        """Load and preprocess JSON file content."""
+        super().load_content()  # Validate the file path
+        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
+
+        content: Dict[Path, str] = {}
+        for path in paths:
+            with open(path, "r", encoding="utf-8") as json_file:
+                data = json.load(json_file)
+            content[path] = self._json_to_text(data)
+        return content
+
+    def _json_to_text(self, data: Any, level: int = 0) -> str:
+        """Recursively convert JSON data to a text representation."""
+        text = ""
+        indent = "  " * level
+        if isinstance(data, dict):
+            for key, value in data.items():
+                text += f"{indent}{key}: {self._json_to_text(value, level + 1)}\n"
+        elif isinstance(data, list):
+            for item in data:
+                text += f"{indent}- {self._json_to_text(item, level + 1)}\n"
+        else:
+            text += f"{str(data)}"
+        return text
+
+    def add(self) -> None:
+        """
+        Add JSON file content to the knowledge source, chunk it, compute embeddings,
+        and save the embeddings.
+        """
+        content_str = (
+            str(self.content) if isinstance(self.content, dict) else self.content
+        )
+        new_chunks = self._chunk_text(content_str)
+        self.chunks.extend(new_chunks)
+        self.save_documents(metadata=self.metadata)
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
diff --git a/src/crewai/knowledge/source/pdf_knowledge_source.py b/src/crewai/knowledge/source/pdf_knowledge_source.py
new file mode 100644
index 000000000..623ba30a2
--- /dev/null
+++ b/src/crewai/knowledge/source/pdf_knowledge_source.py
@@ -0,0 +1,54 @@
+from typing import List, Dict
+from pathlib import Path
+
+from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
+
+
+class PDFKnowledgeSource(BaseFileKnowledgeSource):
+    """A knowledge source that stores and queries PDF file content using embeddings."""
+
+    def load_content(self) -> Dict[Path, str]:
+        """Load and preprocess PDF file content."""
+        super().load_content()  # Validate the file paths
+        pdfplumber = self._import_pdfplumber()
+
+        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
+        content = {}
+
+        for path in paths:
+            text = ""
+            with pdfplumber.open(path) as pdf:
+                for page in pdf.pages:
+                    page_text = page.extract_text()
+                    if page_text:
+                        text += page_text + "\n"
+            content[path] = text
+        return content
+
+    def _import_pdfplumber(self):
+        """Dynamically import pdfplumber."""
+        try:
+            import pdfplumber
+
+            return pdfplumber
+        except ImportError:
+            raise ImportError(
+                "pdfplumber is not installed. Please install it with: pip install pdfplumber"
+            )
+
+    def add(self) -> None:
+        """
+        Add PDF file content to the knowledge source, chunk it, compute embeddings,
+        and save the embeddings.
+        """
+        for _, text in self.content.items():
+            new_chunks = self._chunk_text(text)
+            self.chunks.extend(new_chunks)
+        self.save_documents(metadata=self.metadata)
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
diff --git a/src/crewai/knowledge/source/string_knowledge_source.py b/src/crewai/knowledge/source/string_knowledge_source.py
new file mode 100644
index 000000000..d4c22e3c1
--- /dev/null
+++ b/src/crewai/knowledge/source/string_knowledge_source.py
@@ -0,0 +1,33 @@
+from typing import List
+
+from pydantic import Field
+
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+
+
+class StringKnowledgeSource(BaseKnowledgeSource):
+    """A knowledge source that stores and queries plain text content using embeddings."""
+
+    content: str = Field(...)
+
+    def model_post_init(self, _):
+        """Post-initialization method to validate content."""
+        self.load_content()
+
+    def load_content(self):
+        """Validate string content."""
+        if not isinstance(self.content, str):
+            raise ValueError("StringKnowledgeSource only accepts string content")
+
+    def add(self) -> None:
+        """Add string content to the knowledge source, chunk it, compute embeddings, and save them."""
+        new_chunks = self._chunk_text(self.content)
+        self.chunks.extend(new_chunks)
+        self.save_documents(metadata=self.metadata)
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
diff --git a/src/crewai/knowledge/source/text_file_knowledge_source.py b/src/crewai/knowledge/source/text_file_knowledge_source.py
new file mode 100644
index 000000000..640db4ef9
--- /dev/null
+++ b/src/crewai/knowledge/source/text_file_knowledge_source.py
@@ -0,0 +1,35 @@
+from typing import Dict, List
+from pathlib import Path
+
+from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
+
+
+class TextFileKnowledgeSource(BaseFileKnowledgeSource):
+    """A knowledge source that stores and queries text file content using embeddings."""
+
+    def load_content(self) -> Dict[Path, str]:
+        """Load and preprocess text file content."""
+        super().load_content()
+        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
+        content = {}
+        for path in paths:
+            with path.open("r", encoding="utf-8") as f:
+                content[path] = f.read()  # type: ignore
+        return content
+
+    def add(self) -> None:
+        """
+        Add text file content to the knowledge source, chunk it, compute embeddings,
+        and save the embeddings.
+        """
+        for _, text in self.content.items():
+            new_chunks = self._chunk_text(text)
+            self.chunks.extend(new_chunks)
+        self.save_documents(metadata=self.metadata)
+
+    def _chunk_text(self, text: str) -> List[str]:
+        """Utility method to split text into chunks."""
+        return [
+            text[i : i + self.chunk_size]
+            for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
+        ]
diff --git a/src/crewai/knowledge/storage/__init__.py b/src/crewai/knowledge/storage/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/crewai/knowledge/storage/base_knowledge_storage.py b/src/crewai/knowledge/storage/base_knowledge_storage.py
new file mode 100644
index 000000000..78d370e04
--- /dev/null
+++ b/src/crewai/knowledge/storage/base_knowledge_storage.py
@@ -0,0 +1,29 @@
+from abc import ABC, abstractmethod
+from typing import Dict, Any, List, Optional
+
+
+class BaseKnowledgeStorage(ABC):
+    """Abstract base class for knowledge storage implementations."""
+
+    @abstractmethod
+    def search(
+        self,
+        query: List[str],
+        limit: int = 3,
+        filter: Optional[dict] = None,
+        score_threshold: float = 0.35,
+    ) -> List[Dict[str, Any]]:
+        """Search for documents in the knowledge base."""
+        pass
+
+    @abstractmethod
+    def save(
+        self, documents: List[str], metadata: Dict[str, Any] | List[Dict[str, Any]]
+    ) -> None:
+        """Save documents to the knowledge base."""
+        pass
+
+    @abstractmethod
+    def reset(self) -> None:
+        """Reset the knowledge base."""
+        pass
diff --git a/src/crewai/knowledge/storage/knowledge_storage.py b/src/crewai/knowledge/storage/knowledge_storage.py
new file mode 100644
index 000000000..b3d5ba750
--- /dev/null
+++ b/src/crewai/knowledge/storage/knowledge_storage.py
@@ -0,0 +1,132 @@
+import contextlib
+import io
+import logging
+import chromadb
+import os
+from crewai.utilities.paths import db_storage_path
+from typing import Optional, List
+from typing import Dict, Any
+from crewai.utilities import EmbeddingConfigurator
+from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
+import hashlib
+
+
+@contextlib.contextmanager
+def suppress_logging(
+    logger_name="chromadb.segment.impl.vector.local_persistent_hnsw",
+    level=logging.ERROR,
+):
+    logger = logging.getLogger(logger_name)
+    original_level = logger.getEffectiveLevel()
+    logger.setLevel(level)
+    with (
+        contextlib.redirect_stdout(io.StringIO()),
+        contextlib.redirect_stderr(io.StringIO()),
+        contextlib.suppress(UserWarning),
+    ):
+        yield
+    logger.setLevel(original_level)
+
+
+class KnowledgeStorage(BaseKnowledgeStorage):
+    """
+    Extends Storage to handle embeddings for memory entries, improving
+    search efficiency.
+    """
+
+    collection: Optional[chromadb.Collection] = None
+
+    def __init__(self, embedder_config: Optional[Dict[str, Any]] = None):
+        self._initialize_app(embedder_config or {})
+
+    def search(
+        self,
+        query: List[str],
+        limit: int = 3,
+        filter: Optional[dict] = None,
+        score_threshold: float = 0.35,
+    ) -> List[Dict[str, Any]]:
+        with suppress_logging():
+            if self.collection:
+                fetched = self.collection.query(
+                    query_texts=query,
+                    n_results=limit,
+                    where=filter,
+                )
+                results = []
+                for i in range(len(fetched["ids"][0])):  # type: ignore
+                    result = {
+                        "id": fetched["ids"][0][i],  # type: ignore
+                        "metadata": fetched["metadatas"][0][i],  # type: ignore
+                        "context": fetched["documents"][0][i],  # type: ignore
+                        "score": fetched["distances"][0][i],  # type: ignore
+                    }
+                    if result["score"] >= score_threshold:  # type: ignore
+                        results.append(result)
+                return results
+            else:
+                raise Exception("Collection not initialized")
+
+    def _initialize_app(self, embedder_config: Optional[Dict[str, Any]] = None):
+        import chromadb
+        from chromadb.config import Settings
+
+        self._set_embedder_config(embedder_config)
+
+        chroma_client = chromadb.PersistentClient(
+            path=f"{db_storage_path()}/knowledge",
+            settings=Settings(allow_reset=True),
+        )
+
+        self.app = chroma_client
+
+        try:
+            self.collection = self.app.get_or_create_collection(name="knowledge")
+        except Exception:
+            raise Exception("Failed to create or get collection")
+
+    def reset(self):
+        if self.app:
+            self.app.reset()
+
+    def save(
+        self, documents: List[str], metadata: Dict[str, Any] | List[Dict[str, Any]]
+    ):
+        if self.collection:
+            metadatas = [metadata] if isinstance(metadata, dict) else metadata
+
+            ids = [
+                hashlib.sha256(doc.encode("utf-8")).hexdigest() for doc in documents
+            ]
+
+            self.collection.upsert(
+                documents=documents,
+                metadatas=metadatas,
+                ids=ids,
+            )
+        else:
+            raise Exception("Collection not initialized")
+
+    def _create_default_embedding_function(self):
+        from chromadb.utils.embedding_functions.openai_embedding_function import (
+            OpenAIEmbeddingFunction,
+        )
+
+        return OpenAIEmbeddingFunction(
+            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
+        )
+
+    def _set_embedder_config(
+        self, embedder_config: Optional[Dict[str, Any]] = None
+    ) -> None:
+        """Set the embedding configuration for the knowledge storage.
+
+        Args:
+            embedder_config (Optional[Dict[str, Any]]): Configuration dictionary for the embedder.
+                If None or empty, defaults to the default embedding function.
+        """
+        self.embedder_config = (
+            EmbeddingConfigurator().configure_embedder(embedder_config)
+            if embedder_config
+            else self._create_default_embedding_function()
+        )
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index 7af5fb554..4023cf558 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -4,13 +4,12 @@ import logging
 import os
 import shutil
 import uuid
-from typing import Any, Dict, List, Optional, cast
 
-from chromadb import Documents, EmbeddingFunction, Embeddings
+from typing import Any, Dict, List, Optional
 from chromadb.api import ClientAPI
-from chromadb.api.types import validate_embedding_function
 from crewai.memory.storage.base_rag_storage import BaseRAGStorage
 from crewai.utilities.paths import db_storage_path
+from crewai.utilities import EmbeddingConfigurator
 
 
 @contextlib.contextmanager
@@ -51,133 +50,8 @@ class RAGStorage(BaseRAGStorage):
         self._initialize_app()
 
     def _set_embedder_config(self):
-        if self.embedder_config is None:
-            self.embedder_config = self._create_default_embedding_function()
-
-        if isinstance(self.embedder_config, dict):
-            provider = self.embedder_config.get("provider")
-            config = self.embedder_config.get("config", {})
-            model_name = config.get("model")
-            if provider == "openai":
-                from chromadb.utils.embedding_functions.openai_embedding_function import (
-                    OpenAIEmbeddingFunction,
-                )
-
-                self.embedder_config = OpenAIEmbeddingFunction(
-                    api_key=config.get("api_key") or os.getenv("OPENAI_API_KEY"),
-                    model_name=model_name,
-                )
-            elif provider == "azure":
-                from chromadb.utils.embedding_functions.openai_embedding_function import (
-                    OpenAIEmbeddingFunction,
-                )
-
-                self.embedder_config = OpenAIEmbeddingFunction(
-                    api_key=config.get("api_key"),
-                    api_base=config.get("api_base"),
-                    api_type=config.get("api_type", "azure"),
-                    api_version=config.get("api_version"),
-                    model_name=model_name,
-                )
-            elif provider == "ollama":
-                from chromadb.utils.embedding_functions.ollama_embedding_function import (
-                    OllamaEmbeddingFunction,
-                )
-
-                self.embedder_config = OllamaEmbeddingFunction(
-                    url=config.get("url", "http://localhost:11434/api/embeddings"),
-                    model_name=model_name,
-                )
-            elif provider == "vertexai":
-                from chromadb.utils.embedding_functions.google_embedding_function import (
-                    GoogleVertexEmbeddingFunction,
-                )
-
-                self.embedder_config = GoogleVertexEmbeddingFunction(
-                    model_name=model_name,
-                    api_key=config.get("api_key"),
-                )
-            elif provider == "google":
-                from chromadb.utils.embedding_functions.google_embedding_function import (
-                    GoogleGenerativeAiEmbeddingFunction,
-                )
-
-                self.embedder_config = GoogleGenerativeAiEmbeddingFunction(
-                    model_name=model_name,
-                    api_key=config.get("api_key"),
-                )
-            elif provider == "cohere":
-                from chromadb.utils.embedding_functions.cohere_embedding_function import (
-                    CohereEmbeddingFunction,
-                )
-
-                self.embedder_config = CohereEmbeddingFunction(
-                    model_name=model_name,
-                    api_key=config.get("api_key"),
-                )
-            elif provider == "bedrock":
-                from chromadb.utils.embedding_functions.amazon_bedrock_embedding_function import (
-                    AmazonBedrockEmbeddingFunction,
-                )
-
-                self.embedder_config = AmazonBedrockEmbeddingFunction(
-                    session=config.get("session"),
-                )
-            elif provider == "huggingface":
-                from chromadb.utils.embedding_functions.huggingface_embedding_function import (
-                    HuggingFaceEmbeddingServer,
-                )
-
-                self.embedder_config = HuggingFaceEmbeddingServer(
-                    url=config.get("api_url"),
-                )
-            elif provider == "watson":
-                try:
-                    import ibm_watsonx_ai.foundation_models as watson_models
-                    from ibm_watsonx_ai import Credentials
-                    from ibm_watsonx_ai.metanames import (
-                        EmbedTextParamsMetaNames as EmbedParams,
-                    )
-                except ImportError as e:
-                    raise ImportError(
-                        "IBM Watson dependencies are not installed. Please install them to use Watson embedding."
-                    ) from e
-
-                class WatsonEmbeddingFunction(EmbeddingFunction):
-                    def __call__(self, input: Documents) -> Embeddings:
-                        if isinstance(input, str):
-                            input = [input]
-
-                        embed_params = {
-                            EmbedParams.TRUNCATE_INPUT_TOKENS: 3,
-                            EmbedParams.RETURN_OPTIONS: {"input_text": True},
-                        }
-
-                        embedding = watson_models.Embeddings(
-                            model_id=config.get("model"),
-                            params=embed_params,
-                            credentials=Credentials(
-                                api_key=config.get("api_key"), url=config.get("api_url")
-                            ),
-                            project_id=config.get("project_id"),
-                        )
-
-                        try:
-                            embeddings = embedding.embed_documents(input)
-                            return cast(Embeddings, embeddings)
-
-                        except Exception as e:
-                            print("Error during Watson embedding:", e)
-                            raise e
-
-                self.embedder_config = WatsonEmbeddingFunction()
-            else:
-                raise Exception(
-                    f"Unsupported embedding provider: {provider}, supported providers: [openai, azure, ollama, vertexai, google, cohere, huggingface, watson]"
-                )
-        else:
-            validate_embedding_function(self.embedder_config)
-            self.embedder_config = self.embedder_config
+        configurator = EmbeddingConfigurator()
+        self.embedder_config = configurator.configure_embedder(self.embedder_config)
 
     def _initialize_app(self):
         import chromadb
diff --git a/src/crewai/utilities/__init__.py b/src/crewai/utilities/__init__.py
index 26d35a6cc..dd6d9fa44 100644
--- a/src/crewai/utilities/__init__.py
+++ b/src/crewai/utilities/__init__.py
@@ -10,6 +10,7 @@ from .rpm_controller import RPMController
 from .exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
+from .embedding_configurator import EmbeddingConfigurator
 
 __all__ = [
     "Converter",
@@ -23,4 +24,5 @@ __all__ = [
     "RPMController",
     "YamlParser",
     "LLMContextLengthExceededException",
+    "EmbeddingConfigurator",
 ]
diff --git a/src/crewai/utilities/constants.py b/src/crewai/utilities/constants.py
index 22cc2ffbe..59f789913 100644
--- a/src/crewai/utilities/constants.py
+++ b/src/crewai/utilities/constants.py
@@ -1,2 +1,3 @@
 TRAINING_DATA_FILE = "training_data.pkl"
 TRAINED_AGENTS_DATA_FILE = "trained_agents_data.pkl"
+DEFAULT_SCORE_THRESHOLD = 0.35
diff --git a/src/crewai/utilities/embedding_configurator.py b/src/crewai/utilities/embedding_configurator.py
new file mode 100644
index 000000000..f0f77ffca
--- /dev/null
+++ b/src/crewai/utilities/embedding_configurator.py
@@ -0,0 +1,183 @@
+import os
+from typing import Any, Dict, cast
+from chromadb import EmbeddingFunction, Documents, Embeddings
+from chromadb.api.types import validate_embedding_function
+
+
+class EmbeddingConfigurator:
+    def __init__(self):
+        self.embedding_functions = {
+            "openai": self._configure_openai,
+            "azure": self._configure_azure,
+            "ollama": self._configure_ollama,
+            "vertexai": self._configure_vertexai,
+            "google": self._configure_google,
+            "cohere": self._configure_cohere,
+            "bedrock": self._configure_bedrock,
+            "huggingface": self._configure_huggingface,
+            "watson": self._configure_watson,
+        }
+
+    def configure_embedder(
+        self,
+        embedder_config: Dict[str, Any] | None = None,
+    ) -> EmbeddingFunction:
+        """Configures and returns an embedding function based on the provided config."""
+        if embedder_config is None:
+            return self._create_default_embedding_function()
+
+        provider = embedder_config.get("provider")
+        config = embedder_config.get("config", {})
+        model_name = config.get("model")
+
+        if isinstance(provider, EmbeddingFunction):
+            try:
+                validate_embedding_function(provider)
+                return provider
+            except Exception as e:
+                raise ValueError(f"Invalid custom embedding function: {str(e)}")
+
+        if provider not in self.embedding_functions:
+            raise Exception(
+                f"Unsupported embedding provider: {provider}, supported providers: {list(self.embedding_functions.keys())}"
+            )
+
+        return self.embedding_functions[provider](config, model_name)
+
+    @staticmethod
+    def _create_default_embedding_function():
+        from chromadb.utils.embedding_functions.openai_embedding_function import (
+            OpenAIEmbeddingFunction,
+        )
+
+        return OpenAIEmbeddingFunction(
+            api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"
+        )
+
+    @staticmethod
+    def _configure_openai(config, model_name):
+        from chromadb.utils.embedding_functions.openai_embedding_function import (
+            OpenAIEmbeddingFunction,
+        )
+
+        return OpenAIEmbeddingFunction(
+            api_key=config.get("api_key") or os.getenv("OPENAI_API_KEY"),
+            model_name=model_name,
+        )
+
+    @staticmethod
+    def _configure_azure(config, model_name):
+        from chromadb.utils.embedding_functions.openai_embedding_function import (
+            OpenAIEmbeddingFunction,
+        )
+
+        return OpenAIEmbeddingFunction(
+            api_key=config.get("api_key"),
+            api_base=config.get("api_base"),
+            api_type=config.get("api_type", "azure"),
+            api_version=config.get("api_version"),
+            model_name=model_name,
+        )
+
+    @staticmethod
+    def _configure_ollama(config, model_name):
+        from chromadb.utils.embedding_functions.ollama_embedding_function import (
+            OllamaEmbeddingFunction,
+        )
+
+        return OllamaEmbeddingFunction(
+            url=config.get("url", "http://localhost:11434/api/embeddings"),
+            model_name=model_name,
+        )
+
+    @staticmethod
+    def _configure_vertexai(config, model_name):
+        from chromadb.utils.embedding_functions.google_embedding_function import (
+            GoogleVertexEmbeddingFunction,
+        )
+
+        return GoogleVertexEmbeddingFunction(
+            model_name=model_name,
+            api_key=config.get("api_key"),
+        )
+
+    @staticmethod
+    def _configure_google(config, model_name):
+        from chromadb.utils.embedding_functions.google_embedding_function import (
+            GoogleGenerativeAiEmbeddingFunction,
+        )
+
+        return GoogleGenerativeAiEmbeddingFunction(
+            model_name=model_name,
+            api_key=config.get("api_key"),
+        )
+
+    @staticmethod
+    def _configure_cohere(config, model_name):
+        from chromadb.utils.embedding_functions.cohere_embedding_function import (
+            CohereEmbeddingFunction,
+        )
+
+        return CohereEmbeddingFunction(
+            model_name=model_name,
+            api_key=config.get("api_key"),
+        )
+
+    @staticmethod
+    def _configure_bedrock(config, model_name):
+        from chromadb.utils.embedding_functions.amazon_bedrock_embedding_function import (
+            AmazonBedrockEmbeddingFunction,
+        )
+
+        return AmazonBedrockEmbeddingFunction(
+            session=config.get("session"),
+        )
+
+    @staticmethod
+    def _configure_huggingface(config, model_name):
+        from chromadb.utils.embedding_functions.huggingface_embedding_function import (
+            HuggingFaceEmbeddingServer,
+        )
+
+        return HuggingFaceEmbeddingServer(
+            url=config.get("api_url"),
+        )
+
+    @staticmethod
+    def _configure_watson(config, model_name):
+        try:
+            import ibm_watsonx_ai.foundation_models as watson_models
+            from ibm_watsonx_ai import Credentials
+            from ibm_watsonx_ai.metanames import EmbedTextParamsMetaNames as EmbedParams
+        except ImportError as e:
+            raise ImportError(
+                "IBM Watson dependencies are not installed. Please install them to use Watson embedding."
+            ) from e
+
+        class WatsonEmbeddingFunction(EmbeddingFunction):
+            def __call__(self, input: Documents) -> Embeddings:
+                if isinstance(input, str):
+                    input = [input]
+
+                embed_params = {
+                    EmbedParams.TRUNCATE_INPUT_TOKENS: 3,
+                    EmbedParams.RETURN_OPTIONS: {"input_text": True},
+                }
+
+                embedding = watson_models.Embeddings(
+                    model_id=config.get("model"),
+                    params=embed_params,
+                    credentials=Credentials(
+                        api_key=config.get("api_key"), url=config.get("api_url")
+                    ),
+                    project_id=config.get("project_id"),
+                )
+
+                try:
+                    embeddings = embedding.embed_documents(input)
+                    return cast(Embeddings, embeddings)
+                except Exception as e:
+                    print("Error during Watson embedding:", e)
+                    raise e
+
+        return WatsonEmbeddingFunction()
diff --git a/tests/agent_test.py b/tests/agent_test.py
index c4094d15c..fb6ab22b8 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -10,10 +10,11 @@ from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.llm import LLM
+from crewai.tools import tool
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
-from crewai.tools import tool
 from crewai.tools.tool_usage_events import ToolUsageFinished
 from crewai.utilities import RPMController
 from crewai.utilities.events import Emitter
@@ -1574,3 +1575,42 @@ def test_agent_execute_task_with_ollama():
     result = agent.execute_task(task)
     assert len(result.split(".")) == 2
     assert "AI" in result or "artificial intelligence" in result.lower()
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_with_knowledge_sources():
+    # Create a knowledge source with some content
+    content = "Brandon's favorite color is blue and he likes Mexican food."
+    string_source = StringKnowledgeSource(
+        content=content, metadata={"preference": "personal"}
+    )
+    
+
+    with patch('crewai.knowledge.storage.knowledge_storage.KnowledgeStorage') as MockKnowledge:
+        mock_knowledge_instance = MockKnowledge.return_value
+        mock_knowledge_instance.sources = [string_source]
+        mock_knowledge_instance.query.return_value = [{
+            "content": content,
+            "metadata": {"preference": "personal"}
+        }]
+        
+        agent = Agent(
+            role="Information Agent",
+            goal="Provide information based on knowledge sources",
+            backstory="You have access to specific knowledge sources.",
+            llm=LLM(model="gpt-4o-mini"),
+        )
+
+        # Create a task that requires the agent to use the knowledge
+        task = Task(
+            description="What is Brandon's favorite color?",
+            expected_output="Brandon's favorite color.",
+            agent=agent,
+        )
+
+        crew = Crew(agents=[agent], tasks=[task])
+        result = crew.kickoff()
+
+        # Assert that the agent provides the correct information
+        assert "blue" in result.raw.lower()
+
diff --git a/tests/cassettes/test_agent_with_knowledge_sources.yaml b/tests/cassettes/test_agent_with_knowledge_sources.yaml
new file mode 100644
index 000000000..d483a19d2
--- /dev/null
+++ b/tests/cassettes/test_agent_with_knowledge_sources.yaml
@@ -0,0 +1,115 @@
+interactions:
+- request:
+    body: '{"messages": [{"role": "system", "content": "You are Information Agent.
+      You have access to specific knowledge sources.\nYour personal goal is: Provide
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+      to the task use the exact following format:\n\nThought: I now can give a great
+      answer\nFinal Answer: Your final answer must be the great and the most complete
+      as possible, it must be outcome described.\n\nI MUST use these formats, my job
+      depends on it!"}, {"role": "user", "content": "\nCurrent Task: What is Brandon''s
+      favorite color?\n\nThis is the expect criteria for your final answer: Brandon''s
+      favorite color.\nyou MUST return the actual complete content as the final answer,
+      not a summary.\n\nBegin! This is VERY important to you, use the tools available
+      and give your best Final Answer, your job depends on it!\n\nThought:"}], "model":
+      "gpt-4o-mini", "stop": ["\nObservation:"], "stream": false}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate
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+      - '150000000'
+      x-ratelimit-remaining-requests:
+      - '29999'
+      x-ratelimit-remaining-tokens:
+      - '149999790'
+      x-ratelimit-reset-requests:
+      - 2ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_8f1622677c64913753a595f679596614
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_kickoff_for_each_error_handling.yaml b/tests/cassettes/test_kickoff_for_each_error_handling.yaml
new file mode 100644
index 000000000..6a479332d
--- /dev/null
+++ b/tests/cassettes/test_kickoff_for_each_error_handling.yaml
@@ -0,0 +1,232 @@
+interactions:
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diff --git a/tests/knowledge/__init__.py b/tests/knowledge/__init__.py
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HcmV?d00001

diff --git a/tests/knowledge/knowledge_test.py b/tests/knowledge/knowledge_test.py
new file mode 100644
index 000000000..4f506ff16
--- /dev/null
+++ b/tests/knowledge/knowledge_test.py
@@ -0,0 +1,545 @@
+"""Test Knowledge creation and querying functionality."""
+
+from pathlib import Path
+from unittest.mock import patch
+
+from crewai.knowledge.source.csv_knowledge_source import CSVKnowledgeSource
+from crewai.knowledge.source.excel_knowledge_source import ExcelKnowledgeSource
+from crewai.knowledge.source.json_knowledge_source import JSONKnowledgeSource
+from crewai.knowledge.source.pdf_knowledge_source import PDFKnowledgeSource
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+from crewai.knowledge.source.text_file_knowledge_source import TextFileKnowledgeSource
+
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def mock_vector_db():
+    """Mock vector database operations."""
+    with patch("crewai.knowledge.storage.knowledge_storage.KnowledgeStorage") as mock:
+        # Mock the query method to return a predefined response
+        instance = mock.return_value
+        instance.query.return_value = [
+            {
+                "context": "Brandon's favorite color is blue and he likes Mexican food.",
+                "score": 0.9,
+            }
+        ]
+        instance.reset.return_value = None
+        yield instance
+
+
+@pytest.fixture(autouse=True)
+def reset_knowledge_storage(mock_vector_db):
+    """Fixture to reset knowledge storage before each test."""
+    yield
+
+
+def test_single_short_string(mock_vector_db):
+    # Create a knowledge base with a single short string
+    content = "Brandon's favorite color is blue and he likes Mexican food."
+    string_source = StringKnowledgeSource(
+        content=content, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [string_source]
+    mock_vector_db.query.return_value = [{"context": content, "score": 0.9}]
+    # Perform a query
+    query = "What is Brandon's favorite color?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the results contain the expected information
+    assert any("blue" in result["context"].lower() for result in results)
+    # Verify the mock was called
+    mock_vector_db.query.assert_called_once()
+
+
+# @pytest.mark.vcr(filter_headers=["authorization"])
+def test_single_2k_character_string(mock_vector_db):
+    # Create a 2k character string with various facts about Brandon
+    content = (
+        "Brandon is a software engineer who lives in San Francisco. "
+        "He enjoys hiking and often visits the trails in the Bay Area. "
+        "Brandon has a pet dog named Max, who is a golden retriever. "
+        "He loves reading science fiction books, and his favorite author is Isaac Asimov. "
+        "Brandon's favorite movie is Inception, and he enjoys watching it with his friends. "
+        "He is also a fan of Mexican cuisine, especially tacos and burritos. "
+        "Brandon plays the guitar and often performs at local open mic nights. "
+        "He is learning French and plans to visit Paris next year. "
+        "Brandon is passionate about technology and often attends tech meetups in the city. "
+        "He is also interested in AI and machine learning, and he is currently working on a project related to natural language processing. "
+        "Brandon's favorite color is blue, and he often wears blue shirts. "
+        "He enjoys cooking and often tries new recipes on weekends. "
+        "Brandon is a morning person and likes to start his day with a run in the park. "
+        "He is also a coffee enthusiast and enjoys trying different coffee blends. "
+        "Brandon is a member of a local book club and enjoys discussing books with fellow members. "
+        "He is also a fan of board games and often hosts game nights at his place. "
+        "Brandon is an advocate for environmental conservation and volunteers for local clean-up drives. "
+        "He is also a mentor for aspiring software developers and enjoys sharing his knowledge with others. "
+        "Brandon's favorite sport is basketball, and he often plays with his friends on weekends. "
+        "He is also a fan of the Golden State Warriors and enjoys watching their games. "
+    )
+    string_source = StringKnowledgeSource(
+        content=content, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [string_source]
+    mock_vector_db.query.return_value = [{"context": content, "score": 0.9}]
+
+    # Perform a query
+    query = "What is Brandon's favorite movie?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the results contain the expected information
+    assert any("inception" in result["context"].lower() for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_multiple_short_strings(mock_vector_db):
+    # Create multiple short string sources
+    contents = [
+        "Brandon loves hiking.",
+        "Brandon has a dog named Max.",
+        "Brandon enjoys painting landscapes.",
+    ]
+    string_sources = [
+        StringKnowledgeSource(content=content, metadata={"preference": "personal"})
+        for content in contents
+    ]
+
+    # Mock the vector db query response
+    mock_vector_db.query.return_value = [
+        {"context": "Brandon has a dog named Max.", "score": 0.9}
+    ]
+
+    mock_vector_db.sources = string_sources
+
+    # Perform a query
+    query = "What is the name of Brandon's pet?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any("max" in result["context"].lower() for result in results)
+    # Verify the mock was called
+    mock_vector_db.query.assert_called_once()
+
+
+def test_multiple_2k_character_strings(mock_vector_db):
+    # Create multiple 2k character strings with various facts about Brandon
+    contents = [
+        (
+            "Brandon is a software engineer who lives in San Francisco. "
+            "He enjoys hiking and often visits the trails in the Bay Area. "
+            "Brandon has a pet dog named Max, who is a golden retriever. "
+            "He loves reading science fiction books, and his favorite author is Isaac Asimov. "
+            "Brandon's favorite movie is Inception, and he enjoys watching it with his friends. "
+            "He is also a fan of Mexican cuisine, especially tacos and burritos. "
+            "Brandon plays the guitar and often performs at local open mic nights. "
+            "He is learning French and plans to visit Paris next year. "
+            "Brandon is passionate about technology and often attends tech meetups in the city. "
+            "He is also interested in AI and machine learning, and he is currently working on a project related to natural language processing. "
+            "Brandon's favorite color is blue, and he often wears blue shirts. "
+            "He enjoys cooking and often tries new recipes on weekends. "
+            "Brandon is a morning person and likes to start his day with a run in the park. "
+            "He is also a coffee enthusiast and enjoys trying different coffee blends. "
+            "Brandon is a member of a local book club and enjoys discussing books with fellow members. "
+            "He is also a fan of board games and often hosts game nights at his place. "
+            "Brandon is an advocate for environmental conservation and volunteers for local clean-up drives. "
+            "He is also a mentor for aspiring software developers and enjoys sharing his knowledge with others. "
+            "Brandon's favorite sport is basketball, and he often plays with his friends on weekends. "
+            "He is also a fan of the Golden State Warriors and enjoys watching their games. "
+        )
+        * 2,  # Repeat to ensure it's 2k characters
+        (
+            "Brandon loves traveling and has visited over 20 countries. "
+            "He is fluent in Spanish and often practices with his friends. "
+            "Brandon's favorite city is Barcelona, where he enjoys the architecture and culture. "
+            "He is a foodie and loves trying new cuisines, with a particular fondness for sushi. "
+            "Brandon is an avid cyclist and participates in local cycling events. "
+            "He is also a photographer and enjoys capturing landscapes and cityscapes. "
+            "Brandon is a tech enthusiast and follows the latest trends in gadgets and software. "
+            "He is also a fan of virtual reality and owns a VR headset. "
+            "Brandon's favorite book is 'The Hitchhiker's Guide to the Galaxy'. "
+            "He enjoys watching documentaries and learning about history and science. "
+            "Brandon is a coffee lover and has a collection of coffee mugs from different countries. "
+            "He is also a fan of jazz music and often attends live performances. "
+            "Brandon is a member of a local running club and participates in marathons. "
+            "He is also a volunteer at a local animal shelter and helps with dog walking. "
+            "Brandon's favorite holiday is Christmas, and he enjoys decorating his home. "
+            "He is also a fan of classic movies and has a collection of DVDs. "
+            "Brandon is a mentor for young professionals and enjoys giving career advice. "
+            "He is also a fan of puzzles and enjoys solving them in his free time. "
+            "Brandon's favorite sport is soccer, and he often plays with his friends. "
+            "He is also a fan of FC Barcelona and enjoys watching their matches. "
+        )
+        * 2,  # Repeat to ensure it's 2k characters
+    ]
+    string_sources = [
+        StringKnowledgeSource(content=content, metadata={"preference": "personal"})
+        for content in contents
+    ]
+
+    mock_vector_db.sources = string_sources
+    mock_vector_db.query.return_value = [{"context": contents[1], "score": 0.9}]
+
+    # Perform a query
+    query = "What is Brandon's favorite book?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any(
+        "the hitchhiker's guide to the galaxy" in result["context"].lower()
+        for result in results
+    )
+    mock_vector_db.query.assert_called_once()
+
+
+def test_single_short_file(mock_vector_db, tmpdir):
+    # Create a single short text file
+    content = "Brandon's favorite sport is basketball."
+    file_path = Path(tmpdir.join("short_file.txt"))
+    with open(file_path, "w") as f:
+        f.write(content)
+
+    file_source = TextFileKnowledgeSource(
+        file_path=file_path, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [file_source]
+    mock_vector_db.query.return_value = [{"context": content, "score": 0.9}]
+    # Perform a query
+    query = "What sport does Brandon like?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the results contain the expected information
+    assert any("basketball" in result["context"].lower() for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_single_2k_character_file(mock_vector_db, tmpdir):
+    # Create a single 2k character text file with various facts about Brandon
+    content = (
+        "Brandon is a software engineer who lives in San Francisco. "
+        "He enjoys hiking and often visits the trails in the Bay Area. "
+        "Brandon has a pet dog named Max, who is a golden retriever. "
+        "He loves reading science fiction books, and his favorite author is Isaac Asimov. "
+        "Brandon's favorite movie is Inception, and he enjoys watching it with his friends. "
+        "He is also a fan of Mexican cuisine, especially tacos and burritos. "
+        "Brandon plays the guitar and often performs at local open mic nights. "
+        "He is learning French and plans to visit Paris next year. "
+        "Brandon is passionate about technology and often attends tech meetups in the city. "
+        "He is also interested in AI and machine learning, and he is currently working on a project related to natural language processing. "
+        "Brandon's favorite color is blue, and he often wears blue shirts. "
+        "He enjoys cooking and often tries new recipes on weekends. "
+        "Brandon is a morning person and likes to start his day with a run in the park. "
+        "He is also a coffee enthusiast and enjoys trying different coffee blends. "
+        "Brandon is a member of a local book club and enjoys discussing books with fellow members. "
+        "He is also a fan of board games and often hosts game nights at his place. "
+        "Brandon is an advocate for environmental conservation and volunteers for local clean-up drives. "
+        "He is also a mentor for aspiring software developers and enjoys sharing his knowledge with others. "
+        "Brandon's favorite sport is basketball, and he often plays with his friends on weekends. "
+        "He is also a fan of the Golden State Warriors and enjoys watching their games. "
+    ) * 2  # Repeat to ensure it's 2k characters
+    file_path = Path(tmpdir.join("long_file.txt"))
+    with open(file_path, "w") as f:
+        f.write(content)
+
+    file_source = TextFileKnowledgeSource(
+        file_path=file_path, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [file_source]
+    mock_vector_db.query.return_value = [{"context": content, "score": 0.9}]
+    # Perform a query
+    query = "What is Brandon's favorite movie?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the results contain the expected information
+    assert any("inception" in result["context"].lower() for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_multiple_short_files(mock_vector_db, tmpdir):
+    # Create multiple short text files
+    contents = [
+        {
+            "content": "Brandon works as a software engineer.",
+            "metadata": {"category": "profession", "source": "occupation"},
+        },
+        {
+            "content": "Brandon lives in New York.",
+            "metadata": {"category": "city", "source": "personal"},
+        },
+        {
+            "content": "Brandon enjoys cooking Italian food.",
+            "metadata": {"category": "hobby", "source": "personal"},
+        },
+    ]
+    file_paths = []
+    for i, item in enumerate(contents):
+        file_path = Path(tmpdir.join(f"file_{i}.txt"))
+        with open(file_path, "w") as f:
+            f.write(item["content"])
+        file_paths.append((file_path, item["metadata"]))
+
+    file_sources = [
+        TextFileKnowledgeSource(file_path=path, metadata=metadata)
+        for path, metadata in file_paths
+    ]
+    mock_vector_db.sources = file_sources
+    mock_vector_db.query.return_value = [
+        {"context": "Brandon lives in New York.", "score": 0.9}
+    ]
+    # Perform a query
+    query = "What city does he reside in?"
+    results = mock_vector_db.query(query)
+    # Assert that the correct information is retrieved
+    assert any("new york" in result["context"].lower() for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_multiple_2k_character_files(mock_vector_db, tmpdir):
+    # Create multiple 2k character text files with various facts about Brandon
+    contents = [
+        (
+            "Brandon loves traveling and has visited over 20 countries. "
+            "He is fluent in Spanish and often practices with his friends. "
+            "Brandon's favorite city is Barcelona, where he enjoys the architecture and culture. "
+            "He is a foodie and loves trying new cuisines, with a particular fondness for sushi. "
+            "Brandon is an avid cyclist and participates in local cycling events. "
+            "He is also a photographer and enjoys capturing landscapes and cityscapes. "
+            "Brandon is a tech enthusiast and follows the latest trends in gadgets and software. "
+            "He is also a fan of virtual reality and owns a VR headset. "
+            "Brandon's favorite book is 'The Hitchhiker's Guide to the Galaxy'. "
+            "He enjoys watching documentaries and learning about history and science. "
+            "Brandon is a coffee lover and has a collection of coffee mugs from different countries. "
+            "He is also a fan of jazz music and often attends live performances. "
+            "Brandon is a member of a local running club and participates in marathons. "
+            "He is also a volunteer at a local animal shelter and helps with dog walking. "
+            "Brandon's favorite holiday is Christmas, and he enjoys decorating his home. "
+            "He is also a fan of classic movies and has a collection of DVDs. "
+            "Brandon is a mentor for young professionals and enjoys giving career advice. "
+            "He is also a fan of puzzles and enjoys solving them in his free time. "
+            "Brandon's favorite sport is soccer, and he often plays with his friends. "
+            "He is also a fan of FC Barcelona and enjoys watching their matches. "
+        )
+        * 2,  # Repeat to ensure it's 2k characters
+        (
+            "Brandon is a software engineer who lives in San Francisco. "
+            "He enjoys hiking and often visits the trails in the Bay Area. "
+            "Brandon has a pet dog named Max, who is a golden retriever. "
+            "He loves reading science fiction books, and his favorite author is Isaac Asimov. "
+            "Brandon's favorite movie is Inception, and he enjoys watching it with his friends. "
+            "He is also a fan of Mexican cuisine, especially tacos and burritos. "
+            "Brandon plays the guitar and often performs at local open mic nights. "
+            "He is learning French and plans to visit Paris next year. "
+            "Brandon is passionate about technology and often attends tech meetups in the city. "
+            "He is also interested in AI and machine learning, and he is currently working on a project related to natural language processing. "
+            "Brandon's favorite color is blue, and he often wears blue shirts. "
+            "He enjoys cooking and often tries new recipes on weekends. "
+            "Brandon is a morning person and likes to start his day with a run in the park. "
+            "He is also a coffee enthusiast and enjoys trying different coffee blends. "
+            "Brandon is a member of a local book club and enjoys discussing books with fellow members. "
+            "He is also a fan of board games and often hosts game nights at his place. "
+            "Brandon is an advocate for environmental conservation and volunteers for local clean-up drives. "
+            "He is also a mentor for aspiring software developers and enjoys sharing his knowledge with others. "
+            "Brandon's favorite sport is basketball, and he often plays with his friends on weekends. "
+            "He is also a fan of the Golden State Warriors and enjoys watching their games. "
+        )
+        * 2,  # Repeat to ensure it's 2k characters
+    ]
+    file_paths = []
+    for i, content in enumerate(contents):
+        file_path = Path(tmpdir.join(f"long_file_{i}.txt"))
+        with open(file_path, "w") as f:
+            f.write(content)
+        file_paths.append(file_path)
+
+    file_sources = [
+        TextFileKnowledgeSource(file_path=path, metadata={"preference": "personal"})
+        for path in file_paths
+    ]
+    mock_vector_db.sources = file_sources
+    mock_vector_db.query.return_value = [
+        {
+            "context": "Brandon's favorite book is 'The Hitchhiker's Guide to the Galaxy'.",
+            "score": 0.9,
+        }
+    ]
+    # Perform a query
+    query = "What is Brandon's favorite book?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any(
+        "the hitchhiker's guide to the galaxy" in result["context"].lower()
+        for result in results
+    )
+    mock_vector_db.query.assert_called_once()
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_hybrid_string_and_files(mock_vector_db, tmpdir):
+    # Create string sources
+    string_contents = [
+        "Brandon is learning French.",
+        "Brandon visited Paris last summer.",
+    ]
+    string_sources = [
+        StringKnowledgeSource(content=content, metadata={"preference": "personal"})
+        for content in string_contents
+    ]
+
+    # Create file sources
+    file_contents = [
+        "Brandon prefers tea over coffee.",
+        "Brandon's favorite book is 'The Alchemist'.",
+    ]
+    file_paths = []
+    for i, content in enumerate(file_contents):
+        file_path = Path(tmpdir.join(f"file_{i}.txt"))
+        with open(file_path, "w") as f:
+            f.write(content)
+        file_paths.append(file_path)
+
+    file_sources = [
+        TextFileKnowledgeSource(file_path=path, metadata={"preference": "personal"})
+        for path in file_paths
+    ]
+
+    # Combine string and file sources
+    mock_vector_db.sources = string_sources + file_sources
+    mock_vector_db.query.return_value = [{"context": file_contents[1], "score": 0.9}]
+
+    # Perform a query
+    query = "What is Brandon's favorite book?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any("the alchemist" in result["context"].lower() for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_pdf_knowledge_source(mock_vector_db):
+    # Get the directory of the current file
+    current_dir = Path(__file__).parent
+    # Construct the path to the PDF file
+    pdf_path = current_dir / "crewai_quickstart.pdf"
+
+    # Create a PDFKnowledgeSource
+    pdf_source = PDFKnowledgeSource(
+        file_path=pdf_path, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [pdf_source]
+    mock_vector_db.query.return_value = [
+        {"context": "crewai create crew latest-ai-development", "score": 0.9}
+    ]
+
+    # Perform a query
+    query = "How do you create a crew?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any(
+        "crewai create crew latest-ai-development" in result["context"].lower()
+        for result in results
+    )
+    mock_vector_db.query.assert_called_once()
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_csv_knowledge_source(mock_vector_db, tmpdir):
+    """Test CSVKnowledgeSource with a simple CSV file."""
+
+    # Create a CSV file with sample data
+    csv_content = [
+        ["Name", "Age", "City"],
+        ["Brandon", "30", "New York"],
+        ["Alice", "25", "Los Angeles"],
+        ["Bob", "35", "Chicago"],
+    ]
+    csv_path = Path(tmpdir.join("data.csv"))
+    with open(csv_path, "w", encoding="utf-8") as f:
+        for row in csv_content:
+            f.write(",".join(row) + "\n")
+
+    # Create a CSVKnowledgeSource
+    csv_source = CSVKnowledgeSource(
+        file_path=csv_path, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [csv_source]
+    mock_vector_db.query.return_value = [
+        {"context": "Brandon is 30 years old.", "score": 0.9}
+    ]
+
+    # Perform a query
+    query = "How old is Brandon?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any("30" in result["context"] for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_json_knowledge_source(mock_vector_db, tmpdir):
+    """Test JSONKnowledgeSource with a simple JSON file."""
+
+    # Create a JSON file with sample data
+    json_data = {
+        "people": [
+            {"name": "Brandon", "age": 30, "city": "New York"},
+            {"name": "Alice", "age": 25, "city": "Los Angeles"},
+            {"name": "Bob", "age": 35, "city": "Chicago"},
+        ]
+    }
+    json_path = Path(tmpdir.join("data.json"))
+    with open(json_path, "w", encoding="utf-8") as f:
+        import json
+
+        json.dump(json_data, f)
+
+    # Create a JSONKnowledgeSource
+    json_source = JSONKnowledgeSource(
+        file_path=json_path, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [json_source]
+    mock_vector_db.query.return_value = [
+        {"context": "Alice lives in Los Angeles.", "score": 0.9}
+    ]
+
+    # Perform a query
+    query = "Where does Alice reside?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any("los angeles" in result["context"].lower() for result in results)
+    mock_vector_db.query.assert_called_once()
+
+
+def test_excel_knowledge_source(mock_vector_db, tmpdir):
+    """Test ExcelKnowledgeSource with a simple Excel file."""
+
+    # Create an Excel file with sample data
+    import pandas as pd
+
+    excel_data = {
+        "Name": ["Brandon", "Alice", "Bob"],
+        "Age": [30, 25, 35],
+        "City": ["New York", "Los Angeles", "Chicago"],
+    }
+    df = pd.DataFrame(excel_data)
+    excel_path = Path(tmpdir.join("data.xlsx"))
+    df.to_excel(excel_path, index=False)
+
+    # Create an ExcelKnowledgeSource
+    excel_source = ExcelKnowledgeSource(
+        file_path=excel_path, metadata={"preference": "personal"}
+    )
+    mock_vector_db.sources = [excel_source]
+    mock_vector_db.query.return_value = [
+        {"context": "Brandon is 30 years old.", "score": 0.9}
+    ]
+
+    # Perform a query
+    query = "What is Brandon's age?"
+    results = mock_vector_db.query(query)
+
+    # Assert that the correct information is retrieved
+    assert any("30" in result["context"] for result in results)
+    mock_vector_db.query.assert_called_once()
diff --git a/tests/pipeline/test_pipeline.py b/tests/pipeline/test_pipeline.py
index a08f185c8..bd0a38183 100644
--- a/tests/pipeline/test_pipeline.py
+++ b/tests/pipeline/test_pipeline.py
@@ -38,6 +38,7 @@ def mock_crew_factory():
 
         crew = MockCrew()
         crew.name = name
+        crew.knowledge = None
 
         task_output = TaskOutput(
             description="Test task", raw="Task output", agent="Test Agent"
@@ -67,6 +68,7 @@ def mock_crew_factory():
         crew.process = Process.sequential
         crew.config = None
         crew.cache = True
+        crew.embedder = None
 
         # Add non-empty agents and tasks
         mock_agent = MagicMock(spec=Agent)
diff --git a/uv.lock b/uv.lock
index ab78a63d0..a4b545d07 100644
--- a/uv.lock
+++ b/uv.lock
@@ -638,6 +638,18 @@ dependencies = [
 agentops = [
     { name = "agentops" },
 ]
+fastembed = [
+    { name = "fastembed" },
+]
+openpyxl = [
+    { name = "openpyxl" },
+]
+pandas = [
+    { name = "pandas" },
+]
+pdfplumber = [
+    { name = "pdfplumber" },
+]
 mem0 = [
     { name = "mem0ai" },
 ]
@@ -674,6 +686,7 @@ requires-dist = [
     { name = "click", specifier = ">=8.1.7" },
     { name = "crewai-tools", specifier = ">=0.14.0" },
     { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.14.0" },
+    { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
     { name = "instructor", specifier = ">=1.3.3" },
     { name = "json-repair", specifier = ">=0.25.2" },
     { name = "jsonref", specifier = ">=1.1.0" },
@@ -681,9 +694,12 @@ requires-dist = [
     { name = "litellm", specifier = ">=1.44.22" },
     { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" },
     { name = "openai", specifier = ">=1.13.3" },
+    { name = "openpyxl", marker = "extra == 'openpyxl'", specifier = ">=3.1.5" },
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From c119230fd675d8c48dd1ee241bcdaa9bf1ad8d3b Mon Sep 17 00:00:00 2001
From: Bob Conan <sufssl03@gmail.com>
Date: Wed, 20 Nov 2024 18:52:41 -0600
Subject: [PATCH 072/126] Updated README.md, fix typo(s) (#1637)

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index ceec198c3..c6be68dc1 100644
--- a/README.md
+++ b/README.md
@@ -100,7 +100,7 @@ You can now start developing your crew by editing the files in the `src/my_proje
 
 #### Example of a simple crew with a sequential process:
 
-Instatiate your crew:
+Instantiate your crew:
 
 ```shell
 crewai create crew latest-ai-development
@@ -399,7 +399,7 @@ Data collected includes:
 - Roles of agents in a crew
   - Understand high level use cases so we can build better tools, integrations and examples about it
 - Tools names available
-  - Understand out of the publically available tools, which ones are being used the most so we can improve them
+  - Understand out of the publicly available tools, which ones are being used the most so we can improve them
 
 Users can opt-in to Further Telemetry, sharing the complete telemetry data by setting the `share_crew` attribute to `True` on their Crews. Enabling `share_crew` results in the collection of detailed crew and task execution data, including `goal`, `backstory`, `context`, and `output` of tasks. This enables a deeper insight into usage patterns while respecting the user's choice to share.
 

From f8ca49d8df36cfbc8762b604ca94427cf4db0413 Mon Sep 17 00:00:00 2001
From: Andy Bromberg <abromberg@users.noreply.github.com>
Date: Wed, 20 Nov 2024 16:54:04 -0800
Subject: [PATCH 073/126] Update Perplexity example in documentation (#1623)

---
 docs/concepts/llms.mdx | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 5211e6652..798fea726 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -310,8 +310,8 @@ These are examples of how to configure LLMs for your agent.
     from crewai import LLM
 
     llm = LLM(
-        model="perplexity/mistral-7b-instruct",
-        base_url="https://api.perplexity.ai/v1",
+        model="llama-3.1-sonar-large-128k-online",
+        base_url="https://api.perplexity.ai/",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -400,4 +400,4 @@ This is particularly useful when working with OpenAI-compatible APIs or when you
 - **API Errors**: Check your API key, network connection, and rate limits.
 - **Unexpected Outputs**: Refine your prompts and adjust temperature or top_p.
 - **Performance Issues**: Consider using a more powerful model or optimizing your queries.
-- **Timeout Errors**: Increase the `timeout` parameter or optimize your input.
\ No newline at end of file
+- **Timeout Errors**: Increase the `timeout` parameter or optimize your input.

From 8f5f67de411fcb0606822f216f59676691be6c1a Mon Sep 17 00:00:00 2001
From: Gui Vieira <guilherme_vieira@me.com>
Date: Thu, 21 Nov 2024 15:33:20 -0300
Subject: [PATCH 074/126] Fix threading

---
 src/crewai/llm.py  | 35 ++++++++++++++++++++++-------------
 src/crewai/task.py | 10 +++++++---
 2 files changed, 29 insertions(+), 16 deletions(-)

diff --git a/src/crewai/llm.py b/src/crewai/llm.py
index 7ea8155a6..bfdaa4418 100644
--- a/src/crewai/llm.py
+++ b/src/crewai/llm.py
@@ -1,6 +1,6 @@
-import io
 import logging
 import sys
+import threading
 import warnings
 from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Union
@@ -13,16 +13,25 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 )
 
 
-class FilteredStream(io.StringIO):
-    def write(self, s):
-        if (
-            "Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
-            in s
-            or "LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True`"
-            in s
-        ):
-            return
-        super().write(s)
+class FilteredStream:
+    def __init__(self, original_stream):
+        self._original_stream = original_stream
+        self._lock = threading.Lock()
+
+    def write(self, s) -> int:
+        with self._lock:
+            if (
+                "Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
+                in s
+                or "LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True`"
+                in s
+            ):
+                return 0
+            return self._original_stream.write(s)
+
+    def flush(self):
+        with self._lock:
+            return self._original_stream.flush()
 
 
 LLM_CONTEXT_WINDOW_SIZES = {
@@ -60,8 +69,8 @@ def suppress_warnings():
         # Redirect stdout and stderr
         old_stdout = sys.stdout
         old_stderr = sys.stderr
-        sys.stdout = FilteredStream()
-        sys.stderr = FilteredStream()
+        sys.stdout = FilteredStream(old_stdout)
+        sys.stderr = FilteredStream(old_stderr)
 
         try:
             yield
diff --git a/src/crewai/task.py b/src/crewai/task.py
index 21278af98..59415f1e9 100644
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -20,10 +20,10 @@ from pydantic import (
 from pydantic_core import PydanticCustomError
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
-from crewai.tools.base_tool import BaseTool
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry.telemetry import Telemetry
+from crewai.tools.base_tool import BaseTool
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter, convert_to_model
 from crewai.utilities.i18n import I18N
@@ -208,7 +208,9 @@ class Task(BaseModel):
         """Execute the task asynchronously."""
         future: Future[TaskOutput] = Future()
         threading.Thread(
-            target=self._execute_task_async, args=(agent, context, tools, future)
+            daemon=True,
+            target=self._execute_task_async,
+            args=(agent, context, tools, future),
         ).start()
         return future
 
@@ -277,7 +279,9 @@ class Task(BaseModel):
             content = (
                 json_output
                 if json_output
-                else pydantic_output.model_dump_json() if pydantic_output else result
+                else pydantic_output.model_dump_json()
+                if pydantic_output
+                else result
             )
             self._save_file(content)
 

From 8cf1cd5a62ee68d57445a1eacd3407fbd9808106 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Mon, 25 Nov 2024 10:05:15 -0300
Subject: [PATCH 075/126] preparing new version

---
 docs/concepts/knowledge.mdx                   | 18 +++---
 .../how-to/before-and-after-kickoff-hooks.mdx | 59 +++++++++++++++++++
 docs/quickstart.mdx                           | 48 +++++++++++----
 pyproject.toml                                |  4 +-
 src/crewai/__init__.py                        |  2 +-
 src/crewai/cli/templates/crew/crew.py         | 14 ++++-
 src/crewai/cli/templates/crew/pyproject.toml  |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml  |  2 +-
 .../cli/templates/pipeline/pyproject.toml     |  2 +-
 .../templates/pipeline_router/pyproject.toml  |  2 +-
 src/crewai/cli/templates/tool/pyproject.toml  |  2 +-
 uv.lock                                       | 13 ++--
 12 files changed, 137 insertions(+), 31 deletions(-)
 create mode 100644 docs/how-to/before-and-after-kickoff-hooks.mdx

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index 2afb1b568..ce0203e13 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -1,6 +1,6 @@
 ---
 title: Knowledge
-description: What is knowledge in CrewAI and how to use it.
+description: Understand what knowledge is in CrewAI and how to effectively use it.
 icon: book
 ---
 
@@ -8,7 +8,14 @@ icon: book
 
 ## Introduction
 
+Knowledge in CrewAI serves as a foundational component for enriching AI agents with contextual and relevant information. It enables agents to access and utilize structured data sources during their execution processes, making them more intelligent and responsive.
+
 The Knowledge class in CrewAI provides a powerful way to manage and query knowledge sources for your AI agents. This guide will show you how to implement knowledge management in your CrewAI projects.
+
+## What is Knowledge?
+
+The `Knowledge` class in CrewAI manages various sources that store information, which can be queried and retrieved by AI agents. This modular approach allows you to integrate diverse data formats such as text, PDFs, spreadsheets, and more into your AI workflows.
+
 Additionally, we have specific tools for generate knowledge sources for strings, text files, PDF's, and Spreadsheets. You can expand on any source type by extending the `KnowledgeSource` class.
 
 ## Basic Implementation
@@ -25,17 +32,14 @@ string_source = StringKnowledgeSource(
     content=content, metadata={"preference": "personal"}
 )
 
-
-llm = LLM(model="gpt-4o-mini", temperature=0)
-  # Create an agent with the knowledge store
+# Create an agent with the knowledge store
 agent = Agent(
     role="About User",
     goal="You know everything about the user.",
     backstory="""You are a master at understanding people and their preferences.""",
-    verbose=True,
-    allow_delegation=False,
-    llm=llm,
+    verbose=True
 )
+
 task = Task(
     description="Answer the following questions about the user: {question}",
     expected_output="An answer to the question.",
diff --git a/docs/how-to/before-and-after-kickoff-hooks.mdx b/docs/how-to/before-and-after-kickoff-hooks.mdx
new file mode 100644
index 000000000..83058ce3c
--- /dev/null
+++ b/docs/how-to/before-and-after-kickoff-hooks.mdx
@@ -0,0 +1,59 @@
+---
+title: Before and After Kickoff Hooks
+description: Learn how to use before and after kickoff hooks in CrewAI
+---
+
+CrewAI provides hooks that allow you to execute code before and after a crew's kickoff. These hooks are useful for preprocessing inputs or post-processing results.
+
+## Before Kickoff Hook
+
+The before kickoff hook is executed before the crew starts its tasks. It receives the input dictionary and can modify it before passing it to the crew. You can use this hook to set up your environment, load necessary data, or preprocess your inputs. This is useful in scenarios where the input data might need enrichment or validation before being processed by the crew.
+
+Here's an example of defining a before kickoff function in your `crew.py`:
+
+```python
+from crewai import CrewBase, before_kickoff
+
+@CrewBase
+class MyCrew:
+    @before_kickoff
+    def prepare_data(self, inputs):
+        # Preprocess or modify inputs
+        inputs['processed'] = True
+        return inputs
+
+#...
+```
+
+In this example, the prepare_data function modifies the inputs by adding a new key-value pair indicating that the inputs have been processed.
+
+## After Kickoff Hook
+
+The after kickoff hook is executed after the crew has completed its tasks. It receives the result object, which contains the outputs of the crew's execution. This hook is ideal for post-processing results, such as logging, data transformation, or further analysis.
+
+Here's how you can define an after kickoff function in your `crew.py`:
+
+```python
+from crewai import CrewBase, after_kickoff
+
+@CrewBase
+class MyCrew:
+    @after_kickoff
+    def log_results(self, result):
+        # Log or modify the results
+        print("Crew execution completed with result:", result)
+        return result
+
+# ...
+```
+
+
+In the `log_results` function, the results of the crew execution are simply printed out. You can extend this to perform more complex operations such as sending notifications or integrating with other services.
+
+## Utilizing Both Hooks
+
+Both hooks can be used together to provide a comprehensive setup and teardown process for your crew's execution. They are particularly useful in maintaining clean code architecture by separating concerns and enhancing the modularity of your CrewAI implementations.
+
+## Conclusion
+
+Before and after kickoff hooks in CrewAI offer powerful ways to interact with the lifecycle of a crew's execution. By understanding and utilizing these hooks, you can greatly enhance the robustness and flexibility of your AI agents.
diff --git a/docs/quickstart.mdx b/docs/quickstart.mdx
index ef149bfcc..246bbdf84 100644
--- a/docs/quickstart.mdx
+++ b/docs/quickstart.mdx
@@ -8,7 +8,7 @@ icon: rocket
 
 Let's create a simple crew that will help us `research` and `report` on the `latest AI developments` for a given topic or subject.
 
-Before we proceed, make sure you have `crewai` and `crewai-tools` installed. 
+Before we proceed, make sure you have `crewai` and `crewai-tools` installed.
 If you haven't installed them yet, you can do so by following the [installation guide](/installation).
 
 Follow the steps below to get crewing! 🚣‍♂️
@@ -23,7 +23,7 @@ Follow the steps below to get crewing! 🚣‍♂️
       ```
     </CodeGroup>
   </Step>
-  <Step title="Modify your `agents.yaml` file">  
+  <Step title="Modify your `agents.yaml` file">
   <Tip>
   You can also modify the agents as needed to fit your use case or copy and paste as is to your project.
   Any variable interpolated in your `agents.yaml` and `tasks.yaml` files like `{topic}` will be replaced by the value of the variable in the `main.py` file.
@@ -39,7 +39,7 @@ Follow the steps below to get crewing! 🚣‍♂️
         You're a seasoned researcher with a knack for uncovering the latest
         developments in {topic}. Known for your ability to find the most relevant
         information and present it in a clear and concise manner.
-          
+
     reporting_analyst:
       role: >
         {topic} Reporting Analyst
@@ -51,7 +51,7 @@ Follow the steps below to get crewing! 🚣‍♂️
         it easy for others to understand and act on the information you provide.
     ```
   </Step>
-  <Step title="Modify your `tasks.yaml` file">  
+  <Step title="Modify your `tasks.yaml` file">
     ```yaml tasks.yaml
     # src/latest_ai_development/config/tasks.yaml
     research_task:
@@ -73,8 +73,8 @@ Follow the steps below to get crewing! 🚣‍♂️
       agent: reporting_analyst
       output_file: report.md
     ```
-  </Step>   
-  <Step title="Modify your `crew.py` file">  
+  </Step>
+  <Step title="Modify your `crew.py` file">
     ```python crew.py
     # src/latest_ai_development/crew.py
     from crewai import Agent, Crew, Process, Task
@@ -121,10 +121,34 @@ Follow the steps below to get crewing! 🚣‍♂️
           tasks=self.tasks, # Automatically created by the @task decorator
           process=Process.sequential,
           verbose=True,
-        ) 
+        )
     ```
   </Step>
-  <Step title="Feel free to pass custom inputs to your crew"> 
+  <Step title="[Optional] Add before and after crew functions">
+    ```python crew.py
+    # src/latest_ai_development/crew.py
+    from crewai import Agent, Crew, Process, Task
+    from crewai.project import CrewBase, agent, crew, task, before_kickoff, after_kickoff
+    from crewai_tools import SerperDevTool
+
+    @CrewBase
+    class LatestAiDevelopmentCrew():
+      """LatestAiDevelopment crew"""
+
+      @before_kickoff
+      def before_kickoff_function(self, inputs):
+        print(f"Before kickoff function with inputs: {inputs}")
+        return inputs # You can return the inputs or modify them as needed
+
+      @after_kickoff
+      def after_kickoff_function(self, result):
+        print(f"After kickoff function with result: {result}")
+        return result # You can return the result or modify it as needed
+
+      # ... remaining code
+    ```
+  </Step>
+  <Step title="Feel free to pass custom inputs to your crew">
   For example, you can pass the `topic` input to your crew to customize the research and reporting.
     ```python main.py
     #!/usr/bin/env python
@@ -237,14 +261,14 @@ Follow the steps below to get crewing! 🚣‍♂️
 ### Note on Consistency in Naming
 
 The names you use in your YAML files (`agents.yaml` and `tasks.yaml`) should match the method names in your Python code.
-For example, you can reference the agent for specific tasks from `tasks.yaml` file. 
+For example, you can reference the agent for specific tasks from `tasks.yaml` file.
 This naming consistency allows CrewAI to automatically link your configurations with your code; otherwise, your task won't recognize the reference properly.
 
 #### Example References
 
 <Tip>
   Note how we use the same name for the agent in the `agents.yaml` (`email_summarizer`) file as the method name in the `crew.py` (`email_summarizer`) file.
-</Tip>  
+</Tip>
 
 ```yaml agents.yaml
 email_summarizer:
@@ -281,6 +305,8 @@ Use the annotations to properly reference the agent and task in the `crew.py` fi
 * `@task`
 * `@crew`
 * `@tool`
+* `@before_kickoff`
+* `@after_kickoff`
 * `@callback`
 * `@output_json`
 * `@output_pydantic`
@@ -304,7 +330,7 @@ def email_summarizer_task(self) -> Task:
 
 <Tip>
 In addition to the [sequential process](../how-to/sequential-process), you can use the [hierarchical process](../how-to/hierarchical-process),
-which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results. 
+which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results.
 You can learn more about the core concepts [here](/concepts).
 </Tip>
 
diff --git a/pyproject.toml b/pyproject.toml
index 2dbc00e24..4bd416ab5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.80.0"
+version = "0.83.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
@@ -29,6 +29,8 @@ dependencies = [
     "tomli-w>=1.1.0",
     "tomli>=2.0.2",
     "chromadb>=0.5.18",
+    "pdfplumber>=0.11.4",
+    "openpyxl>=3.1.5",
 ]
 
 [project.urls]
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 6cfa381de..34d7f17c9 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -16,7 +16,7 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.80.0"
+__version__ = "0.83.0"
 __all__ = [
     "Agent",
     "Crew",
diff --git a/src/crewai/cli/templates/crew/crew.py b/src/crewai/cli/templates/crew/crew.py
index c47315415..6f8e66c4a 100644
--- a/src/crewai/cli/templates/crew/crew.py
+++ b/src/crewai/cli/templates/crew/crew.py
@@ -1,5 +1,5 @@
 from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
+from crewai.project import CrewBase, agent, crew, task, before_kickoff, after_kickoff
 
 # Uncomment the following line to use an example of a custom tool
 # from {{folder_name}}.tools.custom_tool import MyCustomTool
@@ -14,6 +14,18 @@ class {{crew_name}}():
 	agents_config = 'config/agents.yaml'
 	tasks_config = 'config/tasks.yaml'
 
+	@before_kickoff # Optional hook to be executed before the crew starts
+	def pull_data_example(self, inputs):
+		# Example of pulling data from an external API, dynamically changing the inputs
+		inputs['extra_data'] = "This is extra data"
+		return inputs
+
+	@after_kickoff # Optional hook to be executed after the crew has finished
+	def log_results(self, output):
+		# Example of logging results, dynamically changing the output
+		print(f"Results: {output}")
+		return output
+
 	@agent
 	def researcher(self) -> Agent:
 		return Agent(
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index a5ab36877..1e456c725 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.80.0,<1.0.0"
+    "crewai[tools]>=0.83.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index e863f20b7..575aaf086 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.80.0,<1.0.0",
+    "crewai[tools]>=0.83.0,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 60294740d..d12dccf11 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.80.0,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.83.0,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 7c022b1f7..06487bcfa 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.80.0,<1.0.0"
+    "crewai[tools]>=0.83.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 4142c325d..7c1afddfa 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.80.0"
+    "crewai[tools]>=0.83.0"
 ]
 
diff --git a/uv.lock b/uv.lock
index a4b545d07..baff09ac8 100644
--- a/uv.lock
+++ b/uv.lock
@@ -608,7 +608,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.80.0"
+version = "0.83.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -622,9 +622,11 @@ dependencies = [
     { name = "langchain" },
     { name = "litellm" },
     { name = "openai" },
+    { name = "openpyxl" },
     { name = "opentelemetry-api" },
     { name = "opentelemetry-exporter-otlp-proto-http" },
     { name = "opentelemetry-sdk" },
+    { name = "pdfplumber" },
     { name = "pydantic" },
     { name = "python-dotenv" },
     { name = "pyvis" },
@@ -641,6 +643,9 @@ agentops = [
 fastembed = [
     { name = "fastembed" },
 ]
+mem0 = [
+    { name = "mem0ai" },
+]
 openpyxl = [
     { name = "openpyxl" },
 ]
@@ -650,9 +655,6 @@ pandas = [
 pdfplumber = [
     { name = "pdfplumber" },
 ]
-mem0 = [
-    { name = "mem0ai" },
-]
 tools = [
     { name = "crewai-tools" },
 ]
@@ -694,11 +696,13 @@ requires-dist = [
     { name = "litellm", specifier = ">=1.44.22" },
     { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" },
     { name = "openai", specifier = ">=1.13.3" },
+    { name = "openpyxl", specifier = ">=3.1.5" },
     { name = "openpyxl", marker = "extra == 'openpyxl'", specifier = ">=3.1.5" },
     { name = "opentelemetry-api", specifier = ">=1.22.0" },
     { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.22.0" },
     { name = "opentelemetry-sdk", specifier = ">=1.22.0" },
     { name = "pandas", marker = "extra == 'pandas'", specifier = ">=2.2.3" },
+    { name = "pdfplumber", specifier = ">=0.11.4" },
     { name = "pdfplumber", marker = "extra == 'pdfplumber'", specifier = ">=0.11.4" },
     { name = "pydantic", specifier = ">=2.4.2" },
     { name = "python-dotenv", specifier = ">=1.0.0" },
@@ -952,7 +956,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c1/8b/5fe2cc11fee489817272089c4203e679c63b570a5aaeb18d852ae3cbba6a/et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa", size = 18059 },
 ]
 
-
 [[package]]
 name = "exceptiongroup"
 version = "1.2.2"

From 63ecb7395df9a9d69b0ef429213b8be410732b35 Mon Sep 17 00:00:00 2001
From: Vini Brasil <vini@hey.com>
Date: Mon, 25 Nov 2024 15:57:47 -0300
Subject: [PATCH 076/126] Log in to Tool Repository on `crewai login` (#1650)

This commit adds an extra step to `crewai login` to ensure users also
log in to Tool Repository, that is, exchanging their Auth0 tokens for a
Tool Repository username and password to be used by UV downloads and API
tool uploads.
---
 src/crewai/cli/authentication/main.py      | 18 +++++++++++++++++-
 src/crewai/cli/authentication/token.py     | 10 ++++++++++
 src/crewai/cli/command.py                  |  2 +-
 src/crewai/cli/plus_api.py                 |  2 +-
 src/crewai/cli/run_crew.py                 |  3 ++-
 src/crewai/cli/utils.py                    | 15 ---------------
 src/crewai/cli/version.py                  |  6 ++++++
 tests/cli/authentication/test_auth_main.py |  8 ++++++--
 tests/cli/deploy/test_deploy_main.py       |  2 +-
 9 files changed, 44 insertions(+), 22 deletions(-)
 create mode 100644 src/crewai/cli/authentication/token.py
 create mode 100644 src/crewai/cli/version.py

diff --git a/src/crewai/cli/authentication/main.py b/src/crewai/cli/authentication/main.py
index 543f06844..c64045801 100644
--- a/src/crewai/cli/authentication/main.py
+++ b/src/crewai/cli/authentication/main.py
@@ -7,6 +7,7 @@ from rich.console import Console
 
 from .constants import AUTH0_AUDIENCE, AUTH0_CLIENT_ID, AUTH0_DOMAIN
 from .utils import TokenManager, validate_token
+from crewai.cli.tools.main import ToolCommand
 
 console = Console()
 
@@ -63,7 +64,22 @@ class AuthenticationCommand:
                 validate_token(token_data["id_token"])
                 expires_in = 360000  # Token expiration time in seconds
                 self.token_manager.save_tokens(token_data["access_token"], expires_in)
-                console.print("\nWelcome to CrewAI+ !!", style="green")
+
+                try:
+                    ToolCommand().login()
+                except Exception:
+                    console.print(
+                        "\n[bold yellow]Warning:[/bold yellow] Authentication with the Tool Repository failed.",
+                        style="yellow",
+                    )
+                    console.print(
+                        "Other features will work normally, but you may experience limitations "
+                        "with downloading and publishing tools."
+                        "\nRun [bold]crewai login[/bold] to try logging in again.\n",
+                        style="yellow",
+                    )
+
+                console.print("\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n")
                 return
 
             if token_data["error"] not in ("authorization_pending", "slow_down"):
diff --git a/src/crewai/cli/authentication/token.py b/src/crewai/cli/authentication/token.py
new file mode 100644
index 000000000..889fdc2eb
--- /dev/null
+++ b/src/crewai/cli/authentication/token.py
@@ -0,0 +1,10 @@
+from .utils import TokenManager
+
+def get_auth_token() -> str:
+    """Get the authentication token."""
+    access_token = TokenManager().get_token()
+    if not access_token:
+        raise Exception()
+    return access_token
+
+
diff --git a/src/crewai/cli/command.py b/src/crewai/cli/command.py
index f05fe237f..f2af92bf5 100644
--- a/src/crewai/cli/command.py
+++ b/src/crewai/cli/command.py
@@ -2,7 +2,7 @@ import requests
 from requests.exceptions import JSONDecodeError
 from rich.console import Console
 from crewai.cli.plus_api import PlusAPI
-from crewai.cli.utils import get_auth_token
+from crewai.cli.authentication.token import get_auth_token
 from crewai.telemetry.telemetry import Telemetry
 
 console = Console()
diff --git a/src/crewai/cli/plus_api.py b/src/crewai/cli/plus_api.py
index 04f6fb8ff..2fce0d6d8 100644
--- a/src/crewai/cli/plus_api.py
+++ b/src/crewai/cli/plus_api.py
@@ -1,7 +1,7 @@
 from typing import Optional
 import requests
 from os import getenv
-from crewai.cli.utils import get_crewai_version
+from crewai.cli.version import get_crewai_version
 from urllib.parse import urljoin
 
 
diff --git a/src/crewai/cli/run_crew.py b/src/crewai/cli/run_crew.py
index 5450cf32b..95b560109 100644
--- a/src/crewai/cli/run_crew.py
+++ b/src/crewai/cli/run_crew.py
@@ -3,7 +3,8 @@ import subprocess
 import click
 from packaging import version
 
-from crewai.cli.utils import get_crewai_version, read_toml
+from crewai.cli.utils import read_toml
+from crewai.cli.version import get_crewai_version
 
 
 def run_crew() -> None:
diff --git a/src/crewai/cli/utils.py b/src/crewai/cli/utils.py
index 25da9e31a..2daba4111 100644
--- a/src/crewai/cli/utils.py
+++ b/src/crewai/cli/utils.py
@@ -1,4 +1,3 @@
-import importlib.metadata
 import os
 import shutil
 import sys
@@ -9,7 +8,6 @@ import click
 import tomli
 from rich.console import Console
 
-from crewai.cli.authentication.utils import TokenManager
 from crewai.cli.constants import ENV_VARS
 
 if sys.version_info >= (3, 11):
@@ -137,11 +135,6 @@ def _get_nested_value(data: Dict[str, Any], keys: List[str]) -> Any:
     return reduce(dict.__getitem__, keys, data)
 
 
-def get_crewai_version() -> str:
-    """Get the version number of CrewAI running the CLI"""
-    return importlib.metadata.version("crewai")
-
-
 def fetch_and_json_env_file(env_file_path: str = ".env") -> dict:
     """Fetch the environment variables from a .env file and return them as a dictionary."""
     try:
@@ -166,14 +159,6 @@ def fetch_and_json_env_file(env_file_path: str = ".env") -> dict:
     return {}
 
 
-def get_auth_token() -> str:
-    """Get the authentication token."""
-    access_token = TokenManager().get_token()
-    if not access_token:
-        raise Exception()
-    return access_token
-
-
 def tree_copy(source, destination):
     """Copies the entire directory structure from the source to the destination."""
     for item in os.listdir(source):
diff --git a/src/crewai/cli/version.py b/src/crewai/cli/version.py
new file mode 100644
index 000000000..543be9c32
--- /dev/null
+++ b/src/crewai/cli/version.py
@@ -0,0 +1,6 @@
+import importlib.metadata
+
+def get_crewai_version() -> str:
+    """Get the version number of CrewAI running the CLI"""
+    return importlib.metadata.version("crewai")
+
diff --git a/tests/cli/authentication/test_auth_main.py b/tests/cli/authentication/test_auth_main.py
index c56968aab..4466cc999 100644
--- a/tests/cli/authentication/test_auth_main.py
+++ b/tests/cli/authentication/test_auth_main.py
@@ -43,10 +43,11 @@ class TestAuthenticationCommand(unittest.TestCase):
         mock_print.assert_any_call("2. Enter the following code: ", "ABCDEF")
         mock_open.assert_called_once_with("https://example.com")
 
+    @patch("crewai.cli.authentication.main.ToolCommand")
     @patch("crewai.cli.authentication.main.requests.post")
     @patch("crewai.cli.authentication.main.validate_token")
     @patch("crewai.cli.authentication.main.console.print")
-    def test_poll_for_token_success(self, mock_print, mock_validate_token, mock_post):
+    def test_poll_for_token_success(self, mock_print, mock_validate_token, mock_post, mock_tool):
         mock_response = MagicMock()
         mock_response.status_code = 200
         mock_response.json.return_value = {
@@ -55,10 +56,13 @@ class TestAuthenticationCommand(unittest.TestCase):
         }
         mock_post.return_value = mock_response
 
+        mock_instance = mock_tool.return_value
+        mock_instance.login.return_value = None
+
         self.auth_command._poll_for_token({"device_code": "123456"})
 
         mock_validate_token.assert_called_once_with("TOKEN")
-        mock_print.assert_called_once_with("\nWelcome to CrewAI+ !!", style="green")
+        mock_print.assert_called_once_with("\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n")
 
     @patch("crewai.cli.authentication.main.requests.post")
     @patch("crewai.cli.authentication.main.console.print")
diff --git a/tests/cli/deploy/test_deploy_main.py b/tests/cli/deploy/test_deploy_main.py
index 385dbb8a5..bf1198a0b 100644
--- a/tests/cli/deploy/test_deploy_main.py
+++ b/tests/cli/deploy/test_deploy_main.py
@@ -260,6 +260,6 @@ class TestDeployCommand(unittest.TestCase):
         self.assertEqual(project_name, "test_project")
 
     def test_get_crewai_version(self):
-        from crewai.cli.utils import get_crewai_version
+        from crewai.cli.version import get_crewai_version
 
         assert isinstance(get_crewai_version(), str)

From 6fe308202e99b706f6925b6968d5209ee6d15e17 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Mon, 25 Nov 2024 20:37:27 +0000
Subject: [PATCH 077/126] add knowledge to mint.json

---
 docs/mint.json | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/mint.json b/docs/mint.json
index 3ea9f5baf..d5aa8cb8f 100644
--- a/docs/mint.json
+++ b/docs/mint.json
@@ -68,6 +68,7 @@
         "concepts/tasks",
         "concepts/crews",
         "concepts/flows",
+        "concepts/knowledge",
         "concepts/llms",
         "concepts/processes",
         "concepts/collaboration",

From 4069b621d540a493afd685a706eccbab1dbcff46 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 26 Nov 2024 09:41:14 -0500
Subject: [PATCH 078/126]  Improve typed task outputs (#1651)

* V1 working

* clean up imports and prints

* more clean up and add tests

* fixing tests

* fix test

* fix linting

* Fix tests

* Fix linting

* add doc string as requested by eduardo
---
 src/crewai/agent.py               | 24 ++++++++++++++--
 src/crewai/task.py                |  4 +--
 src/crewai/translations/en.json   |  5 ++--
 src/crewai/utilities/converter.py | 37 +++++++++++++++++++++++-
 tests/utilities/test_converter.py | 48 +++++++++++++++++++++++++++++--
 5 files changed, 107 insertions(+), 11 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index d17cbbdfe..386a7cc57 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -11,10 +11,12 @@ from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.cli.constants import ENV_VARS
 from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
+from crewai.task import Task
 from crewai.tools import BaseTool
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
+from crewai.utilities.converter import generate_model_description
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
 
@@ -237,7 +239,7 @@ class Agent(BaseAgent):
 
     def execute_task(
         self,
-        task: Any,
+        task: Task,
         context: Optional[str] = None,
         tools: Optional[List[BaseTool]] = None,
     ) -> str:
@@ -256,6 +258,22 @@ class Agent(BaseAgent):
 
         task_prompt = task.prompt()
 
+        # If the task requires output in JSON or Pydantic format,
+        # append specific instructions to the task prompt to ensure
+        # that the final answer does not include any code block markers
+        if task.output_json or task.output_pydantic:
+            # Generate the schema based on the output format
+            if task.output_json:
+                # schema = json.dumps(task.output_json, indent=2)
+                schema = generate_model_description(task.output_json)
+
+            elif task.output_pydantic:
+                schema = generate_model_description(task.output_pydantic)
+
+            task_prompt += "\n" + self.i18n.slice("formatted_task_instructions").format(
+                output_format=schema
+            )
+
         if context:
             task_prompt = self.i18n.slice("task_with_context").format(
                 task=task_prompt, context=context
@@ -277,8 +295,8 @@ class Agent(BaseAgent):
         if self.crew and self.crew.knowledge:
             knowledge_snippets = self.crew.knowledge.query([task.prompt()])
             valid_snippets = [
-                result["context"] 
-                for result in knowledge_snippets 
+                result["context"]
+                for result in knowledge_snippets
                 if result and result.get("context")
             ]
             if valid_snippets:
diff --git a/src/crewai/task.py b/src/crewai/task.py
index 59415f1e9..af5b34c54 100644
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -279,9 +279,7 @@ class Task(BaseModel):
             content = (
                 json_output
                 if json_output
-                else pydantic_output.model_dump_json()
-                if pydantic_output
-                else result
+                else pydantic_output.model_dump_json() if pydantic_output else result
             )
             self._save_file(content)
 
diff --git a/src/crewai/translations/en.json b/src/crewai/translations/en.json
index aad49ff5f..d79076bb7 100644
--- a/src/crewai/translations/en.json
+++ b/src/crewai/translations/en.json
@@ -11,7 +11,7 @@
     "role_playing": "You are {role}. {backstory}\nYour personal goal is: {goal}",
     "tools": "\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\n{tools}\n\nUse the following format:\n\nThought: you should always think about what to do\nAction: the action to take, only one name of [{tool_names}], just the name, exactly as it's written.\nAction Input: the input to the action, just a simple python dictionary, enclosed in curly braces, using \" to wrap keys and values.\nObservation: the result of the action\n\nOnce all necessary information is gathered:\n\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n",
     "no_tools": "\nTo give my best complete final answer to the task use the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!",
-    "format": "I MUST either use a tool (use one at time) OR give my best final answer not both at the same time. To Use the following format:\n\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action, dictionary enclosed in curly braces\nObservation: the result of the action\n... (this Thought/Action/Action Input/Result can repeat N times)\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n ",
+    "format": "I MUST either use a tool (use one at time) OR give my best final answer not both at the same time. To Use the following format:\n\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action, dictionary enclosed in curly braces\nObservation: the result of the action\n... (this Thought/Action/Action Input/Result can repeat N times)\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n",
     "final_answer_format": "If you don't need to use any more tools, you must give your best complete final answer, make sure it satisfy the expect criteria, use the EXACT format below:\n\nThought: I now can give a great answer\nFinal Answer: my best complete final answer to the task.\n\n",
     "format_without_tools": "\nSorry, I didn't use the right format. I MUST either use a tool (among the available ones), OR give my best final answer.\nI just remembered the expected format I must follow:\n\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Result can repeat N times)\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n",
     "task_with_context": "{task}\n\nThis is the context you're working with:\n{context}",
@@ -21,7 +21,8 @@
     "summarizer_system_message": "You are a helpful assistant that summarizes text.",
     "sumamrize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
     "summary": "This is a summary of our conversation so far:\n{merged_summary}",
-    "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared."
+    "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
+    "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python."
   },
   "errors": {
     "force_final_answer_error": "You can't keep going, this was the best you could do.\n {formatted_answer.text}",
diff --git a/src/crewai/utilities/converter.py b/src/crewai/utilities/converter.py
index 4d0af67ca..ba958ddc6 100644
--- a/src/crewai/utilities/converter.py
+++ b/src/crewai/utilities/converter.py
@@ -1,6 +1,6 @@
 import json
 import re
-from typing import Any, Optional, Type, Union
+from typing import Any, Optional, Type, Union, get_args, get_origin
 
 from pydantic import BaseModel, ValidationError
 
@@ -214,3 +214,38 @@ def create_converter(
         raise Exception("No output converter found or set.")
 
     return converter
+
+
+def generate_model_description(model: Type[BaseModel]) -> str:
+    """
+    Generate a string description of a Pydantic model's fields and their types.
+
+    This function takes a Pydantic model class and returns a string that describes
+    the model's fields and their respective types. The description includes handling
+    of complex types such as `Optional`, `List`, and `Dict`, as well as nested Pydantic
+    models.
+    """
+
+    def describe_field(field_type):
+        origin = get_origin(field_type)
+        args = get_args(field_type)
+
+        if origin is Union and type(None) in args:
+            non_none_args = [arg for arg in args if arg is not type(None)]
+            return f"Optional[{describe_field(non_none_args[0])}]"
+        elif origin is list:
+            return f"List[{describe_field(args[0])}]"
+        elif origin is dict:
+            key_type = describe_field(args[0])
+            value_type = describe_field(args[1])
+            return f"Dict[{key_type}, {value_type}]"
+        elif isinstance(field_type, type) and issubclass(field_type, BaseModel):
+            return generate_model_description(field_type)
+        else:
+            return field_type.__name__
+
+    fields = model.__annotations__
+    field_descriptions = [
+        f'"{name}": {describe_field(type_)}' for name, type_ in fields.items()
+    ]
+    return "{\n  " + ",\n  ".join(field_descriptions) + "\n}"
diff --git a/tests/utilities/test_converter.py b/tests/utilities/test_converter.py
index 0bb6b7263..c63d6dba3 100644
--- a/tests/utilities/test_converter.py
+++ b/tests/utilities/test_converter.py
@@ -1,7 +1,10 @@
 import json
+from typing import Dict, List, Optional
 from unittest.mock import MagicMock, Mock, patch
 
 import pytest
+from pydantic import BaseModel
+
 from crewai.llm import LLM
 from crewai.utilities.converter import (
     Converter,
@@ -9,12 +12,11 @@ from crewai.utilities.converter import (
     convert_to_model,
     convert_with_instructions,
     create_converter,
+    generate_model_description,
     get_conversion_instructions,
     handle_partial_json,
     validate_model,
 )
-from pydantic import BaseModel
-
 from crewai.utilities.pydantic_schema_parser import PydanticSchemaParser
 
 
@@ -269,3 +271,45 @@ def test_create_converter_fails_without_agent_or_converter_cls():
         create_converter(
             llm=Mock(), text="Sample", model=SimpleModel, instructions="Convert"
         )
+
+
+def test_generate_model_description_simple_model():
+    description = generate_model_description(SimpleModel)
+    expected_description = '{\n  "name": str,\n  "age": int\n}'
+    assert description == expected_description
+
+
+def test_generate_model_description_nested_model():
+    description = generate_model_description(NestedModel)
+    expected_description = (
+        '{\n  "id": int,\n  "data": {\n  "name": str,\n  "age": int\n}\n}'
+    )
+    assert description == expected_description
+
+
+def test_generate_model_description_optional_field():
+    class ModelWithOptionalField(BaseModel):
+        name: Optional[str]
+        age: int
+
+    description = generate_model_description(ModelWithOptionalField)
+    expected_description = '{\n  "name": Optional[str],\n  "age": int\n}'
+    assert description == expected_description
+
+
+def test_generate_model_description_list_field():
+    class ModelWithListField(BaseModel):
+        items: List[int]
+
+    description = generate_model_description(ModelWithListField)
+    expected_description = '{\n  "items": List[int]\n}'
+    assert description == expected_description
+
+
+def test_generate_model_description_dict_field():
+    class ModelWithDictField(BaseModel):
+        attributes: Dict[str, int]
+
+    description = generate_model_description(ModelWithDictField)
+    expected_description = '{\n  "attributes": Dict[str, int]\n}'
+    assert description == expected_description

From 49d173a02dd7f61fa3670af7d43b099e4f9a6c32 Mon Sep 17 00:00:00 2001
From: Bowen Liang <bowenliang@apache.org>
Date: Wed, 27 Nov 2024 00:08:50 +0800
Subject: [PATCH 079/126]  Update Github actions (#1639)

* actions/checkout@v4

* actions/cache@v4

* actions/setup-python@v5

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 .github/workflows/linter.yml           | 2 +-
 .github/workflows/mkdocs.yml           | 8 ++++----
 .github/workflows/security-checker.yml | 2 +-
 .github/workflows/type-checker.yml     | 2 +-
 4 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/linter.yml b/.github/workflows/linter.yml
index a7223c506..7ced70df9 100644
--- a/.github/workflows/linter.yml
+++ b/.github/workflows/linter.yml
@@ -6,7 +6,7 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - name: Install Requirements
         run: |
diff --git a/.github/workflows/mkdocs.yml b/.github/workflows/mkdocs.yml
index a15ae0363..84d627db4 100644
--- a/.github/workflows/mkdocs.yml
+++ b/.github/workflows/mkdocs.yml
@@ -13,10 +13,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
 
       - name: Setup Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: '3.10'
 
@@ -25,7 +25,7 @@ jobs:
         run: echo "::set-output name=hash::$(sha256sum requirements-doc.txt | awk '{print $1}')"
 
       - name: Setup cache
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         with:
           key: mkdocs-material-${{ steps.req-hash.outputs.hash }}
           path: .cache
@@ -42,4 +42,4 @@ jobs:
           GH_TOKEN: ${{ secrets.GH_TOKEN }}
 
       - name: Build and deploy MkDocs
-        run: mkdocs gh-deploy --force
\ No newline at end of file
+        run: mkdocs gh-deploy --force
diff --git a/.github/workflows/security-checker.yml b/.github/workflows/security-checker.yml
index 665f49292..1588e3ddf 100644
--- a/.github/workflows/security-checker.yml
+++ b/.github/workflows/security-checker.yml
@@ -11,7 +11,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: "3.11.9"
 
diff --git a/.github/workflows/type-checker.yml b/.github/workflows/type-checker.yml
index 72c64dbd3..c694c8cec 100644
--- a/.github/workflows/type-checker.yml
+++ b/.github/workflows/type-checker.yml
@@ -14,7 +14,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Setup Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: "3.11.9"
 

From 6f32bf52ccf5a5a412ac4c67a8177300a76fc6a5 Mon Sep 17 00:00:00 2001
From: Bowen Liang <bowenliang@apache.org>
Date: Wed, 27 Nov 2024 00:24:21 +0800
Subject: [PATCH 080/126] update (#1638)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 src/crewai/agent.py | 17 ++++++-----------
 1 file changed, 6 insertions(+), 11 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 386a7cc57..a3b40c2c9 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -160,28 +160,23 @@ class Agent(BaseAgent):
             for provider, env_vars in ENV_VARS.items():
                 if provider == set_provider:
                     for env_var in env_vars:
-                        if env_var["key_name"] in unnacepted_attributes:
-                            continue
                         # Check if the environment variable is set
-                        if "key_name" in env_var:
-                            env_value = os.environ.get(env_var["key_name"])
+                        key_name = env_var.get("key_name")
+                        if key_name and key_name not in unnacepted_attributes:
+                            env_value = os.environ.get(key_name)
                             if env_value:
                                 # Map key names containing "API_KEY" to "api_key"
                                 key_name = (
-                                    "api_key"
-                                    if "API_KEY" in env_var["key_name"]
-                                    else env_var["key_name"]
+                                    "api_key" if "API_KEY" in key_name else key_name
                                 )
                                 # Map key names containing "API_BASE" to "api_base"
                                 key_name = (
-                                    "api_base"
-                                    if "API_BASE" in env_var["key_name"]
-                                    else key_name
+                                    "api_base" if "API_BASE" in key_name else key_name
                                 )
                                 # Map key names containing "API_VERSION" to "api_version"
                                 key_name = (
                                     "api_version"
-                                    if "API_VERSION" in env_var["key_name"]
+                                    if "API_VERSION" in key_name
                                     else key_name
                                 )
                                 llm_params[key_name] = env_value

From db1b678c3a58d2443b4dab2fb79a31bb10812a2c Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 26 Nov 2024 11:36:29 -0500
Subject: [PATCH 081/126] fix spelling issue found by @Jacques-Murray (#1660)

---
 src/crewai/agent.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index a3b40c2c9..520ee40fd 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -126,7 +126,7 @@ class Agent(BaseAgent):
     @model_validator(mode="after")
     def post_init_setup(self):
         self.agent_ops_agent_name = self.role
-        unnacepted_attributes = [
+        unaccepted_attributes = [
             "AWS_ACCESS_KEY_ID",
             "AWS_SECRET_ACCESS_KEY",
             "AWS_REGION_NAME",
@@ -162,7 +162,7 @@ class Agent(BaseAgent):
                     for env_var in env_vars:
                         # Check if the environment variable is set
                         key_name = env_var.get("key_name")
-                        if key_name and key_name not in unnacepted_attributes:
+                        if key_name and key_name not in unaccepted_attributes:
                             env_value = os.environ.get(key_name)
                             if env_value:
                                 # Map key names containing "API_KEY" to "api_key"

From 8bc09eb0545a05fb802f0423483f30e21c772bfc Mon Sep 17 00:00:00 2001
From: Ivan Peevski <133036+ipeevski@users.noreply.github.com>
Date: Wed, 27 Nov 2024 04:15:08 +1030
Subject: [PATCH 082/126] Update readme for running mypy (#1614)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index c6be68dc1..041735354 100644
--- a/README.md
+++ b/README.md
@@ -121,7 +121,7 @@ researcher:
     You're a seasoned researcher with a knack for uncovering the latest
     developments in {topic}. Known for your ability to find the most relevant
     information and present it in a clear and concise manner.
-      
+
 reporting_analyst:
   role: >
     {topic} Reporting Analyst
@@ -205,7 +205,7 @@ class LatestAiDevelopmentCrew():
 			tasks=self.tasks, # Automatically created by the @task decorator
 			process=Process.sequential,
 			verbose=True,
-		) 
+		)
 ```
 
 **main.py**
@@ -357,7 +357,7 @@ uv run pytest .
 ### Running static type checks
 
 ```bash
-uvx mypy
+uvx mypy src
 ```
 
 ### Packaging

From 293305790d60ff7a8940ff1fafc1ffb27329f4cd Mon Sep 17 00:00:00 2001
From: Eduardo Chiarotti <dudumelgaco@hotmail.com>
Date: Tue, 26 Nov 2024 16:59:52 -0300
Subject: [PATCH 083/126] Feat/remove langchain (#1654)

* feat: add initial changes from langchain

* feat: remove kwargs of being processed

* feat: remove langchain, update uv.lock and fix type_hint

* feat: change docs

* feat: remove forced requirements for parameter

* feat add tests for new structure tool

* feat: fix tests and adapt code for args
---
 pyproject.toml                              |   1 -
 src/crewai/agent.py                         |   2 +-
 src/crewai/tools/base_tool.py               |  18 +-
 src/crewai/tools/cache_tools/cache_tools.py |   5 +-
 src/crewai/tools/structured_tool.py         | 242 ++++++++++++++++++++
 tests/tools/test_base_tool.py               |  21 +-
 tests/tools/test_structured_tool.py         | 146 ++++++++++++
 uv.lock                                     |   2 -
 8 files changed, 408 insertions(+), 29 deletions(-)
 create mode 100644 src/crewai/tools/structured_tool.py
 create mode 100644 tests/tools/test_structured_tool.py

diff --git a/pyproject.toml b/pyproject.toml
index 4bd416ab5..1d7d8cc43 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,7 +9,6 @@ authors = [
 ]
 dependencies = [
     "pydantic>=2.4.2",
-    "langchain>=0.2.16",
     "openai>=1.13.3",
     "opentelemetry-api>=1.22.0",
     "opentelemetry-sdk>=1.22.0",
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 520ee40fd..30edb3be4 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -412,7 +412,7 @@ class Agent(BaseAgent):
 
             for tool in tools:
                 if isinstance(tool, CrewAITool):
-                    tools_list.append(tool.to_langchain())
+                    tools_list.append(tool.to_structured_tool())
                 else:
                     tools_list.append(tool)
         except ModuleNotFoundError:
diff --git a/src/crewai/tools/base_tool.py b/src/crewai/tools/base_tool.py
index f41fb7c0b..06e427528 100644
--- a/src/crewai/tools/base_tool.py
+++ b/src/crewai/tools/base_tool.py
@@ -1,10 +1,11 @@
 from abc import ABC, abstractmethod
 from typing import Any, Callable, Type, get_args, get_origin
 
-from langchain_core.tools import StructuredTool
 from pydantic import BaseModel, ConfigDict, Field, validator
 from pydantic import BaseModel as PydanticBaseModel
 
+from crewai.tools.structured_tool import CrewStructuredTool
+
 
 class BaseTool(BaseModel, ABC):
     class _ArgsSchemaPlaceholder(PydanticBaseModel):
@@ -63,9 +64,10 @@ class BaseTool(BaseModel, ABC):
     ) -> Any:
         """Here goes the actual implementation of the tool."""
 
-    def to_langchain(self) -> StructuredTool:
+    def to_structured_tool(self) -> CrewStructuredTool:
+        """Convert this tool to a CrewStructuredTool instance."""
         self._set_args_schema()
-        return StructuredTool(
+        return CrewStructuredTool(
             name=self.name,
             description=self.description,
             args_schema=self.args_schema,
@@ -73,10 +75,10 @@ class BaseTool(BaseModel, ABC):
         )
 
     @classmethod
-    def from_langchain(cls, tool: StructuredTool) -> "BaseTool":
+    def from_langchain(cls, tool: CrewStructuredTool) -> "BaseTool":
         if cls == Tool:
             if tool.func is None:
-                raise ValueError("StructuredTool must have a callable 'func'")
+                raise ValueError("CrewStructuredTool must have a callable 'func'")
             return Tool(
                 name=tool.name,
                 description=tool.description,
@@ -142,9 +144,9 @@ class Tool(BaseTool):
 
 
 def to_langchain(
-    tools: list[BaseTool | StructuredTool],
-) -> list[StructuredTool]:
-    return [t.to_langchain() if isinstance(t, BaseTool) else t for t in tools]
+    tools: list[BaseTool | CrewStructuredTool],
+) -> list[CrewStructuredTool]:
+    return [t.to_structured_tool() if isinstance(t, BaseTool) else t for t in tools]
 
 
 def tool(*args):
diff --git a/src/crewai/tools/cache_tools/cache_tools.py b/src/crewai/tools/cache_tools/cache_tools.py
index a0bb2dbad..a81ce98cf 100644
--- a/src/crewai/tools/cache_tools/cache_tools.py
+++ b/src/crewai/tools/cache_tools/cache_tools.py
@@ -1,6 +1,7 @@
 from pydantic import BaseModel, Field
 
 from crewai.agents.cache import CacheHandler
+from crewai.tools.structured_tool import CrewStructuredTool
 
 
 class CacheTools(BaseModel):
@@ -13,9 +14,7 @@ class CacheTools(BaseModel):
     )
 
     def tool(self):
-        from langchain.tools import StructuredTool
-
-        return StructuredTool.from_function(
+        return CrewStructuredTool.from_function(
             func=self.hit_cache,
             name=self.name,
             description="Reads directly from the cache",
diff --git a/src/crewai/tools/structured_tool.py b/src/crewai/tools/structured_tool.py
new file mode 100644
index 000000000..bd6818605
--- /dev/null
+++ b/src/crewai/tools/structured_tool.py
@@ -0,0 +1,242 @@
+from __future__ import annotations
+
+import inspect
+import textwrap
+from typing import Any, Callable, Optional, Union, get_type_hints
+
+from pydantic import BaseModel, Field, create_model
+
+from crewai.utilities.logger import Logger
+
+
+class CrewStructuredTool:
+    """A structured tool that can operate on any number of inputs.
+
+    This tool intends to replace StructuredTool with a custom implementation
+    that integrates better with CrewAI's ecosystem.
+    """
+
+    def __init__(
+        self,
+        name: str,
+        description: str,
+        args_schema: type[BaseModel],
+        func: Callable[..., Any],
+    ) -> None:
+        """Initialize the structured tool.
+
+        Args:
+            name: The name of the tool
+            description: A description of what the tool does
+            args_schema: The pydantic model for the tool's arguments
+            func: The function to run when the tool is called
+        """
+        self.name = name
+        self.description = description
+        self.args_schema = args_schema
+        self.func = func
+        self._logger = Logger()
+
+        # Validate the function signature matches the schema
+        self._validate_function_signature()
+
+    @classmethod
+    def from_function(
+        cls,
+        func: Callable,
+        name: Optional[str] = None,
+        description: Optional[str] = None,
+        return_direct: bool = False,
+        args_schema: Optional[type[BaseModel]] = None,
+        infer_schema: bool = True,
+        **kwargs: Any,
+    ) -> CrewStructuredTool:
+        """Create a tool from a function.
+
+        Args:
+            func: The function to create a tool from
+            name: The name of the tool. Defaults to the function name
+            description: The description of the tool. Defaults to the function docstring
+            return_direct: Whether to return the output directly
+            args_schema: Optional schema for the function arguments
+            infer_schema: Whether to infer the schema from the function signature
+            **kwargs: Additional arguments to pass to the tool
+
+        Returns:
+            A CrewStructuredTool instance
+
+        Example:
+            >>> def add(a: int, b: int) -> int:
+            ...     '''Add two numbers'''
+            ...     return a + b
+            >>> tool = CrewStructuredTool.from_function(add)
+        """
+        name = name or func.__name__
+        description = description or inspect.getdoc(func)
+
+        if description is None:
+            raise ValueError(
+                f"Function {name} must have a docstring if description not provided."
+            )
+
+        # Clean up the description
+        description = textwrap.dedent(description).strip()
+
+        if args_schema is not None:
+            # Use provided schema
+            schema = args_schema
+        elif infer_schema:
+            # Infer schema from function signature
+            schema = cls._create_schema_from_function(name, func)
+        else:
+            raise ValueError(
+                "Either args_schema must be provided or infer_schema must be True."
+            )
+
+        return cls(
+            name=name,
+            description=description,
+            args_schema=schema,
+            func=func,
+        )
+
+    @staticmethod
+    def _create_schema_from_function(
+        name: str,
+        func: Callable,
+    ) -> type[BaseModel]:
+        """Create a Pydantic schema from a function's signature.
+
+        Args:
+            name: The name to use for the schema
+            func: The function to create a schema from
+
+        Returns:
+            A Pydantic model class
+        """
+        # Get function signature
+        sig = inspect.signature(func)
+
+        # Get type hints
+        type_hints = get_type_hints(func)
+
+        # Create field definitions
+        fields = {}
+        for param_name, param in sig.parameters.items():
+            # Skip self/cls for methods
+            if param_name in ("self", "cls"):
+                continue
+
+            # Get type annotation
+            annotation = type_hints.get(param_name, Any)
+
+            # Get default value
+            default = ... if param.default == param.empty else param.default
+
+            # Add field
+            fields[param_name] = (annotation, Field(default=default))
+
+        # Create model
+        schema_name = f"{name.title()}Schema"
+        return create_model(schema_name, **fields)
+
+    def _validate_function_signature(self) -> None:
+        """Validate that the function signature matches the args schema."""
+        sig = inspect.signature(self.func)
+        schema_fields = self.args_schema.model_fields
+
+        # Check required parameters
+        for param_name, param in sig.parameters.items():
+            # Skip self/cls for methods
+            if param_name in ("self", "cls"):
+                continue
+
+            # Skip **kwargs parameters
+            if param.kind in (
+                inspect.Parameter.VAR_KEYWORD,
+                inspect.Parameter.VAR_POSITIONAL,
+            ):
+                continue
+
+            # Only validate required parameters without defaults
+            if param.default == inspect.Parameter.empty:
+                if param_name not in schema_fields:
+                    raise ValueError(
+                        f"Required function parameter '{param_name}' "
+                        f"not found in args_schema"
+                    )
+
+    def _parse_args(self, raw_args: Union[str, dict]) -> dict:
+        """Parse and validate the input arguments against the schema.
+
+        Args:
+            raw_args: The raw arguments to parse, either as a string or dict
+
+        Returns:
+            The validated arguments as a dictionary
+        """
+        if isinstance(raw_args, str):
+            try:
+                import json
+
+                raw_args = json.loads(raw_args)
+            except json.JSONDecodeError as e:
+                raise ValueError(f"Failed to parse arguments as JSON: {e}")
+
+        try:
+            validated_args = self.args_schema.model_validate(raw_args)
+            return validated_args.model_dump()
+        except Exception as e:
+            raise ValueError(f"Arguments validation failed: {e}")
+
+    async def ainvoke(
+        self,
+        input: Union[str, dict],
+        config: Optional[dict] = None,
+        **kwargs: Any,
+    ) -> Any:
+        """Asynchronously invoke the tool.
+
+        Args:
+            input: The input arguments
+            config: Optional configuration
+            **kwargs: Additional keyword arguments
+
+        Returns:
+            The result of the tool execution
+        """
+        parsed_args = self._parse_args(input)
+
+        if inspect.iscoroutinefunction(self.func):
+            return await self.func(**parsed_args, **kwargs)
+        else:
+            # Run sync functions in a thread pool
+            import asyncio
+
+            return await asyncio.get_event_loop().run_in_executor(
+                None, lambda: self.func(**parsed_args, **kwargs)
+            )
+
+    def _run(self, *args, **kwargs) -> Any:
+        """Legacy method for compatibility."""
+        # Convert args/kwargs to our expected format
+        input_dict = dict(zip(self.args_schema.model_fields.keys(), args))
+        input_dict.update(kwargs)
+        return self.invoke(input_dict)
+
+    def invoke(
+        self, input: Union[str, dict], config: Optional[dict] = None, **kwargs: Any
+    ) -> Any:
+        """Main method for tool execution."""
+        parsed_args = self._parse_args(input)
+        return self.func(**parsed_args, **kwargs)
+
+    @property
+    def args(self) -> dict:
+        """Get the tool's input arguments schema."""
+        return self.args_schema.model_json_schema()["properties"]
+
+    def __repr__(self) -> str:
+        return (
+            f"CrewStructuredTool(name='{self.name}', description='{self.description}')"
+        )
diff --git a/tests/tools/test_base_tool.py b/tests/tools/test_base_tool.py
index eca36739c..cd4b53caf 100644
--- a/tests/tools/test_base_tool.py
+++ b/tests/tools/test_base_tool.py
@@ -1,4 +1,5 @@
 from typing import Callable
+
 from crewai.tools import BaseTool, tool
 
 
@@ -21,8 +22,7 @@ def test_creating_a_tool_using_annotation():
         my_tool.func("What is the meaning of life?") == "What is the meaning of life?"
     )
 
-    # Assert the langchain tool conversion worked as expected
-    converted_tool = my_tool.to_langchain()
+    converted_tool = my_tool.to_structured_tool()
     assert converted_tool.name == "Name of my tool"
 
     assert (
@@ -41,9 +41,7 @@ def test_creating_a_tool_using_annotation():
 def test_creating_a_tool_using_baseclass():
     class MyCustomTool(BaseTool):
         name: str = "Name of my tool"
-        description: str = (
-            "Clear description for what this tool is useful for, you agent will need this information to use it."
-        )
+        description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
 
         def _run(self, question: str) -> str:
             return question
@@ -61,8 +59,7 @@ def test_creating_a_tool_using_baseclass():
     }
     assert my_tool.run("What is the meaning of life?") == "What is the meaning of life?"
 
-    # Assert the langchain tool conversion worked as expected
-    converted_tool = my_tool.to_langchain()
+    converted_tool = my_tool.to_structured_tool()
     assert converted_tool.name == "Name of my tool"
 
     assert (
@@ -73,7 +70,7 @@ def test_creating_a_tool_using_baseclass():
         "question": {"title": "Question", "type": "string"}
     }
     assert (
-        converted_tool.run("What is the meaning of life?")
+        converted_tool._run("What is the meaning of life?")
         == "What is the meaning of life?"
     )
 
@@ -81,9 +78,7 @@ def test_creating_a_tool_using_baseclass():
 def test_setting_cache_function():
     class MyCustomTool(BaseTool):
         name: str = "Name of my tool"
-        description: str = (
-            "Clear description for what this tool is useful for, you agent will need this information to use it."
-        )
+        description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
         cache_function: Callable = lambda: False
 
         def _run(self, question: str) -> str:
@@ -97,9 +92,7 @@ def test_setting_cache_function():
 def test_default_cache_function_is_true():
     class MyCustomTool(BaseTool):
         name: str = "Name of my tool"
-        description: str = (
-            "Clear description for what this tool is useful for, you agent will need this information to use it."
-        )
+        description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
 
         def _run(self, question: str) -> str:
             return question
diff --git a/tests/tools/test_structured_tool.py b/tests/tools/test_structured_tool.py
new file mode 100644
index 000000000..32ebd805b
--- /dev/null
+++ b/tests/tools/test_structured_tool.py
@@ -0,0 +1,146 @@
+from typing import Optional
+
+import pytest
+from pydantic import BaseModel, Field
+
+from crewai.tools.structured_tool import CrewStructuredTool
+
+
+# Test fixtures
+@pytest.fixture
+def basic_function():
+    def test_func(param1: str, param2: int = 0) -> str:
+        """Test function with basic params."""
+        return f"{param1} {param2}"
+
+    return test_func
+
+
+@pytest.fixture
+def schema_class():
+    class TestSchema(BaseModel):
+        param1: str
+        param2: int = Field(default=0)
+
+    return TestSchema
+
+
+class TestCrewStructuredTool:
+    def test_initialization(self, basic_function, schema_class):
+        """Test basic initialization of CrewStructuredTool"""
+        tool = CrewStructuredTool(
+            name="test_tool",
+            description="Test tool description",
+            func=basic_function,
+            args_schema=schema_class,
+        )
+
+        assert tool.name == "test_tool"
+        assert tool.description == "Test tool description"
+        assert tool.func == basic_function
+        assert tool.args_schema == schema_class
+
+    def test_from_function(self, basic_function):
+        """Test creating tool from function"""
+        tool = CrewStructuredTool.from_function(
+            func=basic_function, name="test_tool", description="Test description"
+        )
+
+        assert tool.name == "test_tool"
+        assert tool.description == "Test description"
+        assert tool.func == basic_function
+        assert isinstance(tool.args_schema, type(BaseModel))
+
+    def test_validate_function_signature(self, basic_function, schema_class):
+        """Test function signature validation"""
+        tool = CrewStructuredTool(
+            name="test_tool",
+            description="Test tool",
+            func=basic_function,
+            args_schema=schema_class,
+        )
+
+        # Should not raise any exceptions
+        tool._validate_function_signature()
+
+    @pytest.mark.asyncio
+    async def test_ainvoke(self, basic_function):
+        """Test asynchronous invocation"""
+        tool = CrewStructuredTool.from_function(func=basic_function, name="test_tool")
+
+        result = await tool.ainvoke(input={"param1": "test"})
+        assert result == "test 0"
+
+    def test_parse_args_dict(self, basic_function):
+        """Test parsing dictionary arguments"""
+        tool = CrewStructuredTool.from_function(func=basic_function, name="test_tool")
+
+        parsed = tool._parse_args({"param1": "test", "param2": 42})
+        assert parsed["param1"] == "test"
+        assert parsed["param2"] == 42
+
+    def test_parse_args_string(self, basic_function):
+        """Test parsing string arguments"""
+        tool = CrewStructuredTool.from_function(func=basic_function, name="test_tool")
+
+        parsed = tool._parse_args('{"param1": "test", "param2": 42}')
+        assert parsed["param1"] == "test"
+        assert parsed["param2"] == 42
+
+    def test_complex_types(self):
+        """Test handling of complex parameter types"""
+
+        def complex_func(nested: dict, items: list) -> str:
+            """Process complex types."""
+            return f"Processed {len(items)} items with {len(nested)} nested keys"
+
+        tool = CrewStructuredTool.from_function(
+            func=complex_func, name="test_tool", description="Test complex types"
+        )
+        result = tool.invoke({"nested": {"key": "value"}, "items": [1, 2, 3]})
+        assert result == "Processed 3 items with 1 nested keys"
+
+    def test_schema_inheritance(self):
+        """Test tool creation with inherited schema"""
+
+        def extended_func(base_param: str, extra_param: int) -> str:
+            """Test function with inherited schema."""
+            return f"{base_param} {extra_param}"
+
+        class BaseSchema(BaseModel):
+            base_param: str
+
+        class ExtendedSchema(BaseSchema):
+            extra_param: int
+
+        tool = CrewStructuredTool.from_function(
+            func=extended_func, name="test_tool", args_schema=ExtendedSchema
+        )
+
+        result = tool.invoke({"base_param": "test", "extra_param": 42})
+        assert result == "test 42"
+
+    def test_default_values_in_schema(self):
+        """Test handling of default values in schema"""
+
+        def default_func(
+            required_param: str,
+            optional_param: str = "default",
+            nullable_param: Optional[int] = None,
+        ) -> str:
+            """Test function with default values."""
+            return f"{required_param} {optional_param} {nullable_param}"
+
+        tool = CrewStructuredTool.from_function(
+            func=default_func, name="test_tool", description="Test defaults"
+        )
+
+        # Test with minimal parameters
+        result = tool.invoke({"required_param": "test"})
+        assert result == "test default None"
+
+        # Test with all parameters
+        result = tool.invoke(
+            {"required_param": "test", "optional_param": "custom", "nullable_param": 42}
+        )
+        assert result == "test custom 42"
diff --git a/uv.lock b/uv.lock
index baff09ac8..050602e61 100644
--- a/uv.lock
+++ b/uv.lock
@@ -619,7 +619,6 @@ dependencies = [
     { name = "instructor" },
     { name = "json-repair" },
     { name = "jsonref" },
-    { name = "langchain" },
     { name = "litellm" },
     { name = "openai" },
     { name = "openpyxl" },
@@ -692,7 +691,6 @@ requires-dist = [
     { name = "instructor", specifier = ">=1.3.3" },
     { name = "json-repair", specifier = ">=0.25.2" },
     { name = "jsonref", specifier = ">=1.1.0" },
-    { name = "langchain", specifier = ">=0.2.16" },
     { name = "litellm", specifier = ">=1.44.22" },
     { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" },
     { name = "openai", specifier = ">=1.13.3" },

From 366bbbbea3d6c0e341cb4dd4ef3584ef05c86e40 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 27 Nov 2024 11:22:49 -0500
Subject: [PATCH 084/126] Feat/remove langchain (#1668)

* feat: add initial changes from langchain

* feat: remove kwargs of being processed

* feat: remove langchain, update uv.lock and fix type_hint

* feat: change docs

* feat: remove forced requirements for parameter

* feat add tests for new structure tool

* feat: fix tests and adapt code for args

* fix tool calling for langchain tools

* doc strings

---------

Co-authored-by: Eduardo Chiarotti <dudumelgaco@hotmail.com>
---
 src/crewai/agents/agent_builder/base_agent.py |  32 ++++-
 src/crewai/tools/base_tool.py                 | 110 +++++++++++++++---
 2 files changed, 128 insertions(+), 14 deletions(-)

diff --git a/src/crewai/agents/agent_builder/base_agent.py b/src/crewai/agents/agent_builder/base_agent.py
index 55315e7ff..207a1769a 100644
--- a/src/crewai/agents/agent_builder/base_agent.py
+++ b/src/crewai/agents/agent_builder/base_agent.py
@@ -19,6 +19,7 @@ from crewai.agents.agent_builder.utilities.base_token_process import TokenProces
 from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.tools import BaseTool
+from crewai.tools.base_tool import Tool
 from crewai.utilities import I18N, Logger, RPMController
 from crewai.utilities.config import process_config
 
@@ -106,7 +107,7 @@ class BaseAgent(ABC, BaseModel):
         default=False,
         description="Enable agent to delegate and ask questions among each other.",
     )
-    tools: Optional[List[BaseTool]] = Field(
+    tools: Optional[List[Any]] = Field(
         default_factory=list, description="Tools at agents' disposal"
     )
     max_iter: Optional[int] = Field(
@@ -135,6 +136,35 @@ class BaseAgent(ABC, BaseModel):
     def process_model_config(cls, values):
         return process_config(values, cls)
 
+    @field_validator("tools")
+    @classmethod
+    def validate_tools(cls, tools: List[Any]) -> List[BaseTool]:
+        """Validate and process the tools provided to the agent.
+
+        This method ensures that each tool is either an instance of BaseTool
+        or an object with 'name', 'func', and 'description' attributes. If the
+        tool meets these criteria, it is processed and added to the list of
+        tools. Otherwise, a ValueError is raised.
+        """
+        processed_tools = []
+        for tool in tools:
+            if isinstance(tool, BaseTool):
+                processed_tools.append(tool)
+            elif (
+                hasattr(tool, "name")
+                and hasattr(tool, "func")
+                and hasattr(tool, "description")
+            ):
+                # Tool has the required attributes, create a Tool instance
+                processed_tools.append(Tool.from_langchain(tool))
+            else:
+                raise ValueError(
+                    f"Invalid tool type: {type(tool)}. "
+                    "Tool must be an instance of BaseTool or "
+                    "an object with 'name', 'func', and 'description' attributes."
+                )
+        return processed_tools
+
     @model_validator(mode="after")
     def validate_and_set_attributes(self):
         # Validate required fields
diff --git a/src/crewai/tools/base_tool.py b/src/crewai/tools/base_tool.py
index 06e427528..46bfc03a6 100644
--- a/src/crewai/tools/base_tool.py
+++ b/src/crewai/tools/base_tool.py
@@ -1,7 +1,8 @@
 from abc import ABC, abstractmethod
+from inspect import signature
 from typing import Any, Callable, Type, get_args, get_origin
 
-from pydantic import BaseModel, ConfigDict, Field, validator
+from pydantic import BaseModel, ConfigDict, Field, create_model, validator
 from pydantic import BaseModel as PydanticBaseModel
 
 from crewai.tools.structured_tool import CrewStructuredTool
@@ -75,17 +76,47 @@ class BaseTool(BaseModel, ABC):
         )
 
     @classmethod
-    def from_langchain(cls, tool: CrewStructuredTool) -> "BaseTool":
-        if cls == Tool:
-            if tool.func is None:
-                raise ValueError("CrewStructuredTool must have a callable 'func'")
-            return Tool(
-                name=tool.name,
-                description=tool.description,
-                args_schema=tool.args_schema,
-                func=tool.func,
-            )
-        raise NotImplementedError(f"from_langchain not implemented for {cls.__name__}")
+    def from_langchain(cls, tool: Any) -> "BaseTool":
+        """Create a Tool instance from a CrewStructuredTool.
+
+        This method takes a CrewStructuredTool object and converts it into a
+        Tool instance. It ensures that the provided tool has a callable 'func'
+        attribute and infers the argument schema if not explicitly provided.
+        """
+        if not hasattr(tool, "func") or not callable(tool.func):
+            raise ValueError("The provided tool must have a callable 'func' attribute.")
+
+        args_schema = getattr(tool, "args_schema", None)
+
+        if args_schema is None:
+            # Infer args_schema from the function signature if not provided
+            func_signature = signature(tool.func)
+            annotations = func_signature.parameters
+            args_fields = {}
+            for name, param in annotations.items():
+                if name != "self":
+                    param_annotation = (
+                        param.annotation if param.annotation != param.empty else Any
+                    )
+                    field_info = Field(
+                        default=...,
+                        description="",
+                    )
+                    args_fields[name] = (param_annotation, field_info)
+            if args_fields:
+                args_schema = create_model(f"{tool.name}Input", **args_fields)
+            else:
+                # Create a default schema with no fields if no parameters are found
+                args_schema = create_model(
+                    f"{tool.name}Input", __base__=PydanticBaseModel
+                )
+
+        return cls(
+            name=getattr(tool, "name", "Unnamed Tool"),
+            description=getattr(tool, "description", ""),
+            func=tool.func,
+            args_schema=args_schema,
+        )
 
     def _set_args_schema(self):
         if self.args_schema is None:
@@ -136,12 +167,65 @@ class BaseTool(BaseModel, ABC):
 
 
 class Tool(BaseTool):
-    func: Callable
     """The function that will be executed when the tool is called."""
 
+    func: Callable
+
     def _run(self, *args: Any, **kwargs: Any) -> Any:
         return self.func(*args, **kwargs)
 
+    @classmethod
+    def from_langchain(cls, tool: Any) -> "Tool":
+        """Create a Tool instance from a CrewStructuredTool.
+
+        This method takes a CrewStructuredTool object and converts it into a
+        Tool instance. It ensures that the provided tool has a callable 'func'
+        attribute and infers the argument schema if not explicitly provided.
+
+        Args:
+            tool (Any): The CrewStructuredTool object to be converted.
+
+        Returns:
+            Tool: A new Tool instance created from the provided CrewStructuredTool.
+
+        Raises:
+            ValueError: If the provided tool does not have a callable 'func' attribute.
+        """
+        if not hasattr(tool, "func") or not callable(tool.func):
+            raise ValueError("The provided tool must have a callable 'func' attribute.")
+
+        args_schema = getattr(tool, "args_schema", None)
+
+        if args_schema is None:
+            # Infer args_schema from the function signature if not provided
+            func_signature = signature(tool.func)
+            annotations = func_signature.parameters
+            args_fields = {}
+            for name, param in annotations.items():
+                if name != "self":
+                    param_annotation = (
+                        param.annotation if param.annotation != param.empty else Any
+                    )
+                    field_info = Field(
+                        default=...,
+                        description="",
+                    )
+                    args_fields[name] = (param_annotation, field_info)
+            if args_fields:
+                args_schema = create_model(f"{tool.name}Input", **args_fields)
+            else:
+                # Create a default schema with no fields if no parameters are found
+                args_schema = create_model(
+                    f"{tool.name}Input", __base__=PydanticBaseModel
+                )
+
+        return cls(
+            name=getattr(tool, "name", "Unnamed Tool"),
+            description=getattr(tool, "description", ""),
+            func=tool.func,
+            args_schema=args_schema,
+        )
+
 
 def to_langchain(
     tools: list[BaseTool | CrewStructuredTool],

From c6a6c918e0eba167be1fb82831c73dd664c641e3 Mon Sep 17 00:00:00 2001
From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Date: Wed, 27 Nov 2024 11:33:07 -0800
Subject: [PATCH 085/126] added knowledge to agent level (#1655)

* added knowledge to agent level

* linted

* added doc

* added from suggestions

* added test

* fixes from discussion

* fix docs

* fix test

* rm cassette for knowledge_sources test as its a mock and update agent doc string

* fix test

* rm unused

* linted
---
 docs/concepts/knowledge.mdx                   |  38 +-
 src/crewai/agent.py                           |  59 ++-
 src/crewai/crew.py                            |  34 +-
 src/crewai/knowledge/knowledge.py             |  38 +-
 .../knowledge/source/base_knowledge_source.py |   3 +-
 .../source/string_knowledge_source.py         |   3 +-
 .../knowledge/storage/knowledge_storage.py    |  87 +++-
 src/crewai/knowledge/utils/knowledge_utils.py |  12 +
 tests/agent_test.py                           |  19 +-
 .../test_agent_with_knowledge_sources.yaml    | 452 +++++++++++++++++-
 10 files changed, 654 insertions(+), 91 deletions(-)
 create mode 100644 src/crewai/knowledge/utils/knowledge_utils.py

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index ce0203e13..e51602947 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -51,12 +51,41 @@ crew = Crew(
     tasks=[task],
     verbose=True,
     process=Process.sequential,
-    knowledge={"sources": [string_source], "metadata": {"preference": "personal"}}, # Enable knowledge by adding the sources here. You can also add more sources to the sources list.
+    knowledge_sources=[string_source], # Enable knowledge by adding the sources here.
 )
 
 result = crew.kickoff(inputs={"question": "What city does John live in and how old is he?"})
 ```
 
+## Appending Knowledge Sources To Individual Agents
+Sometimes you may want to append knowledge sources to an individual agent. You can do this by setting the `knowledge` parameter in the `Agent` class.
+
+```python
+agent = Agent(
+    ...
+    knowledge_sources=[
+        StringKnowledgeSource(
+            content="Users name is John. He is 30 years old and lives in San Francisco.",
+            metadata={"preference": "personal"},
+        )
+    ],
+)
+```
+
+## Agent Level Knowledge Sources
+
+You can also append knowledge sources to an individual agent by setting the `knowledge_sources` parameter in the `Agent` class.
+
+```python
+string_source = StringKnowledgeSource(
+    content="Users name is John. He is 30 years old and lives in San Francisco.",
+    metadata={"preference": "personal"},
+)
+agent = Agent(
+    ...
+    knowledge_sources=[string_source],
+)
+```
 
 ## Embedder Configuration
 
@@ -70,10 +99,7 @@ string_source = StringKnowledgeSource(
 )
 crew = Crew(
     ...
-    knowledge={
-        "sources": [string_source],
-        "metadata": {"preference": "personal"},
-        "embedder_config": {"provider": "openai", "config": {"model": "text-embedding-3-small"}},
-    },
+    knowledge_sources=[string_source],
+    embedder_config={"provider": "ollama", "config": {"model": "nomic-embed-text:latest"}},
 )
 ```
diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 30edb3be4..26380ebc2 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -1,7 +1,7 @@
 import os
 import shutil
 import subprocess
-from typing import Any, List, Literal, Optional, Union
+from typing import Any, List, Literal, Optional, Union, Dict
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -10,6 +10,8 @@ from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.cli.constants import ENV_VARS
 from crewai.llm import LLM
+from crewai.knowledge.knowledge import Knowledge
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.task import Task
 from crewai.tools import BaseTool
@@ -19,6 +21,7 @@ from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_F
 from crewai.utilities.converter import generate_model_description
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
+from crewai.knowledge.utils.knowledge_utils import extract_knowledge_context
 
 
 def mock_agent_ops_provider():
@@ -65,6 +68,7 @@ class Agent(BaseAgent):
             allow_delegation: Whether the agent is allowed to delegate tasks to other agents.
             tools: Tools at agents disposal
             step_callback: Callback to be executed after each step of the agent execution.
+            knowledge_sources: Knowledge sources for the agent.
     """
 
     _times_executed: int = PrivateAttr(default=0)
@@ -122,9 +126,21 @@ class Agent(BaseAgent):
         default="safe",
         description="Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution).",
     )
+    embedder_config: Optional[Dict[str, Any]] = Field(
+        default=None,
+        description="Embedder configuration for the agent.",
+    )
+    knowledge_sources: Optional[List[BaseKnowledgeSource]] = Field(
+        default=None,
+        description="Knowledge sources for the agent.",
+    )
+    _knowledge: Optional[Knowledge] = PrivateAttr(
+        default=None,
+    )
 
     @model_validator(mode="after")
     def post_init_setup(self):
+        self._set_knowledge()
         self.agent_ops_agent_name = self.role
         unaccepted_attributes = [
             "AWS_ACCESS_KEY_ID",
@@ -232,6 +248,21 @@ class Agent(BaseAgent):
             self.cache_handler = CacheHandler()
         self.set_cache_handler(self.cache_handler)
 
+    def _set_knowledge(self):
+        try:
+            if self.knowledge_sources:
+                knowledge_agent_name = f"{self.role.replace(' ', '_')}"
+                if isinstance(self.knowledge_sources, list) and all(
+                    isinstance(k, BaseKnowledgeSource) for k in self.knowledge_sources
+                ):
+                    self._knowledge = Knowledge(
+                        sources=self.knowledge_sources,
+                        embedder_config=self.embedder_config,
+                        collection_name=knowledge_agent_name,
+                    )
+        except (TypeError, ValueError) as e:
+            raise ValueError(f"Invalid Knowledge Configuration: {str(e)}")
+
     def execute_task(
         self,
         task: Task,
@@ -286,17 +317,21 @@ class Agent(BaseAgent):
             if memory.strip() != "":
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 
-        # Integrate the knowledge base
-        if self.crew and self.crew.knowledge:
-            knowledge_snippets = self.crew.knowledge.query([task.prompt()])
-            valid_snippets = [
-                result["context"]
-                for result in knowledge_snippets
-                if result and result.get("context")
-            ]
-            if valid_snippets:
-                formatted_knowledge = "\n".join(valid_snippets)
-                task_prompt += f"\n\nAdditional Information:\n{formatted_knowledge}"
+        if self._knowledge:
+            agent_knowledge_snippets = self._knowledge.query([task.prompt()])
+            if agent_knowledge_snippets:
+                agent_knowledge_context = extract_knowledge_context(
+                    agent_knowledge_snippets
+                )
+                if agent_knowledge_context:
+                    task_prompt += agent_knowledge_context
+
+        if self.crew:
+            knowledge_snippets = self.crew.query_knowledge([task.prompt()])
+            if knowledge_snippets:
+                crew_knowledge_context = extract_knowledge_context(knowledge_snippets)
+                if crew_knowledge_context:
+                    task_prompt += crew_knowledge_context
 
         tools = tools or self.tools or []
         self.create_agent_executor(tools=tools, task=task)
diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 4c3886a3f..3b6ee44b4 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -28,6 +28,7 @@ from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
 from crewai.knowledge.knowledge import Knowledge
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.memory.user.user_memory import UserMemory
 from crewai.process import Process
 from crewai.task import Task
@@ -202,10 +203,13 @@ class Crew(BaseModel):
         default=[],
         description="List of execution logs for tasks",
     )
-    knowledge: Optional[Dict[str, Any]] = Field(
-        default=None, description="Knowledge for the crew. Add knowledge sources to the knowledge object."
+    knowledge_sources: Optional[List[BaseKnowledgeSource]] = Field(
+        default=None,
+        description="Knowledge sources for the crew. Add knowledge sources to the knowledge object.",
+    )
+    _knowledge: Optional[Knowledge] = PrivateAttr(
+        default=None,
     )
-
 
     @field_validator("id", mode="before")
     @classmethod
@@ -282,11 +286,22 @@ class Crew(BaseModel):
 
     @model_validator(mode="after")
     def create_crew_knowledge(self) -> "Crew":
-        if self.knowledge:
+        """Create the knowledge for the crew."""
+        if self.knowledge_sources:
             try:
-                self.knowledge = Knowledge(**self.knowledge) if isinstance(self.knowledge, dict) else self.knowledge
-            except (TypeError, ValueError) as e:
-                raise ValueError(f"Invalid knowledge configuration: {str(e)}")
+                if isinstance(self.knowledge_sources, list) and all(
+                    isinstance(k, BaseKnowledgeSource) for k in self.knowledge_sources
+                ):
+                    self._knowledge = Knowledge(
+                        sources=self.knowledge_sources,
+                        embedder_config=self.embedder,
+                        collection_name="crew",
+                    )
+
+            except Exception as e:
+                self._logger.log(
+                    "warning", f"Failed to init knowledge: {e}", color="yellow"
+                )
         return self
 
     @model_validator(mode="after")
@@ -942,6 +957,11 @@ class Crew(BaseModel):
         result = self._execute_tasks(self.tasks, start_index, True)
         return result
 
+    def query_knowledge(self, query: List[str]) -> Union[List[Dict[str, Any]], None]:
+        if self._knowledge:
+            return self._knowledge.query(query)
+        return None
+
     def copy(self):
         """Create a deep copy of the Crew."""
 
diff --git a/src/crewai/knowledge/knowledge.py b/src/crewai/knowledge/knowledge.py
index cf2907e67..4a1331799 100644
--- a/src/crewai/knowledge/knowledge.py
+++ b/src/crewai/knowledge/knowledge.py
@@ -5,8 +5,8 @@ from pydantic import BaseModel, ConfigDict, Field
 
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
-from crewai.utilities.logger import Logger
 from crewai.utilities.constants import DEFAULT_SCORE_THRESHOLD
+
 os.environ["TOKENIZERS_PARALLELISM"] = "false"  # removes logging from fastembed
 
 
@@ -18,24 +18,33 @@ class Knowledge(BaseModel):
         storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
         embedder_config: Optional[Dict[str, Any]] = None
     """
+
     sources: List[BaseKnowledgeSource] = Field(default_factory=list)
     model_config = ConfigDict(arbitrary_types_allowed=True)
     storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
     embedder_config: Optional[Dict[str, Any]] = None
+    collection_name: Optional[str] = None
 
-    def __init__(self, embedder_config: Optional[Dict[str, Any]] = None, **data):
+    def __init__(
+        self,
+        collection_name: str,
+        sources: List[BaseKnowledgeSource],
+        embedder_config: Optional[Dict[str, Any]] = None,
+        storage: Optional[KnowledgeStorage] = None,
+        **data,
+    ):
         super().__init__(**data)
-        self.storage = KnowledgeStorage(embedder_config=embedder_config or None)
-
-        try:
-            for source in self.sources:
-                source.add()
-        except Exception as e:
-            Logger(verbose=True).log(
-                "warning",
-                f"Failed to init knowledge: {e}",
-                color="yellow",
+        if storage:
+            self.storage = storage
+        else:
+            self.storage = KnowledgeStorage(
+                embedder_config=embedder_config, collection_name=collection_name
             )
+        self.sources = sources
+        self.storage.initialize_knowledge_storage()
+        for source in sources:
+            source.storage = self.storage
+            source.add()
 
     def query(
         self, query: List[str], limit: int = 3, preference: Optional[str] = None
@@ -52,3 +61,8 @@ class Knowledge(BaseModel):
             score_threshold=DEFAULT_SCORE_THRESHOLD,
         )
         return results
+
+    def _add_sources(self):
+        for source in self.sources:
+            source.storage = self.storage
+            source.add()
diff --git a/src/crewai/knowledge/source/base_knowledge_source.py b/src/crewai/knowledge/source/base_knowledge_source.py
index bb4c69cf3..6be76ca40 100644
--- a/src/crewai/knowledge/source/base_knowledge_source.py
+++ b/src/crewai/knowledge/source/base_knowledge_source.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import List, Dict, Any
+from typing import List, Dict, Any, Optional
 
 import numpy as np
 from pydantic import BaseModel, ConfigDict, Field
@@ -18,6 +18,7 @@ class BaseKnowledgeSource(BaseModel, ABC):
     model_config = ConfigDict(arbitrary_types_allowed=True)
     storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
     metadata: Dict[str, Any] = Field(default_factory=dict)
+    collection_name: Optional[str] = Field(default=None)
 
     @abstractmethod
     def load_content(self) -> Dict[Any, str]:
diff --git a/src/crewai/knowledge/source/string_knowledge_source.py b/src/crewai/knowledge/source/string_knowledge_source.py
index d4c22e3c1..7336fd3ea 100644
--- a/src/crewai/knowledge/source/string_knowledge_source.py
+++ b/src/crewai/knowledge/source/string_knowledge_source.py
@@ -1,4 +1,4 @@
-from typing import List
+from typing import List, Optional
 
 from pydantic import Field
 
@@ -9,6 +9,7 @@ class StringKnowledgeSource(BaseKnowledgeSource):
     """A knowledge source that stores and queries plain text content using embeddings."""
 
     content: str = Field(...)
+    collection_name: Optional[str] = Field(default=None)
 
     def model_post_init(self, _):
         """Post-initialization method to validate content."""
diff --git a/src/crewai/knowledge/storage/knowledge_storage.py b/src/crewai/knowledge/storage/knowledge_storage.py
index b3d5ba750..79aa385a8 100644
--- a/src/crewai/knowledge/storage/knowledge_storage.py
+++ b/src/crewai/knowledge/storage/knowledge_storage.py
@@ -3,12 +3,16 @@ import io
 import logging
 import chromadb
 import os
+
+import chromadb.errors
 from crewai.utilities.paths import db_storage_path
-from typing import Optional, List
-from typing import Dict, Any
+from typing import Optional, List, Dict, Any, Union
 from crewai.utilities import EmbeddingConfigurator
 from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
 import hashlib
+from chromadb.config import Settings
+from chromadb.api import ClientAPI
+from crewai.utilities.logger import Logger
 
 
 @contextlib.contextmanager
@@ -35,9 +39,16 @@ class KnowledgeStorage(BaseKnowledgeStorage):
     """
 
     collection: Optional[chromadb.Collection] = None
+    collection_name: Optional[str] = "knowledge"
+    app: Optional[ClientAPI] = None
 
-    def __init__(self, embedder_config: Optional[Dict[str, Any]] = None):
-        self._initialize_app(embedder_config or {})
+    def __init__(
+        self,
+        embedder_config: Optional[Dict[str, Any]] = None,
+        collection_name: Optional[str] = None,
+    ):
+        self.collection_name = collection_name
+        self._set_embedder_config(embedder_config)
 
     def search(
         self,
@@ -67,43 +78,75 @@ class KnowledgeStorage(BaseKnowledgeStorage):
             else:
                 raise Exception("Collection not initialized")
 
-    def _initialize_app(self, embedder_config: Optional[Dict[str, Any]] = None):
-        import chromadb
-        from chromadb.config import Settings
-
-        self._set_embedder_config(embedder_config)
-
+    def initialize_knowledge_storage(self):
+        base_path = os.path.join(db_storage_path(), "knowledge")
         chroma_client = chromadb.PersistentClient(
-            path=f"{db_storage_path()}/knowledge",
+            path=base_path,
             settings=Settings(allow_reset=True),
         )
 
         self.app = chroma_client
 
         try:
-            self.collection = self.app.get_or_create_collection(name="knowledge")
+            collection_name = (
+                f"knowledge_{self.collection_name}"
+                if self.collection_name
+                else "knowledge"
+            )
+            if self.app:
+                self.collection = self.app.get_or_create_collection(
+                    name=collection_name, embedding_function=self.embedder_config
+                )
+            else:
+                raise Exception("Vector Database Client not initialized")
         except Exception:
             raise Exception("Failed to create or get collection")
 
     def reset(self):
         if self.app:
             self.app.reset()
+        else:
+            base_path = os.path.join(db_storage_path(), "knowledge")
+            self.app = chromadb.PersistentClient(
+                path=base_path,
+                settings=Settings(allow_reset=True),
+            )
+            self.app.reset()
 
     def save(
-        self, documents: List[str], metadata: Dict[str, Any] | List[Dict[str, Any]]
+        self,
+        documents: List[str],
+        metadata: Union[Dict[str, Any], List[Dict[str, Any]]],
     ):
         if self.collection:
-            metadatas = [metadata] if isinstance(metadata, dict) else metadata
+            try:
+                metadatas = [metadata] if isinstance(metadata, dict) else metadata
 
-            ids = [
-                hashlib.sha256(doc.encode("utf-8")).hexdigest() for doc in documents
-            ]
+                ids = [
+                    hashlib.sha256(doc.encode("utf-8")).hexdigest() for doc in documents
+                ]
 
-            self.collection.upsert(
-                documents=documents,
-                metadatas=metadatas,
-                ids=ids,
-            )
+                self.collection.upsert(
+                    documents=documents,
+                    metadatas=metadatas,
+                    ids=ids,
+                )
+            except chromadb.errors.InvalidDimensionException as e:
+                Logger(verbose=True).log(
+                    "error",
+                    "Embedding dimension mismatch. This usually happens when mixing different embedding models. Try resetting the collection using `crewai reset-memories -a`",
+                    "red",
+                )
+                raise ValueError(
+                    "Embedding dimension mismatch. Make sure you're using the same embedding model "
+                    "across all operations with this collection."
+                    "Try resetting the collection using `crewai reset-memories -a`"
+                ) from e
+            except Exception as e:
+                Logger(verbose=True).log(
+                    "error", f"Failed to upsert documents: {e}", "red"
+                )
+                raise
         else:
             raise Exception("Collection not initialized")
 
diff --git a/src/crewai/knowledge/utils/knowledge_utils.py b/src/crewai/knowledge/utils/knowledge_utils.py
new file mode 100644
index 000000000..bdd8b9a4e
--- /dev/null
+++ b/src/crewai/knowledge/utils/knowledge_utils.py
@@ -0,0 +1,12 @@
+from typing import Any, Dict, List
+
+
+def extract_knowledge_context(knowledge_snippets: List[Dict[str, Any]]) -> str:
+    """Extract knowledge from the task prompt."""
+    valid_snippets = [
+        result["context"]
+        for result in knowledge_snippets
+        if result and result.get("context")
+    ]
+    snippet = "\n".join(valid_snippets)
+    return f"Additional Information: {snippet}" if valid_snippets else ""
diff --git a/tests/agent_test.py b/tests/agent_test.py
index fb6ab22b8..1f4b62fd0 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -3,20 +3,19 @@
 import os
 from unittest import mock
 from unittest.mock import patch
-
 import pytest
 
 from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
-from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.llm import LLM
 from crewai.tools import tool
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
 from crewai.tools.tool_usage_events import ToolUsageFinished
 from crewai.utilities import RPMController
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.utilities.events import Emitter
 
 
@@ -1584,21 +1583,22 @@ def test_agent_with_knowledge_sources():
     string_source = StringKnowledgeSource(
         content=content, metadata={"preference": "personal"}
     )
-    
 
-    with patch('crewai.knowledge.storage.knowledge_storage.KnowledgeStorage') as MockKnowledge:
+    with patch(
+        "crewai.knowledge.storage.knowledge_storage.KnowledgeStorage"
+    ) as MockKnowledge:
         mock_knowledge_instance = MockKnowledge.return_value
         mock_knowledge_instance.sources = [string_source]
-        mock_knowledge_instance.query.return_value = [{
-            "content": content,
-            "metadata": {"preference": "personal"}
-        }]
-        
+        mock_knowledge_instance.query.return_value = [
+            {"content": content, "metadata": {"preference": "personal"}}
+        ]
+
         agent = Agent(
             role="Information Agent",
             goal="Provide information based on knowledge sources",
             backstory="You have access to specific knowledge sources.",
             llm=LLM(model="gpt-4o-mini"),
+            knowledge_sources=[string_source],
         )
 
         # Create a task that requires the agent to use the knowledge
@@ -1613,4 +1613,3 @@ def test_agent_with_knowledge_sources():
 
         # Assert that the agent provides the correct information
         assert "blue" in result.raw.lower()
-
diff --git a/tests/cassettes/test_agent_with_knowledge_sources.yaml b/tests/cassettes/test_agent_with_knowledge_sources.yaml
index d483a19d2..fdc9f912e 100644
--- a/tests/cassettes/test_agent_with_knowledge_sources.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_sources.yaml
@@ -1,4 +1,415 @@
 interactions:
+- request:
+    body: '{"input": ["Brandon''s favorite color is blue and he likes Mexican food."],
+      "model": "text-embedding-3-small", "encoding_format": "base64"}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      content-length:
+      - '138'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.52.1
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.52.1
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.11.9
+    method: POST
+    uri: https://api.openai.com/v1/embeddings
+  response:
+    body:
+      string: !!binary |
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From 588ad3c4a437096d42b390679064da21af4c8b85 Mon Sep 17 00:00:00 2001
From: Rok Benko <ksjeno@gmail.com>
Date: Thu, 28 Nov 2024 17:20:53 +0100
Subject: [PATCH 086/126] Update Agents docs to include two approaches for
 creating an agent: with and without YAML configuration

---
 docs/concepts/agents.mdx | 170 +++++++++++++++++++++++++++++++--------
 1 file changed, 138 insertions(+), 32 deletions(-)

diff --git a/docs/concepts/agents.mdx b/docs/concepts/agents.mdx
index 6c939b321..84e22ef89 100644
--- a/docs/concepts/agents.mdx
+++ b/docs/concepts/agents.mdx
@@ -7,49 +7,154 @@ icon: robot
 ## What is an agent?
 
 An agent is an **autonomous unit** programmed to:
+
 <ul>
-    <li class='leading-3'>Perform tasks</li>
-    <li class='leading-3'>Make decisions</li>
-    <li class='leading-3'>Communicate with other agents</li>
+  <li class="leading-3">Perform tasks</li>
+  <li class="leading-3">Make decisions</li>
+  <li class="leading-3">Communicate with other agents</li>
 </ul>
 
 <Tip>
-Think of an agent as a member of a team, with specific skills and a particular job to do. Agents can have different roles like `Researcher`, `Writer`, or `Customer Support`, each contributing to the overall goal of the crew.
+  Think of an agent as a member of a team, with specific skills and a particular
+  job to do. Agents can have different roles like `Researcher`, `Writer`, or
+  `Customer Support`, each contributing to the overall goal of the crew.
 </Tip>
 
 ## Agent attributes
 
-| Attribute                  | Parameter  | Description                                                                                                                                                                                                                                    |
-| :------------------------- | :--------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Role**                   | `role`     | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for.                                                                                                                                    |
-| **Goal**                   | `goal`     | The individual objective that the agent aims to achieve. It guides the agent's decision-making process.                                                                                                                                        |
-| **Backstory**              | `backstory`| Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics.                                                                                                                                           |
-| **LLM** *(optional)*       | `llm`      | Represents the language model that will run the agent. It dynamically fetches the model name from the `OPENAI_MODEL_NAME` environment variable, defaulting to "gpt-4" if not specified.                                                         |
-| **Tools** *(optional)*     | `tools`    | Set of capabilities or functions that the agent can use to perform tasks. Expected to be instances of custom classes compatible with the agent's execution environment. Tools are initialized with a default value of an empty list.             |
-| **Function Calling LLM** *(optional)* | `function_calling_llm`  | Specifies the language model that will handle the tool calling for this agent, overriding the crew function calling LLM if passed. Default is `None`.                                                                                          |
-| **Max Iter** *(optional)*  | `max_iter` | Max Iter is the maximum number of iterations the agent can perform before being forced to give its best answer. Default is `25`.                                                                                                                           |
-| **Max RPM** *(optional)*   | `max_rpm`  | Max RPM is the maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified, with a default value of `None`.                                                                               |
-| **Max Execution Time** *(optional)*   | `max_execution_time`  | Max Execution Time is the maximum execution time for an agent to execute a task. It's optional and can be left unspecified, with a default value of `None`, meaning no max execution time.                                                                     |
-| **Verbose** *(optional)*   | `verbose`  | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`.                                                                                              |
-| **Allow Delegation** *(optional)* | `allow_delegation`  | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `False`.                                                                                                      |
-| **Step Callback** *(optional)* | `step_callback`  | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`.                                                               |
-| **Cache** *(optional)*     | `cache`  | Indicates if the agent should use a cache for tool usage. Default is `True`.                                                                                                                                                                  |
-| **System Template** *(optional)*     | `system_template`  | Specifies the system format for the agent. Default is `None`.                                                                                                                                                                  |
-| **Prompt Template** *(optional)*     | `prompt_template`  | Specifies the prompt format for the agent. Default is `None`.                                                                                                                                                                  |
-| **Response Template** *(optional)*     | `response_template`  | Specifies the response format for the agent. Default is `None`.                                                                                                                                                                  |
-| **Allow Code Execution** *(optional)*     | `allow_code_execution`  | Enable code execution for the agent. Default is `False`.                                                                                                                                                                  |
-| **Max Retry Limit** *(optional)*     | `max_retry_limit`  | Maximum number of retries for an agent to execute a task when an error occurs. Default is `2`.                                                                                                                                                                  |
-| **Use System Prompt** *(optional)*     | `use_system_prompt`  | Adds the ability to not use system prompt (to support o1 models). Default is `True`.                                                                                                                                                                  |
-| **Respect Context Window** *(optional)*     | `respect_context_window`  | Summary strategy to avoid overflowing the context window. Default is `True`.                                                                                                                                                                  |
-| **Code Execution Mode** *(optional)* | `code_execution_mode` | Determines the mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution on the host machine). Default is `safe`.                                                                                                          |
+| Attribute                               | Parameter                | Description                                                                                                                                                                                                                          |
+| :-------------------------------------- | :----------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **Role**                                | `role`                   | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for.                                                                                                                          |
+| **Goal**                                | `goal`                   | The individual objective that the agent aims to achieve. It guides the agent's decision-making process.                                                                                                                              |
+| **Backstory**                           | `backstory`              | Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics.                                                                                                                                 |
+| **LLM** _(optional)_                    | `llm`                    | Represents the language model that will run the agent. It dynamically fetches the model name from the `OPENAI_MODEL_NAME` environment variable, defaulting to "gpt-4" if not specified.                                              |
+| **Tools** _(optional)_                  | `tools`                  | Set of capabilities or functions that the agent can use to perform tasks. Expected to be instances of custom classes compatible with the agent's execution environment. Tools are initialized with a default value of an empty list. |
+| **Function Calling LLM** _(optional)_   | `function_calling_llm`   | Specifies the language model that will handle the tool calling for this agent, overriding the crew function calling LLM if passed. Default is `None`.                                                                                |
+| **Max Iter** _(optional)_               | `max_iter`               | Max Iter is the maximum number of iterations the agent can perform before being forced to give its best answer. Default is `25`.                                                                                                     |
+| **Max RPM** _(optional)_                | `max_rpm`                | Max RPM is the maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified, with a default value of `None`.                                                          |
+| **Max Execution Time** _(optional)_     | `max_execution_time`     | Max Execution Time is the maximum execution time for an agent to execute a task. It's optional and can be left unspecified, with a default value of `None`, meaning no max execution time.                                           |
+| **Verbose** _(optional)_                | `verbose`                | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`.                                                                                    |
+| **Allow Delegation** _(optional)_       | `allow_delegation`       | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `False`.                                                                                            |
+| **Step Callback** _(optional)_          | `step_callback`          | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`.                                                      |
+| **Cache** _(optional)_                  | `cache`                  | Indicates if the agent should use a cache for tool usage. Default is `True`.                                                                                                                                                         |
+| **System Template** _(optional)_        | `system_template`        | Specifies the system format for the agent. Default is `None`.                                                                                                                                                                        |
+| **Prompt Template** _(optional)_        | `prompt_template`        | Specifies the prompt format for the agent. Default is `None`.                                                                                                                                                                        |
+| **Response Template** _(optional)_      | `response_template`      | Specifies the response format for the agent. Default is `None`.                                                                                                                                                                      |
+| **Allow Code Execution** _(optional)_   | `allow_code_execution`   | Enable code execution for the agent. Default is `False`.                                                                                                                                                                             |
+| **Max Retry Limit** _(optional)_        | `max_retry_limit`        | Maximum number of retries for an agent to execute a task when an error occurs. Default is `2`.                                                                                                                                       |
+| **Use System Prompt** _(optional)_      | `use_system_prompt`      | Adds the ability to not use system prompt (to support o1 models). Default is `True`.                                                                                                                                                 |
+| **Respect Context Window** _(optional)_ | `respect_context_window` | Summary strategy to avoid overflowing the context window. Default is `True`.                                                                                                                                                         |
+| **Code Execution Mode** _(optional)_    | `code_execution_mode`    | Determines the mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution on the host machine). Default is `safe`.                                                                                                 |
 
 ## Creating an agent
 
 <Note>
-  **Agent interaction**: Agents can interact with each other using CrewAI's built-in delegation and communication mechanisms. This allows for dynamic task management and problem-solving within the crew.
+  **Agent interaction**: Agents can interact with each other using CrewAI's
+  built-in delegation and communication mechanisms. This allows for dynamic task
+  management and problem-solving within the crew.
 </Note>
 
-To create an agent, you would typically initialize an instance of the `Agent` class with the desired properties. Here's a conceptual example including all attributes:
+Agents can be created using one of the following methods:
+
+<ul>
+  <li class="leading-3">
+    **With a YAML configuration (recommended):** Define agent properties in a
+    structured YAML file, promoting reusability and cleaner code.
+  </li>
+  <li class="leading-3">
+    **Without a YAML configuration:** Define agent properties directly in your
+    code.
+  </li>
+</ul>
+
+### Creating an agent with a YAML configuration (recommended)
+
+The YAML configuration approach allows you to separate the agent's required properties (i.e., `role`, `goal`, and `backstory`) from the code logic. This makes your setup modular, easier to manage, and reusable across multiple projects.
+
+#### Step 1: Define an agent in a YAML file
+
+The YAML file contains required properties of the agent:
+
+<ul>
+  <li class="leading-3">
+    `role`: A short description of the agent's purpose or position.
+  </li>
+  <li class="leading-3">
+    `goal`: The primary objective the agent is designed to accomplish.
+  </li>
+  <li class="leading-3">
+    `backstory`: A detailed description of the agent's context to enhance its
+    understanding and responses.
+  </li>
+</ul>
+
+<Note>
+  The YAML file should only include these three properties (i.e., `role`,
+  `goal`, and `backstory`). Any additional configurations must be defined in the
+  `crew.py` file.
+</Note>
+
+```yaml agents.yaml
+data_analyst:
+  role: |
+    Data Analyst
+  goal: |
+    Extract actionable insights
+  backstory: >
+    You're a data analyst at a large company. You're responsible for analyzing
+    data and providing insights to the business. You're currently working on a
+    project to analyze the performance of our marketing campaigns.
+```
+
+#### Step 2: Initialize the agent in `crew.py`
+
+After defining the agent in the YAML file, you need to create an instance of the `Agent` class in your code and link it to the YAML configuration. This is done in the `crew.py` file, where additional properties can be specified.
+
+```python crew.py
+from crewai import Agent, Crew, Process, Task
+from crewai.project import CrewBase, agent, crew, task
+
+@CrewBase
+class ResearchCrew():
+  """Research crew"""
+
+  agents_config = "your/path/to/agents.yaml"
+
+  @agent
+  def data_analyst(self) -> Agent:
+    return Agent(
+      config=self.agents_config['data_analyst'],
+      tools=[my_tool1, my_tool2],  # Optional, defaults to an empty list
+      llm=my_llm,  # Optional
+      function_calling_llm=my_llm,  # Optional
+      max_iter=15,  # Optional
+      max_rpm=None, # Optional
+      max_execution_time=None, # Optional
+      verbose=True,  # Optional
+      allow_delegation=False,  # Optional
+      step_callback=my_intermediate_step_callback,  # Optional
+      cache=True,  # Optional
+      system_template=my_system_template,  # Optional
+      prompt_template=my_prompt_template,  # Optional
+      response_template=my_response_template,  # Optional
+      config=my_config,  # Optional
+      crew=my_crew,  # Optional
+      tools_handler=my_tools_handler,  # Optional
+      cache_handler=my_cache_handler,  # Optional
+      callbacks=[callback1, callback2],  # Optional
+      allow_code_execution=True,  # Optional
+      max_retry_limit=2,  # Optional
+      use_system_prompt=True,  # Optional
+      respect_context_window=True,  # Optional
+      code_execution_mode='safe',  # Optional, defaults to 'safe'
+    )
+
+  # ... remaining code
+```
+
+### Creating an agent without a YAML configuration
+
+The non-YAML configuration approach allows you to define the agent's properties directly in your code. Initialize an instance of the `Agent` class with the desired properties.
 
 ```python Code example
 from crewai import Agent
@@ -110,8 +215,9 @@ agent = Agent(
 
 Extend your third-party agents like LlamaIndex, Langchain, Autogen or fully custom agents using the the CrewAI's `BaseAgent` class.
 
-<Note>   
-  **BaseAgent** includes attributes and methods required to integrate with your crews to run and delegate tasks to other agents within your own crew.
+<Note>
+  **BaseAgent** includes attributes and methods required to integrate with your
+  crews to run and delegate tasks to other agents within your own crew.
 </Note>
 
 CrewAI is a universal multi-agent framework that allows for all agents to work together to automate tasks and solve problems.
@@ -157,5 +263,5 @@ crew = my_crew.kickoff(inputs={"input": "Mark Twain"})
 
 ## Conclusion
 
-Agents are the building blocks of the CrewAI framework. By understanding how to define and interact with agents, 
+Agents are the building blocks of the CrewAI framework. By understanding how to define and interact with agents,
 you can create sophisticated AI systems that leverage the power of collaborative intelligence. The `code_execution_mode` attribute provides flexibility in how agents execute code, allowing for both secure and direct execution options.

From 4bc23affe0e322f4c48be7ea4e5abb0e273569d6 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Mon, 2 Dec 2024 09:50:12 -0500
Subject: [PATCH 087/126] Documentation Improvements: LLM Configuration and
 Usage (#1684)

* docs: improve tasks documentation clarity and structure

- Add Task Execution Flow section
- Add variable interpolation explanation
- Add Task Dependencies section with examples
- Improve overall document structure and readability
- Update code examples with proper syntax highlighting

* docs: update agent documentation with improved examples and formatting

- Replace DuckDuckGoSearchRun with SerperDevTool
- Update code block formatting to be consistent
- Improve template examples with actual syntax
- Update LLM examples to use current models
- Clean up formatting and remove redundant comments

* docs: enhance LLM documentation with Cerebras provider and formatting improvements

* docs: simplify LLMs documentation title

* docs: improve installation guide clarity and structure

- Add clear Python version requirements with check command
- Simplify installation options to recommended method
- Improve upgrade section clarity for existing users
- Add better visual structure with Notes and Tips
- Update description and formatting

* docs: improve introduction page organization and clarity

- Update organizational analogy in Note section
- Improve table formatting and alignment
- Remove emojis from component table for cleaner look
- Add 'helps you' to make the note more action-oriented

* docs: add enterprise and community cards

- Add Enterprise deployment card in quickstart
- Add community card focused on open source discussions
- Remove deployment reference from community description
- Clean up introduction page cards
- Remove link from Enterprise description text
---
 docs/concepts/agents.mdx    | 490 ++++++++++++---------
 docs/concepts/knowledge.mdx | 253 +++++++----
 docs/concepts/llms.mdx      | 821 +++++++++++++++++++++++-------------
 docs/concepts/tasks.mdx     | 203 +++++++--
 docs/installation.mdx       | 223 +++++-----
 docs/introduction.mdx       |  96 +++--
 docs/quickstart.mdx         |  19 +-
 7 files changed, 1369 insertions(+), 736 deletions(-)

diff --git a/docs/concepts/agents.mdx b/docs/concepts/agents.mdx
index 84e22ef89..fda4fc55f 100644
--- a/docs/concepts/agents.mdx
+++ b/docs/concepts/agents.mdx
@@ -1,267 +1,343 @@
 ---
 title: Agents
-description: What are CrewAI Agents and how to use them.
+description: Detailed guide on creating and managing agents within the CrewAI framework.
 icon: robot
 ---
 
-## What is an agent?
+## Overview of an Agent
 
-An agent is an **autonomous unit** programmed to:
-
-<ul>
-  <li class="leading-3">Perform tasks</li>
-  <li class="leading-3">Make decisions</li>
-  <li class="leading-3">Communicate with other agents</li>
-</ul>
+In the CrewAI framework, an `Agent` is an autonomous unit that can:
+- Perform specific tasks
+- Make decisions based on its role and goal
+- Use tools to accomplish objectives
+- Communicate and collaborate with other agents
+- Maintain memory of interactions
+- Delegate tasks when allowed
 
 <Tip>
-  Think of an agent as a member of a team, with specific skills and a particular
-  job to do. Agents can have different roles like `Researcher`, `Writer`, or
-  `Customer Support`, each contributing to the overall goal of the crew.
+Think of an agent as a specialized team member with specific skills, expertise, and responsibilities. For example, a `Researcher` agent might excel at gathering and analyzing information, while a `Writer` agent might be better at creating content.
 </Tip>
 
-## Agent attributes
+## Agent Attributes
 
-| Attribute                               | Parameter                | Description                                                                                                                                                                                                                          |
-| :-------------------------------------- | :----------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Role**                                | `role`                   | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for.                                                                                                                          |
-| **Goal**                                | `goal`                   | The individual objective that the agent aims to achieve. It guides the agent's decision-making process.                                                                                                                              |
-| **Backstory**                           | `backstory`              | Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics.                                                                                                                                 |
-| **LLM** _(optional)_                    | `llm`                    | Represents the language model that will run the agent. It dynamically fetches the model name from the `OPENAI_MODEL_NAME` environment variable, defaulting to "gpt-4" if not specified.                                              |
-| **Tools** _(optional)_                  | `tools`                  | Set of capabilities or functions that the agent can use to perform tasks. Expected to be instances of custom classes compatible with the agent's execution environment. Tools are initialized with a default value of an empty list. |
-| **Function Calling LLM** _(optional)_   | `function_calling_llm`   | Specifies the language model that will handle the tool calling for this agent, overriding the crew function calling LLM if passed. Default is `None`.                                                                                |
-| **Max Iter** _(optional)_               | `max_iter`               | Max Iter is the maximum number of iterations the agent can perform before being forced to give its best answer. Default is `25`.                                                                                                     |
-| **Max RPM** _(optional)_                | `max_rpm`                | Max RPM is the maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified, with a default value of `None`.                                                          |
-| **Max Execution Time** _(optional)_     | `max_execution_time`     | Max Execution Time is the maximum execution time for an agent to execute a task. It's optional and can be left unspecified, with a default value of `None`, meaning no max execution time.                                           |
-| **Verbose** _(optional)_                | `verbose`                | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`.                                                                                    |
-| **Allow Delegation** _(optional)_       | `allow_delegation`       | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `False`.                                                                                            |
-| **Step Callback** _(optional)_          | `step_callback`          | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`.                                                      |
-| **Cache** _(optional)_                  | `cache`                  | Indicates if the agent should use a cache for tool usage. Default is `True`.                                                                                                                                                         |
-| **System Template** _(optional)_        | `system_template`        | Specifies the system format for the agent. Default is `None`.                                                                                                                                                                        |
-| **Prompt Template** _(optional)_        | `prompt_template`        | Specifies the prompt format for the agent. Default is `None`.                                                                                                                                                                        |
-| **Response Template** _(optional)_      | `response_template`      | Specifies the response format for the agent. Default is `None`.                                                                                                                                                                      |
-| **Allow Code Execution** _(optional)_   | `allow_code_execution`   | Enable code execution for the agent. Default is `False`.                                                                                                                                                                             |
-| **Max Retry Limit** _(optional)_        | `max_retry_limit`        | Maximum number of retries for an agent to execute a task when an error occurs. Default is `2`.                                                                                                                                       |
-| **Use System Prompt** _(optional)_      | `use_system_prompt`      | Adds the ability to not use system prompt (to support o1 models). Default is `True`.                                                                                                                                                 |
-| **Respect Context Window** _(optional)_ | `respect_context_window` | Summary strategy to avoid overflowing the context window. Default is `True`.                                                                                                                                                         |
-| **Code Execution Mode** _(optional)_    | `code_execution_mode`    | Determines the mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution on the host machine). Default is `safe`.                                                                                                 |
+| Attribute                               | Parameter                | Type                          | Description                                                                                                          |
+| :-------------------------------------- | :----------------------- | :---------------------------- | :------------------------------------------------------------------------------------------------------------------- |
+| **Role**                                | `role`                   | `str`                         | Defines the agent's function and expertise within the crew.                                                           |
+| **Goal**                                | `goal`                   | `str`                         | The individual objective that guides the agent's decision-making.                                                     |
+| **Backstory**                           | `backstory`              | `str`                         | Provides context and personality to the agent, enriching interactions.                                                |
+| **LLM** _(optional)_                    | `llm`                    | `Union[str, LLM, Any]`        | Language model that powers the agent. Defaults to the model specified in `OPENAI_MODEL_NAME` or "gpt-4".              |
+| **Tools** _(optional)_                  | `tools`                  | `List[BaseTool]`              | Capabilities or functions available to the agent. Defaults to an empty list.                                          |
+| **Function Calling LLM** _(optional)_   | `function_calling_llm`   | `Optional[Any]`               | Language model for tool calling, overrides crew's LLM if specified.                                                   |
+| **Max Iterations** _(optional)_         | `max_iter`               | `int`                         | Maximum iterations before the agent must provide its best answer. Default is 20.                                      |
+| **Max RPM** _(optional)_                | `max_rpm`                | `Optional[int]`               | Maximum requests per minute to avoid rate limits.                                                                     |
+| **Max Execution Time** _(optional)_     | `max_execution_time`     | `Optional[int]`               | Maximum time (in seconds) for task execution.                                                                         |
+| **Memory** _(optional)_                 | `memory`                 | `bool`                        | Whether the agent should maintain memory of interactions. Default is True.                                            |
+| **Verbose** _(optional)_                | `verbose`                | `bool`                        | Enable detailed execution logs for debugging. Default is False.                                                       |
+| **Allow Delegation** _(optional)_       | `allow_delegation`       | `bool`                        | Allow the agent to delegate tasks to other agents. Default is False.                                                  |
+| **Step Callback** _(optional)_          | `step_callback`          | `Optional[Any]`               | Function called after each agent step, overrides crew callback.                                                       |
+| **Cache** _(optional)_                  | `cache`                  | `bool`                        | Enable caching for tool usage. Default is True.                                                                       |
+| **System Template** _(optional)_        | `system_template`        | `Optional[str]`               | Custom system prompt template for the agent.                                                                          |
+| **Prompt Template** _(optional)_        | `prompt_template`        | `Optional[str]`               | Custom prompt template for the agent.                                                                                 |
+| **Response Template** _(optional)_      | `response_template`      | `Optional[str]`               | Custom response template for the agent.                                                                               |
+| **Allow Code Execution** _(optional)_   | `allow_code_execution`   | `Optional[bool]`              | Enable code execution for the agent. Default is False.                                                                |
+| **Max Retry Limit** _(optional)_        | `max_retry_limit`        | `int`                         | Maximum number of retries when an error occurs. Default is 2.                                                         |
+| **Respect Context Window** _(optional)_ | `respect_context_window` | `bool`                        | Keep messages under context window size by summarizing. Default is True.                                              |
+| **Code Execution Mode** _(optional)_    | `code_execution_mode`    | `Literal["safe", "unsafe"]`   | Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct). Default is 'safe'.                               |
+| **Embedder Config** _(optional)_        | `embedder_config`        | `Optional[Dict[str, Any]]`    | Configuration for the embedder used by the agent.                                                                     |
+| **Knowledge Sources** _(optional)_      | `knowledge_sources`      | `Optional[List[BaseKnowledgeSource]]` | Knowledge sources available to the agent.                                                                     |
+| **Use System Prompt** _(optional)_      | `use_system_prompt`      | `Optional[bool]`              | Whether to use system prompt (for o1 model support). Default is True.                                                 |
 
-## Creating an agent
+## Creating Agents
+
+There are two ways to create agents in CrewAI: using **YAML configuration (recommended)** or defining them **directly in code**.
+
+### YAML Configuration (Recommended)
+
+Using YAML configuration provides a cleaner, more maintainable way to define agents. We strongly recommend using this approach in your CrewAI projects.
+
+After creating your CrewAI project as outlined in the [Installation](/installation) section, navigate to the `src/latest_ai_development/config/agents.yaml` file and modify the template to match your requirements.
 
 <Note>
-  **Agent interaction**: Agents can interact with each other using CrewAI's
-  built-in delegation and communication mechanisms. This allows for dynamic task
-  management and problem-solving within the crew.
+Variables in your YAML files (like `{topic}`) will be replaced with values from your inputs when running the crew:
+```python Code
+crew.kickoff(inputs={'topic': 'AI Agents'})
+```
 </Note>
 
-Agents can be created using one of the following methods:
-
-<ul>
-  <li class="leading-3">
-    **With a YAML configuration (recommended):** Define agent properties in a
-    structured YAML file, promoting reusability and cleaner code.
-  </li>
-  <li class="leading-3">
-    **Without a YAML configuration:** Define agent properties directly in your
-    code.
-  </li>
-</ul>
-
-### Creating an agent with a YAML configuration (recommended)
-
-The YAML configuration approach allows you to separate the agent's required properties (i.e., `role`, `goal`, and `backstory`) from the code logic. This makes your setup modular, easier to manage, and reusable across multiple projects.
-
-#### Step 1: Define an agent in a YAML file
-
-The YAML file contains required properties of the agent:
-
-<ul>
-  <li class="leading-3">
-    `role`: A short description of the agent's purpose or position.
-  </li>
-  <li class="leading-3">
-    `goal`: The primary objective the agent is designed to accomplish.
-  </li>
-  <li class="leading-3">
-    `backstory`: A detailed description of the agent's context to enhance its
-    understanding and responses.
-  </li>
-</ul>
-
-<Note>
-  The YAML file should only include these three properties (i.e., `role`,
-  `goal`, and `backstory`). Any additional configurations must be defined in the
-  `crew.py` file.
-</Note>
+Here's an example of how to configure agents using YAML:
 
 ```yaml agents.yaml
-data_analyst:
-  role: |
-    Data Analyst
-  goal: |
-    Extract actionable insights
+# src/latest_ai_development/config/agents.yaml
+researcher:
+  role: >
+    {topic} Senior Data Researcher
+  goal: >
+    Uncover cutting-edge developments in {topic}
   backstory: >
-    You're a data analyst at a large company. You're responsible for analyzing
-    data and providing insights to the business. You're currently working on a
-    project to analyze the performance of our marketing campaigns.
+    You're a seasoned researcher with a knack for uncovering the latest
+    developments in {topic}. Known for your ability to find the most relevant
+    information and present it in a clear and concise manner.
+
+reporting_analyst:
+  role: >
+    {topic} Reporting Analyst
+  goal: >
+    Create detailed reports based on {topic} data analysis and research findings
+  backstory: >
+    You're a meticulous analyst with a keen eye for detail. You're known for
+    your ability to turn complex data into clear and concise reports, making
+    it easy for others to understand and act on the information you provide.
 ```
 
-#### Step 2: Initialize the agent in `crew.py`
+To use this YAML configuration in your code, create a crew class that inherits from `CrewBase`:
 
-After defining the agent in the YAML file, you need to create an instance of the `Agent` class in your code and link it to the YAML configuration. This is done in the `crew.py` file, where additional properties can be specified.
-
-```python crew.py
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
+```python Code
+# src/latest_ai_development/crew.py
+from crewai import Agent, Crew, Process
+from crewai.project import CrewBase, agent, crew
+from crewai_tools import SerperDevTool
 
 @CrewBase
-class ResearchCrew():
-  """Research crew"""
-
-  agents_config = "your/path/to/agents.yaml"
+class LatestAiDevelopmentCrew():
+  """LatestAiDevelopment crew"""
 
   @agent
-  def data_analyst(self) -> Agent:
+  def researcher(self) -> Agent:
     return Agent(
-      config=self.agents_config['data_analyst'],
-      tools=[my_tool1, my_tool2],  # Optional, defaults to an empty list
-      llm=my_llm,  # Optional
-      function_calling_llm=my_llm,  # Optional
-      max_iter=15,  # Optional
-      max_rpm=None, # Optional
-      max_execution_time=None, # Optional
-      verbose=True,  # Optional
-      allow_delegation=False,  # Optional
-      step_callback=my_intermediate_step_callback,  # Optional
-      cache=True,  # Optional
-      system_template=my_system_template,  # Optional
-      prompt_template=my_prompt_template,  # Optional
-      response_template=my_response_template,  # Optional
-      config=my_config,  # Optional
-      crew=my_crew,  # Optional
-      tools_handler=my_tools_handler,  # Optional
-      cache_handler=my_cache_handler,  # Optional
-      callbacks=[callback1, callback2],  # Optional
-      allow_code_execution=True,  # Optional
-      max_retry_limit=2,  # Optional
-      use_system_prompt=True,  # Optional
-      respect_context_window=True,  # Optional
-      code_execution_mode='safe',  # Optional, defaults to 'safe'
+      config=self.agents_config['researcher'],
+      verbose=True,
+      tools=[SerperDevTool()]
     )
 
-  # ... remaining code
+  @agent
+  def reporting_analyst(self) -> Agent:
+    return Agent(
+      config=self.agents_config['reporting_analyst'],
+      verbose=True
+    )
 ```
 
-### Creating an agent without a YAML configuration
+<Note>
+The names you use in your YAML files (`agents.yaml`) should match the method names in your Python code.
+</Note>
 
-The non-YAML configuration approach allows you to define the agent's properties directly in your code. Initialize an instance of the `Agent` class with the desired properties.
+### Direct Code Definition
 
-```python Code example
+You can create agents directly in code by instantiating the `Agent` class. Here's a comprehensive example showing all available parameters:
+
+```python Code
 from crewai import Agent
+from crewai_tools import SerperDevTool
 
+# Create an agent with all available parameters
 agent = Agent(
-  role='Data Analyst',
-  goal='Extract actionable insights',
-  backstory="""You're a data analyst at a large company.
-    You're responsible for analyzing data and providing insights
-    to the business.
-    You're currently working on a project to analyze the
-    performance of our marketing campaigns.""",
-  tools=[my_tool1, my_tool2],  # Optional, defaults to an empty list
-  llm=my_llm,  # Optional
-  function_calling_llm=my_llm,  # Optional
-  max_iter=15,  # Optional
-  max_rpm=None, # Optional
-  max_execution_time=None, # Optional
-  verbose=True,  # Optional
-  allow_delegation=False,  # Optional
-  step_callback=my_intermediate_step_callback,  # Optional
-  cache=True,  # Optional
-  system_template=my_system_template,  # Optional
-  prompt_template=my_prompt_template,  # Optional
-  response_template=my_response_template,  # Optional
-  config=my_config,  # Optional
-  crew=my_crew,  # Optional
-  tools_handler=my_tools_handler,  # Optional
-  cache_handler=my_cache_handler,  # Optional
-  callbacks=[callback1, callback2],  # Optional
-  allow_code_execution=True,  # Optional
-  max_retry_limit=2,  # Optional
-  use_system_prompt=True,  # Optional
-  respect_context_window=True,  # Optional
-  code_execution_mode='safe',  # Optional, defaults to 'safe'
+    role="Senior Data Scientist",
+    goal="Analyze and interpret complex datasets to provide actionable insights",
+    backstory="With over 10 years of experience in data science and machine learning, "
+              "you excel at finding patterns in complex datasets.",
+    llm="gpt-4",  # Default: OPENAI_MODEL_NAME or "gpt-4"
+    function_calling_llm=None,  # Optional: Separate LLM for tool calling
+    memory=True,  # Default: True
+    verbose=False,  # Default: False
+    allow_delegation=False,  # Default: False
+    max_iter=20,  # Default: 20 iterations
+    max_rpm=None,  # Optional: Rate limit for API calls
+    max_execution_time=None,  # Optional: Maximum execution time in seconds
+    max_retry_limit=2,  # Default: 2 retries on error
+    allow_code_execution=False,  # Default: False
+    code_execution_mode="safe",  # Default: "safe" (options: "safe", "unsafe")
+    respect_context_window=True,  # Default: True
+    use_system_prompt=True,  # Default: True
+    tools=[SerperDevTool()],  # Optional: List of tools
+    knowledge_sources=None,  # Optional: List of knowledge sources
+    embedder_config=None,  # Optional: Custom embedder configuration
+    system_template=None,  # Optional: Custom system prompt template
+    prompt_template=None,  # Optional: Custom prompt template
+    response_template=None,  # Optional: Custom response template
+    step_callback=None,  # Optional: Callback function for monitoring
 )
 ```
 
-## Setting prompt templates
+Let's break down some key parameter combinations for common use cases:
 
-Prompt templates are used to format the prompt for the agent. You can use to update the system, regular and response templates for the agent. Here's an example of how to set prompt templates:
+#### Basic Research Agent
+```python Code
+research_agent = Agent(
+    role="Research Analyst",
+    goal="Find and summarize information about specific topics",
+    backstory="You are an experienced researcher with attention to detail",
+    tools=[SerperDevTool()],
+    verbose=True  # Enable logging for debugging
+)
+```
 
-```python Code example
-agent = Agent(
-        role="{topic} specialist",
-        goal="Figure {goal} out",
-        backstory="I am the master of {role}",
-        system_template="""<|start_header_id|>system<|end_header_id|>
+#### Code Development Agent
+```python Code
+dev_agent = Agent(
+    role="Senior Python Developer",
+    goal="Write and debug Python code",
+    backstory="Expert Python developer with 10 years of experience",
+    allow_code_execution=True,
+    code_execution_mode="safe",  # Uses Docker for safety
+    max_execution_time=300,  # 5-minute timeout
+    max_retry_limit=3  # More retries for complex code tasks
+)
+```
+
+#### Long-Running Analysis Agent
+```python Code
+analysis_agent = Agent(
+    role="Data Analyst",
+    goal="Perform deep analysis of large datasets",
+    backstory="Specialized in big data analysis and pattern recognition",
+    memory=True,
+    respect_context_window=True,
+    max_rpm=10,  # Limit API calls
+    function_calling_llm="gpt-4o-mini"  # Cheaper model for tool calls
+)
+```
+
+#### Custom Template Agent
+```python Code
+custom_agent = Agent(
+    role="Customer Service Representative",
+    goal="Assist customers with their inquiries",
+    backstory="Experienced in customer support with a focus on satisfaction",
+    system_template="""<|start_header_id|>system<|end_header_id|>
                         {{ .System }}<|eot_id|>""",
-        prompt_template="""<|start_header_id|>user<|end_header_id|>
+    prompt_template="""<|start_header_id|>user<|end_header_id|>
                         {{ .Prompt }}<|eot_id|>""",
-        response_template="""<|start_header_id|>assistant<|end_header_id|>
+    response_template="""<|start_header_id|>assistant<|end_header_id|>
                         {{ .Response }}<|eot_id|>""",
 )
 ```
 
-## Bring your third-party agents
+### Parameter Details
 
-Extend your third-party agents like LlamaIndex, Langchain, Autogen or fully custom agents using the the CrewAI's `BaseAgent` class.
+#### Critical Parameters
+- `role`, `goal`, and `backstory` are required and shape the agent's behavior
+- `llm` determines the language model used (default: OpenAI's GPT-4)
+
+#### Memory and Context
+- `memory`: Enable to maintain conversation history
+- `respect_context_window`: Prevents token limit issues
+- `knowledge_sources`: Add domain-specific knowledge bases
+
+#### Execution Control
+- `max_iter`: Maximum attempts before giving best answer
+- `max_execution_time`: Timeout in seconds
+- `max_rpm`: Rate limiting for API calls
+- `max_retry_limit`: Retries on error
+
+#### Code Execution
+- `allow_code_execution`: Must be True to run code
+- `code_execution_mode`: 
+  - `"safe"`: Uses Docker (recommended for production)
+  - `"unsafe"`: Direct execution (use only in trusted environments)
+
+#### Templates
+- `system_template`: Defines agent's core behavior
+- `prompt_template`: Structures input format
+- `response_template`: Formats agent responses
 
 <Note>
-  **BaseAgent** includes attributes and methods required to integrate with your
-  crews to run and delegate tasks to other agents within your own crew.
+When using custom templates, you can use variables like `{role}`, `{goal}`, and `{input}` in your templates. These will be automatically populated during execution.
 </Note>
 
-CrewAI is a universal multi-agent framework that allows for all agents to work together to automate tasks and solve problems.
+## Agent Tools
 
-```python Code example
-from crewai import Agent, Task, Crew
-from custom_agent import CustomAgent # You need to build and extend your own agent logic with the CrewAI BaseAgent class then import it here.
+Agents can be equipped with various tools to enhance their capabilities. CrewAI supports tools from:
+- [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools)
+- [LangChain Tools](https://python.langchain.com/docs/integrations/tools)
 
-from langchain.agents import load_tools
+Here's how to add tools to an agent:
 
-langchain_tools = load_tools(["google-serper"], llm=llm)
+```python Code
+from crewai import Agent
+from crewai_tools import SerperDevTool, WikipediaTools
 
-agent1 = CustomAgent(
-    role="agent role",
-    goal="who is {input}?",
-    backstory="agent backstory",
-    verbose=True,
+# Create tools
+search_tool = SerperDevTool()
+wiki_tool = WikipediaTools()
+
+# Add tools to agent
+researcher = Agent(
+    role="AI Technology Researcher",
+    goal="Research the latest AI developments",
+    tools=[search_tool, wiki_tool],
+    verbose=True
 )
-
-task1 = Task(
-    expected_output="a short biography of {input}",
-    description="a short biography of {input}",
-    agent=agent1,
-)
-
-agent2 = Agent(
-    role="agent role",
-    goal="summarize the short bio for {input} and if needed do more research",
-    backstory="agent backstory",
-    verbose=True,
-)
-
-task2 = Task(
-    description="a tldr summary of the short biography",
-    expected_output="5 bullet point summary of the biography",
-    agent=agent2,
-    context=[task1],
-)
-
-my_crew = Crew(agents=[agent1, agent2], tasks=[task1, task2])
-crew = my_crew.kickoff(inputs={"input": "Mark Twain"})
 ```
 
-## Conclusion
+## Agent Memory and Context
 
-Agents are the building blocks of the CrewAI framework. By understanding how to define and interact with agents,
-you can create sophisticated AI systems that leverage the power of collaborative intelligence. The `code_execution_mode` attribute provides flexibility in how agents execute code, allowing for both secure and direct execution options.
+Agents can maintain memory of their interactions and use context from previous tasks. This is particularly useful for complex workflows where information needs to be retained across multiple tasks.
+
+```python Code
+from crewai import Agent
+
+analyst = Agent(
+    role="Data Analyst",
+    goal="Analyze and remember complex data patterns",
+    memory=True,  # Enable memory
+    verbose=True
+)
+```
+
+<Note>
+When `memory` is enabled, the agent will maintain context across multiple interactions, improving its ability to handle complex, multi-step tasks.
+</Note>
+
+## Important Considerations and Best Practices
+
+### Security and Code Execution
+- When using `allow_code_execution`, be cautious with user input and always validate it
+- Use `code_execution_mode: "safe"` (Docker) in production environments
+- Consider setting appropriate `max_execution_time` limits to prevent infinite loops
+
+### Performance Optimization
+- Use `respect_context_window: true` to prevent token limit issues
+- Set appropriate `max_rpm` to avoid rate limiting
+- Enable `cache: true` to improve performance for repetitive tasks
+- Adjust `max_iter` and `max_retry_limit` based on task complexity
+
+### Memory and Context Management
+- Use `memory: true` for tasks requiring historical context
+- Leverage `knowledge_sources` for domain-specific information
+- Configure `embedder_config` when using custom embedding models
+- Use custom templates (`system_template`, `prompt_template`, `response_template`) for fine-grained control over agent behavior
+
+### Agent Collaboration
+- Enable `allow_delegation: true` when agents need to work together
+- Use `step_callback` to monitor and log agent interactions
+- Consider using different LLMs for different purposes:
+  - Main `llm` for complex reasoning
+  - `function_calling_llm` for efficient tool usage
+
+### Model Compatibility
+- Set `use_system_prompt: false` for older models that don't support system messages
+- Ensure your chosen `llm` supports the features you need (like function calling)
+
+## Troubleshooting Common Issues
+
+1. **Rate Limiting**: If you're hitting API rate limits:
+   - Implement appropriate `max_rpm`
+   - Use caching for repetitive operations
+   - Consider batching requests
+
+2. **Context Window Errors**: If you're exceeding context limits:
+   - Enable `respect_context_window`
+   - Use more efficient prompts
+   - Clear agent memory periodically
+
+3. **Code Execution Issues**: If code execution fails:
+   - Verify Docker is installed for safe mode
+   - Check execution permissions
+   - Review code sandbox settings
+
+4. **Memory Issues**: If agent responses seem inconsistent:
+   - Verify memory is enabled
+   - Check knowledge source configuration
+   - Review conversation history management
+
+Remember that agents are most effective when configured according to their specific use case. Take time to understand your requirements and adjust these parameters accordingly.
diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index e51602947..69fa4e644 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -6,100 +6,205 @@ icon: book
 
 # Using Knowledge in CrewAI
 
-## Introduction
-
-Knowledge in CrewAI serves as a foundational component for enriching AI agents with contextual and relevant information. It enables agents to access and utilize structured data sources during their execution processes, making them more intelligent and responsive.
-
-The Knowledge class in CrewAI provides a powerful way to manage and query knowledge sources for your AI agents. This guide will show you how to implement knowledge management in your CrewAI projects.
-
 ## What is Knowledge?
 
-The `Knowledge` class in CrewAI manages various sources that store information, which can be queried and retrieved by AI agents. This modular approach allows you to integrate diverse data formats such as text, PDFs, spreadsheets, and more into your AI workflows.
+Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks. Think of it as giving your agents a reference library they can consult while working.
 
-Additionally, we have specific tools for generate knowledge sources for strings, text files, PDF's, and Spreadsheets. You can expand on any source type by extending the `KnowledgeSource` class.
+<Info>
+  Key benefits of using Knowledge:
+  - Enhance agents with domain-specific information
+  - Support decisions with real-world data
+  - Maintain context across conversations
+  - Ground responses in factual information
+</Info>
 
-## Basic Implementation
+## Supported Knowledge Sources
 
-Here's a simple example of how to use the Knowledge class:
+CrewAI supports various types of knowledge sources out of the box:
+
+<CardGroup cols={2}>
+  <Card title="Text Sources" icon="text">
+    - Raw strings
+    - Text files (.txt)
+    - PDF documents
+  </Card>
+  <Card title="Structured Data" icon="table">
+    - CSV files
+    - Excel spreadsheets
+    - JSON documents
+  </Card>
+</CardGroup>
+
+## Quick Start
+
+Here's a simple example using string-based knowledge:
 
 ```python
-from crewai import Agent, Task, Crew, Process, LLM
-from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+from crewai import Agent, Task, Crew
+from crewai.knowledge import StringKnowledgeSource
 
-# Create a knowledge source
-content = "Users name is John. He is 30 years old and lives in San Francisco."
-string_source = StringKnowledgeSource(
-    content=content, metadata={"preference": "personal"}
+# 1. Create a knowledge source
+product_info = StringKnowledgeSource(
+    content="""Our product X1000 has the following features:
+    - 10-hour battery life
+    - Water-resistant
+    - Available in black and silver
+    Price: $299.99""",
+    metadata={"category": "product"}
 )
 
-# Create an agent with the knowledge store
-agent = Agent(
-    role="About User",
-    goal="You know everything about the user.",
-    backstory="""You are a master at understanding people and their preferences.""",
-    verbose=True
+# 2. Create an agent with knowledge
+sales_agent = Agent(
+    role="Sales Representative",
+    goal="Accurately answer customer questions about products",
+    backstory="Expert in product features and customer service",
+    knowledge_sources=[product_info]  # Attach knowledge to agent
 )
 
-task = Task(
-    description="Answer the following questions about the user: {question}",
-    expected_output="An answer to the question.",
-    agent=agent,
+# 3. Create a task
+answer_task = Task(
+    description="Answer: What colors is the X1000 available in and how much does it cost?",
+    agent=sales_agent
 )
 
+# 4. Create and run the crew
+crew = Crew(
+    agents=[sales_agent],
+    tasks=[answer_task]
+)
+
+result = crew.kickoff()
+```
+
+## Knowledge Configuration
+
+### Collection Names
+
+Knowledge sources are organized into collections for better management:
+
+```python
+# Create knowledge sources with specific collections
+tech_specs = StringKnowledgeSource(
+    content="Technical specifications...",
+    collection_name="product_tech_specs"
+)
+
+pricing_info = StringKnowledgeSource(
+    content="Pricing information...",
+    collection_name="product_pricing"
+)
+```
+
+### Metadata and Filtering
+
+Add metadata to organize and filter knowledge:
+
+```python
+knowledge_source = StringKnowledgeSource(
+    content="Product details...",
+    metadata={
+        "category": "electronics",
+        "product_line": "premium",
+        "last_updated": "2024-03"
+    }
+)
+```
+
+### Chunking Configuration
+
+Control how your content is split for processing:
+
+```python
+knowledge_source = PDFKnowledgeSource(
+    file_path="product_manual.pdf",
+    chunk_size=2000,     # Characters per chunk
+    chunk_overlap=200    # Overlap between chunks
+)
+```
+
+## Advanced Usage
+
+### Custom Knowledge Sources
+
+Create your own knowledge source by extending the base class:
+
+```python
+from crewai.knowledge.source import BaseKnowledgeSource
+
+class APIKnowledgeSource(BaseKnowledgeSource):
+    def __init__(self, api_endpoint: str, **kwargs):
+        super().__init__(**kwargs)
+        self.api_endpoint = api_endpoint
+    
+    def load_content(self):
+        # Implement API data fetching
+        response = requests.get(self.api_endpoint)
+        return response.json()
+    
+    def add(self):
+        content = self.load_content()
+        # Process and store content
+        self.save_documents({"source": "api"})
+```
+
+### Embedder Configuration
+
+Customize the embedding process:
+
+```python
 crew = Crew(
     agents=[agent],
     tasks=[task],
-    verbose=True,
-    process=Process.sequential,
-    knowledge_sources=[string_source], # Enable knowledge by adding the sources here.
-)
-
-result = crew.kickoff(inputs={"question": "What city does John live in and how old is he?"})
-```
-
-## Appending Knowledge Sources To Individual Agents
-Sometimes you may want to append knowledge sources to an individual agent. You can do this by setting the `knowledge` parameter in the `Agent` class.
-
-```python
-agent = Agent(
-    ...
-    knowledge_sources=[
-        StringKnowledgeSource(
-            content="Users name is John. He is 30 years old and lives in San Francisco.",
-            metadata={"preference": "personal"},
-        )
-    ],
+    knowledge_sources=[source],
+    embedder_config={
+        "model": "BAAI/bge-small-en-v1.5",
+        "normalize": True,
+        "max_length": 512
+    }
 )
 ```
 
-## Agent Level Knowledge Sources
+## Best Practices
 
-You can also append knowledge sources to an individual agent by setting the `knowledge_sources` parameter in the `Agent` class.
+<AccordionGroup>
+  <Accordion title="Content Organization">
+    - Use meaningful collection names
+    - Add detailed metadata for filtering
+    - Keep chunk sizes appropriate for your content
+    - Consider content overlap for context preservation
+  </Accordion>
+  
+  <Accordion title="Performance Tips">
+    - Use smaller chunk sizes for precise retrieval
+    - Implement metadata filtering for faster searches
+    - Choose appropriate embedding models for your use case
+    - Cache frequently accessed knowledge
+  </Accordion>
+  
+  <Accordion title="Error Handling">
+    - Validate knowledge source content
+    - Handle missing or corrupted files
+    - Monitor embedding generation
+    - Implement fallback options
+  </Accordion>
+</AccordionGroup>
 
-```python
-string_source = StringKnowledgeSource(
-    content="Users name is John. He is 30 years old and lives in San Francisco.",
-    metadata={"preference": "personal"},
-)
-agent = Agent(
-    ...
-    knowledge_sources=[string_source],
-)
-```
+## Common Issues and Solutions
 
-## Embedder Configuration
-
-You can also configure the embedder for the knowledge store. This is useful if you want to use a different embedder for the knowledge store than the one used for the agents.
-
-```python
-...
-string_source = StringKnowledgeSource(
-    content="Users name is John. He is 30 years old and lives in San Francisco.",
-    metadata={"preference": "personal"}
-)
-crew = Crew(
-    ...
-    knowledge_sources=[string_source],
-    embedder_config={"provider": "ollama", "config": {"model": "nomic-embed-text:latest"}},
-)
-```
+<AccordionGroup>
+  <Accordion title="Content Not Found">
+    If agents can't find relevant information:
+    - Check chunk sizes
+    - Verify knowledge source loading
+    - Review metadata filters
+    - Test with simpler queries first
+  </Accordion>
+  
+  <Accordion title="Performance Issues">
+    If knowledge retrieval is slow:
+    - Reduce chunk sizes
+    - Optimize metadata filtering
+    - Consider using a lighter embedding model
+    - Cache frequently accessed content
+  </Accordion>
+</AccordionGroup>
diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 798fea726..1f01ca0eb 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -1,205 +1,323 @@
 ---
-title: LLMs
-description: Learn how to configure and optimize LLMs for your CrewAI projects.
-icon: microchip-ai
+title: 'LLMs'
+description: 'A comprehensive guide to configuring and using Large Language Models (LLMs) in your CrewAI projects'
+icon: 'microchip-ai'
 ---
 
-# Large Language Models (LLMs) in CrewAI
+<Note>
+  CrewAI integrates with multiple LLM providers through LiteLLM, giving you the flexibility to choose the right model for your specific use case. This guide will help you understand how to configure and use different LLM providers in your CrewAI projects.
+</Note>
 
-Large Language Models (LLMs) are the backbone of intelligent agents in the CrewAI framework. This guide will help you understand, configure, and optimize LLM usage for your CrewAI projects.
+## What are LLMs?
 
-## Key Concepts
+Large Language Models (LLMs) are the core intelligence behind CrewAI agents. They enable agents to understand context, make decisions, and generate human-like responses. Here's what you need to know:
 
-- **LLM**: Large Language Model, the AI powering agent intelligence
-- **Agent**: A CrewAI entity that uses an LLM to perform tasks
-- **Provider**: A service that offers LLM capabilities (e.g., OpenAI, Anthropic, Ollama, [more providers](https://docs.litellm.ai/docs/providers))
+<CardGroup cols={2}>
+  <Card title="LLM Basics" icon="brain">
+    Large Language Models are AI systems trained on vast amounts of text data. They power the intelligence of your CrewAI agents, enabling them to understand and generate human-like text.
+  </Card>
+  <Card title="Context Window" icon="window">
+    The context window determines how much text an LLM can process at once. Larger windows (e.g., 128K tokens) allow for more context but may be more expensive and slower.
+  </Card>
+  <Card title="Temperature" icon="temperature-three-quarters">
+    Temperature (0.0 to 1.0) controls response randomness. Lower values (e.g., 0.2) produce more focused, deterministic outputs, while higher values (e.g., 0.8) increase creativity and variability.
+  </Card>
+  <Card title="Provider Selection" icon="server">
+    Each LLM provider (e.g., OpenAI, Anthropic, Google) offers different models with varying capabilities, pricing, and features. Choose based on your needs for accuracy, speed, and cost.
+  </Card>
+</CardGroup>
 
-## Configuring LLMs for Agents
+## Available Models and Their Capabilities
 
-CrewAI offers flexible options for setting up LLMs:
-
-### 1. Default Configuration
-
-By default, CrewAI uses the `gpt-4o-mini` model. It uses environment variables if no LLM is specified:
-- `OPENAI_MODEL_NAME` (defaults to "gpt-4o-mini" if not set)
-- `OPENAI_API_BASE`
-- `OPENAI_API_KEY`
-
-### 2. Updating YAML files
-
-You can update the `agents.yml` file to refer to the LLM you want to use:
-
-```yaml Code
-researcher:
-    role: Research Specialist
-    goal: Conduct comprehensive research and analysis to gather relevant information,
-        synthesize findings, and produce well-documented insights.
-    backstory: A dedicated research professional with years of experience in academic
-        investigation, literature review, and data analysis, known for thorough and
-        methodical approaches to complex research questions.
-    verbose: true
-    llm: openai/gpt-4o
-    # llm: azure/gpt-4o-mini
-    # llm: gemini/gemini-pro
-    # llm: anthropic/claude-3-5-sonnet-20240620
-    # llm: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
-    # llm: mistral/mistral-large-latest
-    # llm: ollama/llama3:70b
-    # llm: groq/llama-3.2-90b-vision-preview
-    # llm: watsonx/meta-llama/llama-3-1-70b-instruct
-    # llm: nvidia_nim/meta/llama3-70b-instruct
-    # llm: sambanova/Meta-Llama-3.1-8B-Instruct
-    # ...
-```
-
-Keep in mind that you will need to set certain ENV vars depending on the model you are
-using to account for the credentials or set a custom LLM object like described below.
-Here are some of the required ENV vars for some of the LLM integrations:
-
-<AccordionGroup>
-    <Accordion title="OpenAI">
-    ```python Code
-    OPENAI_API_KEY=<your-api-key>
-    OPENAI_API_BASE=<optional-custom-base-url>
-    OPENAI_MODEL_NAME=<openai-model-name>
-    OPENAI_ORGANIZATION=<your-org-id>       # OPTIONAL
-    OPENAI_API_BASE=<openaiai-api-base>     # OPTIONAL
-    ```
-    </Accordion>
-
-    <Accordion title="Anthropic">
-    ```python Code
-    ANTHROPIC_API_KEY=<your-api-key>
-    ```
-    </Accordion>
-
-    <Accordion title="Google">
-    ```python Code
-    GEMINI_API_KEY=<your-api-key>
-    ```
-    </Accordion>
-
-    <Accordion title="Azure">
-    ```python Code
-    AZURE_API_KEY=<your-api-key>                    # "my-azure-api-key"
-    AZURE_API_BASE=<your-resource-url>              # "https://example-endpoint.openai.azure.com"
-    AZURE_API_VERSION=<api-version>                 # "2023-05-15"
-    AZURE_AD_TOKEN=<your-azure-ad-token>            # Optional
-    AZURE_API_TYPE=<your-azure-api-type>            # Optional
-    ```
-    </Accordion>
-
-    <Accordion title="AWS Bedrock">
-    ```python Code
-    AWS_ACCESS_KEY_ID=<your-access-key>
-    AWS_SECRET_ACCESS_KEY=<your-secret-key>
-    AWS_DEFAULT_REGION=<your-region>
-    ```
-    </Accordion>
-
-    <Accordion title="Mistral">
-    ```python Code
-    MISTRAL_API_KEY=<your-api-key>
-    ```
-    </Accordion>
-
-    <Accordion title="Groq">
-    ```python Code
-    GROQ_API_KEY=<your-api-key>
-    ```
-    </Accordion>
-
-    <Accordion title="IBM watsonx.ai">
-    ```python Code
-    WATSONX_URL=<your-url>                          # (required) Base URL of your WatsonX instance
-    WATSONX_APIKEY=<your-apikey>                    # (required) IBM cloud API key
-    WATSONX_TOKEN=<your-token>                      # (required) IAM auth token (alternative to APIKEY)
-    WATSONX_PROJECT_ID=<your-project-id>            # (optional) Project ID of your WatsonX instance
-    WATSONX_DEPLOYMENT_SPACE_ID=<your-space-id>     # (optional) ID of deployment space for deployed models
-    ```
-    </Accordion>
-</AccordionGroup>
-
-### 3. Custom LLM Objects
-
-Pass a custom LLM implementation or object from another library.
-
-See below for examples.
+Here's a detailed breakdown of supported models and their capabilities:
 
 <Tabs>
-    <Tab title="String Identifier">
-    ```python Code
-    agent = Agent(llm="gpt-4o", ...)
-    ```
-    </Tab>
+  <Tab title="OpenAI">
+    | Model | Context Window | Best For |
+    |-------|---------------|-----------|
+    | GPT-4 | 8,192 tokens | High-accuracy tasks, complex reasoning |
+    | GPT-4 Turbo | 128,000 tokens | Long-form content, document analysis |
+    | GPT-4o & GPT-4o-mini | 128,000 tokens | Cost-effective large context processing |
 
-    <Tab title="LLM Instance">
-    ```python Code
-    from crewai import LLM
+    <Note>
+      1 token ≈ 4 characters in English. For example, 8,192 tokens ≈ 32,768 characters or about 6,000 words.
+    </Note>
+  </Tab>
+  <Tab title="Groq">
+    | Model | Context Window | Best For |
+    |-------|---------------|-----------|
+    | Llama 3.1 70B/8B | 131,072 tokens | High-performance, large context tasks |
+    | Llama 3.2 Series | 8,192 tokens | General-purpose tasks |
+    | Mixtral 8x7B | 32,768 tokens | Balanced performance and context |
+    | Gemma Series | 8,192 tokens | Efficient, smaller-scale tasks |
 
-    llm = LLM(model="gpt-4", temperature=0.7)
-    agent = Agent(llm=llm, ...)
-    ```
-    </Tab>
+    <Tip>
+      Groq is known for its fast inference speeds, making it suitable for real-time applications.
+    </Tip>
+  </Tab>
+  <Tab title="Others">
+    | Provider | Context Window | Key Features |
+    |----------|---------------|--------------|
+    | Deepseek Chat | 128,000 tokens | Specialized in technical discussions |
+    | Claude 3 | Up to 200K tokens | Strong reasoning, code understanding |
+    | Gemini | Varies by model | Multimodal capabilities |
+
+    <Info>
+      Provider selection should consider factors like:
+      - API availability in your region
+      - Pricing structure
+      - Required features (e.g., streaming, function calling)
+      - Performance requirements
+    </Info>
+  </Tab>
 </Tabs>
 
-## Connecting to OpenAI-Compatible LLMs
+## Setting Up Your LLM
 
-You can connect to OpenAI-compatible LLMs using either environment variables or by setting specific attributes on the LLM class:
+There are three ways to configure LLMs in CrewAI. Choose the method that best fits your workflow:
 
 <Tabs>
-    <Tab title="Using Environment Variables">
-    ```python Code
-    import os
+  <Tab title="1. Environment Variables">
+    The simplest way to get started. Set these variables in your environment:
 
-    os.environ["OPENAI_API_KEY"] = "your-api-key"
-    os.environ["OPENAI_API_BASE"] = "https://api.your-provider.com/v1"
+    ```bash
+    # Required: Your API key for authentication
+    OPENAI_API_KEY=<your-api-key>
+
+    # Optional: Default model selection
+    OPENAI_MODEL_NAME=gpt-4o-mini  # Default if not set
+
+    # Optional: Organization ID (if applicable)
+    OPENAI_ORGANIZATION_ID=<your-org-id>
     ```
-    </Tab>
-    <Tab title="Using LLM Class Attributes">
-    ```python Code
+
+    <Warning>
+      Never commit API keys to version control. Use environment files (.env) or your system's secret management.
+    </Warning>
+  </Tab>
+  <Tab title="2. YAML Configuration">
+    Create a YAML file to define your agent configurations. This method is great for version control and team collaboration:
+
+    ```yaml
+    researcher:
+        # Agent Definition
+        role: Research Specialist
+        goal: Conduct comprehensive research and analysis
+        backstory: A dedicated research professional with years of experience
+        verbose: true
+
+        # Model Selection (uncomment your choice)
+        
+        # OpenAI Models - Known for reliability and performance
+        llm: openai/gpt-4o-mini
+        # llm: openai/gpt-4        # More accurate but expensive
+        # llm: openai/gpt-4-turbo  # Fast with large context
+        # llm: openai/gpt-4o       # Optimized for longer texts
+        # llm: openai/o1-preview   # Latest features
+        # llm: openai/o1-mini      # Cost-effective
+
+        # Azure Models - For enterprise deployments
+        # llm: azure/gpt-4o-mini
+        # llm: azure/gpt-4
+        # llm: azure/gpt-35-turbo
+
+        # Anthropic Models - Strong reasoning capabilities
+        # llm: anthropic/claude-3-opus-20240229-v1:0
+        # llm: anthropic/claude-3-sonnet-20240229-v1:0
+        # llm: anthropic/claude-3-haiku-20240307-v1:0
+        # llm: anthropic/claude-2.1
+        # llm: anthropic/claude-2.0
+
+        # Google Models - Good for general tasks
+        # llm: gemini/gemini-pro
+        # llm: gemini/gemini-1.5-pro-latest
+        # llm: gemini/gemini-1.0-pro-latest
+
+        # AWS Bedrock Models - Enterprise-grade
+        # llm: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
+        # llm: bedrock/anthropic.claude-v2:1
+        # llm: bedrock/amazon.titan-text-express-v1
+        # llm: bedrock/meta.llama2-70b-chat-v1
+
+        # Mistral Models - Open source alternative
+        # llm: mistral/mistral-large-latest
+        # llm: mistral/mistral-medium-latest
+        # llm: mistral/mistral-small-latest
+
+        # Groq Models - Fast inference
+        # llm: groq/mixtral-8x7b-32768
+        # llm: groq/llama-3.1-70b-versatile
+        # llm: groq/llama-3.2-90b-text-preview
+        # llm: groq/gemma2-9b-it
+        # llm: groq/gemma-7b-it
+
+        # IBM watsonx.ai Models - Enterprise features
+        # llm: watsonx/ibm/granite-13b-chat-v2
+        # llm: watsonx/meta-llama/llama-3-1-70b-instruct
+        # llm: watsonx/bigcode/starcoder2-15b
+
+        # Ollama Models - Local deployment
+        # llm: ollama/llama3:70b
+        # llm: ollama/codellama
+        # llm: ollama/mistral
+        # llm: ollama/mixtral
+        # llm: ollama/phi
+
+        # Fireworks AI Models - Specialized tasks
+        # llm: fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct
+        # llm: fireworks_ai/accounts/fireworks/models/mixtral-8x7b
+        # llm: fireworks_ai/accounts/fireworks/models/zephyr-7b-beta
+
+        # Perplexity AI Models - Research focused
+        # llm: pplx/llama-3.1-sonar-large-128k-online
+        # llm: pplx/mistral-7b-instruct
+        # llm: pplx/codellama-34b-instruct
+        # llm: pplx/mixtral-8x7b-instruct
+
+        # Hugging Face Models - Community models
+        # llm: huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct
+        # llm: huggingface/mistralai/Mixtral-8x7B-Instruct-v0.1
+        # llm: huggingface/tiiuae/falcon-180B-chat
+        # llm: huggingface/google/gemma-7b-it
+
+        # Nvidia NIM Models - GPU-optimized
+        # llm: nvidia_nim/meta/llama3-70b-instruct
+        # llm: nvidia_nim/mistral/mixtral-8x7b
+        # llm: nvidia_nim/google/gemma-7b
+
+        # SambaNova Models - Enterprise AI
+        # llm: sambanova/Meta-Llama-3.1-8B-Instruct
+        # llm: sambanova/BioMistral-7B
+        # llm: sambanova/Falcon-180B
+    ```
+
+    <Info>
+      The YAML configuration allows you to:
+      - Version control your agent settings
+      - Easily switch between different models
+      - Share configurations across team members
+      - Document model choices and their purposes
+    </Info>
+  </Tab>
+  <Tab title="3. Direct Code">
+    For maximum flexibility, configure LLMs directly in your Python code:
+
+    ```python
     from crewai import LLM
 
+    # Basic configuration
+    llm = LLM(model="gpt-4")
+
+    # Advanced configuration with detailed parameters
+    llm = LLM(
+        model="gpt-4o-mini",
+        temperature=0.7,        # Higher for more creative outputs
+        timeout=120,           # Seconds to wait for response
+        max_tokens=4000,       # Maximum length of response
+        top_p=0.9,            # Nucleus sampling parameter
+        frequency_penalty=0.1, # Reduce repetition
+        presence_penalty=0.1,  # Encourage topic diversity
+        response_format={"type": "json"},  # For structured outputs
+        seed=42               # For reproducible results
+    )
+    ```
+
+    <Info>
+      Parameter explanations:
+      - `temperature`: Controls randomness (0.0-1.0)
+      - `timeout`: Maximum wait time for response
+      - `max_tokens`: Limits response length
+      - `top_p`: Alternative to temperature for sampling
+      - `frequency_penalty`: Reduces word repetition
+      - `presence_penalty`: Encourages new topics
+      - `response_format`: Specifies output structure
+      - `seed`: Ensures consistent outputs
+    </Info>
+  </Tab>
+</Tabs>
+
+## Advanced Features and Optimization
+
+Learn how to get the most out of your LLM configuration:
+
+<AccordionGroup>
+  <Accordion title="Context Window Management">
+    CrewAI includes smart context management features:
+
+    ```python
+    from crewai import LLM
+
+    # CrewAI automatically handles:
+    # 1. Token counting and tracking
+    # 2. Content summarization when needed
+    # 3. Task splitting for large contexts
+
     llm = LLM(
-        model="custom-model-name",
-        api_key="your-api-key",
-        base_url="https://api.your-provider.com/v1"
+        model="gpt-4",
+        max_tokens=4000,  # Limit response length
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Tab>
-</Tabs>
 
-## LLM Configuration Options
+    <Info>
+      Best practices for context management:
+      1. Choose models with appropriate context windows
+      2. Pre-process long inputs when possible
+      3. Use chunking for large documents
+      4. Monitor token usage to optimize costs
+    </Info>
+  </Accordion>
 
-When configuring an LLM for your agent, you have access to a wide range of parameters:
+  <Accordion title="Performance Optimization">
+    <Steps>
+      <Step title="Token Usage Optimization">
+        Choose the right context window for your task:
+        - Small tasks (up to 4K tokens): Standard models
+        - Medium tasks (between 4K-32K): Enhanced models
+        - Large tasks (over 32K): Large context models
+        
+        ```python
+        # Configure model with appropriate settings
+        llm = LLM(
+            model="openai/gpt-4-turbo-preview",
+            temperature=0.7,    # Adjust based on task
+            max_tokens=4096,    # Set based on output needs
+            timeout=300        # Longer timeout for complex tasks
+        )
+        ```
+        <Tip>
+          - Lower temperature (0.1 to 0.3) for factual responses
+          - Higher temperature (0.7 to 0.9) for creative tasks
+        </Tip>
+      </Step>
 
-| Parameter         | Type            | Description                                                                                      |
-|:------------------|:---------------:|:-------------------------------------------------------------------------------------------------|
-| **model**            | `str`             | Name of the model to use (e.g., "gpt-4", "gpt-3.5-turbo", "ollama/llama3.1"). For more options, visit the providers documentation. |
-| **timeout**          | `float, int`      | Maximum time (in seconds) to wait for a response.                                                |
-| **temperature**      | `float`           | Controls randomness in output (0.0 to 1.0).                                                      |
-| **top_p**            | `float`           | Controls diversity of output (0.0 to 1.0).                                                       |
-| **n**                | `int`             | Number of completions to generate.                                                               |
-| **stop**             | `str, List[str]`  | Sequence(s) where generation should stop.                                                        |
-| **max_tokens**       | `int`             | Maximum number of tokens to generate.                                                            |
-| **presence_penalty** | `float`           | Penalizes new tokens based on their presence in prior text.                                      |
-| **frequency_penalty**| `float`           | Penalizes new tokens based on their frequency in prior text.                                     |
-| **logit_bias**       | `Dict[int, float]`| Modifies likelihood of specified tokens appearing.                                              |
-| **response_format**  | `Dict[str, Any]`  | Specifies the format of the response (e.g., JSON object).                                        |
-| **seed**             | `int`             | Sets a random seed for deterministic results.                                                    |
-| **logprobs**         | `bool`            | Returns log probabilities of output tokens if enabled.                                           |
-| **top_logprobs**     | `int`             | Number of most likely tokens for which to return log probabilities.                              |
-| **base_url**         | `str`             | The base URL for the API endpoint.                                                               |
-| **api_version**      | `str`             | Version of the API to use.                                                                       |
-| **api_key**          | `str`             | Your API key for authentication.                                                                 |
+      <Step title="Best Practices">
+        1. Monitor token usage
+        2. Implement rate limiting
+        3. Use caching when possible
+        4. Set appropriate max_tokens limits
+      </Step>
+    </Steps>
 
+    <Info>
+      Remember to regularly monitor your token usage and adjust your configuration as needed to optimize costs and performance.
+    </Info>
+  </Accordion>
+</AccordionGroup>
 
-These are examples of how to configure LLMs for your agent.
+## Provider Configuration Examples
 
 <AccordionGroup>
-    <Accordion title="OpenAI">
+  <Accordion title="OpenAI">
+    ```python Code
+    # Required
+    OPENAI_API_KEY=sk-...
+    
+    # Optional
+    OPENAI_API_BASE=<custom-base-url>
+    OPENAI_ORGANIZATION=<your-org-id>
+    ```
 
+    Example usage:
     ```python Code
     from crewai import LLM
 
@@ -211,193 +329,306 @@ These are examples of how to configure LLMs for your agent.
         frequency_penalty=0.1,
         presence_penalty=0.1,
         stop=["END"],
-        seed=42,
-        base_url="https://api.openai.com/v1",
-        api_key="your-api-key-here"
+        seed=42
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
-
-    <Accordion title="Cerebras">
+  </Accordion>
 
+  <Accordion title="Anthropic">
     ```python Code
-    from crewai import LLM
+    ANTHROPIC_API_KEY=sk-ant-...
+    ```
 
+    Example usage:
+    ```python Code
     llm = LLM(
-        model="cerebras/llama-3.1-70b",
-        api_key="your-api-key-here"
-    )
-    agent = Agent(llm=llm, ...)
-    ```
-    </Accordion>
-
-    <Accordion title="Ollama (Local LLMs)">
-
-    CrewAI supports using Ollama for running open-source models locally:
-
-    1. Install Ollama: [ollama.ai](https://ollama.ai/)
-    2. Run a model: `ollama run llama2`
-    3. Configure agent:
-
-    ```python Code
-    from crewai import LLM
-
-    agent = Agent(
-        llm=LLM(
-            model="ollama/llama3.1",
-            base_url="http://localhost:11434"
-        ),
-        ...
+        model="anthropic/claude-3-sonnet-20240229-v1:0",
+        temperature=0.7
     )
     ```
-    </Accordion>
-
-    <Accordion title="Groq">
+  </Accordion>
 
+  <Accordion title="Google">
     ```python Code
-    from crewai import LLM
+    GEMINI_API_KEY=<your-api-key>
+    ```
 
+    Example usage:
+    ```python Code
     llm = LLM(
-        model="groq/llama3-8b-8192",
-        api_key="your-api-key-here"
+        model="gemini/gemini-pro",
+        temperature=0.7
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
-
-    <Accordion title="Anthropic">
+  </Accordion>
 
+  <Accordion title="Azure">
     ```python Code
-    from crewai import LLM
+    # Required
+    AZURE_API_KEY=<your-api-key>
+    AZURE_API_BASE=<your-resource-url>
+    AZURE_API_VERSION=<api-version>
+    
+    # Optional
+    AZURE_AD_TOKEN=<your-azure-ad-token>
+    AZURE_API_TYPE=<your-azure-api-type>
+    ```
 
+    Example usage:
+    ```python Code
     llm = LLM(
-        model="anthropic/claude-3-5-sonnet-20241022",
-        api_key="your-api-key-here"
+        model="azure/gpt-4",
+        api_version="2023-05-15"
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
+  </Accordion>
 
-    <Accordion title="Fireworks AI">
+  <Accordion title="AWS Bedrock">
     ```python Code
-    from crewai import LLM
+    AWS_ACCESS_KEY_ID=<your-access-key>
+    AWS_SECRET_ACCESS_KEY=<your-secret-key>
+    AWS_DEFAULT_REGION=<your-region>
+    ```
 
+    Example usage:
+    ```python Code
     llm = LLM(
-        model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct",
-        api_key="your-api-key-here"
+        model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
-
-    <Accordion title="Gemini">
+  </Accordion>
 
+  <Accordion title="Mistral">
     ```python Code
-    from crewai import LLM
+    MISTRAL_API_KEY=<your-api-key>
+    ```
 
+    Example usage:
+    ```python Code
     llm = LLM(
-        model="gemini/gemini-1.5-pro-002",
-        api_key="your-api-key-here"
+        model="mistral/mistral-large-latest",
+        temperature=0.7
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
-
-    <Accordion title="Perplexity AI (pplx-api)">
+  </Accordion>
 
+  <Accordion title="Groq">
     ```python Code
-    from crewai import LLM
+    GROQ_API_KEY=<your-api-key>
+    ```
 
+    Example usage:
+    ```python Code
     llm = LLM(
-        model="llama-3.1-sonar-large-128k-online",
-        base_url="https://api.perplexity.ai/",
-        api_key="your-api-key-here"
+        model="groq/llama-3.2-90b-text-preview",
+        temperature=0.7
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
-
-    <Accordion title="IBM watsonx.ai">
-    You can use IBM Watson by seeting the following ENV vars:
+  </Accordion>
 
+  <Accordion title="IBM watsonx.ai">
     ```python Code
+    # Required
     WATSONX_URL=<your-url>
     WATSONX_APIKEY=<your-apikey>
     WATSONX_PROJECT_ID=<your-project-id>
+    
+    # Optional
+    WATSONX_TOKEN=<your-token>
+    WATSONX_DEPLOYMENT_SPACE_ID=<your-space-id>
     ```
 
-    You can then define your agents llms by updating the `agents.yml`
-
-    ```yaml Code
-    researcher:
-        role: Research Specialist
-        goal: Conduct comprehensive research and analysis to gather relevant information,
-            synthesize findings, and produce well-documented insights.
-        backstory: A dedicated research professional with years of experience in academic
-            investigation, literature review, and data analysis, known for thorough and
-            methodical approaches to complex research questions.
-        verbose: true
-        llm: watsonx/meta-llama/llama-3-1-70b-instruct
-    ```
-
-    You can also set up agents more dynamically as a base level LLM instance, like bellow:
-
+    Example usage:
     ```python Code
-    from crewai import LLM
-
     llm = LLM(
-        model="watsonx/ibm/granite-13b-chat-v2",
-        base_url="https://api.watsonx.ai/v1",
-        api_key="your-api-key-here"
+        model="watsonx/meta-llama/llama-3-1-70b-instruct",
+        base_url="https://api.watsonx.ai/v1"
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
+  </Accordion>
 
-    <Accordion title="Hugging Face">
+  <Accordion title="Ollama (Local LLMs)">
+    1. Install Ollama: [ollama.ai](https://ollama.ai/)
+    2. Run a model: `ollama run llama2`
+    3. Configure:
 
     ```python Code
-    from crewai import LLM
+    llm = LLM(
+        model="ollama/llama3:70b",
+        base_url="http://localhost:11434"
+    )
+    ```
+  </Accordion>
 
+  <Accordion title="Fireworks AI">
+    ```python Code
+    FIREWORKS_API_KEY=<your-api-key>
+    ```
+
+    Example usage:
+    ```python Code
+    llm = LLM(
+        model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct",
+        temperature=0.7
+    )
+    ```
+  </Accordion>
+
+  <Accordion title="Perplexity AI">
+    ```python Code
+    PERPLEXITY_API_KEY=<your-api-key>
+    ```
+
+    Example usage:
+    ```python Code
+    llm = LLM(
+        model="llama-3.1-sonar-large-128k-online",
+        base_url="https://api.perplexity.ai/"
+    )
+    ```
+  </Accordion>
+
+  <Accordion title="Hugging Face">
+    ```python Code
+    HUGGINGFACE_API_KEY=<your-api-key>
+    ```
+
+    Example usage:
+    ```python Code
     llm = LLM(
         model="huggingface/meta-llama/Meta-Llama-3.1-8B-Instruct",
-        api_key="your-api-key-here",
         base_url="your_api_endpoint"
     )
-    agent = Agent(llm=llm, ...)
     ```
-    </Accordion>
+  </Accordion>
+
+  <Accordion title="Nvidia NIM">
+    ```python Code
+    NVIDIA_API_KEY=<your-api-key>
+    ```
+
+    Example usage:
+    ```python Code
+    llm = LLM(
+        model="nvidia_nim/meta/llama3-70b-instruct",
+        temperature=0.7
+    )
+    ```
+  </Accordion>
+
+  <Accordion title="SambaNova">
+    ```python Code
+    SAMBANOVA_API_KEY=<your-api-key>
+    ```
+
+    Example usage:
+    ```python Code
+    llm = LLM(
+        model="sambanova/Meta-Llama-3.1-8B-Instruct",
+        temperature=0.7
+    )
+    ```
+  </Accordion>
+
+  <Accordion title="Cerebras">
+    ```python Code
+    # Required
+    CEREBRAS_API_KEY=<your-api-key>
+    ```
+
+    Example usage:
+    ```python Code
+    llm = LLM(
+        model="cerebras/llama3.1-70b",
+        temperature=0.7,
+        max_tokens=8192
+    )
+    ```
+
+    <Info>
+      Cerebras features:
+      - Fast inference speeds
+      - Competitive pricing
+      - Good balance of speed and quality
+      - Support for long context windows
+    </Info>
+  </Accordion>
 </AccordionGroup>
 
-## Changing the Base API URL
+## Common Issues and Solutions
 
-You can change the base API URL for any LLM provider by setting the `base_url` parameter:
+<Tabs>
+  <Tab title="Authentication">
+    <Warning>
+      Most authentication issues can be resolved by checking API key format and environment variable names.
+    </Warning>
+    
+    ```bash
+    # OpenAI
+    OPENAI_API_KEY=sk-...
+    
+    # Anthropic
+    ANTHROPIC_API_KEY=sk-ant-...
+    ```
+  </Tab>
+  <Tab title="Model Names">
+    <Check>
+      Always include the provider prefix in model names
+    </Check>
+    
+    ```python
+    # Correct
+    llm = LLM(model="openai/gpt-4")
+    
+    # Incorrect
+    llm = LLM(model="gpt-4")
+    ```
+  </Tab>
+  <Tab title="Context Length">
+    <Tip>
+      Use larger context models for extensive tasks
+    </Tip>
+    
+    ```python
+    # Large context model
+    llm = LLM(model="openai/gpt-4o")  # 128K tokens
+    ```
+  </Tab>
+</Tabs>
 
-```python Code
-from crewai import LLM
+## Getting Help
 
-llm = LLM(
-    model="custom-model-name",
-    base_url="https://api.your-provider.com/v1",
-    api_key="your-api-key"
-)
-agent = Agent(llm=llm, ...)
-```
+If you need assistance, these resources are available:
 
-This is particularly useful when working with OpenAI-compatible APIs or when you need to specify a different endpoint for your chosen provider.
+<CardGroup cols={3}>
+  <Card
+    title="LiteLLM Documentation"
+    href="https://docs.litellm.ai/docs/"
+    icon="book"
+  >
+    Comprehensive documentation for LiteLLM integration and troubleshooting common issues.
+  </Card>
+  <Card
+    title="GitHub Issues"
+    href="https://github.com/joaomdmoura/crewAI/issues"
+    icon="bug"
+  >
+    Report bugs, request features, or browse existing issues for solutions.
+  </Card>
+  <Card
+    title="Community Forum"
+    href="https://community.crewai.com"
+    icon="comment-question"
+  >
+    Connect with other CrewAI users, share experiences, and get help from the community.
+  </Card>
+</CardGroup>
 
-## Best Practices
-
-1. **Choose the right model**: Balance capability and cost.
-2. **Optimize prompts**: Clear, concise instructions improve output.
-3. **Manage tokens**: Monitor and limit token usage for efficiency.
-4. **Use appropriate temperature**: Lower for factual tasks, higher for creative ones.
-5. **Implement error handling**: Gracefully manage API errors and rate limits.
-
-## Troubleshooting
-
-- **API Errors**: Check your API key, network connection, and rate limits.
-- **Unexpected Outputs**: Refine your prompts and adjust temperature or top_p.
-- **Performance Issues**: Consider using a more powerful model or optimizing your queries.
-- **Timeout Errors**: Increase the `timeout` parameter or optimize your input.
+<Note>
+  Best Practices for API Key Security:
+  - Use environment variables or secure vaults
+  - Never commit keys to version control
+  - Rotate keys regularly
+  - Use separate keys for development and production
+  - Monitor key usage for unusual patterns
+</Note>
diff --git a/docs/concepts/tasks.mdx b/docs/concepts/tasks.mdx
index 884c8fd27..fd48c242d 100644
--- a/docs/concepts/tasks.mdx
+++ b/docs/concepts/tasks.mdx
@@ -1,6 +1,6 @@
 ---
 title: Tasks
-description: Detailed guide on managing and creating tasks within the CrewAI framework, reflecting the latest codebase updates.
+description: Detailed guide on managing and creating tasks within the CrewAI framework.
 icon: list-check
 ---
 
@@ -8,41 +8,171 @@ icon: list-check
 
 In the CrewAI framework, a `Task` is a specific assignment completed by an `Agent`. 
 
-They provide all necessary details for execution, such as a description, the agent responsible, required tools, and more, facilitating a wide range of action complexities.
-
+Tasks provide all necessary details for execution, such as a description, the agent responsible, required tools, and more, facilitating a wide range of action complexities.
 
 Tasks within CrewAI can be collaborative, requiring multiple agents to work together. This is managed through the task properties and orchestrated by the Crew's process, enhancing teamwork and efficiency.
 
+### Task Execution Flow
+
+Tasks can be executed in two ways:
+- **Sequential**: Tasks are executed in the order they are defined
+- **Hierarchical**: Tasks are assigned to agents based on their roles and expertise
+
+The execution flow is defined when creating the crew:
+```python Code
+crew = Crew(
+    agents=[agent1, agent2],
+    tasks=[task1, task2],
+    process=Process.sequential  # or Process.hierarchical
+)
+```
+
 ## Task Attributes
 
 | Attribute                        | Parameters        | Type                          | Description                                                                                                          |
 | :------------------------------- | :---------------- | :---------------------------- | :------------------------------------------------------------------------------------------------------------------- |
 | **Description**                  | `description`     | `str`                         | A clear, concise statement of what the task entails.                                                                 |
-| **Agent**                        | `agent`           | `Optional[BaseAgent]`         | The agent responsible for the task, assigned either directly or by the crew's process.                               |
 | **Expected Output**              | `expected_output` | `str`                         | A detailed description of what the task's completion looks like.                                                     |
-| **Tools** _(optional)_           | `tools`           | `Optional[List[Any]]`         | The functions or capabilities the agent can utilize to perform the task. Defaults to an empty list.                  |
-| **Async Execution** _(optional)_ | `async_execution` | `Optional[bool]`              | If set, the task executes asynchronously, allowing progression without waiting for completion. Defaults to False.    |
-| **Context** _(optional)_         | `context`         | `Optional[List["Task"]]`      | Specifies tasks whose outputs are used as context for this task.                                                     |
-| **Config** _(optional)_          | `config`          | `Optional[Dict[str, Any]]`    | Additional configuration details for the agent executing the task, allowing further customization. Defaults to None. |
-| **Output JSON** _(optional)_     | `output_json`     | `Optional[Type[BaseModel]]`   | Outputs a JSON object, requiring an OpenAI client. Only one output format can be set.                                |
-| **Output Pydantic** _(optional)_ | `output_pydantic` | `Optional[Type[BaseModel]]`   | Outputs a Pydantic model object, requiring an OpenAI client. Only one output format can be set.                      |
-| **Output File** _(optional)_     | `output_file`     | `Optional[str]`               | Saves the task output to a file. If used with `Output JSON` or `Output Pydantic`, specifies how the output is saved. |
-| **Output** _(optional)_          | `output`          | `Optional[TaskOutput]`        | An instance of `TaskOutput`, containing the raw, JSON, and Pydantic output plus additional details.                  |
-| **Callback** _(optional)_        | `callback`        | `Optional[Any]`               | A callable that is executed with the task's output upon completion.                                                  |
-| **Human Input** _(optional)_     | `human_input`     | `Optional[bool]`              | Indicates if the task should involve human review at the end, useful for tasks needing human oversight. Defaults to False.|
-| **Converter Class** _(optional)_ | `converter_cls`   | `Optional[Type[Converter]]`   | A converter class used to export structured output. Defaults to None.                                                |
+| **Name** _(optional)_           | `name`           | `Optional[str]`               | A name identifier for the task.                                                                                      |
+| **Agent** _(optional)_          | `agent`           | `Optional[BaseAgent]`         | The agent responsible for executing the task.                                                                        |
+| **Tools** _(optional)_          | `tools`           | `List[BaseTool]`             | The tools/resources the agent is limited to use for this task.                                                       |
+| **Context** _(optional)_         | `context`         | `Optional[List["Task"]]`      | Other tasks whose outputs will be used as context for this task.                                                     |
+| **Async Execution** _(optional)_ | `async_execution` | `Optional[bool]`              | Whether the task should be executed asynchronously. Defaults to False.                                               |
+| **Config** _(optional)_          | `config`          | `Optional[Dict[str, Any]]`    | Task-specific configuration parameters.                                                                              |
+| **Output File** _(optional)_     | `output_file`     | `Optional[str]`               | File path for storing the task output.                                                                               |
+| **Output JSON** _(optional)_     | `output_json`     | `Optional[Type[BaseModel]]`   | A Pydantic model to structure the JSON output.                                                                       |
+| **Output Pydantic** _(optional)_ | `output_pydantic` | `Optional[Type[BaseModel]]`   | A Pydantic model for task output.                                                                                    |
+| **Callback** _(optional)_        | `callback`        | `Optional[Any]`               | Function/object to be executed after task completion.                                                                |
 
-## Creating a Task
+## Creating Tasks
 
-Creating a task involves defining its scope, responsible agent, and any additional attributes for flexibility:
+There are two ways to create tasks in CrewAI: using **YAML configuration (recommended)** or defining them **directly in code**.
 
+### YAML Configuration (Recommended)
+
+Using YAML configuration provides a cleaner, more maintainable way to define tasks. We strongly recommend using this approach to define tasks in your CrewAI projects.
+
+After creating your CrewAI project as outlined in the [Installation](/installation) section, navigate to the `src/latest_ai_development/config/tasks.yaml` file and modify the template to match your specific task requirements.
+
+<Note>
+Variables in your YAML files (like `{topic}`) will be replaced with values from your inputs when running the crew:
 ```python Code
+crew.kickoff(inputs={'topic': 'AI Agents'})
+```
+</Note>
+
+Here's an example of how to configure tasks using YAML:
+
+```yaml tasks.yaml
+research_task:
+  description: >
+    Conduct a thorough research about {topic}
+    Make sure you find any interesting and relevant information given
+    the current year is 2024.
+  expected_output: >
+    A list with 10 bullet points of the most relevant information about {topic}
+  agent: researcher
+
+reporting_task:
+  description: >
+    Review the context you got and expand each topic into a full section for a report.
+    Make sure the report is detailed and contains any and all relevant information.
+  expected_output: >
+    A fully fledge reports with the mains topics, each with a full section of information.
+    Formatted as markdown without '```'
+  agent: reporting_analyst
+  output_file: report.md
+```
+
+To use this YAML configuration in your code, create a crew class that inherits from `CrewBase`:
+
+```python crew.py
+# src/latest_ai_development/crew.py
+
+from crewai import Agent, Crew, Process, Task
+from crewai.project import CrewBase, agent, crew, task
+from crewai_tools import SerperDevTool
+
+@CrewBase
+class LatestAiDevelopmentCrew():
+  """LatestAiDevelopment crew"""
+
+  @agent
+  def researcher(self) -> Agent:
+    return Agent(
+      config=self.agents_config['researcher'],
+      verbose=True,
+      tools=[SerperDevTool()]
+    )
+
+  @agent
+  def reporting_analyst(self) -> Agent:
+    return Agent(
+      config=self.agents_config['reporting_analyst'],
+      verbose=True
+    )
+
+  @task
+  def research_task(self) -> Task:
+    return Task(
+      config=self.tasks_config['research_task']
+    )
+
+  @task
+  def reporting_task(self) -> Task:
+    return Task(
+      config=self.tasks_config['reporting_task']
+    )
+
+  @crew
+  def crew(self) -> Crew:
+    return Crew(
+      agents=[
+        self.researcher(),
+        self.reporting_analyst()
+      ],
+      tasks=[
+        self.research_task(),
+        self.reporting_task()
+      ],
+      process=Process.sequential
+    )
+```
+
+<Note>
+The names you use in your YAML files (`agents.yaml` and `tasks.yaml`) should match the method names in your Python code.
+</Note>
+
+### Direct Code Definition (Alternative)
+
+Alternatively, you can define tasks directly in your code without using YAML configuration:
+
+```python task.py
 from crewai import Task
 
-task = Task(
-    description='Find and summarize the latest and most relevant news on AI',
-    agent=sales_agent,
-    expected_output='A bullet list summary of the top 5 most important AI news',
+research_task = Task(
+    description="""
+        Conduct a thorough research about AI Agents.
+        Make sure you find any interesting and relevant information given
+        the current year is 2024.
+    """,
+    expected_output="""
+        A list with 10 bullet points of the most relevant information about AI Agents
+    """,
+    agent=researcher
+)
+
+reporting_task = Task(
+    description="""
+        Review the context you got and expand each topic into a full section for a report.
+        Make sure the report is detailed and contains any and all relevant information.
+    """,
+    expected_output="""
+        A fully fledge reports with the mains topics, each with a full section of information.
+        Formatted as markdown without '```'
+    """,
+    agent=reporting_analyst,
+    output_file="report.md"
 )
 ```
 
@@ -52,6 +182,8 @@ task = Task(
 
 ## Task Output
 
+Understanding task outputs is crucial for building effective AI workflows. CrewAI provides a structured way to handle task results through the `TaskOutput` class, which supports multiple output formats and can be easily passed between tasks.
+
 The output of a task in CrewAI framework is encapsulated within the `TaskOutput` class. This class provides a structured way to access results of a task, including various formats such as raw output, JSON, and Pydantic models.
 
 By default, the `TaskOutput` will only include the `raw` output. A `TaskOutput` will only include the `pydantic` or `json_dict` output if the original `Task` object was configured with `output_pydantic` or `output_json`, respectively.
@@ -112,6 +244,25 @@ if task_output.pydantic:
     print(f"Pydantic Output: {task_output.pydantic}")
 ```
 
+## Task Dependencies and Context
+
+Tasks can depend on the output of other tasks using the `context` attribute. For example:
+
+```python Code
+research_task = Task(
+    description="Research the latest developments in AI",
+    expected_output="A list of recent AI developments",
+    agent=researcher
+)
+
+analysis_task = Task(
+    description="Analyze the research findings and identify key trends",
+    expected_output="Analysis report of AI trends",
+    agent=analyst,
+    context=[research_task]  # This task will wait for research_task to complete
+)
+```
+
 ## Integrating Tools with Tasks
 
 Leverage tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools) for enhanced task performance and agent interaction.
@@ -167,16 +318,16 @@ This is useful when you have a task that depends on the output of another task t
 # ...
 
 research_ai_task = Task(
-    description='Find and summarize the latest AI news',
-    expected_output='A bullet list summary of the top 5 most important AI news',
+    description="Research the latest developments in AI",
+    expected_output="A list of recent AI developments",
     async_execution=True,
     agent=research_agent,
     tools=[search_tool]
 )
 
 research_ops_task = Task(
-    description='Find and summarize the latest AI Ops news',
-    expected_output='A bullet list summary of the top 5 most important AI Ops news',
+    description="Research the latest developments in AI Ops",
+    expected_output="A list of recent AI Ops developments",
     async_execution=True,
     agent=research_agent,
     tools=[search_tool]
@@ -184,7 +335,7 @@ research_ops_task = Task(
 
 write_blog_task = Task(
     description="Write a full blog post about the importance of AI and its latest news",
-    expected_output='Full blog post that is 4 paragraphs long',
+    expected_output="Full blog post that is 4 paragraphs long",
     agent=writer_agent,
     context=[research_ai_task, research_ops_task]
 )
diff --git a/docs/installation.mdx b/docs/installation.mdx
index ec3da38b7..ab3bf341b 100644
--- a/docs/installation.mdx
+++ b/docs/installation.mdx
@@ -1,128 +1,145 @@
 ---
 title: Installation
-description: 
+description: Get started with CrewAI - Install, configure, and build your first AI crew
 icon: wrench
 ---
 
-This guide will walk you through the installation process for CrewAI and its dependencies. 
-CrewAI is a flexible and powerful AI framework that enables you to create and manage AI agents, tools, and tasks efficiently. 
-Let's get started! 🚀
+<Note>
+  **Python Version Requirements**
+  
+  CrewAI requires `Python >=3.10 and <=3.13`. Here's how to check your version:
+  ```bash
+  python3 --version
+  ```
+  
+  If you need to update Python, visit [python.org/downloads](https://python.org/downloads)
+</Note>
 
-<Tip>
-    Make sure you have `Python >=3.10 <=3.13` installed on your system before you proceed.
-</Tip>
+# Installing CrewAI
+
+CrewAI is a flexible and powerful AI framework that enables you to create and manage AI agents, tools, and tasks efficiently. 
+Let's get you set up! 🚀
 
 <Steps>
     <Step title="Install CrewAI">
-    Install the main CrewAI package with the following command:
-    <CodeGroup>
-    ```shell Terminal
-    pip install crewai
-    ```
-    </CodeGroup>
-    You can also install the main CrewAI package and the tools package that include a series of helpful tools for your agents:
-    <CodeGroup>
-    ```shell Terminal
-    pip install 'crewai[tools]'
-    ```
-    </CodeGroup>
-    Alternatively, you can also use:
-    <CodeGroup>
-    ```shell Terminal
-    pip install crewai crewai-tools
-    ```
-    </CodeGroup>
-    </Step>
-    <Step title="Upgrade CrewAI">
-    To upgrade CrewAI and CrewAI Tools to the latest version, run the following command
-    <CodeGroup>
-    ```shell Terminal
-    pip install --upgrade crewai crewai-tools
-    ```
-    </CodeGroup>
-    <Note>
-    1. If you're using an older version of CrewAI, you may receive a warning about using `Poetry` for dependency management. 
-      ![Error from older versions](./images/crewai-run-poetry-error.png)
-
-    2. In this case, you'll need to run the command below to update your project. 
-      This command will migrate your project to use [UV](https://github.com/astral-sh/uv) and update the necessary files.
+        Install CrewAI with all recommended tools using either method:
         ```shell Terminal
-        crewai update
+        pip install 'crewai[tools]'
+        ```
+        or
+        ```shell Terminal
+        pip install crewai crewai-tools
         ```
-    3. After running the command above, you should see the following output:
-      ![Successfully migrated to UV](./images/crewai-update.png)
 
-    4. You're all set! You can now proceed to the next step! 🎉
-    </Note>
+        <Note>
+          Both methods install the core package and additional tools needed for most use cases.
+        </Note>
     </Step>
-    <Step title="Verify the installation">
-    To verify that `crewai` and `crewai-tools` are installed correctly, run the following command
-    <CodeGroup>
-    ```shell Terminal
-    pip freeze | grep crewai
-    ```
-    </CodeGroup>
-    You should see the version number of `crewai` and `crewai-tools`.
-    <CodeGroup>
-    ```markdown Version
-    crewai==X.X.X
-    crewai-tools==X.X.X
-    ```
-    </CodeGroup>
-    If you see the version number, then the installation was successful! 🎉
+
+    <Step title="Upgrade CrewAI (Existing Installations Only)">
+        If you have an older version of CrewAI installed, you can upgrade it:
+        ```shell Terminal
+        pip install --upgrade crewai crewai-tools
+        ```
+
+        <Warning>
+            If you see a Poetry-related warning, you'll need to migrate to our new dependency manager:
+            ```shell Terminal
+            crewai update
+            ```
+            This will update your project to use [UV](https://github.com/astral-sh/uv), our new faster dependency manager.
+        </Warning>
+
+        <Note>
+            Skip this step if you're doing a fresh installation.
+        </Note>
+    </Step>
+
+    <Step title="Verify Installation">
+        Check your installed versions:
+        ```shell Terminal
+        pip freeze | grep crewai
+        ```
+
+        You should see something like:
+        ```markdown Output
+        crewai==X.X.X
+        crewai-tools==X.X.X
+        ```
+        <Check>Installation successful! You're ready to create your first crew.</Check>
     </Step>
 </Steps>
 
-## Create a new CrewAI project
+# Creating a New Project
 
-The next step is to create a new CrewAI project. 
-We recommend using the YAML Template scaffolding to get started as it provides a structured approach to defining agents and tasks.
+<Info>
+  We recommend using the YAML Template scaffolding for a structured approach to defining agents and tasks.
+</Info>
 
 <Steps>
-  <Step title="Create a new CrewAI project using the YAML Template Configuration">
-  To create a new CrewAI project, run the following CLI (Command Line Interface) command:
-  <CodeGroup>
-      ```shell Terminal
-      crewai create crew <project_name>
-      ```
-    </CodeGroup>
-  This command creates a new project folder with the following structure:
-    | File/Directory          | Description                                      |
-    |:------------------------|:-------------------------------------------------|
-    | `my_project/`           | Root directory of the project                    |
-    | ├── `.gitignore`        | Specifies files and directories to ignore in Git |
-    | ├── `pyproject.toml`    | Project configuration and dependencies           |
-    | ├── `README.md`         | Project documentation                            |
-    | ├── `.env`              | Environment variables                            |
-    | └── `src/`              | Source code directory                            |
-    | &nbsp;&nbsp;&nbsp;&nbsp;└── `my_project/` | Main application package                      |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;├── `__init__.py` | Marks the directory as a Python package     |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;├── `main.py`     | Main application script                    |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;├── `crew.py`     | Crew-related functionalities                |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;├── `tools/`      | Custom tools directory                      |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│   ├── `custom_tool.py` | Custom tool implementation              |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;│   └── `__init__.py`    | Marks tools directory as a package       |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;└── `config/`     | Configuration files directory               |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;├── `agents.yaml`  | Agent configurations                    |
-    | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;└── `tasks.yaml`   | Task configurations                      |
+  <Step title="Generate Project Structure">
+    Run the CrewAI CLI command:
+    ```shell Terminal
+    crewai create crew <project_name>
+    ```
 
-  You can now start developing your crew by editing the files in the `src/my_project` folder. 
-  The `main.py` file is the entry point of the project, the `crew.py` file is where you define your crew, the `agents.yaml` file is where you define your agents, 
-  and the `tasks.yaml` file is where you define your tasks.
+    This creates a new project with the following structure:
+    <Frame>
+    ```
+    my_project/
+    ├── .gitignore
+    ├── pyproject.toml
+    ├── README.md
+    ├── .env
+    └── src/
+        └── my_project/
+            ├── __init__.py
+            ├── main.py
+            ├── crew.py
+            ├── tools/
+            │   ├── custom_tool.py
+            │   └── __init__.py
+            └── config/
+                ├── agents.yaml
+                └── tasks.yaml
+    ```
+    </Frame>
   </Step>   
-  <Step title="Customize your project">
-  To customize your project, you can:
-    - Modify `src/my_project/config/agents.yaml` to define your agents.
-    - Modify `src/my_project/config/tasks.yaml` to define your tasks.
-    - Modify `src/my_project/crew.py` to add your own logic, tools, and specific arguments.
-    - Modify `src/my_project/main.py` to add custom inputs for your agents and tasks.
-    - Add your environment variables into the `.env` file.
+
+  <Step title="Customize Your Project">
+    Your project will contain these essential files:
+
+    | File | Purpose |
+    | --- | --- |
+    | `agents.yaml` | Define your AI agents and their roles |
+    | `tasks.yaml` | Set up agent tasks and workflows |
+    | `.env` | Store API keys and environment variables |
+    | `main.py` | Project entry point and execution flow |
+    | `crew.py` | Crew orchestration and coordination |
+    | `tools/` | Directory for custom agent tools |
+
+    <Tip>
+      Start by editing `agents.yaml` and `tasks.yaml` to define your crew's behavior.
+      Keep sensitive information like API keys in `.env`.
+    </Tip>
   </Step>
 </Steps>
 
-## Next steps
+## Next Steps
 
-Now that you have installed `crewai` and `crewai-tools`, you're ready to spin up your first crew!
-
-- 👨‍💻 Build your first agent with CrewAI by following the [Quickstart](/quickstart) guide.
-- 💬 Join the [Community](https://community.crewai.com) to get help and share your feedback.
+<CardGroup cols={2}>
+  <Card
+    title="Build Your First Agent"
+    icon="code"
+    href="/quickstart"
+  >
+    Follow our quickstart guide to create your first CrewAI agent and get hands-on experience.
+  </Card>
+  <Card
+    title="Join the Community"
+    icon="comments"
+    href="https://community.crewai.com"
+  >
+    Connect with other developers, get help, and share your CrewAI experiences.
+  </Card>
+</CardGroup>
diff --git a/docs/introduction.mdx b/docs/introduction.mdx
index d657c9fb2..9aed6cdea 100644
--- a/docs/introduction.mdx
+++ b/docs/introduction.mdx
@@ -1,49 +1,85 @@
 ---
 title: Introduction
-description: Welcome to CrewAI docs!
+description: Build AI agent teams that work together to tackle complex tasks
 icon: handshake
 ---
 
 # What is CrewAI?
 
-**CrewAI is a cutting-edge Python framework for orchestrating role-playing, autonomous AI agents.**
+**CrewAI is a cutting-edge framework for orchestrating autonomous AI agents.** 
 
-By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
+CrewAI enables you to create AI teams where each agent has specific roles, tools, and goals, working together to accomplish complex tasks.
 
-<Frame caption="CrewAI Mindmap">
-  <img src="crewAI-mindmap.png" alt="CrewAI Mindmap" />
-</Frame>  
+Think of it as assembling your dream team - each member (agent) brings unique skills and expertise, collaborating seamlessly to achieve your objectives.
 
-## Why CrewAI?
-- 🤼‍♀️ **Role-Playing Agents**: Agents can take on different roles and personas to better understand and interact with complex systems.
-- 🤖 **Autonomous Decision Making**: Agents can make decisions autonomously based on the given context and available tools.
-- 🤝 **Seamless Collaboration**: Agents can work together seamlessly, sharing information and resources to achieve common goals.
-- 🧠 **Complex Task Tackling**: CrewAI is designed to tackle complex tasks, such as multi-step workflows, decision making, and problem solving.
+## How CrewAI Works
 
-# Get Started with CrewAI
+<Note>
+  Just like a company has departments (Sales, Engineering, Marketing) working together under leadership to achieve business goals, CrewAI helps you create an organization of AI agents with specialized roles collaborating to accomplish complex tasks.
+</Note>
+
+<Frame caption="CrewAI Framework Overview">
+  <img src="crewAI-mindmap.png" alt="CrewAI Framework Overview" />
+</Frame>
+
+| Component | Description | Key Features |
+|:----------|:-----------:|:------------|
+| **Crew** | The top-level organization | • Manages AI agent teams<br/>• Oversees workflows<br/>• Ensures collaboration<br/>• Delivers outcomes |
+| **AI Agents** | Specialized team members | • Have specific roles (researcher, writer)<br/>• Use designated tools<br/>• Can delegate tasks<br/>• Make autonomous decisions |
+| **Process** | Workflow management system | • Defines collaboration patterns<br/>• Controls task assignments<br/>• Manages interactions<br/>• Ensures efficient execution |
+| **Tasks** | Individual assignments | • Have clear objectives<br/>• Use specific tools<br/>• Feed into larger process<br/>• Produce actionable results |
+
+### How It All Works Together
+
+1. The **Crew** organizes the overall operation
+2. **AI Agents** work on their specialized tasks
+3. The **Process** ensures smooth collaboration
+4. **Tasks** get completed to achieve the goal
+
+## Key Features
 
 <CardGroup cols={2}>
+  <Card title="Role-Based Agents" icon="users">
+    Create specialized agents with defined roles, expertise, and goals - from researchers to analysts to writers
+  </Card>
+  <Card title="Flexible Tools" icon="screwdriver-wrench">
+    Equip agents with custom tools and APIs to interact with external services and data sources
+  </Card>
+  <Card title="Intelligent Collaboration" icon="people-arrows">
+    Agents work together, sharing insights and coordinating tasks to achieve complex objectives
+  </Card>
+  <Card title="Task Management" icon="list-check">
+    Define sequential or parallel workflows, with agents automatically handling task dependencies
+  </Card>
+</CardGroup>
+
+## Why Choose CrewAI?
+
+- 🧠 **Autonomous Operation**: Agents make intelligent decisions based on their roles and available tools
+- 📝 **Natural Interaction**: Agents communicate and collaborate like human team members
+- 🛠️ **Extensible Design**: Easy to add new tools, roles, and capabilities
+- 🚀 **Production Ready**: Built for reliability and scalability in real-world applications
+
+<CardGroup cols={3}>
   <Card
-  title="Quickstart"
-  color="#F3A78B"
-  href="quickstart"
-  icon="terminal"
-    iconType="solid"
+    title="Install CrewAI"
+    icon="wrench"
+    href="/installation"
   >
-    Getting started with CrewAI 
+    Get started with CrewAI in your development environment.
+  </Card>
+  <Card
+    title="Quick Start"
+    icon="bolt"
+    href="/quickstart"
+  >
+    Follow our quickstart guide to create your first CrewAI agent and get hands-on experience.
   </Card>
   <Card
     title="Join the Community"
-    color="#F3A78B"
+    icon="comments"
     href="https://community.crewai.com"
-    icon="comment-question"
-      iconType="duotone"
-    >
-      Join the CrewAI community and get help with your project!
-    </Card>
-</CardGroup>
-
-## Next Step
-
-- [Install CrewAI](/installation) to get started with your first agent.
-
+  >
+    Connect with other developers, get help, and share your CrewAI experiences.
+  </Card>
+</CardGroup>
\ No newline at end of file
diff --git a/docs/quickstart.mdx b/docs/quickstart.mdx
index 246bbdf84..a78a56182 100644
--- a/docs/quickstart.mdx
+++ b/docs/quickstart.mdx
@@ -356,4 +356,21 @@ This will clear the crew's memory, allowing for a fresh start.
 
 ## Deploying Your Project
 
-The easiest way to deploy your crew is through [CrewAI Enterprise](http://app.crewai.com/), where you can deploy your crew in a few clicks.
+The easiest way to deploy your crew is through CrewAI Enterprise, where you can deploy your crew in a few clicks.
+
+<CardGroup cols={2}>
+  <Card
+    title="Deploy on Enterprise"
+    icon="rocket"
+    href="http://app.crewai.com"
+  >
+    Get started with CrewAI Enterprise and deploy your crew in a production environment with just a few clicks.
+  </Card>
+  <Card
+    title="Join the Community"
+    icon="comments"
+    href="https://community.crewai.com"
+  >
+    Join our open source community to discuss ideas, share your projects, and connect with other CrewAI developers.
+  </Card>
+</CardGroup>

From 3285c1b1967027f97ddda4133f1f6f9142692904 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 2 Dec 2024 13:38:17 -0500
Subject: [PATCH 088/126] Fixes issues with result as answer not properly
 exiting LLM loop (#1689)

* v1 of fix implemented. Need to confirm with tokens.

* remove print statements
---
 src/crewai/agent.py                      |  6 +--
 src/crewai/agents/crew_agent_executor.py | 48 ++++++++++++++++++------
 src/crewai/tools/base_tool.py            |  1 +
 src/crewai/tools/structured_tool.py      |  4 ++
 4 files changed, 44 insertions(+), 15 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index 26380ebc2..abe678db1 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -1,7 +1,7 @@
 import os
 import shutil
 import subprocess
-from typing import Any, List, Literal, Optional, Union, Dict
+from typing import Any, Dict, List, Literal, Optional, Union
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -9,9 +9,10 @@ from crewai.agents import CacheHandler
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.cli.constants import ENV_VARS
-from crewai.llm import LLM
 from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+from crewai.knowledge.utils.knowledge_utils import extract_knowledge_context
+from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.task import Task
 from crewai.tools import BaseTool
@@ -21,7 +22,6 @@ from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_F
 from crewai.utilities.converter import generate_model_description
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
-from crewai.knowledge.utils.knowledge_utils import extract_knowledge_context
 
 
 def mock_agent_ops_provider():
diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index bf14e6915..2c880a634 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -1,5 +1,6 @@
 import json
 import re
+from dataclasses import dataclass
 from typing import Any, Dict, List, Union
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
@@ -12,6 +13,7 @@ from crewai.agents.parser import (
     OutputParserException,
 )
 from crewai.agents.tools_handler import ToolsHandler
+from crewai.tools.base_tool import BaseTool
 from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
 from crewai.utilities import I18N, Printer
 from crewai.utilities.constants import TRAINING_DATA_FILE
@@ -22,6 +24,12 @@ from crewai.utilities.logger import Logger
 from crewai.utilities.training_handler import CrewTrainingHandler
 
 
+@dataclass
+class ToolResult:
+    result: Any
+    result_as_answer: bool
+
+
 class CrewAgentExecutor(CrewAgentExecutorMixin):
     _logger: Logger = Logger()
 
@@ -33,7 +41,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         agent: BaseAgent,
         prompt: dict[str, str],
         max_iter: int,
-        tools: List[Any],
+        tools: List[BaseTool],
         tools_names: str,
         stop_words: List[str],
         tools_description: str,
@@ -70,7 +78,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         self.iterations = 0
         self.log_error_after = 3
         self.have_forced_answer = False
-        self.name_to_tool_map = {tool.name: tool for tool in self.tools}
+        self.tool_name_to_tool_map: Dict[str, BaseTool] = {
+            tool.name: tool for tool in self.tools
+        }
         if self.llm.stop:
             self.llm.stop = list(set(self.llm.stop + self.stop))
         else:
@@ -140,9 +150,17 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                     formatted_answer = self._format_answer(answer)
 
                     if isinstance(formatted_answer, AgentAction):
-                        action_result = self._use_tool(formatted_answer)
-                        formatted_answer.text += f"\nObservation: {action_result}"
-                        formatted_answer.result = action_result
+                        tool_result = self._execute_tool_and_check_finality(
+                            formatted_answer
+                        )
+                        formatted_answer.text += f"\nObservation: {tool_result.result}"
+                        formatted_answer.result = tool_result.result
+                        if tool_result.result_as_answer:
+                            return AgentFinish(
+                                thought="",
+                                output=tool_result.result,
+                                text=formatted_answer.text,
+                            )
                         self._show_logs(formatted_answer)
 
                     if self.step_callback:
@@ -239,7 +257,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                     content=f"\033[95m## Final Answer:\033[00m \033[92m\n{formatted_answer.output}\033[00m\n\n"
                 )
 
-    def _use_tool(self, agent_action: AgentAction) -> Any:
+    def _execute_tool_and_check_finality(self, agent_action: AgentAction) -> ToolResult:
         tool_usage = ToolUsage(
             tools_handler=self.tools_handler,
             tools=self.tools,
@@ -255,19 +273,25 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
         if isinstance(tool_calling, ToolUsageErrorException):
             tool_result = tool_calling.message
+            return ToolResult(result=tool_result, result_as_answer=False)
         else:
             if tool_calling.tool_name.casefold().strip() in [
-                name.casefold().strip() for name in self.name_to_tool_map
+                name.casefold().strip() for name in self.tool_name_to_tool_map
             ] or tool_calling.tool_name.casefold().replace("_", " ") in [
-                name.casefold().strip() for name in self.name_to_tool_map
+                name.casefold().strip() for name in self.tool_name_to_tool_map
             ]:
                 tool_result = tool_usage.use(tool_calling, agent_action.text)
+                tool = self.tool_name_to_tool_map.get(tool_calling.tool_name)
+                if tool:
+                    return ToolResult(
+                        result=tool_result, result_as_answer=tool.result_as_answer
+                    )
             else:
                 tool_result = self._i18n.errors("wrong_tool_name").format(
                     tool=tool_calling.tool_name,
                     tools=", ".join([tool.name.casefold() for tool in self.tools]),
                 )
-        return tool_result
+        return ToolResult(result=tool_result, result_as_answer=False)
 
     def _summarize_messages(self) -> None:
         messages_groups = []
@@ -333,9 +357,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             if self.crew is not None and hasattr(self.crew, "_train_iteration"):
                 train_iteration = self.crew._train_iteration
                 if agent_id in training_data and isinstance(train_iteration, int):
-                    training_data[agent_id][train_iteration]["improved_output"] = (
-                        result.output
-                    )
+                    training_data[agent_id][train_iteration][
+                        "improved_output"
+                    ] = result.output
                     training_handler.save(training_data)
                 else:
                     self._logger.log(
diff --git a/src/crewai/tools/base_tool.py b/src/crewai/tools/base_tool.py
index 46bfc03a6..c3840d23c 100644
--- a/src/crewai/tools/base_tool.py
+++ b/src/crewai/tools/base_tool.py
@@ -73,6 +73,7 @@ class BaseTool(BaseModel, ABC):
             description=self.description,
             args_schema=self.args_schema,
             func=self._run,
+            result_as_answer=self.result_as_answer,
         )
 
     @classmethod
diff --git a/src/crewai/tools/structured_tool.py b/src/crewai/tools/structured_tool.py
index bd6818605..dfd23a9cb 100644
--- a/src/crewai/tools/structured_tool.py
+++ b/src/crewai/tools/structured_tool.py
@@ -22,6 +22,7 @@ class CrewStructuredTool:
         description: str,
         args_schema: type[BaseModel],
         func: Callable[..., Any],
+        result_as_answer: bool = False,
     ) -> None:
         """Initialize the structured tool.
 
@@ -30,12 +31,14 @@ class CrewStructuredTool:
             description: A description of what the tool does
             args_schema: The pydantic model for the tool's arguments
             func: The function to run when the tool is called
+            result_as_answer: Whether to return the output directly
         """
         self.name = name
         self.description = description
         self.args_schema = args_schema
         self.func = func
         self._logger = Logger()
+        self.result_as_answer = result_as_answer
 
         # Validate the function signature matches the schema
         self._validate_function_signature()
@@ -98,6 +101,7 @@ class CrewStructuredTool:
             description=description,
             args_schema=schema,
             func=func,
+            result_as_answer=return_direct,
         )
 
     @staticmethod

From f8a8e7b2a5e35205453f114b78d7768c7e37607e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Mon, 2 Dec 2024 18:28:58 -0300
Subject: [PATCH 089/126] preparing new version

---
 pyproject.toml                                          | 2 +-
 src/crewai/__init__.py                                  | 2 +-
 src/crewai/cli/templates/crew/pyproject.toml            | 2 +-
 src/crewai/cli/templates/flow/pyproject.toml            | 2 +-
 src/crewai/cli/templates/pipeline/pyproject.toml        | 2 +-
 src/crewai/cli/templates/pipeline_router/pyproject.toml | 2 +-
 src/crewai/cli/templates/tool/pyproject.toml            | 2 +-
 uv.lock                                                 | 2 +-
 8 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 1d7d8cc43..86891294c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.83.0"
+version = "0.85.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 34d7f17c9..440ba090c 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -16,7 +16,7 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.83.0"
+__version__ = "0.85.0"
 __all__ = [
     "Agent",
     "Crew",
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 1e456c725..e45732685 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.83.0,<1.0.0"
+    "crewai[tools]>=0.85.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 575aaf086..d981987c8 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.83.0,<1.0.0",
+    "crewai[tools]>=0.85.0,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index d12dccf11..1e7f4efd5 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.83.0,<1.0.0" }
+crewai = { extras = ["tools"], version = ">=0.85.0,<1.0.0" }
 asyncio = "*"
 
 [tool.poetry.scripts]
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
index 06487bcfa..49208d120 100644
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline_router/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.83.0,<1.0.0"
+    "crewai[tools]>=0.85.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 7c1afddfa..33dabd38e 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.83.0"
+    "crewai[tools]>=0.85.0"
 ]
 
diff --git a/uv.lock b/uv.lock
index 050602e61..900e730da 100644
--- a/uv.lock
+++ b/uv.lock
@@ -608,7 +608,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.83.0"
+version = "0.85.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 7d9d0ff6f7fe38395ee2c7f2e8f26b1afa54f5d3 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Tue, 3 Dec 2024 10:02:06 -0500
Subject: [PATCH 090/126] fix missing code in flows docs (#1690)

* docs: improve tasks documentation clarity and structure

- Add Task Execution Flow section
- Add variable interpolation explanation
- Add Task Dependencies section with examples
- Improve overall document structure and readability
- Update code examples with proper syntax highlighting

* docs: update agent documentation with improved examples and formatting

- Replace DuckDuckGoSearchRun with SerperDevTool
- Update code block formatting to be consistent
- Improve template examples with actual syntax
- Update LLM examples to use current models
- Clean up formatting and remove redundant comments

* docs: enhance LLM documentation with Cerebras provider and formatting improvements

* docs: simplify LLMs documentation title

* docs: improve installation guide clarity and structure

- Add clear Python version requirements with check command
- Simplify installation options to recommended method
- Improve upgrade section clarity for existing users
- Add better visual structure with Notes and Tips
- Update description and formatting

* docs: improve introduction page organization and clarity

- Update organizational analogy in Note section
- Improve table formatting and alignment
- Remove emojis from component table for cleaner look
- Add 'helps you' to make the note more action-oriented

* docs: add enterprise and community cards

- Add Enterprise deployment card in quickstart
- Add community card focused on open source discussions
- Remove deployment reference from community description
- Clean up introduction page cards
- Remove link from Enterprise description text

* docs: add code snippet to Getting Started section in flows.mdx

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/concepts/flows.mdx | 270 ++++++++++------------------------------
 1 file changed, 68 insertions(+), 202 deletions(-)

diff --git a/docs/concepts/flows.mdx b/docs/concepts/flows.mdx
index 9ead26d70..324118310 100644
--- a/docs/concepts/flows.mdx
+++ b/docs/concepts/flows.mdx
@@ -18,63 +18,60 @@ Flows allow you to create structured, event-driven workflows. They provide a sea
 
 4. **Flexible Control Flow**: Implement conditional logic, loops, and branching within your workflows.
 
-5. **Input Flexibility**: Flows can accept inputs to initialize or update their state, with different handling for structured and unstructured state management.
-
 ## Getting Started
 
 Let's create a simple Flow where you will use OpenAI to generate a random city in one task and then use that city to generate a fun fact in another task.
 
-### Passing Inputs to Flows
+```python Code
 
-Flows can accept inputs to initialize or update their state before execution. The way inputs are handled depends on whether the flow uses structured or unstructured state management.
-
-#### Structured State Management
-
-In structured state management, the flow's state is defined using a Pydantic `BaseModel`. Inputs must match the model's schema, and any updates will overwrite the default values.
-
-```python
 from crewai.flow.flow import Flow, listen, start
-from pydantic import BaseModel
+from dotenv import load_dotenv
+from litellm import completion
 
-class ExampleState(BaseModel):
-    counter: int = 0
-    message: str = ""
 
-class StructuredExampleFlow(Flow[ExampleState]):
+class ExampleFlow(Flow):
+    model = "gpt-4o-mini"
+
     @start()
-    def first_method(self):
-        # Implementation
+    def generate_city(self):
+        print("Starting flow")
 
-flow = StructuredExampleFlow()
-flow.kickoff(inputs={"counter": 10})
-```
+        response = completion(
+            model=self.model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": "Return the name of a random city in the world.",
+                },
+            ],
+        )
 
-In this example, the `counter` is initialized to `10`, while `message` retains its default value.
+        random_city = response["choices"][0]["message"]["content"]
+        print(f"Random City: {random_city}")
 
-#### Unstructured State Management
+        return random_city
 
-In unstructured state management, the flow's state is a dictionary. You can pass any dictionary to update the state.
+    @listen(generate_city)
+    def generate_fun_fact(self, random_city):
+        response = completion(
+            model=self.model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": f"Tell me a fun fact about {random_city}",
+                },
+            ],
+        )
 
-```python
-from crewai.flow.flow import Flow, listen, start
+        fun_fact = response["choices"][0]["message"]["content"]
+        return fun_fact
 
-class UnstructuredExampleFlow(Flow):
-    @start()
-    def first_method(self):
-        # Implementation
 
-flow = UnstructuredExampleFlow()
-flow.kickoff(inputs={"counter": 5, "message": "Initial message"})
-```
 
-Here, both `counter` and `message` are updated based on the provided inputs.
+flow = ExampleFlow()
+result = flow.kickoff()
 
-**Note:** Ensure that inputs for structured state management adhere to the defined schema to avoid validation errors.
-
-### Example Flow
-
-```python
-# Existing example code
+print(f"Generated fun fact: {result}")
 ```
 
 In the above example, we have created a simple Flow that generates a random city using OpenAI and then generates a fun fact about that city. The Flow consists of two tasks: `generate_city` and `generate_fun_fact`. The `generate_city` task is the starting point of the Flow, and the `generate_fun_fact` task listens for the output of the `generate_city` task.
@@ -97,14 +94,14 @@ The `@listen()` decorator can be used in several ways:
 
 1. **Listening to a Method by Name**: You can pass the name of the method you want to listen to as a string. When that method completes, the listener method will be triggered.
 
-   ```python
+   ```python Code
    @listen("generate_city")
    def generate_fun_fact(self, random_city):
        # Implementation
    ```
 
 2. **Listening to a Method Directly**: You can pass the method itself. When that method completes, the listener method will be triggered.
-   ```python
+   ```python Code
    @listen(generate_city)
    def generate_fun_fact(self, random_city):
        # Implementation
@@ -121,7 +118,7 @@ When you run a Flow, the final output is determined by the last method that comp
 Here's how you can access the final output:
 
 <CodeGroup>
-```python
+```python Code
 from crewai.flow.flow import Flow, listen, start
 
 class OutputExampleFlow(Flow):
@@ -133,17 +130,18 @@ class OutputExampleFlow(Flow):
     def second_method(self, first_output):
         return f"Second method received: {first_output}"
 
+
 flow = OutputExampleFlow()
 final_output = flow.kickoff()
 
 print("---- Final Output ----")
 print(final_output)
-```
+````
 
-```text
+``` text Output
 ---- Final Output ----
 Second method received: Output from first_method
-```
+````
 
 </CodeGroup>
 
@@ -158,7 +156,7 @@ Here's an example of how to update and access the state:
 
 <CodeGroup>
 
-```python
+```python Code
 from crewai.flow.flow import Flow, listen, start
 from pydantic import BaseModel
 
@@ -186,7 +184,7 @@ print("Final State:")
 print(flow.state)
 ```
 
-```text
+```text Output
 Final Output: Hello from first_method - updated by second_method
 Final State:
 counter=2 message='Hello from first_method - updated by second_method'
@@ -210,10 +208,10 @@ allowing developers to choose the approach that best fits their application's ne
 In unstructured state management, all state is stored in the `state` attribute of the `Flow` class.
 This approach offers flexibility, enabling developers to add or modify state attributes on the fly without defining a strict schema.
 
-```python
+```python Code
 from crewai.flow.flow import Flow, listen, start
 
-class UnstructuredExampleFlow(Flow):
+class UntructuredExampleFlow(Flow):
 
     @start()
     def first_method(self):
@@ -232,7 +230,8 @@ class UnstructuredExampleFlow(Flow):
 
         print(f"State after third_method: {self.state}")
 
-flow = UnstructuredExampleFlow()
+
+flow = UntructuredExampleFlow()
 flow.kickoff()
 ```
 
@@ -246,14 +245,16 @@ flow.kickoff()
 Structured state management leverages predefined schemas to ensure consistency and type safety across the workflow.
 By using models like Pydantic's `BaseModel`, developers can define the exact shape of the state, enabling better validation and auto-completion in development environments.
 
-```python
+```python Code
 from crewai.flow.flow import Flow, listen, start
 from pydantic import BaseModel
 
+
 class ExampleState(BaseModel):
     counter: int = 0
     message: str = ""
 
+
 class StructuredExampleFlow(Flow[ExampleState]):
 
     @start()
@@ -272,6 +273,7 @@ class StructuredExampleFlow(Flow[ExampleState]):
 
         print(f"State after third_method: {self.state}")
 
+
 flow = StructuredExampleFlow()
 flow.kickoff()
 ```
@@ -305,7 +307,7 @@ The `or_` function in Flows allows you to listen to multiple methods and trigger
 
 <CodeGroup>
 
-```python
+```python Code
 from crewai.flow.flow import Flow, listen, or_, start
 
 class OrExampleFlow(Flow):
@@ -322,11 +324,13 @@ class OrExampleFlow(Flow):
     def logger(self, result):
         print(f"Logger: {result}")
 
+
+
 flow = OrExampleFlow()
 flow.kickoff()
 ```
 
-```text
+```text Output
 Logger: Hello from the start method
 Logger: Hello from the second method
 ```
@@ -342,7 +346,7 @@ The `and_` function in Flows allows you to listen to multiple methods and trigge
 
 <CodeGroup>
 
-```python
+```python Code
 from crewai.flow.flow import Flow, and_, listen, start
 
 class AndExampleFlow(Flow):
@@ -364,7 +368,7 @@ flow = AndExampleFlow()
 flow.kickoff()
 ```
 
-```text
+```text Output
 ---- Logger ----
 {'greeting': 'Hello from the start method', 'joke': 'What do computers eat? Microchips.'}
 ```
@@ -381,7 +385,7 @@ You can specify different routes based on the output of the method, allowing you
 
 <CodeGroup>
 
-```python
+```python Code
 import random
 from crewai.flow.flow import Flow, listen, router, start
 from pydantic import BaseModel
@@ -412,11 +416,12 @@ class RouterFlow(Flow[ExampleState]):
     def fourth_method(self):
         print("Fourth method running")
 
+
 flow = RouterFlow()
 flow.kickoff()
 ```
 
-```text
+```text Output
 Starting the structured flow
 Third method running
 Fourth method running
@@ -479,7 +484,7 @@ The `main.py` file is where you create your flow and connect the crews together.
 
 Here's an example of how you can connect the `poem_crew` in the `main.py` file:
 
-```python
+```python Code
 #!/usr/bin/env python
 from random import randint
 
@@ -555,42 +560,6 @@ uv run kickoff
 
 The flow will execute, and you should see the output in the console.
 
-
-### Adding Additional Crews Using the CLI
-
-Once you have created your initial flow, you can easily add additional crews to your project using the CLI. This allows you to expand your flow's capabilities by integrating new crews without starting from scratch.
-
-To add a new crew to your existing flow, use the following command:
-
-```bash
-crewai flow add-crew <crew_name>
-```
-
-This command will create a new directory for your crew within the `crews` folder of your flow project. It will include the necessary configuration files and a crew definition file, similar to the initial setup.
-
-#### Folder Structure
-
-After adding a new crew, your folder structure will look like this:
-
-| Directory/File         | Description                                                        |
-| :--------------------- | :----------------------------------------------------------------- |
-| `name_of_flow/`        | Root directory for the flow.                                       |
-| ├── `crews/`           | Contains directories for specific crews.                           |
-| │   ├── `poem_crew/`   | Directory for the "poem_crew" with its configurations and scripts. |
-| │   │   ├── `config/`  | Configuration files directory for the "poem_crew".                 |
-| │   │   │  ├── `agents.yaml` | YAML file defining the agents for "poem_crew".                     |
-| │   │   │  └── `tasks.yaml`  | YAML file defining the tasks for "poem_crew".                      |
-| │   │   └── `poem_crew.py`    | Script for "poem_crew" functionality.                              |
-| └── `name_of_crew/`       | Directory for the new crew.                                          |
-|     ├── `config/`         | Configuration files directory for the new crew.                     |
-|     │   ├── `agents.yaml` | YAML file defining the agents for the new crew.                     |
-|     │   └── `tasks.yaml`  | YAML file defining the tasks for the new crew.                      |
-|     └── `name_of_crew.py` | Script for the new crew functionality.                              |
-
-You can then customize the `agents.yaml` and `tasks.yaml` files to define the agents and tasks for your new crew. The `name_of_crew.py` file will contain the crew's logic, which you can modify to suit your needs.
-
-By using the CLI to add additional crews, you can efficiently build complex AI workflows that leverage multiple crews working together.
-
 ## Plot Flows
 
 Visualizing your AI workflows can provide valuable insights into the structure and execution paths of your flows. CrewAI offers a powerful visualization tool that allows you to generate interactive plots of your flows, making it easier to understand and optimize your AI workflows.
@@ -607,7 +576,7 @@ CrewAI provides two convenient methods to generate plots of your flows:
 
 If you are working directly with a flow instance, you can generate a plot by calling the `plot()` method on your flow object. This method will create an HTML file containing the interactive plot of your flow.
 
-```python
+```python Code
 # Assuming you have a flow instance
 flow.plot("my_flow_plot")
 ```
@@ -630,114 +599,13 @@ The generated plot will display nodes representing the tasks in your flow, with
 
 By visualizing your flows, you can gain a clearer understanding of the workflow's structure, making it easier to debug, optimize, and communicate your AI processes to others.
 
+### Conclusion
 
-## Advanced
-
-In this section, we explore more complex use cases of CrewAI Flows, starting with a self-evaluation loop. This pattern is crucial for developing AI systems that can iteratively improve their outputs through feedback.
-
-### 1) Self-Evaluation Loop
-
-The self-evaluation loop is a powerful pattern that allows AI workflows to automatically assess and refine their outputs. This example demonstrates how to set up a flow that generates content, evaluates it, and iterates based on feedback until the desired quality is achieved.
-
-#### Overview
-
-The self-evaluation loop involves two main Crews:
-
-1. **ShakespeareanXPostCrew**: Generates a Shakespearean-style post on a given topic.
-2. **XPostReviewCrew**: Evaluates the generated post, providing feedback on its validity and quality.
-
-The process iterates until the post meets the criteria or a maximum retry limit is reached. This approach ensures high-quality outputs through iterative refinement.
-
-#### Importance
-
-This pattern is essential for building robust AI systems that can adapt and improve over time. By automating the evaluation and feedback loop, developers can ensure that their AI workflows produce reliable and high-quality results.
-
-#### Main Code Highlights
-
-Below is the `main.py` file for the self-evaluation loop flow:
-
-```python
-from typing import Optional
-from crewai.flow.flow import Flow, listen, router, start
-from pydantic import BaseModel
-from self_evaluation_loop_flow.crews.shakespeare_crew.shakespeare_crew import (
-    ShakespeareanXPostCrew,
-)
-from self_evaluation_loop_flow.crews.x_post_review_crew.x_post_review_crew import (
-    XPostReviewCrew,
-)
-
-class ShakespeareXPostFlowState(BaseModel):
-    x_post: str = ""
-    feedback: Optional[str] = None
-    valid: bool = False
-    retry_count: int = 0
-
-class ShakespeareXPostFlow(Flow[ShakespeareXPostFlowState]):
-
-    @start("retry")
-    def generate_shakespeare_x_post(self):
-        print("Generating Shakespearean X post")
-        topic = "Flying cars"
-        result = (
-            ShakespeareanXPostCrew()
-            .crew()
-            .kickoff(inputs={"topic": topic, "feedback": self.state.feedback})
-        )
-        print("X post generated", result.raw)
-        self.state.x_post = result.raw
-
-    @router(generate_shakespeare_x_post)
-    def evaluate_x_post(self):
-        if self.state.retry_count > 3:
-            return "max_retry_exceeded"
-        result = XPostReviewCrew().crew().kickoff(inputs={"x_post": self.state.x_post})
-        self.state.valid = result["valid"]
-        self.state.feedback = result["feedback"]
-        print("valid", self.state.valid)
-        print("feedback", self.state.feedback)
-        self.state.retry_count += 1
-        if self.state.valid:
-            return "complete"
-        return "retry"
-
-    @listen("complete")
-    def save_result(self):
-        print("X post is valid")
-        print("X post:", self.state.x_post)
-        with open("x_post.txt", "w") as file:
-            file.write(self.state.x_post)
-
-    @listen("max_retry_exceeded")
-    def max_retry_exceeded_exit(self):
-        print("Max retry count exceeded")
-        print("X post:", self.state.x_post)
-        print("Feedback:", self.state.feedback)
-
-def kickoff():
-    shakespeare_flow = ShakespeareXPostFlow()
-    shakespeare_flow.kickoff()
-
-def plot():
-    shakespeare_flow = ShakespeareXPostFlow()
-    shakespeare_flow.plot()
-
-if __name__ == "__main__":
-    kickoff()
-```
-
-#### Code Highlights
-
-- **Retry Mechanism**: The flow uses a retry mechanism to regenerate the post if it doesn't meet the criteria, up to a maximum of three retries.
-- **Feedback Loop**: Feedback from the `XPostReviewCrew` is used to refine the post iteratively.
-- **State Management**: The flow maintains state using a Pydantic model, ensuring type safety and clarity.
-
-For a complete example and further details, please refer to the [Self Evaluation Loop Flow repository](https://github.com/crewAIInc/crewAI-examples/tree/main/self_evaluation_loop_flow).
-
+Plotting your flows is a powerful feature of CrewAI that enhances your ability to design and manage complex AI workflows. Whether you choose to use the `plot()` method or the command line, generating plots will provide you with a visual representation of your workflows, aiding in both development and presentation.
 
 ## Next Steps
 
-If you're interested in exploring additional examples of flows, we have a variety of recommendations in our examples repository. Here are five specific flow examples, each showcasing unique use cases to help you match your current problem type to a specific example:
+If you're interested in exploring additional examples of flows, we have a variety of recommendations in our examples repository. Here are four specific flow examples, each showcasing unique use cases to help you match your current problem type to a specific example:
 
 1. **Email Auto Responder Flow**: This example demonstrates an infinite loop where a background job continually runs to automate email responses. It's a great use case for tasks that need to be performed repeatedly without manual intervention. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/email_auto_responder_flow)
 
@@ -747,8 +615,6 @@ If you're interested in exploring additional examples of flows, we have a variet
 
 4. **Meeting Assistant Flow**: This flow demonstrates how to broadcast one event to trigger multiple follow-up actions. For instance, after a meeting is completed, the flow can update a Trello board, send a Slack message, and save the results. It's a great example of handling multiple outcomes from a single event, making it ideal for comprehensive task management and notification systems. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/meeting_assistant_flow)
 
-5. **Self Evaluation Loop Flow**: This flow demonstrates a self-evaluation loop where AI workflows automatically assess and refine their outputs through feedback. It involves generating content, evaluating it, and iterating until the desired quality is achieved. This pattern is crucial for developing robust AI systems that can adapt and improve over time. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/self_evaluation_loop_flow)
-
 By exploring these examples, you can gain insights into how to leverage CrewAI Flows for various use cases, from automating repetitive tasks to managing complex, multi-step processes with dynamic decision-making and human feedback.
 
 Also, check out our YouTube video on how to use flows in CrewAI below!
@@ -762,4 +628,4 @@ Also, check out our YouTube video on how to use flows in CrewAI below!
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
   referrerpolicy="strict-origin-when-cross-origin"
   allowfullscreen
-></iframe>
+></iframe>
\ No newline at end of file

From 308a8dc925ecc719c5f3fabaa05b301b0e600a45 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Javier=20Salda=C3=B1a?= <cjaviersaldana@outlook.com>
Date: Tue, 3 Dec 2024 10:09:30 -0500
Subject: [PATCH 091/126] Update reset memories command based on the SDK
 (#1688)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/quickstart.mdx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/quickstart.mdx b/docs/quickstart.mdx
index a78a56182..9ec3170e1 100644
--- a/docs/quickstart.mdx
+++ b/docs/quickstart.mdx
@@ -349,7 +349,7 @@ Replace `<task_id>` with the ID of the task you want to replay.
 If you need to reset the memory of your crew before running it again, you can do so by calling the reset memory feature:
 
 ```shell
-crewai reset-memory
+crewai reset-memories --all
 ```
 
 This will clear the crew's memory, allowing for a fresh start.

From 9e9b945a4662e6cea9f6ca621cac3224a3119622 Mon Sep 17 00:00:00 2001
From: Ola Hungerford <olahungerford@gmail.com>
Date: Tue, 3 Dec 2024 08:13:06 -0800
Subject: [PATCH 092/126] Update using langchain tools docs (#1664)

* Update example of how to use LangChain tools with correct syntax

* Use .env

* Add  Code back

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/concepts/langchain-tools.mdx | 53 +++++++++++++++++++------------
 1 file changed, 33 insertions(+), 20 deletions(-)

diff --git a/docs/concepts/langchain-tools.mdx b/docs/concepts/langchain-tools.mdx
index 538581aee..68a7998a9 100644
--- a/docs/concepts/langchain-tools.mdx
+++ b/docs/concepts/langchain-tools.mdx
@@ -7,32 +7,45 @@ icon: link
 ## Using LangChain Tools
 
 <Info>
-    CrewAI seamlessly integrates with LangChain’s comprehensive [list of tools](https://python.langchain.com/docs/integrations/tools/), all of which can be used with CrewAI.
+    CrewAI seamlessly integrates with LangChain's comprehensive [list of tools](https://python.langchain.com/docs/integrations/tools/), all of which can be used with CrewAI.
 </Info>
 
 ```python Code
 import os
-from crewai import Agent
-from langchain.agents import Tool
-from langchain.utilities import GoogleSerperAPIWrapper
+from dotenv import load_dotenv
+from crewai import Agent, Task, Crew
+from crewai.tools import BaseTool
+from pydantic import Field
+from langchain_community.utilities import GoogleSerperAPIWrapper
 
-# Setup API keys
-os.environ["SERPER_API_KEY"] = "Your Key"
+# Set up your SERPER_API_KEY key in an .env file, eg:
+# SERPER_API_KEY=<your api key>
+load_dotenv()
 
 search = GoogleSerperAPIWrapper()
 
-# Create and assign the search tool to an agent
-serper_tool = Tool(
-  name="Intermediate Answer",
-  func=search.run,
-  description="Useful for search-based queries",
-)
+class SearchTool(BaseTool):
+    name: str = "Search"
+    description: str = "Useful for search-based queries. Use this to find current information about markets, companies, and trends."
+    search: GoogleSerperAPIWrapper = Field(default_factory=GoogleSerperAPIWrapper)
 
-agent = Agent(
-  role='Research Analyst',
-  goal='Provide up-to-date market analysis',
-  backstory='An expert analyst with a keen eye for market trends.',
-  tools=[serper_tool]
+    def _run(self, query: str) -> str:
+        """Execute the search query and return results"""
+        try:
+            return self.search.run(query)
+        except Exception as e:
+            return f"Error performing search: {str(e)}"
+
+# Create Agents
+researcher = Agent(
+    role='Research Analyst',
+    goal='Gather current market data and trends',
+    backstory="""You are an expert research analyst with years of experience in
+    gathering market intelligence. You're known for your ability to find
+    relevant and up-to-date market information and present it in a clear,
+    actionable format.""",
+    tools=[SearchTool()],
+    verbose=True
 )
 
 # rest of the code ...
@@ -40,6 +53,6 @@ agent = Agent(
 
 ## Conclusion
 
-Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively. 
-When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling, caching mechanisms, 
-and the flexibility of tool arguments to optimize your agents' performance and capabilities.
\ No newline at end of file
+Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively.
+When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling, caching mechanisms,
+and the flexibility of tool arguments to optimize your agents' performance and capabilities.

From aaf80d1d43a02a9b135743b3e67c2d4cccd16d23 Mon Sep 17 00:00:00 2001
From: "Tom Mahler, PhD" <tom@mahler.tech>
Date: Tue, 3 Dec 2024 19:22:29 +0200
Subject: [PATCH 093/126] [FEATURE] Support for custom path in RAGStorage
 (#1659)

* added path to RAGStorage

* added path to short term and entity memory

* add path for long_term_storage for completeness

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 src/crewai/memory/entity/entity_memory.py         | 3 ++-
 src/crewai/memory/long_term/long_term_memory.py   | 5 +++--
 src/crewai/memory/short_term/short_term_memory.py | 4 ++--
 src/crewai/memory/storage/rag_storage.py          | 5 +++--
 4 files changed, 10 insertions(+), 7 deletions(-)

diff --git a/src/crewai/memory/entity/entity_memory.py b/src/crewai/memory/entity/entity_memory.py
index 88d33c09a..67c72e927 100644
--- a/src/crewai/memory/entity/entity_memory.py
+++ b/src/crewai/memory/entity/entity_memory.py
@@ -10,7 +10,7 @@ class EntityMemory(Memory):
     Inherits from the Memory class.
     """
 
-    def __init__(self, crew=None, embedder_config=None, storage=None):
+    def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
         if hasattr(crew, "memory_config") and crew.memory_config is not None:
             self.memory_provider = crew.memory_config.get("provider")
         else:
@@ -33,6 +33,7 @@ class EntityMemory(Memory):
                     allow_reset=True,
                     embedder_config=embedder_config,
                     crew=crew,
+                    path=path,
                 )
             )
         super().__init__(storage)
diff --git a/src/crewai/memory/long_term/long_term_memory.py b/src/crewai/memory/long_term/long_term_memory.py
index b9c36bdc9..656709ac9 100644
--- a/src/crewai/memory/long_term/long_term_memory.py
+++ b/src/crewai/memory/long_term/long_term_memory.py
@@ -14,8 +14,9 @@ class LongTermMemory(Memory):
     LongTermMemoryItem instances.
     """
 
-    def __init__(self, storage=None):
-        storage = storage if storage else LTMSQLiteStorage()
+    def __init__(self, storage=None, path=None):
+        if not storage:
+            storage = LTMSQLiteStorage(db_path=path) if path else LTMSQLiteStorage()
         super().__init__(storage)
 
     def save(self, item: LongTermMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"
diff --git a/src/crewai/memory/short_term/short_term_memory.py b/src/crewai/memory/short_term/short_term_memory.py
index 67a568d63..4ade7eb93 100644
--- a/src/crewai/memory/short_term/short_term_memory.py
+++ b/src/crewai/memory/short_term/short_term_memory.py
@@ -13,7 +13,7 @@ class ShortTermMemory(Memory):
     MemoryItem instances.
     """
 
-    def __init__(self, crew=None, embedder_config=None, storage=None):
+    def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
         if hasattr(crew, "memory_config") and crew.memory_config is not None:
             self.memory_provider = crew.memory_config.get("provider")
         else:
@@ -32,7 +32,7 @@ class ShortTermMemory(Memory):
                 storage
                 if storage
                 else RAGStorage(
-                    type="short_term", embedder_config=embedder_config, crew=crew
+                    type="short_term", embedder_config=embedder_config, crew=crew, path=path
                 )
             )
         super().__init__(storage)
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index 4023cf558..ded340a19 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -37,7 +37,7 @@ class RAGStorage(BaseRAGStorage):
 
     app: ClientAPI | None = None
 
-    def __init__(self, type, allow_reset=True, embedder_config=None, crew=None):
+    def __init__(self, type, allow_reset=True, embedder_config=None, crew=None, path=None):
         super().__init__(type, allow_reset, embedder_config, crew)
         agents = crew.agents if crew else []
         agents = [self._sanitize_role(agent.role) for agent in agents]
@@ -47,6 +47,7 @@ class RAGStorage(BaseRAGStorage):
         self.type = type
 
         self.allow_reset = allow_reset
+        self.path = path
         self._initialize_app()
 
     def _set_embedder_config(self):
@@ -59,7 +60,7 @@ class RAGStorage(BaseRAGStorage):
 
         self._set_embedder_config()
         chroma_client = chromadb.PersistentClient(
-            path=f"{db_storage_path()}/{self.type}/{self.agents}",
+            path=self.path if self.path else f"{db_storage_path()}/{self.type}/{self.agents}",
             settings=Settings(allow_reset=self.allow_reset),
         )
 

From 77af733e448ce25c6d539c36e731e7668336370d Mon Sep 17 00:00:00 2001
From: Patcher <patcher@openlit.io>
Date: Tue, 3 Dec 2024 12:38:49 -0500
Subject: [PATCH 094/126] [Doc]: Add documenation for openlit observability
 (#1612)

* Create openlit-observability.mdx

* Update doc with images and steps

* Update mkdocs.yml and add OpenLIT guide link

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/how-to/openlit-observability.mdx | 181 ++++++++++++++++++++++++++
 docs/images/openlit1.png              | Bin 0 -> 399532 bytes
 docs/images/openlit2.png              | Bin 0 -> 432643 bytes
 docs/images/openlit3.png              | Bin 0 -> 818085 bytes
 docs/mint.json                        |   3 +-
 mkdocs.yml                            |   1 +
 6 files changed, 184 insertions(+), 1 deletion(-)
 create mode 100644 docs/how-to/openlit-observability.mdx
 create mode 100644 docs/images/openlit1.png
 create mode 100644 docs/images/openlit2.png
 create mode 100644 docs/images/openlit3.png

diff --git a/docs/how-to/openlit-observability.mdx b/docs/how-to/openlit-observability.mdx
new file mode 100644
index 000000000..e95989e8e
--- /dev/null
+++ b/docs/how-to/openlit-observability.mdx
@@ -0,0 +1,181 @@
+---
+title: Agent Monitoring with OpenLIT
+description: Quickly start monitoring your Agents in just a single line of code with OpenTelemetry.
+icon: magnifying-glass-chart
+---
+
+# OpenLIT Overview
+
+[OpenLIT](https://github.com/openlit/openlit?src=crewai-docs) is an open-source tool that makes it simple to monitor the performance of AI agents, LLMs, VectorDBs, and GPUs with just **one** line of code. 
+
+It provides OpenTelemetry-native tracing and metrics to track important parameters like cost, latency, interactions and task sequences. 
+This setup enables you to track hyperparameters and monitor for performance issues, helping you find ways to enhance and fine-tune your agents over time.
+
+<Frame caption="OpenLIT Dashboard">
+  <img src="/images/openlit1.png" alt="Overview Agent usage including cost and tokens" />
+  <img src="/images/openlit2.png" alt="Overview of agent otel traces and metrics" />
+  <img src="/images/openlit3.png" alt="Overview of agent traces in details" />
+</Frame>
+
+### Features
+
+- **Analytics Dashboard**: Monitor your Agents health and performance with detailed dashboards that track metrics, costs, and user interactions.
+- **OpenTelemetry-native Observability SDK**: Vendor-neutral SDKs to send traces and metrics to your existing observability tools like Grafana, DataDog and more.
+- **Cost Tracking for Custom and Fine-Tuned Models**: Tailor cost estimations for specific models using custom pricing files for precise budgeting.
+- **Exceptions Monitoring Dashboard**: Quickly spot and resolve issues by tracking common exceptions and errors with a monitoring dashboard.
+- **Compliance and Security**: Detect potential threats such as profanity and PII leaks.
+- **Prompt Injection Detection**: Identify potential code injection and secret leaks.
+- **API Keys and Secrets Management**: Securely handle your LLM API keys and secrets centrally, avoiding insecure practices.
+- **Prompt Management**: Manage and version Agent prompts using PromptHub for consistent and easy access across Agents.
+- **Model Playground** Test and compare different models for your CrewAI agents before deployment.
+
+## Setup Instructions
+
+<Steps>
+    <Step title="Deploy OpenLIT">
+      <Steps>
+        <Step title="Git Clone OpenLIT Repository">
+          ```shell
+          git clone git@github.com:openlit/openlit.git
+          ```
+        </Step>
+        <Step title="Start Docker Compose">
+          From the root directory of the [OpenLIT Repo](https://github.com/openlit/openlit), Run the below command:
+          ```shell
+          docker compose up -d
+          ```
+        </Step>
+      </Steps>
+    </Step>
+    <Step title="Install OpenLIT SDK">
+      ```shell
+      pip install openlit
+      ```
+    </Step>
+    <Step title="Initialize OpenLIT in Your Application">
+      Add the following two lines to your application code:
+      <Tabs>
+        <Tab title="Setup using function arguments">
+          ```python
+          import openlit
+          openlit.init(otlp_endpoint="http://127.0.0.1:4318")
+          ```
+          
+          Example Usage for monitoring a CrewAI Agent:
+    
+          ```python
+          from crewai import Agent, Task, Crew, Process
+          import openlit
+
+          openlit.init(disable_metrics=True)
+          # Define your agents
+          researcher = Agent(
+              role="Researcher",
+              goal="Conduct thorough research and analysis on AI and AI agents",
+              backstory="You're an expert researcher, specialized in technology, software engineering, AI, and startups. You work as a freelancer and are currently researching for a new client.",
+              allow_delegation=False,
+              llm='command-r'
+          )
+
+
+          # Define your task
+          task = Task(
+              description="Generate a list of 5 interesting ideas for an article, then write one captivating paragraph for each idea that showcases the potential of a full article on this topic. Return the list of ideas with their paragraphs and your notes.",
+              expected_output="5 bullet points, each with a paragraph and accompanying notes.",
+          )
+
+          # Define the manager agent
+          manager = Agent(
+              role="Project Manager",
+              goal="Efficiently manage the crew and ensure high-quality task completion",
+              backstory="You're an experienced project manager, skilled in overseeing complex projects and guiding teams to success. Your role is to coordinate the efforts of the crew members, ensuring that each task is completed on time and to the highest standard.",
+              allow_delegation=True,
+              llm='command-r'
+          )
+
+          # Instantiate your crew with a custom manager
+          crew = Crew(
+              agents=[researcher],
+              tasks=[task],
+              manager_agent=manager,
+              process=Process.hierarchical,
+          )
+
+          # Start the crew's work
+          result = crew.kickoff()
+
+          print(result)
+          ```
+        </Tab>
+        <Tab title="Setup using Environment Variables">
+
+          Add the following two lines to your application code:
+          ```python
+          import openlit
+
+          openlit.init()
+          ```
+
+          Run the following command to configure the OTEL export endpoint:
+          ```shell
+          export OTEL_EXPORTER_OTLP_ENDPOINT = "http://127.0.0.1:4318"
+          ```
+
+          Example Usage for monitoring a CrewAI Async Agent:
+
+          ```python
+          import asyncio
+          from crewai import Crew, Agent, Task
+          import openlit
+
+          openlit.init(otlp_endpoint="http://127.0.0.1:4318")
+
+          # Create an agent with code execution enabled
+          coding_agent = Agent(
+            role="Python Data Analyst",
+            goal="Analyze data and provide insights using Python",
+            backstory="You are an experienced data analyst with strong Python skills.",
+            allow_code_execution=True,
+            llm="command-r"
+          )
+
+          # Create a task that requires code execution
+          data_analysis_task = Task(
+            description="Analyze the given dataset and calculate the average age of participants. Ages: {ages}",
+            agent=coding_agent,
+            expected_output="5 bullet points, each with a paragraph and accompanying notes.",
+          )
+
+          # Create a crew and add the task
+          analysis_crew = Crew(
+            agents=[coding_agent],
+            tasks=[data_analysis_task]
+          )
+
+          # Async function to kickoff the crew asynchronously
+          async def async_crew_execution():
+              result = await analysis_crew.kickoff_async(inputs={"ages": [25, 30, 35, 40, 45]})
+              print("Crew Result:", result)
+
+          # Run the async function
+          asyncio.run(async_crew_execution())
+          ```
+        </Tab>
+      </Tabs>
+      Refer to OpenLIT [Python SDK repository](https://github.com/openlit/openlit/tree/main/sdk/python) for more advanced configurations and use cases.
+    </Step>
+    <Step title="Visualize and Analyze">
+      With the Agent Observability data now being collected and sent to OpenLIT, the next step is to visualize and analyze this data to get insights into your Agent's performance, behavior, and identify areas of improvement.
+
+      Just head over to OpenLIT at `127.0.0.1:3000` on your browser to start exploring. You can login using the default credentials
+      - **Email**: `user@openlit.io`
+      - **Password**: `openlituser`
+      
+      <Frame caption="OpenLIT Dashboard">
+        <img src="/images/openlit1.png" alt="Overview Agent usage including cost and tokens" />
+        <img src="/images/openlit2.png" alt="Overview of agent otel traces and metrics" />
+      </Frame>
+
+    </Step>
+</Steps> 
+
diff --git a/docs/images/openlit1.png b/docs/images/openlit1.png
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literal 0
HcmV?d00001

diff --git a/docs/mint.json b/docs/mint.json
index d5aa8cb8f..fad9689b8 100644
--- a/docs/mint.json
+++ b/docs/mint.json
@@ -99,7 +99,8 @@
         "how-to/replay-tasks-from-latest-crew-kickoff",
         "how-to/conditional-tasks",
         "how-to/agentops-observability",
-        "how-to/langtrace-observability"
+        "how-to/langtrace-observability",
+        "how-to/openlit-observability"
       ]
     },
     {
diff --git a/mkdocs.yml b/mkdocs.yml
index 1b6c1f959..df8a1ee70 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -152,6 +152,7 @@ nav:
     - Conditional Tasks: 'how-to/Conditional-Tasks.md'
     - Agent Monitoring with AgentOps: 'how-to/AgentOps-Observability.md'
     - Agent Monitoring with LangTrace: 'how-to/Langtrace-Observability.md'
+    - Agent Monitoring with OpenLIT: 'how-to/openlit-Observability.md'
   - Tools Docs:
     - Browserbase Web Loader: 'tools/BrowserbaseLoadTool.md'
     - Code Docs RAG Search: 'tools/CodeDocsSearchTool.md'

From ed3487aa2225888d7c809b0b1ecea1ee96da1935 Mon Sep 17 00:00:00 2001
From: Feynman Liang <feynman.liang@gmail.com>
Date: Tue, 3 Dec 2024 09:52:23 -0800
Subject: [PATCH 095/126] Fix indentation in llm-connections.mdx code block
 (#1573)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/how-to/llm-connections.mdx | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/docs/how-to/llm-connections.mdx b/docs/how-to/llm-connections.mdx
index 542a9c110..a2fc540cc 100644
--- a/docs/how-to/llm-connections.mdx
+++ b/docs/how-to/llm-connections.mdx
@@ -125,10 +125,10 @@ You can connect to OpenAI-compatible LLMs using either environment variables or
     </Tab>
     <Tab title="Using LLM Class Attributes">
         <CodeGroup>
-        ```python Code
-        llm = LLM(
-            model="custom-model-name",
-            api_key="your-api-key",
+            ```python Code
+            llm = LLM(
+                model="custom-model-name",
+                api_key="your-api-key",
                 base_url="https://api.your-provider.com/v1"
             )
             agent = Agent(llm=llm, ...)
@@ -179,4 +179,4 @@ This is particularly useful when working with OpenAI-compatible APIs or when you
 
 ## Conclusion
 
-By leveraging LiteLLM, CrewAI offers seamless integration with a vast array of LLMs. This flexibility allows you to choose the most suitable model for your specific needs, whether you prioritize performance, cost-efficiency, or local deployment. Remember to consult the [LiteLLM documentation](https://docs.litellm.ai/docs/) for the most up-to-date information on supported models and configuration options.
\ No newline at end of file
+By leveraging LiteLLM, CrewAI offers seamless integration with a vast array of LLMs. This flexibility allows you to choose the most suitable model for your specific needs, whether you prioritize performance, cost-efficiency, or local deployment. Remember to consult the [LiteLLM documentation](https://docs.litellm.ai/docs/) for the most up-to-date information on supported models and configuration options.

From 1af95f5146758aed5b07b389e06f7ca0ae99bc66 Mon Sep 17 00:00:00 2001
From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Date: Tue, 3 Dec 2024 12:27:48 -0800
Subject: [PATCH 096/126] Knowledge project directory standard (#1691)

* Knowledge project directory standard

* fixed types

* comment fix

* made base file knowledge source an abstract class

* cleaner validator on model_post_init

* fix type checker

* cleaner refactor

* better template
---
 docs/concepts/knowledge.mdx                   | 29 ++++++++--
 src/crewai/cli/create_crew.py                 | 14 ++++-
 src/crewai/cli/templates/crew/crew.py         | 13 ++++-
 .../crew/knowledge/user_preference.txt        |  4 ++
 .../source/base_file_knowledge_source.py      | 54 +++++++++++++++----
 .../knowledge/source/csv_knowledge_source.py  | 22 ++++----
 .../source/excel_knowledge_source.py          | 16 +++---
 .../knowledge/source/json_knowledge_source.py |  6 +--
 .../knowledge/source/pdf_knowledge_source.py  |  5 +-
 .../source/text_file_knowledge_source.py      |  9 ++--
 src/crewai/utilities/constants.py             |  1 +
 11 files changed, 123 insertions(+), 50 deletions(-)
 create mode 100644 src/crewai/cli/templates/crew/knowledge/user_preference.txt

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index 69fa4e644..a00b2c2f0 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -156,14 +156,35 @@ crew = Crew(
     agents=[agent],
     tasks=[task],
     knowledge_sources=[source],
-    embedder_config={
-        "model": "BAAI/bge-small-en-v1.5",
-        "normalize": True,
-        "max_length": 512
+    embedder={
+        "provider": "ollama",
+        "config": {"model": "nomic-embed-text:latest"},
     }
 )
 ```
 
+### Referencing Sources
+
+You can reference knowledge sources by their collection name or metadata.
+
+* Add a directory to your crew project called `knowledge`:
+* File paths in knowledge can be referenced relative to the `knowledge` directory.
+
+Example:
+A file inside the `knowledge` directory called `example.txt` can be referenced as `example.txt`.
+
+```python
+source = TextFileKnowledgeSource(
+    file_path="example.txt", # or /example.txt
+    collection_name="example"
+)
+crew = Crew(
+    agents=[agent],
+    tasks=[task],
+    knowledge_sources=[source],
+)
+```
+
 ## Best Practices
 
 <AccordionGroup>
diff --git a/src/crewai/cli/create_crew.py b/src/crewai/cli/create_crew.py
index 06440d74e..c658b0de1 100644
--- a/src/crewai/cli/create_crew.py
+++ b/src/crewai/cli/create_crew.py
@@ -39,6 +39,7 @@ def create_folder_structure(name, parent_folder=None):
 
     folder_path.mkdir(parents=True)
     (folder_path / "tests").mkdir(exist_ok=True)
+    (folder_path / "knowledge").mkdir(exist_ok=True)
     if not parent_folder:
         (folder_path / "src" / folder_name).mkdir(parents=True)
         (folder_path / "src" / folder_name / "tools").mkdir(parents=True)
@@ -52,7 +53,14 @@ def copy_template_files(folder_path, name, class_name, parent_folder):
     templates_dir = package_dir / "templates" / "crew"
 
     root_template_files = (
-        [".gitignore", "pyproject.toml", "README.md"] if not parent_folder else []
+        [
+            ".gitignore",
+            "pyproject.toml",
+            "README.md",
+            "knowledge/user_preference.txt",
+        ]
+        if not parent_folder
+        else []
     )
     tools_template_files = ["tools/custom_tool.py", "tools/__init__.py"]
     config_template_files = ["config/agents.yaml", "config/tasks.yaml"]
@@ -168,7 +176,9 @@ def create_crew(name, provider=None, skip_provider=False, parent_folder=None):
     templates_dir = package_dir / "templates" / "crew"
 
     root_template_files = (
-        [".gitignore", "pyproject.toml", "README.md"] if not parent_folder else []
+        [".gitignore", "pyproject.toml", "README.md", "knowledge/user_preference.txt"]
+        if not parent_folder
+        else []
     )
     tools_template_files = ["tools/custom_tool.py", "tools/__init__.py"]
     config_template_files = ["config/agents.yaml", "config/tasks.yaml"]
diff --git a/src/crewai/cli/templates/crew/crew.py b/src/crewai/cli/templates/crew/crew.py
index 6f8e66c4a..0a8c7481a 100644
--- a/src/crewai/cli/templates/crew/crew.py
+++ b/src/crewai/cli/templates/crew/crew.py
@@ -1,8 +1,9 @@
 from crewai import Agent, Crew, Process, Task
 from crewai.project import CrewBase, agent, crew, task, before_kickoff, after_kickoff
-
 # Uncomment the following line to use an example of a custom tool
 # from {{folder_name}}.tools.custom_tool import MyCustomTool
+# Uncomment the following line to use an example of a knowledge source
+# from crewai.knowledge.source.text_file_knowledge_source import TextFileKnowledgeSource
 
 # Check our tools documentations for more information on how to use them
 # from crewai_tools import SerperDevTool
@@ -57,10 +58,20 @@ class {{crew_name}}():
 	@crew
 	def crew(self) -> Crew:
 		"""Creates the {{crew_name}} crew"""
+		# You can add knowledge sources here
+		# knowledge_path = "user_preference.txt"
+		# sources = [
+		# 	TextFileKnowledgeSource(
+		# 		file_path="knowledge/user_preference.txt",
+		# 		metadata={"preference": "personal"}
+		# 	),
+		# ]
+
 		return Crew(
 			agents=self.agents, # Automatically created by the @agent decorator
 			tasks=self.tasks, # Automatically created by the @task decorator
 			process=Process.sequential,
 			verbose=True,
 			# process=Process.hierarchical, # In case you wanna use that instead https://docs.crewai.com/how-to/Hierarchical/
+			# knowledge_sources=sources, # In the case you want to add knowledge sources
 		)
diff --git a/src/crewai/cli/templates/crew/knowledge/user_preference.txt b/src/crewai/cli/templates/crew/knowledge/user_preference.txt
new file mode 100644
index 000000000..dd63a17bf
--- /dev/null
+++ b/src/crewai/cli/templates/crew/knowledge/user_preference.txt
@@ -0,0 +1,4 @@
+User name is John Doe.
+User is an AI Engineer.
+User is interested in AI Agents.
+User is based in San Francisco, California.
diff --git a/src/crewai/knowledge/source/base_file_knowledge_source.py b/src/crewai/knowledge/source/base_file_knowledge_source.py
index b6e346534..9cb9ec2a2 100644
--- a/src/crewai/knowledge/source/base_file_knowledge_source.py
+++ b/src/crewai/knowledge/source/base_file_knowledge_source.py
@@ -1,36 +1,72 @@
+from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Union, List
+from typing import Union, List, Dict, Any
 
 from pydantic import Field
 
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
-from typing import Dict, Any
+from crewai.utilities.logger import Logger
 from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
 
 
-class BaseFileKnowledgeSource(BaseKnowledgeSource):
+class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
     """Base class for knowledge sources that load content from files."""
 
-    file_path: Union[Path, List[Path]] = Field(...)
+    _logger: Logger = Logger(verbose=True)
+    file_path: Union[Path, List[Path], str, List[str]] = Field(
+        ..., description="The path to the file"
+    )
     content: Dict[Path, str] = Field(init=False, default_factory=dict)
     storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
+    safe_file_paths: List[Path] = Field(default_factory=list)
 
     def model_post_init(self, _):
         """Post-initialization method to load content."""
+        self.safe_file_paths = self._process_file_paths()
+        self.validate_paths()
         self.content = self.load_content()
 
+    @abstractmethod
     def load_content(self) -> Dict[Path, str]:
-        """Load and preprocess file content. Should be overridden by subclasses."""
-        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
+        """Load and preprocess file content. Should be overridden by subclasses. Assume that the file path is relative to the project root in the knowledge directory."""
+        pass
 
-        for path in paths:
+    def validate_paths(self):
+        """Validate the paths."""
+        for path in self.safe_file_paths:
             if not path.exists():
+                self._logger.log(
+                    "error",
+                    f"File not found: {path}. Try adding sources to the knowledge directory. If its inside the knowledge directory, use the relative path.",
+                    color="red",
+                )
                 raise FileNotFoundError(f"File not found: {path}")
             if not path.is_file():
-                raise ValueError(f"Path is not a file: {path}")
-        return {}
+                self._logger.log(
+                    "error",
+                    f"Path is not a file: {path}",
+                    color="red",
+                )
 
     def save_documents(self, metadata: Dict[str, Any]):
         """Save the documents to the storage."""
         chunk_metadatas = [metadata.copy() for _ in self.chunks]
         self.storage.save(self.chunks, chunk_metadatas)
+
+    def convert_to_path(self, path: Union[Path, str]) -> Path:
+        """Convert a path to a Path object."""
+        return Path(KNOWLEDGE_DIRECTORY + "/" + path) if isinstance(path, str) else path
+
+    def _process_file_paths(self) -> List[Path]:
+        """Convert file_path to a list of Path objects."""
+        paths = (
+            [self.file_path]
+            if isinstance(self.file_path, (str, Path))
+            else self.file_path
+        )
+
+        if not isinstance(paths, list):
+            raise ValueError("file_path must be a Path, str, or a list of these types")
+
+        return [self.convert_to_path(path) for path in paths]
diff --git a/src/crewai/knowledge/source/csv_knowledge_source.py b/src/crewai/knowledge/source/csv_knowledge_source.py
index 0946104a4..117cbe32f 100644
--- a/src/crewai/knowledge/source/csv_knowledge_source.py
+++ b/src/crewai/knowledge/source/csv_knowledge_source.py
@@ -10,19 +10,15 @@ class CSVKnowledgeSource(BaseFileKnowledgeSource):
 
     def load_content(self) -> Dict[Path, str]:
         """Load and preprocess CSV file content."""
-        super().load_content()  # Validate the file path
-
-        file_path = (
-            self.file_path[0] if isinstance(self.file_path, list) else self.file_path
-        )
-        file_path = Path(file_path) if isinstance(file_path, str) else file_path
-
-        with open(file_path, "r", encoding="utf-8") as csvfile:
-            reader = csv.reader(csvfile)
-            content = ""
-            for row in reader:
-                content += " ".join(row) + "\n"
-        return {file_path: content}
+        content_dict = {}
+        for file_path in self.safe_file_paths:
+            with open(file_path, "r", encoding="utf-8") as csvfile:
+                reader = csv.reader(csvfile)
+                content = ""
+                for row in reader:
+                    content += " ".join(row) + "\n"
+                content_dict[file_path] = content
+        return content_dict
 
     def add(self) -> None:
         """
diff --git a/src/crewai/knowledge/source/excel_knowledge_source.py b/src/crewai/knowledge/source/excel_knowledge_source.py
index 3b5c71514..5484e59d5 100644
--- a/src/crewai/knowledge/source/excel_knowledge_source.py
+++ b/src/crewai/knowledge/source/excel_knowledge_source.py
@@ -8,17 +8,15 @@ class ExcelKnowledgeSource(BaseFileKnowledgeSource):
 
     def load_content(self) -> Dict[Path, str]:
         """Load and preprocess Excel file content."""
-        super().load_content()  # Validate the file path
         pd = self._import_dependencies()
 
-        if isinstance(self.file_path, list):
-            file_path = self.file_path[0]
-        else:
-            file_path = self.file_path
-
-        df = pd.read_excel(file_path)
-        content = df.to_csv(index=False)
-        return {file_path: content}
+        content_dict = {}
+        for file_path in self.safe_file_paths:
+            file_path = self.convert_to_path(file_path)
+            df = pd.read_excel(file_path)
+            content = df.to_csv(index=False)
+            content_dict[file_path] = content
+        return content_dict
 
     def _import_dependencies(self):
         """Dynamically import dependencies."""
diff --git a/src/crewai/knowledge/source/json_knowledge_source.py b/src/crewai/knowledge/source/json_knowledge_source.py
index 490423a00..ed6eec86d 100644
--- a/src/crewai/knowledge/source/json_knowledge_source.py
+++ b/src/crewai/knowledge/source/json_knowledge_source.py
@@ -10,11 +10,9 @@ class JSONKnowledgeSource(BaseFileKnowledgeSource):
 
     def load_content(self) -> Dict[Path, str]:
         """Load and preprocess JSON file content."""
-        super().load_content()  # Validate the file path
-        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
-
         content: Dict[Path, str] = {}
-        for path in paths:
+        for path in self.safe_file_paths:
+            path = self.convert_to_path(path)
             with open(path, "r", encoding="utf-8") as json_file:
                 data = json.load(json_file)
             content[path] = self._json_to_text(data)
diff --git a/src/crewai/knowledge/source/pdf_knowledge_source.py b/src/crewai/knowledge/source/pdf_knowledge_source.py
index 623ba30a2..e6733d78b 100644
--- a/src/crewai/knowledge/source/pdf_knowledge_source.py
+++ b/src/crewai/knowledge/source/pdf_knowledge_source.py
@@ -9,14 +9,13 @@ class PDFKnowledgeSource(BaseFileKnowledgeSource):
 
     def load_content(self) -> Dict[Path, str]:
         """Load and preprocess PDF file content."""
-        super().load_content()  # Validate the file paths
         pdfplumber = self._import_pdfplumber()
 
-        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
         content = {}
 
-        for path in paths:
+        for path in self.safe_file_paths:
             text = ""
+            path = self.convert_to_path(path)
             with pdfplumber.open(path) as pdf:
                 for page in pdf.pages:
                     page_text = page.extract_text()
diff --git a/src/crewai/knowledge/source/text_file_knowledge_source.py b/src/crewai/knowledge/source/text_file_knowledge_source.py
index 640db4ef9..1ceb02843 100644
--- a/src/crewai/knowledge/source/text_file_knowledge_source.py
+++ b/src/crewai/knowledge/source/text_file_knowledge_source.py
@@ -9,12 +9,11 @@ class TextFileKnowledgeSource(BaseFileKnowledgeSource):
 
     def load_content(self) -> Dict[Path, str]:
         """Load and preprocess text file content."""
-        super().load_content()
-        paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
         content = {}
-        for path in paths:
-            with path.open("r", encoding="utf-8") as f:
-                content[path] = f.read()  # type: ignore
+        for path in self.safe_file_paths:
+            path = self.convert_to_path(path)
+            with open(path, "r", encoding="utf-8") as f:
+                content[path] = f.read()
         return content
 
     def add(self) -> None:
diff --git a/src/crewai/utilities/constants.py b/src/crewai/utilities/constants.py
index 59f789913..97fadda48 100644
--- a/src/crewai/utilities/constants.py
+++ b/src/crewai/utilities/constants.py
@@ -1,3 +1,4 @@
 TRAINING_DATA_FILE = "training_data.pkl"
 TRAINED_AGENTS_DATA_FILE = "trained_agents_data.pkl"
 DEFAULT_SCORE_THRESHOLD = 0.35
+KNOWLEDGE_DIRECTORY = "knowledge"

From b6c6eea6f52c213caf828b7fe51634c0f901ea80 Mon Sep 17 00:00:00 2001
From: Stephen <stephen-talari@users.noreply.github.com>
Date: Wed, 4 Dec 2024 02:38:19 +0530
Subject: [PATCH 097/126] Update README.md (#1694)

Corrected the statement which says users can not disable telemetry, but now users can disable by setting the environment variable OTEL_SDK_DISABLED to true.

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 041735354..706dc065a 100644
--- a/README.md
+++ b/README.md
@@ -376,7 +376,7 @@ pip install dist/*.tar.gz
 
 CrewAI uses anonymous telemetry to collect usage data with the main purpose of helping us improve the library by focusing our efforts on the most used features, integrations and tools.
 
-It's pivotal to understand that **NO data is collected** concerning prompts, task descriptions, agents' backstories or goals, usage of tools, API calls, responses, any data processed by the agents, or secrets and environment variables, with the exception of the conditions mentioned. When the `share_crew` feature is enabled, detailed data including task descriptions, agents' backstories or goals, and other specific attributes are collected to provide deeper insights while respecting user privacy. We don't offer a way to disable it now, but we will in the future.
+It's pivotal to understand that **NO data is collected** concerning prompts, task descriptions, agents' backstories or goals, usage of tools, API calls, responses, any data processed by the agents, or secrets and environment variables, with the exception of the conditions mentioned. When the `share_crew` feature is enabled, detailed data including task descriptions, agents' backstories or goals, and other specific attributes are collected to provide deeper insights while respecting user privacy. Users can disable telemetry by setting the environment variable OTEL_SDK_DISABLED to true.
 
 Data collected includes:
 

From 4fb3331c6af231568e49a671a5e333bf6fd85cfe Mon Sep 17 00:00:00 2001
From: Brandon Hancock <brandon@brandonhancock.io>
Date: Wed, 4 Dec 2024 10:46:39 -0500
Subject: [PATCH 098/126] Talk about getting structured consistent outputs with
 tasks.

---
 docs/concepts/tasks.mdx | 163 +++++++++++++++++++++++++++++++++++++++-
 1 file changed, 162 insertions(+), 1 deletion(-)

diff --git a/docs/concepts/tasks.mdx b/docs/concepts/tasks.mdx
index fd48c242d..9ca90fcb5 100644
--- a/docs/concepts/tasks.mdx
+++ b/docs/concepts/tasks.mdx
@@ -263,6 +263,167 @@ analysis_task = Task(
 )
 ```
 
+## Getting Structured Consistent Outputs from Tasks
+When you need to ensure that a task outputs a structured and consistent format, you can use the `output_pydantic` or `output_json` properties on a task. These properties allow you to define the expected output structure, making it easier to parse and utilize the results in your application. 
+
+<Note>
+It's also important to note that the output of the final task of a crew becomes the final output of the actual crew itself.
+</Note>
+
+### Using `output_pydantic`
+The `output_pydantic` property allows you to define a Pydantic model that the task output should conform to. This ensures that the output is not only structured but also validated according to the Pydantic model.
+
+Here’s an example demonstrating how to use output_pydantic:
+
+```python Code
+import json
+
+from crewai import Agent, Crew, Process, Task
+from pydantic import BaseModel
+
+
+class Blog(BaseModel):
+    title: str
+    content: str
+
+
+blog_agent = Agent(
+    role="Blog Content Generator Agent",
+    goal="Generate a blog title and content",
+    backstory="""You are an expert content creator, skilled in crafting engaging and informative blog posts.""",
+    verbose=False,
+    allow_delegation=False,
+    llm="gpt-4o",
+)
+
+task1 = Task(
+    description="""Create a blog title and content on a given topic. Make sure the content is under 200 words.""",
+    expected_output="A compelling blog title and well-written content.",
+    agent=blog_agent,
+    output_pydantic=Blog,
+)
+
+# Instantiate your crew with a sequential process
+crew = Crew(
+    agents=[blog_agent],
+    tasks=[task1],
+    verbose=True,
+    process=Process.sequential,
+)
+
+result = crew.kickoff()
+
+# Option 1: Accessing Properties Using Dictionary-Style Indexing
+print("Accessing Properties - Option 1")
+title = result["title"]
+content = result["content"]
+print("Title:", title)
+print("Content:", content)
+
+# Option 2: Accessing Properties Directly from the Pydantic Model
+print("Accessing Properties - Option 2")
+title = result.pydantic.title
+content = result.pydantic.content
+print("Title:", title)
+print("Content:", content)
+
+# Option 3: Accessing Properties Using the to_dict() Method
+print("Accessing Properties - Option 3")
+output_dict = result.to_dict()
+title = output_dict["title"]
+content = output_dict["content"]
+print("Title:", title)
+print("Content:", content)
+
+# Option 4: Printing the Entire Blog Object
+print("Accessing Properties - Option 5")
+print("Blog:", result)
+
+```
+In this example:
+* A Pydantic model Blog is defined with title and content fields.
+* The task task1 uses the output_pydantic property to specify that its output should conform to the Blog model.
+* After executing the crew, you can access the structured output in multiple ways as shown.
+
+#### Explanation of Accessing the Output
+1. Dictionary-Style Indexing: You can directly access the fields using result["field_name"]. This works because the CrewOutput class implements the __getitem__ method.
+2. Directly from Pydantic Model: Access the attributes directly from the result.pydantic object.
+3. Using to_dict() Method: Convert the output to a dictionary and access the fields.
+4. Printing the Entire Object: Simply print the result object to see the structured output.
+
+### Using `output_json`
+The `output_json` property allows you to define the expected output in JSON format. This ensures that the task's output is a valid JSON structure that can be easily parsed and used in your application.
+
+Here’s an example demonstrating how to use `output_json`:
+
+```python Code
+import json
+
+from crewai import Agent, Crew, Process, Task
+from pydantic import BaseModel
+
+
+# Define the Pydantic model for the blog
+class Blog(BaseModel):
+    title: str
+    content: str
+
+
+# Define the agent
+blog_agent = Agent(
+    role="Blog Content Generator Agent",
+    goal="Generate a blog title and content",
+    backstory="""You are an expert content creator, skilled in crafting engaging and informative blog posts.""",
+    verbose=False,
+    allow_delegation=False,
+    llm="gpt-4o",
+)
+
+# Define the task with output_json set to the Blog model
+task1 = Task(
+    description="""Create a blog title and content on a given topic. Make sure the content is under 200 words.""",
+    expected_output="A JSON object with 'title' and 'content' fields.",
+    agent=blog_agent,
+    output_json=Blog,
+)
+
+# Instantiate the crew with a sequential process
+crew = Crew(
+    agents=[blog_agent],
+    tasks=[task1],
+    verbose=True,
+    process=Process.sequential,
+)
+
+# Kickoff the crew to execute the task
+result = crew.kickoff()
+
+# Option 1: Accessing Properties Using Dictionary-Style Indexing
+print("Accessing Properties - Option 1")
+title = result["title"]
+content = result["content"]
+print("Title:", title)
+print("Content:", content)
+
+# Option 2: Printing the Entire Blog Object
+print("Accessing Properties - Option 2")
+print("Blog:", result)
+```
+
+In this example:
+* A Pydantic model Blog is defined with title and content fields, which is used to specify the structure of the JSON output.
+* The task task1 uses the output_json property to indicate that it expects a JSON output conforming to the Blog model.
+* After executing the crew, you can access the structured JSON output in two ways as shown.
+
+#### Explanation of Accessing the Output
+
+1. Accessing Properties Using Dictionary-Style Indexing: You can access the fields directly using result["field_name"]. This is possible because the CrewOutput class implements the __getitem__ method, allowing you to treat the output like a dictionary. In this option, we're retrieving the title and content from the result.
+2. Printing the Entire Blog Object: By printing result, you get the string representation of the CrewOutput object. Since the __str__ method is implemented to return the JSON output, this will display the entire output as a formatted string representing the Blog object.
+
+---
+
+By using output_pydantic or output_json, you ensure that your tasks produce outputs in a consistent and structured format, making it easier to process and utilize the data within your application or across multiple tasks.
+
 ## Integrating Tools with Tasks
 
 Leverage tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools) for enhanced task performance and agent interaction.
@@ -471,4 +632,4 @@ save_output_task = Task(
 Tasks are the driving force behind the actions of agents in CrewAI. 
 By properly defining tasks and their outcomes, you set the stage for your AI agents to work effectively, either independently or as a collaborative unit. 
 Equipping tasks with appropriate tools, understanding the execution process, and following robust validation practices are crucial for maximizing CrewAI's potential, 
-ensuring agents are effectively prepared for their assignments and that tasks are executed as intended.
\ No newline at end of file
+ensuring agents are effectively prepared for their assignments and that tasks are executed as intended.

From bbea797b0cdff5c30821ab877aaa30162d69523e Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 4 Dec 2024 12:39:34 -0500
Subject: [PATCH 099/126] remove all references to pipeline and pipeline router
 (#1661)

* remove all references to pipeline and router

* fix linting

* drop poetry.lock
---
 docs/concepts/cli.mdx                         |    9 +-
 mkdocs.yml                                    |    1 -
 poetry.lock                                   | 7507 -----------------
 src/crewai/__init__.py                        |    4 -
 src/crewai/cli/cli.py                         |   11 +-
 src/crewai/cli/create_pipeline.py             |  107 -
 src/crewai/cli/templates/pipeline/.gitignore  |    2 -
 src/crewai/cli/templates/pipeline/README.md   |   57 -
 src/crewai/cli/templates/pipeline/__init__.py |    0
 .../crews/research_crew/config/agents.yaml    |   19 -
 .../crews/research_crew/config/tasks.yaml     |   16 -
 .../crews/research_crew/research_crew.py      |   58 -
 .../write_linkedin_crew/config/agents.yaml    |    0
 .../write_linkedin_crew/config/tasks.yaml     |    0
 .../write_linkedin_crew.py                    |   51 -
 .../crews/write_x_crew/config/agents.yaml     |   14 -
 .../crews/write_x_crew/config/tasks.yaml      |   22 -
 .../crews/write_x_crew/write_x_crew.py        |   36 -
 src/crewai/cli/templates/pipeline/main.py     |   26 -
 .../templates/pipeline/pipelines/__init__.py  |    0
 .../templates/pipeline/pipelines/pipeline.py  |   87 -
 .../cli/templates/pipeline/pyproject.toml     |   17 -
 .../cli/templates/pipeline/tools/__init__.py  |    0
 .../templates/pipeline/tools/custom_tool.py   |   19 -
 .../cli/templates/pipeline_router/.gitignore  |    2 -
 .../cli/templates/pipeline_router/README.md   |   54 -
 .../cli/templates/pipeline_router/__init__.py |    0
 .../pipeline_router/config/agents.yaml        |   19 -
 .../pipeline_router/config/tasks.yaml         |   17 -
 .../crews/classifier_crew/classifier_crew.py  |   40 -
 .../crews/classifier_crew/config/agents.yaml  |    7 -
 .../crews/classifier_crew/config/tasks.yaml   |    7 -
 .../crews/normal_crew/config/agents.yaml      |    7 -
 .../crews/normal_crew/config/tasks.yaml       |    6 -
 .../crews/normal_crew/normal_crew.py          |   36 -
 .../crews/urgent_crew/config/agents.yaml      |    7 -
 .../crews/urgent_crew/config/tasks.yaml       |    6 -
 .../crews/urgent_crew/urgent_crew.py          |   36 -
 .../cli/templates/pipeline_router/main.py     |   75 -
 .../pipeline_router/pipelines/__init__.py     |    0
 .../pipelines/pipeline_classifier.py          |   24 -
 .../pipelines/pipeline_normal.py              |   24 -
 .../pipelines/pipeline_urgent.py              |   23 -
 .../templates/pipeline_router/pyproject.toml  |   21 -
 .../pipeline_router/tools/__init__.py         |    0
 .../pipeline_router/tools/custom_tool.py      |   19 -
 src/crewai/crew.py                            |   20 +-
 src/crewai/pipeline/__init__.py               |    5 -
 src/crewai/pipeline/pipeline.py               |  405 -
 .../pipeline/pipeline_kickoff_result.py       |   61 -
 src/crewai/pipeline/pipeline_output.py        |   20 -
 src/crewai/project/__init__.py                |    4 -
 src/crewai/project/annotations.py             |   15 -
 src/crewai/project/pipeline_base.py           |   58 -
 src/crewai/routers/__init__.py                |    3 -
 src/crewai/routers/router.py                  |   84 -
 tests/pipeline/test_pipeline.py               |  921 --
 57 files changed, 10 insertions(+), 10079 deletions(-)
 delete mode 100644 poetry.lock
 delete mode 100644 src/crewai/cli/create_pipeline.py
 delete mode 100644 src/crewai/cli/templates/pipeline/.gitignore
 delete mode 100644 src/crewai/cli/templates/pipeline/README.md
 delete mode 100644 src/crewai/cli/templates/pipeline/__init__.py
 delete mode 100644 src/crewai/cli/templates/pipeline/crews/research_crew/config/agents.yaml
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 delete mode 100644 src/crewai/cli/templates/pipeline/crews/research_crew/research_crew.py
 delete mode 100644 src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/config/agents.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/config/tasks.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/write_linkedin_crew.py
 delete mode 100644 src/crewai/cli/templates/pipeline/crews/write_x_crew/config/agents.yaml
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 delete mode 100644 src/crewai/cli/templates/pipeline/crews/write_x_crew/write_x_crew.py
 delete mode 100644 src/crewai/cli/templates/pipeline/main.py
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 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/classifier_crew/classifier_crew.py
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/agents.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/tasks.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/agents.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/tasks.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/normal_crew/normal_crew.py
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/agents.yaml
 delete mode 100644 src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/tasks.yaml
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 delete mode 100644 src/crewai/cli/templates/pipeline_router/main.py
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 delete mode 100644 src/crewai/cli/templates/pipeline_router/pipelines/pipeline_classifier.py
 delete mode 100644 src/crewai/cli/templates/pipeline_router/pipelines/pipeline_normal.py
 delete mode 100644 src/crewai/cli/templates/pipeline_router/pipelines/pipeline_urgent.py
 delete mode 100644 src/crewai/cli/templates/pipeline_router/pyproject.toml
 delete mode 100644 src/crewai/cli/templates/pipeline_router/tools/__init__.py
 delete mode 100644 src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
 delete mode 100644 src/crewai/pipeline/__init__.py
 delete mode 100644 src/crewai/pipeline/pipeline.py
 delete mode 100644 src/crewai/pipeline/pipeline_kickoff_result.py
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 delete mode 100644 src/crewai/project/pipeline_base.py
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 delete mode 100644 tests/pipeline/test_pipeline.py

diff --git a/docs/concepts/cli.mdx b/docs/concepts/cli.mdx
index 2afc6b56c..ab21232ad 100644
--- a/docs/concepts/cli.mdx
+++ b/docs/concepts/cli.mdx
@@ -28,20 +28,19 @@ crewai [COMMAND] [OPTIONS] [ARGUMENTS]
 
 ### 1. Create
 
-Create a new crew or pipeline.
+Create a new crew or flow.
 
 ```shell
 crewai create [OPTIONS] TYPE NAME
 ```
 
-- `TYPE`: Choose between "crew" or "pipeline"
-- `NAME`: Name of the crew or pipeline
-- `--router`: (Optional) Create a pipeline with router functionality
+- `TYPE`: Choose between "crew" or "flow"
+- `NAME`: Name of the crew or flow
 
 Example:
 ```shell
 crewai create crew my_new_crew
-crewai create pipeline my_new_pipeline --router
+crewai create flow my_new_flow
 ```
 
 ### 2. Version
diff --git a/mkdocs.yml b/mkdocs.yml
index df8a1ee70..948744de2 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -129,7 +129,6 @@ nav:
     - Processes: 'core-concepts/Processes.md'
     - Crews: 'core-concepts/Crews.md'
     - Collaboration: 'core-concepts/Collaboration.md'
-    - Pipeline: 'core-concepts/Pipeline.md'
     - Training: 'core-concepts/Training-Crew.md'
     - Memory: 'core-concepts/Memory.md'
     - Planning: 'core-concepts/Planning.md'
diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index 094b84664..000000000
--- a/poetry.lock
+++ /dev/null
@@ -1,7507 +0,0 @@
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-
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-    {file = "yarl-1.14.0-py3-none-any.whl", hash = "sha256:c8ed4034f0765f8861620c1f2f2364d2e58520ea288497084dae880424fc0d9f"},
-    {file = "yarl-1.14.0.tar.gz", hash = "sha256:88c7d9d58aab0724b979ab5617330acb1c7030b79379c8138c1c8c94e121d1b3"},
-]
-
-[package.dependencies]
-idna = ">=2.0"
-multidict = ">=4.0"
-propcache = ">=0.2.0"
-
-[[package]]
-name = "zipp"
-version = "3.20.2"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
-    {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
-]
-
-[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
-cover = ["pytest-cov"]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
-type = ["pytest-mypy"]
-
-[extras]
-agentops = ["agentops"]
-tools = ["crewai-tools"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = ">=3.10,<=3.13"
-content-hash = "0b833460455da407e9b73fe545bb8dfccc114384d3ce1aa66a1d2fc83afb00f7"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 440ba090c..a6ec565e9 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -5,9 +5,7 @@ from crewai.crew import Crew
 from crewai.flow.flow import Flow
 from crewai.knowledge.knowledge import Knowledge
 from crewai.llm import LLM
-from crewai.pipeline import Pipeline
 from crewai.process import Process
-from crewai.routers import Router
 from crewai.task import Task
 
 warnings.filterwarnings(
@@ -22,8 +20,6 @@ __all__ = [
     "Crew",
     "Process",
     "Task",
-    "Pipeline",
-    "Router",
     "LLM",
     "Flow",
     "Knowledge",
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 600eb6142..6e8560133 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -6,7 +6,6 @@ import pkg_resources
 from crewai.cli.add_crew_to_flow import add_crew_to_flow
 from crewai.cli.create_crew import create_crew
 from crewai.cli.create_flow import create_flow
-from crewai.cli.create_pipeline import create_pipeline
 from crewai.memory.storage.kickoff_task_outputs_storage import (
     KickoffTaskOutputsSQLiteStorage,
 )
@@ -31,22 +30,18 @@ def crewai():
 
 
 @crewai.command()
-@click.argument("type", type=click.Choice(["crew", "pipeline", "flow"]))
+@click.argument("type", type=click.Choice(["crew", "flow"]))
 @click.argument("name")
 @click.option("--provider", type=str, help="The provider to use for the crew")
 @click.option("--skip_provider", is_flag=True, help="Skip provider validation")
 def create(type, name, provider, skip_provider=False):
-    """Create a new crew, pipeline, or flow."""
+    """Create a new crew, or flow."""
     if type == "crew":
         create_crew(name, provider, skip_provider)
-    elif type == "pipeline":
-        create_pipeline(name)
     elif type == "flow":
         create_flow(name)
     else:
-        click.secho(
-            "Error: Invalid type. Must be 'crew', 'pipeline', or 'flow'.", fg="red"
-        )
+        click.secho("Error: Invalid type. Must be 'crew' or 'flow'.", fg="red")
 
 
 @crewai.command()
diff --git a/src/crewai/cli/create_pipeline.py b/src/crewai/cli/create_pipeline.py
deleted file mode 100644
index b26acf818..000000000
--- a/src/crewai/cli/create_pipeline.py
+++ /dev/null
@@ -1,107 +0,0 @@
-import shutil
-from pathlib import Path
-
-import click
-
-
-def create_pipeline(name, router=False):
-    """Create a new pipeline project."""
-    folder_name = name.replace(" ", "_").replace("-", "_").lower()
-    class_name = name.replace("_", " ").replace("-", " ").title().replace(" ", "")
-
-    click.secho(f"Creating pipeline {folder_name}...", fg="green", bold=True)
-
-    project_root = Path(folder_name)
-    if project_root.exists():
-        click.secho(f"Error: Folder {folder_name} already exists.", fg="red")
-        return
-
-    # Create directory structure
-    (project_root / "src" / folder_name).mkdir(parents=True)
-    (project_root / "src" / folder_name / "pipelines").mkdir(parents=True)
-    (project_root / "src" / folder_name / "crews").mkdir(parents=True)
-    (project_root / "src" / folder_name / "tools").mkdir(parents=True)
-    (project_root / "tests").mkdir(exist_ok=True)
-
-    # Create .env file
-    with open(project_root / ".env", "w") as file:
-        file.write("OPENAI_API_KEY=YOUR_API_KEY")
-
-    package_dir = Path(__file__).parent
-    template_folder = "pipeline_router" if router else "pipeline"
-    templates_dir = package_dir / "templates" / template_folder
-
-    # List of template files to copy
-    root_template_files = [".gitignore", "pyproject.toml", "README.md"]
-    src_template_files = ["__init__.py", "main.py"]
-    tools_template_files = ["tools/__init__.py", "tools/custom_tool.py"]
-
-    if router:
-        crew_folders = [
-            "classifier_crew",
-            "normal_crew",
-            "urgent_crew",
-        ]
-        pipelines_folders = [
-            "pipelines/__init__.py",
-            "pipelines/pipeline_classifier.py",
-            "pipelines/pipeline_normal.py",
-            "pipelines/pipeline_urgent.py",
-        ]
-    else:
-        crew_folders = [
-            "research_crew",
-            "write_linkedin_crew",
-            "write_x_crew",
-        ]
-        pipelines_folders = ["pipelines/__init__.py", "pipelines/pipeline.py"]
-
-    def process_file(src_file, dst_file):
-        with open(src_file, "r") as file:
-            content = file.read()
-
-        content = content.replace("{{name}}", name)
-        content = content.replace("{{crew_name}}", class_name)
-        content = content.replace("{{folder_name}}", folder_name)
-        content = content.replace("{{pipeline_name}}", class_name)
-
-        with open(dst_file, "w") as file:
-            file.write(content)
-
-    # Copy and process root template files
-    for file_name in root_template_files:
-        src_file = templates_dir / file_name
-        dst_file = project_root / file_name
-        process_file(src_file, dst_file)
-
-    # Copy and process src template files
-    for file_name in src_template_files:
-        src_file = templates_dir / file_name
-        dst_file = project_root / "src" / folder_name / file_name
-        process_file(src_file, dst_file)
-
-    # Copy tools files
-    for file_name in tools_template_files:
-        src_file = templates_dir / file_name
-        dst_file = project_root / "src" / folder_name / file_name
-        shutil.copy(src_file, dst_file)
-
-    # Copy pipelines folders
-    for file_name in pipelines_folders:
-        src_file = templates_dir / file_name
-        dst_file = project_root / "src" / folder_name / file_name
-        process_file(src_file, dst_file)
-
-    # Copy crew folders
-    for crew_folder in crew_folders:
-        src_crew_folder = templates_dir / "crews" / crew_folder
-        dst_crew_folder = project_root / "src" / folder_name / "crews" / crew_folder
-        if src_crew_folder.exists():
-            shutil.copytree(src_crew_folder, dst_crew_folder)
-        else:
-            click.secho(
-                f"Warning: Crew folder {crew_folder} not found in template.",
-                fg="yellow",
-            )
-
-    click.secho(f"Pipeline {name} created successfully!", fg="green", bold=True)
diff --git a/src/crewai/cli/templates/pipeline/.gitignore b/src/crewai/cli/templates/pipeline/.gitignore
deleted file mode 100644
index d50a09fc9..000000000
--- a/src/crewai/cli/templates/pipeline/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.env
-__pycache__/
diff --git a/src/crewai/cli/templates/pipeline/README.md b/src/crewai/cli/templates/pipeline/README.md
deleted file mode 100644
index 433e43abe..000000000
--- a/src/crewai/cli/templates/pipeline/README.md
+++ /dev/null
@@ -1,57 +0,0 @@
-# {{crew_name}} Crew
-
-Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.com). This template is designed to help you set up a multi-agent AI system with ease, leveraging the powerful and flexible framework provided by crewAI. Our goal is to enable your agents to collaborate effectively on complex tasks, maximizing their collective intelligence and capabilities.
-
-## Installation
-
-Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [Poetry](https://python-poetry.org/) for dependency management and package handling, offering a seamless setup and execution experience.
-
-First, if you haven't already, install Poetry:
-
-```bash
-pip install poetry
-```
-
-Next, navigate to your project directory and install the dependencies:
-
-1. First lock the dependencies and then install them:
-
-```bash
-crewai install
-```
-
-### Customizing
-
-**Add your `OPENAI_API_KEY` into the `.env` file**
-
-- Modify `src/{{folder_name}}/config/agents.yaml` to define your agents
-- Modify `src/{{folder_name}}/config/tasks.yaml` to define your tasks
-- Modify `src/{{folder_name}}/crew.py` to add your own logic, tools and specific args
-- Modify `src/{{folder_name}}/main.py` to add custom inputs for your agents and tasks
-
-## Running the Project
-
-To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:
-
-```bash
-crewai run
-```
-
-This command initializes the {{name}} Crew, assembling the agents and assigning them tasks as defined in your configuration.
-
-This example, unmodified, will run the create a `report.md` file with the output of a research on LLMs in the root folder.
-
-## Understanding Your Crew
-
-The {{name}} Crew is composed of multiple AI agents, each with unique roles, goals, and tools. These agents collaborate on a series of tasks, defined in `config/tasks.yaml`, leveraging their collective skills to achieve complex objectives. The `config/agents.yaml` file outlines the capabilities and configurations of each agent in your crew.
-
-## Support
-
-For support, questions, or feedback regarding the {{crew_name}} Crew or crewAI.
-
-- Visit our [documentation](https://docs.crewai.com)
-- Reach out to us through our [GitHub repository](https://github.com/joaomdmoura/crewai)
-- [Join our Discord](https://discord.com/invite/X4JWnZnxPb)
-- [Chat with our docs](https://chatg.pt/DWjSBZn)
-
-Let's create wonders together with the power and simplicity of crewAI.
diff --git a/src/crewai/cli/templates/pipeline/__init__.py b/src/crewai/cli/templates/pipeline/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline/crews/research_crew/config/agents.yaml b/src/crewai/cli/templates/pipeline/crews/research_crew/config/agents.yaml
deleted file mode 100644
index f8cf1f5c1..000000000
--- a/src/crewai/cli/templates/pipeline/crews/research_crew/config/agents.yaml
+++ /dev/null
@@ -1,19 +0,0 @@
-researcher:
-  role: >
-    {topic} Senior Data Researcher
-  goal: >
-    Uncover cutting-edge developments in {topic}
-  backstory: >
-    You're a seasoned researcher with a knack for uncovering the latest
-    developments in {topic}. Known for your ability to find the most relevant
-    information and present it in a clear and concise manner.
-
-reporting_analyst:
-  role: >
-    {topic} Reporting Analyst
-  goal: >
-    Create detailed reports based on {topic} data analysis and research findings
-  backstory: >
-    You're a meticulous analyst with a keen eye for detail. You're known for
-    your ability to turn complex data into clear and concise reports, making
-    it easy for others to understand and act on the information you provide.
diff --git a/src/crewai/cli/templates/pipeline/crews/research_crew/config/tasks.yaml b/src/crewai/cli/templates/pipeline/crews/research_crew/config/tasks.yaml
deleted file mode 100644
index e78091842..000000000
--- a/src/crewai/cli/templates/pipeline/crews/research_crew/config/tasks.yaml
+++ /dev/null
@@ -1,16 +0,0 @@
-research_task:
-  description: >
-    Conduct a thorough research about {topic}
-    Make sure you find any interesting and relevant information given
-    the current year is 2024.
-  expected_output: >
-    A list with 10 bullet points of the most relevant information about {topic}
-  agent: researcher
-
-reporting_task:
-  description: >
-    Review the context you got and expand each topic into a full section for a report.
-    Make sure the report is detailed and contains any and all relevant information.
-  expected_output: >
-    A fully fledge reports with a title, mains topics, each with a full section of information.
-  agent: reporting_analyst
diff --git a/src/crewai/cli/templates/pipeline/crews/research_crew/research_crew.py b/src/crewai/cli/templates/pipeline/crews/research_crew/research_crew.py
deleted file mode 100644
index f26ad712a..000000000
--- a/src/crewai/cli/templates/pipeline/crews/research_crew/research_crew.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from pydantic import BaseModel
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-
-# Uncomment the following line to use an example of a custom tool
-# from demo_pipeline.tools.custom_tool import MyCustomTool
-
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
-
-
-class ResearchReport(BaseModel):
-	"""Research Report"""
-	title: str
-	body: str
-
-@CrewBase
-class ResearchCrew():
-	"""Research Crew"""
-	agents_config = 'config/agents.yaml'
-	tasks_config = 'config/tasks.yaml'
-
-	@agent
-	def researcher(self) -> Agent:
-		return Agent(
-			config=self.agents_config['researcher'],
-			verbose=True
-		)
-
-	@agent
-	def reporting_analyst(self) -> Agent:
-		return Agent(
-			config=self.agents_config['reporting_analyst'],
-			verbose=True
-		)
-
-	@task
-	def research_task(self) -> Task:
-		return Task(
-			config=self.tasks_config['research_task'],
-		)
-
-	@task
-	def reporting_task(self) -> Task:
-		return Task(
-			config=self.tasks_config['reporting_task'],
-			output_pydantic=ResearchReport
-		)
-
-	@crew
-	def crew(self) -> Crew:
-		"""Creates the Research Crew"""
-		return Crew(
-			agents=self.agents, # Automatically created by the @agent decorator
-			tasks=self.tasks, # Automatically created by the @task decorator
-			process=Process.sequential,
-			verbose=True,
-		)
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/config/agents.yaml b/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/config/agents.yaml
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/config/tasks.yaml b/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/config/tasks.yaml
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/write_linkedin_crew.py b/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/write_linkedin_crew.py
deleted file mode 100644
index 4a40c3fb4..000000000
--- a/src/crewai/cli/templates/pipeline/crews/write_linkedin_crew/write_linkedin_crew.py
+++ /dev/null
@@ -1,51 +0,0 @@
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-
-# Uncomment the following line to use an example of a custom tool
-# from {{folder_name}}.tools.custom_tool import MyCustomTool
-
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
-
-@CrewBase
-class WriteLinkedInCrew():
-	"""Research Crew"""
-	agents_config = 'config/agents.yaml'
-	tasks_config = 'config/tasks.yaml'
-
-	@agent
-	def researcher(self) -> Agent:
-		return Agent(
-			config=self.agents_config['researcher'],
-			verbose=True
-		)
-
-	@agent
-	def reporting_analyst(self) -> Agent:
-		return Agent(
-			config=self.agents_config['reporting_analyst'],
-			verbose=True
-		)
-
-	@task
-	def research_task(self) -> Task:
-		return Task(
-			config=self.tasks_config['research_task'],
-		)
-
-	@task
-	def reporting_task(self) -> Task:
-		return Task(
-			config=self.tasks_config['reporting_task'],
-			output_file='report.md'
-		)
-
-	@crew
-	def crew(self) -> Crew:
-		"""Creates the {{crew_name}} crew"""
-		return Crew(
-			agents=self.agents, # Automatically created by the @agent decorator
-			tasks=self.tasks, # Automatically created by the @task decorator
-			process=Process.sequential,
-			verbose=True,
-		)
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline/crews/write_x_crew/config/agents.yaml b/src/crewai/cli/templates/pipeline/crews/write_x_crew/config/agents.yaml
deleted file mode 100644
index 1401dcbe0..000000000
--- a/src/crewai/cli/templates/pipeline/crews/write_x_crew/config/agents.yaml
+++ /dev/null
@@ -1,14 +0,0 @@
-x_writer_agent:
-  role: >
-    Expert Social Media Content Creator specializing in short form written content
-  goal: >
-    Create viral-worthy, engaging short form posts that distill complex {topic} information
-    into compelling 280-character messages
-  backstory: >
-    You're a social media virtuoso with a particular talent for short form content. Your posts
-    consistently go viral due to your ability to craft hooks that stop users mid-scroll.
-    You've studied the techniques of social media masters like Justin Welsh, Dickie Bush,
-    Nicolas Cole, and Shaan Puri, incorporating their best practices into your own unique style.
-    Your superpower is taking intricate {topic} concepts and transforming them into
-    bite-sized, shareable content that resonates with a wide audience. You know exactly
-    how to structure a post for maximum impact and engagement.
diff --git a/src/crewai/cli/templates/pipeline/crews/write_x_crew/config/tasks.yaml b/src/crewai/cli/templates/pipeline/crews/write_x_crew/config/tasks.yaml
deleted file mode 100644
index 1ffbc207a..000000000
--- a/src/crewai/cli/templates/pipeline/crews/write_x_crew/config/tasks.yaml
+++ /dev/null
@@ -1,22 +0,0 @@
-write_x_task:
-  description: >
-    Using the research report provided, create an engaging short form post about {topic}.
-    Your post should have a great hook, summarize key points, and be structured for easy
-    consumption on a digital platform. The post must be under 280 characters.
-    Follow these guidelines:
-    1. Start with an attention-grabbing hook
-    2. Condense the main insights from the research
-    3. Use clear, concise language
-    4. Include a call-to-action or thought-provoking question if space allows
-    5. Ensure the post flows well and is easy to read quickly
-
-    Here is the title of the research report you will be using
-
-    Title: {title}
-    Research: 
-    {body}
-
-  expected_output: >
-    A compelling X post under 280 characters that effectively summarizes the key findings
-    about {topic}, starts with a strong hook, and is optimized for engagement on the platform.
-  agent: x_writer_agent
diff --git a/src/crewai/cli/templates/pipeline/crews/write_x_crew/write_x_crew.py b/src/crewai/cli/templates/pipeline/crews/write_x_crew/write_x_crew.py
deleted file mode 100644
index 454aafdc0..000000000
--- a/src/crewai/cli/templates/pipeline/crews/write_x_crew/write_x_crew.py
+++ /dev/null
@@ -1,36 +0,0 @@
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-
-# Uncomment the following line to use an example of a custom tool
-# from demo_pipeline.tools.custom_tool import MyCustomTool
-
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
-
-
-@CrewBase
-class WriteXCrew:
-    """Research Crew"""
-
-    agents_config = "config/agents.yaml"
-    tasks_config = "config/tasks.yaml"
-
-    @agent
-    def x_writer_agent(self) -> Agent:
-        return Agent(config=self.agents_config["x_writer_agent"], verbose=True)
-
-    @task
-    def write_x_task(self) -> Task:
-        return Task(
-            config=self.tasks_config["write_x_task"],
-        )
-
-    @crew
-    def crew(self) -> Crew:
-        """Creates the Write X Crew"""
-        return Crew(
-            agents=self.agents,  # Automatically created by the @agent decorator
-            tasks=self.tasks,  # Automatically created by the @task decorator
-            process=Process.sequential,
-            verbose=True,
-        )
diff --git a/src/crewai/cli/templates/pipeline/main.py b/src/crewai/cli/templates/pipeline/main.py
deleted file mode 100644
index 376693330..000000000
--- a/src/crewai/cli/templates/pipeline/main.py
+++ /dev/null
@@ -1,26 +0,0 @@
-#!/usr/bin/env python
-import asyncio
-from {{folder_name}}.pipelines.pipeline import {{pipeline_name}}Pipeline
-
-async def run():
-    """
-    Run the pipeline.
-    """
-    inputs = [
-        {"topic": "AI wearables"},
-    ]
-    pipeline = {{pipeline_name}}Pipeline()
-    results = await pipeline.kickoff(inputs)
-    
-    # Process and print results
-    for result in results:
-        print(f"Raw output: {result.raw}")
-        if result.json_dict:
-            print(f"JSON output: {result.json_dict}")
-        print("\n")
-
-def main():
-    asyncio.run(run())
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline/pipelines/__init__.py b/src/crewai/cli/templates/pipeline/pipelines/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline/pipelines/pipeline.py b/src/crewai/cli/templates/pipeline/pipelines/pipeline.py
deleted file mode 100644
index 8ca8dfa44..000000000
--- a/src/crewai/cli/templates/pipeline/pipelines/pipeline.py
+++ /dev/null
@@ -1,87 +0,0 @@
-"""
-This pipeline file includes two different examples to demonstrate the flexibility of crewAI pipelines.
-
-Example 1: Two-Stage Pipeline
------------------------------
-This pipeline consists of two crews:
-1. ResearchCrew: Performs research on a given topic.
-2. WriteXCrew: Generates an X (Twitter) post based on the research findings.
-
-Key features:
-- The ResearchCrew's final task uses output_json to store all research findings in a JSON object.
-- This JSON object is then passed to the WriteXCrew, where tasks can access the research findings.
-
-Example 2: Two-Stage Pipeline with Parallel Execution
--------------------------------------------------------
-This pipeline consists of three crews:
-1. ResearchCrew: Performs research on a given topic.
-2. WriteXCrew and WriteLinkedInCrew: Run in parallel, using the research findings to generate posts for X and LinkedIn, respectively.
-
-Key features:
-- Demonstrates the ability to run multiple crews in parallel.
-- Shows how to structure a pipeline with both sequential and parallel stages.
-
-Usage:
-- To switch between examples, comment/uncomment the respective code blocks below.
-- Ensure that you have implemented all necessary crew classes (ResearchCrew, WriteXCrew, WriteLinkedInCrew) before running.
-"""
-
-# Common imports for both examples
-from crewai import Pipeline
-
-
-
-# Uncomment the crews you need for your chosen example
-from ..crews.research_crew.research_crew import ResearchCrew
-from ..crews.write_x_crew.write_x_crew import WriteXCrew
-# from .crews.write_linkedin_crew.write_linkedin_crew import WriteLinkedInCrew  # Uncomment for Example 2
-
-# EXAMPLE 1: Two-Stage Pipeline
-# -----------------------------
-# Uncomment the following code block to use Example 1
-
-class {{pipeline_name}}Pipeline:
-    def __init__(self):
-        # Initialize crews
-        self.research_crew = ResearchCrew().crew()
-        self.write_x_crew = WriteXCrew().crew()
-    
-    def create_pipeline(self):
-        return Pipeline(
-            stages=[
-                self.research_crew,
-                self.write_x_crew
-            ]
-        )
-    
-    async def kickoff(self, inputs):
-        pipeline = self.create_pipeline()
-        results = await pipeline.kickoff(inputs)
-        return results
-
-
-# EXAMPLE 2: Two-Stage Pipeline with Parallel Execution
-# -------------------------------------------------------
-# Uncomment the following code block to use Example 2
-
-# @PipelineBase
-# class {{pipeline_name}}Pipeline:
-#     def __init__(self):
-#         # Initialize crews
-#         self.research_crew = ResearchCrew().crew()
-#         self.write_x_crew = WriteXCrew().crew()
-#         self.write_linkedin_crew = WriteLinkedInCrew().crew()
-    
-#     @pipeline
-#     def create_pipeline(self):
-#         return Pipeline(
-#             stages=[
-#                 self.research_crew,
-#                 [self.write_x_crew, self.write_linkedin_crew]  # Parallel execution
-#             ]
-#         )
-
-#     async def run(self, inputs):
-#         pipeline = self.create_pipeline()
-#         results = await pipeline.kickoff(inputs)
-#         return results
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
deleted file mode 100644
index 1e7f4efd5..000000000
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ /dev/null
@@ -1,17 +0,0 @@
-[tool.poetry]
-name = "{{folder_name}}"
-version = "0.1.0"
-description = "{{name}} using crewAI"
-authors = ["Your Name <you@example.com>"]
-
-[tool.poetry.dependencies]
-python = ">=3.10,<=3.13"
-crewai = { extras = ["tools"], version = ">=0.85.0,<1.0.0" }
-asyncio = "*"
-
-[tool.poetry.scripts]
-{{folder_name}} = "{{folder_name}}.main:main"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline/tools/__init__.py b/src/crewai/cli/templates/pipeline/tools/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline/tools/custom_tool.py b/src/crewai/cli/templates/pipeline/tools/custom_tool.py
deleted file mode 100644
index fbd53cf02..000000000
--- a/src/crewai/cli/templates/pipeline/tools/custom_tool.py
+++ /dev/null
@@ -1,19 +0,0 @@
-from typing import Type
-from crewai.tools import BaseTool
-from pydantic import BaseModel, Field
-
-
-class MyCustomToolInput(BaseModel):
-    """Input schema for MyCustomTool."""
-    argument: str = Field(..., description="Description of the argument.")
-
-class MyCustomTool(BaseTool):
-    name: str = "Name of my tool"
-    description: str = (
-        "Clear description for what this tool is useful for, you agent will need this information to use it."
-    )
-    args_schema: Type[BaseModel] = MyCustomToolInput
-
-    def _run(self, argument: str) -> str:
-        # Implementation goes here
-        return "this is an example of a tool output, ignore it and move along."
diff --git a/src/crewai/cli/templates/pipeline_router/.gitignore b/src/crewai/cli/templates/pipeline_router/.gitignore
deleted file mode 100644
index d50a09fc9..000000000
--- a/src/crewai/cli/templates/pipeline_router/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.env
-__pycache__/
diff --git a/src/crewai/cli/templates/pipeline_router/README.md b/src/crewai/cli/templates/pipeline_router/README.md
deleted file mode 100644
index d710c341a..000000000
--- a/src/crewai/cli/templates/pipeline_router/README.md
+++ /dev/null
@@ -1,54 +0,0 @@
-# {{crew_name}} Crew
-
-Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.com). This template is designed to help you set up a multi-agent AI system with ease, leveraging the powerful and flexible framework provided by crewAI. Our goal is to enable your agents to collaborate effectively on complex tasks, maximizing their collective intelligence and capabilities.
-
-## Installation
-
-Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [Poetry](https://python-poetry.org/) for dependency management and package handling, offering a seamless setup and execution experience.
-
-First, if you haven't already, install Poetry:
-
-```bash
-pip install poetry
-```
-
-Next, navigate to your project directory and install the dependencies:
-
-1. First lock the dependencies and then install them:
-```bash
-crewai install
-```
-### Customizing
-
-**Add your `OPENAI_API_KEY` into the `.env` file**
-
-- Modify `src/{{folder_name}}/config/agents.yaml` to define your agents
-- Modify `src/{{folder_name}}/config/tasks.yaml` to define your tasks
-- Modify `src/{{folder_name}}/crew.py` to add your own logic, tools and specific args
-- Modify `src/{{folder_name}}/main.py` to add custom inputs for your agents and tasks
-
-## Running the Project
-
-To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:
-
-```bash
-crewai run
-```
-
-This command initializes the {{name}} Crew, assembling the agents and assigning them tasks as defined in your configuration.
-
-This example, unmodified, will run the create a `report.md` file with the output of a research on LLMs in the root folder.
-
-## Understanding Your Crew
-
-The {{name}} Crew is composed of multiple AI agents, each with unique roles, goals, and tools. These agents collaborate on a series of tasks, defined in `config/tasks.yaml`, leveraging their collective skills to achieve complex objectives. The `config/agents.yaml` file outlines the capabilities and configurations of each agent in your crew.
-
-## Support
-
-For support, questions, or feedback regarding the {{crew_name}} Crew or crewAI.
-- Visit our [documentation](https://docs.crewai.com)
-- Reach out to us through our [GitHub repository](https://github.com/joaomdmoura/crewai)
-- [Join our Discord](https://discord.com/invite/X4JWnZnxPb)
-- [Chat with our docs](https://chatg.pt/DWjSBZn)
-
-Let's create wonders together with the power and simplicity of crewAI.
diff --git a/src/crewai/cli/templates/pipeline_router/__init__.py b/src/crewai/cli/templates/pipeline_router/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline_router/config/agents.yaml b/src/crewai/cli/templates/pipeline_router/config/agents.yaml
deleted file mode 100644
index 72ed6939e..000000000
--- a/src/crewai/cli/templates/pipeline_router/config/agents.yaml
+++ /dev/null
@@ -1,19 +0,0 @@
-researcher:
-  role: >
-    {topic} Senior Data Researcher
-  goal: >
-    Uncover cutting-edge developments in {topic}
-  backstory: >
-    You're a seasoned researcher with a knack for uncovering the latest
-    developments in {topic}. Known for your ability to find the most relevant
-    information and present it in a clear and concise manner.
-
-reporting_analyst:
-  role: >
-    {topic} Reporting Analyst
-  goal: >
-    Create detailed reports based on {topic} data analysis and research findings
-  backstory: >
-    You're a meticulous analyst with a keen eye for detail. You're known for
-    your ability to turn complex data into clear and concise reports, making
-    it easy for others to understand and act on the information you provide.
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline_router/config/tasks.yaml b/src/crewai/cli/templates/pipeline_router/config/tasks.yaml
deleted file mode 100644
index f30820855..000000000
--- a/src/crewai/cli/templates/pipeline_router/config/tasks.yaml
+++ /dev/null
@@ -1,17 +0,0 @@
-research_task:
-  description: >
-    Conduct a thorough research about {topic}
-    Make sure you find any interesting and relevant information given
-    the current year is 2024.
-  expected_output: >
-    A list with 10 bullet points of the most relevant information about {topic}
-  agent: researcher
-
-reporting_task:
-  description: >
-    Review the context you got and expand each topic into a full section for a report.
-    Make sure the report is detailed and contains any and all relevant information.
-  expected_output: >
-    A fully fledge reports with the mains topics, each with a full section of information.
-    Formatted as markdown without '```'
-  agent: reporting_analyst
diff --git a/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/classifier_crew.py b/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/classifier_crew.py
deleted file mode 100644
index af6be20ab..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/classifier_crew.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-from pydantic import BaseModel
-
-# Uncomment the following line to use an example of a custom tool
-# from demo_pipeline.tools.custom_tool import MyCustomTool
-
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
-
-class UrgencyScore(BaseModel):
-    urgency_score: int
-
-@CrewBase
-class ClassifierCrew:
-    """Email Classifier Crew"""
-
-    agents_config = "config/agents.yaml"
-    tasks_config = "config/tasks.yaml"
-
-    @agent
-    def classifier(self) -> Agent:
-        return Agent(config=self.agents_config["classifier"], verbose=True)
-
-    @task
-    def urgent_task(self) -> Task:
-        return Task(
-            config=self.tasks_config["classify_email"],
-            output_pydantic=UrgencyScore,
-        )
-
-    @crew
-    def crew(self) -> Crew:
-        """Creates the Email Classifier Crew"""
-        return Crew(
-            agents=self.agents,  # Automatically created by the @agent decorator
-            tasks=self.tasks,  # Automatically created by the @task decorator
-            process=Process.sequential,
-            verbose=True,
-        )
diff --git a/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/agents.yaml b/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/agents.yaml
deleted file mode 100644
index 45506d038..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/agents.yaml
+++ /dev/null
@@ -1,7 +0,0 @@
-classifier:
-  role: >
-    Email Classifier
-  goal: >
-    Classify the email: {email} as urgent or normal from a score of 1 to 10, where 1 is not urgent and 10 is urgent. Return the urgency score only.`
-  backstory: >
-    You are a highly efficient and experienced email classifier, trained to quickly assess and classify emails. Your ability to remain calm under pressure and provide concise, actionable responses has made you an invaluable asset in managing normal situations and maintaining smooth operations.
diff --git a/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/tasks.yaml b/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/tasks.yaml
deleted file mode 100644
index cd843fd1a..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/classifier_crew/config/tasks.yaml
+++ /dev/null
@@ -1,7 +0,0 @@
-classify_email:
-  description: >
-    Classify the email: {email}
-    as urgent or normal.
-  expected_output: >
-    Classify the email from a scale of 1 to 10, where 1 is not urgent and 10 is urgent. Return the urgency score only.
-  agent: classifier
diff --git a/src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/agents.yaml b/src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/agents.yaml
deleted file mode 100644
index c847ce8f5..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/agents.yaml
+++ /dev/null
@@ -1,7 +0,0 @@
-normal_handler:
-  role: >
-    Normal Email Processor
-  goal: >
-    Process normal emails and create an email to respond to the sender.
-  backstory: >
-    You are a highly efficient and experienced normal email handler, trained to quickly assess and respond to normal communications. Your ability to remain calm under pressure and provide concise, actionable responses has made you an invaluable asset in managing normal situations and maintaining smooth operations.
diff --git a/src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/tasks.yaml b/src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/tasks.yaml
deleted file mode 100644
index 341303e90..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/normal_crew/config/tasks.yaml
+++ /dev/null
@@ -1,6 +0,0 @@
-normal_task:
-  description: >
-    Process and respond to normal email quickly.
-  expected_output: >
-    An email response to the normal email.
-  agent: normal_handler
diff --git a/src/crewai/cli/templates/pipeline_router/crews/normal_crew/normal_crew.py b/src/crewai/cli/templates/pipeline_router/crews/normal_crew/normal_crew.py
deleted file mode 100644
index c240acfd1..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/normal_crew/normal_crew.py
+++ /dev/null
@@ -1,36 +0,0 @@
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-
-# Uncomment the following line to use an example of a custom tool
-# from demo_pipeline.tools.custom_tool import MyCustomTool
-
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
-
-
-@CrewBase
-class NormalCrew:
-    """Normal Email Crew"""
-
-    agents_config = "config/agents.yaml"
-    tasks_config = "config/tasks.yaml"
-
-    @agent
-    def normal_handler(self) -> Agent:
-        return Agent(config=self.agents_config["normal_handler"], verbose=True)
-
-    @task
-    def urgent_task(self) -> Task:
-        return Task(
-            config=self.tasks_config["normal_task"],
-        )
-
-    @crew
-    def crew(self) -> Crew:
-        """Creates the Normal Email Crew"""
-        return Crew(
-            agents=self.agents,  # Automatically created by the @agent decorator
-            tasks=self.tasks,  # Automatically created by the @task decorator
-            process=Process.sequential,
-            verbose=True,
-        )
diff --git a/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/agents.yaml b/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/agents.yaml
deleted file mode 100644
index 52804a9c1..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/agents.yaml
+++ /dev/null
@@ -1,7 +0,0 @@
-urgent_handler:
-  role: >
-    Urgent Email Processor
-  goal: >
-    Process urgent emails and create an email to respond to the sender.
-  backstory: >
-    You are a highly efficient and experienced urgent email handler, trained to quickly assess and respond to time-sensitive communications. Your ability to remain calm under pressure and provide concise, actionable responses has made you an invaluable asset in managing critical situations and maintaining smooth operations.
diff --git a/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/tasks.yaml b/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/tasks.yaml
deleted file mode 100644
index dc2ee1c2a..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/config/tasks.yaml
+++ /dev/null
@@ -1,6 +0,0 @@
-urgent_task:
-  description: >
-    Process and respond to urgent email quickly.
-  expected_output: >
-    An email response to the urgent email.
-  agent: urgent_handler
diff --git a/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/urgent_crew.py b/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/urgent_crew.py
deleted file mode 100644
index 54c804c79..000000000
--- a/src/crewai/cli/templates/pipeline_router/crews/urgent_crew/urgent_crew.py
+++ /dev/null
@@ -1,36 +0,0 @@
-from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task
-
-# Uncomment the following line to use an example of a custom tool
-# from demo_pipeline.tools.custom_tool import MyCustomTool
-
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
-
-
-@CrewBase
-class UrgentCrew:
-    """Urgent Email Crew"""
-
-    agents_config = "config/agents.yaml"
-    tasks_config = "config/tasks.yaml"
-
-    @agent
-    def urgent_handler(self) -> Agent:
-        return Agent(config=self.agents_config["urgent_handler"], verbose=True)
-
-    @task
-    def urgent_task(self) -> Task:
-        return Task(
-            config=self.tasks_config["urgent_task"],
-        )
-
-    @crew
-    def crew(self) -> Crew:
-        """Creates the Urgent Email Crew"""
-        return Crew(
-            agents=self.agents,  # Automatically created by the @agent decorator
-            tasks=self.tasks,  # Automatically created by the @task decorator
-            process=Process.sequential,
-            verbose=True,
-        )
diff --git a/src/crewai/cli/templates/pipeline_router/main.py b/src/crewai/cli/templates/pipeline_router/main.py
deleted file mode 100644
index 5d1cdc370..000000000
--- a/src/crewai/cli/templates/pipeline_router/main.py
+++ /dev/null
@@ -1,75 +0,0 @@
-#!/usr/bin/env python
-import asyncio
-from crewai.routers.router import Route
-from crewai.routers.router import Router
-
-from {{folder_name}}.pipelines.pipeline_classifier import EmailClassifierPipeline
-from {{folder_name}}.pipelines.pipeline_normal import NormalPipeline
-from {{folder_name}}.pipelines.pipeline_urgent import UrgentPipeline
-
-async def run():
-    """
-    Run the pipeline.
-    """
-    inputs = [
-       {
-        "email": """
-            Subject: URGENT: Marketing Campaign Launch - Immediate Action Required
-            Dear Team,
-            I'm reaching out regarding our upcoming marketing campaign that requires your immediate attention and swift action. We're facing a critical deadline, and our success hinges on our ability to mobilize quickly.
-            Key points:
-            
-            Campaign launch: 48 hours from now
-            Target audience: 250,000 potential customers
-            Expected ROI: 35% increase in Q3 sales
-            
-            What we need from you NOW:
-            
-            Final approval on creative assets (due in 3 hours)
-            Confirmation of media placements (due by end of day)
-            Last-minute budget allocation for paid social media push
-            
-            Our competitors are poised to launch similar campaigns, and we must act fast to maintain our market advantage. Delays could result in significant lost opportunities and potential revenue.
-            Please prioritize this campaign above all other tasks. I'll be available for the next 24 hours to address any concerns or roadblocks.
-            Let's make this happen!
-            [Your Name]
-            Marketing Director
-            P.S. I'll be scheduling an emergency team meeting in 1 hour to discuss our action plan. Attendance is mandatory.
-        """
-       }
-    ]
-
-    pipeline_classifier = EmailClassifierPipeline().create_pipeline()
-    pipeline_urgent = UrgentPipeline().create_pipeline()
-    pipeline_normal = NormalPipeline().create_pipeline()
-
-    router = Router(
-        routes={
-            "high_urgency": Route(
-                condition=lambda x: x.get("urgency_score", 0) > 7,
-                pipeline=pipeline_urgent
-            ),
-            "low_urgency": Route(
-                condition=lambda x: x.get("urgency_score", 0) <= 7,
-                pipeline=pipeline_normal
-            )
-        },
-        default=pipeline_normal
-    )
-
-    pipeline = pipeline_classifier >> router
-
-    results = await pipeline.kickoff(inputs)
-
-    # Process and print results
-    for result in results:
-        print(f"Raw output: {result.raw}")
-        if result.json_dict:
-            print(f"JSON output: {result.json_dict}")
-        print("\n")
-
-def main():
-    asyncio.run(run())
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/src/crewai/cli/templates/pipeline_router/pipelines/__init__.py b/src/crewai/cli/templates/pipeline_router/pipelines/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_classifier.py b/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_classifier.py
deleted file mode 100644
index 5047d1602..000000000
--- a/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_classifier.py
+++ /dev/null
@@ -1,24 +0,0 @@
-from crewai import Pipeline
-from crewai.project import PipelineBase
-from ..crews.classifier_crew.classifier_crew import ClassifierCrew
-
-
-@PipelineBase
-class EmailClassifierPipeline:
-    def __init__(self):
-        # Initialize crews
-        self.classifier_crew = ClassifierCrew().crew()
-
-    def create_pipeline(self):
-        return Pipeline(
-            stages=[
-                self.classifier_crew
-            ]
-        )
-    
-    async def kickoff(self, inputs):
-        pipeline = self.create_pipeline()
-        results = await pipeline.kickoff(inputs)
-        return results
-
-
diff --git a/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_normal.py b/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_normal.py
deleted file mode 100644
index 936af4176..000000000
--- a/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_normal.py
+++ /dev/null
@@ -1,24 +0,0 @@
-from crewai import Pipeline
-from crewai.project import PipelineBase
-from ..crews.normal_crew.normal_crew import NormalCrew
-
-
-@PipelineBase
-class NormalPipeline:
-    def __init__(self):
-        # Initialize crews
-        self.normal_crew = NormalCrew().crew()
-
-    def create_pipeline(self):
-        return Pipeline(
-            stages=[
-                self.normal_crew
-            ]
-        )
-    
-    async def kickoff(self, inputs):
-        pipeline = self.create_pipeline()
-        results = await pipeline.kickoff(inputs)
-        return results
-
-
diff --git a/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_urgent.py b/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_urgent.py
deleted file mode 100644
index 07297bf75..000000000
--- a/src/crewai/cli/templates/pipeline_router/pipelines/pipeline_urgent.py
+++ /dev/null
@@ -1,23 +0,0 @@
-from crewai import Pipeline
-from crewai.project import PipelineBase
-from ..crews.urgent_crew.urgent_crew import UrgentCrew
-
-@PipelineBase
-class UrgentPipeline:
-    def __init__(self):
-        # Initialize crews
-        self.urgent_crew = UrgentCrew().crew()
-    
-    def create_pipeline(self):
-        return Pipeline(
-            stages=[
-                self.urgent_crew
-            ]
-        )
-    
-    async def kickoff(self, inputs):
-        pipeline = self.create_pipeline()
-        results = await pipeline.kickoff(inputs)
-        return results
-
-
diff --git a/src/crewai/cli/templates/pipeline_router/pyproject.toml b/src/crewai/cli/templates/pipeline_router/pyproject.toml
deleted file mode 100644
index 49208d120..000000000
--- a/src/crewai/cli/templates/pipeline_router/pyproject.toml
+++ /dev/null
@@ -1,21 +0,0 @@
-[project]
-name = "{{folder_name}}"
-version = "0.1.0"
-description = "{{name}} using crewAI"
-authors = ["Your Name <you@example.com>"]
-requires-python = ">=3.10,<=3.13"
-dependencies = [
-    "crewai[tools]>=0.85.0,<1.0.0"
-]
-
-[project.scripts]
-{{folder_name}} = "{{folder_name}}.main:main"
-run_crew = "{{folder_name}}.main:main"
-train = "{{folder_name}}.main:train"
-replay = "{{folder_name}}.main:replay"
-test = "{{folder_name}}.main:test"
-
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
diff --git a/src/crewai/cli/templates/pipeline_router/tools/__init__.py b/src/crewai/cli/templates/pipeline_router/tools/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py b/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
deleted file mode 100644
index fbd53cf02..000000000
--- a/src/crewai/cli/templates/pipeline_router/tools/custom_tool.py
+++ /dev/null
@@ -1,19 +0,0 @@
-from typing import Type
-from crewai.tools import BaseTool
-from pydantic import BaseModel, Field
-
-
-class MyCustomToolInput(BaseModel):
-    """Input schema for MyCustomTool."""
-    argument: str = Field(..., description="Description of the argument.")
-
-class MyCustomTool(BaseTool):
-    name: str = "Name of my tool"
-    description: str = (
-        "Clear description for what this tool is useful for, you agent will need this information to use it."
-    )
-    args_schema: Type[BaseModel] = MyCustomToolInput
-
-    def _run(self, argument: str) -> str:
-        # Implementation goes here
-        return "this is an example of a tool output, ignore it and move along."
diff --git a/src/crewai/crew.py b/src/crewai/crew.py
index 3b6ee44b4..943320ceb 100644
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -5,7 +5,7 @@ import uuid
 import warnings
 from concurrent.futures import Future
 from hashlib import md5
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 from pydantic import (
     UUID4,
@@ -23,12 +23,12 @@ from crewai.agent import Agent
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.cache import CacheHandler
 from crewai.crews.crew_output import CrewOutput
+from crewai.knowledge.knowledge import Knowledge
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.llm import LLM
 from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
-from crewai.knowledge.knowledge import Knowledge
-from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.memory.user.user_memory import UserMemory
 from crewai.process import Process
 from crewai.task import Task
@@ -56,8 +56,6 @@ if os.environ.get("AGENTOPS_API_KEY"):
     except ImportError:
         pass
 
-if TYPE_CHECKING:
-    from crewai.pipeline.pipeline import Pipeline
 
 warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
 
@@ -1073,17 +1071,5 @@ class Crew(BaseModel):
 
         evaluator.print_crew_evaluation_result()
 
-    def __rshift__(self, other: "Crew") -> "Pipeline":
-        """
-        Implements the >> operator to add another Crew to an existing Pipeline.
-        """
-        from crewai.pipeline.pipeline import Pipeline
-
-        if not isinstance(other, Crew):
-            raise TypeError(
-                f"Unsupported operand type for >>: '{type(self).__name__}' and '{type(other).__name__}'"
-            )
-        return Pipeline(stages=[self, other])
-
     def __repr__(self):
         return f"Crew(id={self.id}, process={self.process}, number_of_agents={len(self.agents)}, number_of_tasks={len(self.tasks)})"
diff --git a/src/crewai/pipeline/__init__.py b/src/crewai/pipeline/__init__.py
deleted file mode 100644
index d9821e34c..000000000
--- a/src/crewai/pipeline/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from crewai.pipeline.pipeline import Pipeline
-from crewai.pipeline.pipeline_kickoff_result import PipelineKickoffResult
-from crewai.pipeline.pipeline_output import PipelineOutput
-
-__all__ = ["Pipeline", "PipelineKickoffResult", "PipelineOutput"]
diff --git a/src/crewai/pipeline/pipeline.py b/src/crewai/pipeline/pipeline.py
deleted file mode 100644
index e65529092..000000000
--- a/src/crewai/pipeline/pipeline.py
+++ /dev/null
@@ -1,405 +0,0 @@
-import asyncio
-import copy
-from typing import Any, Dict, List, Tuple, Union
-
-from pydantic import BaseModel, Field, model_validator
-
-from crewai.crew import Crew
-from crewai.crews.crew_output import CrewOutput
-from crewai.pipeline.pipeline_kickoff_result import PipelineKickoffResult
-from crewai.routers.router import Router
-from crewai.types.usage_metrics import UsageMetrics
-
-Trace = Union[Union[str, Dict[str, Any]], List[Union[str, Dict[str, Any]]]]
-PipelineStage = Union[Crew, List[Crew], Router]
-
-"""
-Developer Notes:
-
-This module defines a Pipeline class that represents a sequence of operations (stages)
-to process inputs. Each stage can be either sequential or parallel, and the pipeline
-can process multiple kickoffs concurrently.
-
-Core Loop Explanation:
-1. The `process_kickoffs` method processes multiple kickoffs in parallel, each going through
-   all pipeline stages.
-2. The `process_single_kickoff` method handles the processing of a single kickouff through
-   all stages, updating metrics and input data along the way.
-3. The `_process_stage` method determines whether a stage is sequential or parallel
-   and processes it accordingly.
-4. The `_process_single_crew` and `_process_parallel_crews` methods handle the
-   execution of single and parallel crew stages.
-5. The `_update_metrics_and_input` method updates usage metrics and the current input
-   with the outputs from a stage.
-6. The `_build_pipeline_kickoff_results` method constructs the final results of the
-   pipeline kickoff, including traces and outputs.
-
-Handling Traces and Crew Outputs:
-- During the processing of stages, we handle the results (traces and crew outputs)
-  for all stages except the last one differently from the final stage.
-- For intermediate stages, the primary focus is on passing the input data between stages.
-  This involves merging the output dictionaries from all crews in a stage into a single
-  dictionary and passing it to the next stage. This merged dictionary allows for smooth
-  data flow between stages.
-- For the final stage, in addition to passing the input data, we also need to prepare
-  the final outputs and traces to be returned as the overall result of the pipeline kickoff.
-  In this case, we do not merge the results, as each result needs to be included
-  separately in its own pipeline kickoff result.
-
-Pipeline Terminology:
-- Pipeline: The overall structure that defines a sequence of operations.
-- Stage: A distinct part of the pipeline, which can be either sequential or parallel.
-- Kickoff: A specific execution of the pipeline for a given set of inputs, representing a single instance of processing through the pipeline.
-- Branch: Parallel executions within a stage (e.g., concurrent crew operations).
-- Trace: The journey of an individual input through the entire pipeline.
-
-Example pipeline structure:
-crew1 >> crew2 >> crew3 
-
-This represents a pipeline with three sequential stages:
-1. crew1 is the first stage, which processes the input and passes its output to crew2.
-2. crew2 is the second stage, which takes the output from crew1 as its input, processes it, and passes its output to crew3.
-3. crew3 is the final stage, which takes the output from crew2 as its input and produces the final output of the pipeline.
-
-Each input creates its own kickoff, flowing through all stages of the pipeline.
-Multiple kickoffss can be processed concurrently, each following the defined pipeline structure.
-
-Another example pipeline structure:
-crew1 >> [crew2, crew3] >> crew4
-
-This represents a pipeline with three stages:
-1. A sequential stage (crew1)
-2. A parallel stage with two branches (crew2 and crew3 executing concurrently)
-3. Another sequential stage (crew4)
-
-Each input creates its own kickoff, flowing through all stages of the pipeline.
-Multiple kickoffs can be processed concurrently, each following the defined pipeline structure.
-"""
-
-
-class Pipeline(BaseModel):
-    stages: List[PipelineStage] = Field(
-        ..., description="List of crews representing stages to be executed in sequence"
-    )
-
-    @model_validator(mode="before")
-    @classmethod
-    def validate_stages(cls, values):
-        stages = values.get("stages", [])
-
-        def check_nesting_and_type(item, depth=0):
-            if depth > 1:
-                raise ValueError("Double nesting is not allowed in pipeline stages")
-            if isinstance(item, list):
-                for sub_item in item:
-                    check_nesting_and_type(sub_item, depth + 1)
-            elif not isinstance(item, (Crew, Router)):
-                raise ValueError(
-                    f"Expected Crew instance, Router instance, or list of Crews, got {type(item)}"
-                )
-
-        for stage in stages:
-            check_nesting_and_type(stage)
-        return values
-
-    async def kickoff(
-        self, inputs: List[Dict[str, Any]]
-    ) -> List[PipelineKickoffResult]:
-        """
-        Processes multiple runs in parallel, each going through all pipeline stages.
-
-        Args:
-            inputs (List[Dict[str, Any]]): List of inputs for each run.
-
-        Returns:
-            List[PipelineKickoffResult]: List of results from each run.
-        """
-        pipeline_results: List[PipelineKickoffResult] = []
-
-        # Process all runs in parallel
-        all_run_results = await asyncio.gather(
-            *(self.process_single_kickoff(input_data) for input_data in inputs)
-        )
-
-        # Flatten the list of lists into a single list of results
-        pipeline_results.extend(
-            result for run_result in all_run_results for result in run_result
-        )
-
-        return pipeline_results
-
-    async def process_single_kickoff(
-        self, kickoff_input: Dict[str, Any]
-    ) -> List[PipelineKickoffResult]:
-        """
-        Processes a single run through all pipeline stages.
-
-        Args:
-            input (Dict[str, Any]): The input for the run.
-
-        Returns:
-            List[PipelineKickoffResult]: The results of processing the run.
-        """
-        initial_input = copy.deepcopy(kickoff_input)
-        current_input = copy.deepcopy(kickoff_input)
-        stages = self._copy_stages()
-        pipeline_usage_metrics: Dict[str, UsageMetrics] = {}
-        all_stage_outputs: List[List[CrewOutput]] = []
-        traces: List[List[Union[str, Dict[str, Any]]]] = [[initial_input]]
-
-        stage_index = 0
-        while stage_index < len(stages):
-            stage = stages[stage_index]
-            stage_input = copy.deepcopy(current_input)
-
-            if isinstance(stage, Router):
-                next_pipeline, route_taken = stage.route(stage_input)
-                stages = (
-                    stages[: stage_index + 1]
-                    + list(next_pipeline.stages)
-                    + stages[stage_index + 1 :]
-                )
-                traces.append([{"route_taken": route_taken}])
-                stage_index += 1
-                continue
-
-            stage_outputs, stage_trace = await self._process_stage(stage, stage_input)
-
-            self._update_metrics_and_input(
-                pipeline_usage_metrics, current_input, stage, stage_outputs
-            )
-            traces.append(stage_trace)
-            all_stage_outputs.append(stage_outputs)
-            stage_index += 1
-
-        return self._build_pipeline_kickoff_results(
-            all_stage_outputs, traces, pipeline_usage_metrics
-        )
-
-    async def _process_stage(
-        self, stage: PipelineStage, current_input: Dict[str, Any]
-    ) -> Tuple[List[CrewOutput], List[Union[str, Dict[str, Any]]]]:
-        """
-        Processes a single stage of the pipeline, which can be either sequential or parallel.
-
-        Args:
-            stage (Union[Crew, List[Crew]]): The stage to process.
-            current_input (Dict[str, Any]): The input for the stage.
-
-        Returns:
-            Tuple[List[CrewOutput], List[Union[str, Dict[str, Any]]]]: The outputs and trace of the stage.
-        """
-        if isinstance(stage, Crew):
-            return await self._process_single_crew(stage, current_input)
-        elif isinstance(stage, list) and all(isinstance(crew, Crew) for crew in stage):
-            return await self._process_parallel_crews(stage, current_input)
-        else:
-            raise ValueError(f"Unsupported stage type: {type(stage)}")
-
-    async def _process_single_crew(
-        self, crew: Crew, current_input: Dict[str, Any]
-    ) -> Tuple[List[CrewOutput], List[Union[str, Dict[str, Any]]]]:
-        """
-        Processes a single crew.
-
-        Args:
-            crew (Crew): The crew to process.
-            current_input (Dict[str, Any]): The input for the crew.
-
-        Returns:
-            Tuple[List[CrewOutput], List[Union[str, Dict[str, Any]]]]: The output and trace of the crew.
-        """
-        output = await crew.kickoff_async(inputs=current_input)
-        return [output], [crew.name or str(crew.id)]
-
-    async def _process_parallel_crews(
-        self, crews: List[Crew], current_input: Dict[str, Any]
-    ) -> Tuple[List[CrewOutput], List[Union[str, Dict[str, Any]]]]:
-        """
-        Processes multiple crews in parallel.
-
-        Args:
-            crews (List[Crew]): The list of crews to process in parallel.
-            current_input (Dict[str, Any]): The input for the crews.
-
-        Returns:
-            Tuple[List[CrewOutput], List[Union[str, Dict[str, Any]]]]: The outputs and traces of the crews.
-        """
-        parallel_outputs = await asyncio.gather(
-            *[crew.kickoff_async(inputs=current_input) for crew in crews]
-        )
-        return parallel_outputs, [crew.name or str(crew.id) for crew in crews]
-
-    def _update_metrics_and_input(
-        self,
-        usage_metrics: Dict[str, UsageMetrics],
-        current_input: Dict[str, Any],
-        stage: PipelineStage,
-        outputs: List[CrewOutput],
-    ) -> None:
-        """
-        Updates metrics and current input with the outputs of a stage.
-
-        Args:
-            usage_metrics (Dict[str, Any]): The usage metrics to update.
-            current_input (Dict[str, Any]): The current input to update.
-            stage (Union[Crew, List[Crew]]): The stage that was processed.
-            outputs (List[CrewOutput]): The outputs of the stage.
-        """
-        if isinstance(stage, Crew):
-            usage_metrics[stage.name or str(stage.id)] = outputs[0].token_usage
-            current_input.update(outputs[0].to_dict())
-        elif isinstance(stage, list) and all(isinstance(crew, Crew) for crew in stage):
-            for crew, output in zip(stage, outputs):
-                usage_metrics[crew.name or str(crew.id)] = output.token_usage
-                current_input.update(output.to_dict())
-        else:
-            raise ValueError(f"Unsupported stage type: {type(stage)}")
-
-    def _build_pipeline_kickoff_results(
-        self,
-        all_stage_outputs: List[List[CrewOutput]],
-        traces: List[List[Union[str, Dict[str, Any]]]],
-        token_usage: Dict[str, UsageMetrics],
-    ) -> List[PipelineKickoffResult]:
-        """
-        Builds the results of a pipeline run.
-
-        Args:
-            all_stage_outputs (List[List[CrewOutput]]): All stage outputs.
-            traces (List[List[Union[str, Dict[str, Any]]]]): All traces.
-            token_usage (Dict[str, Any]): Token usage metrics.
-
-        Returns:
-            List[PipelineKickoffResult]: The results of the pipeline run.
-        """
-        formatted_traces = self._format_traces(traces)
-        formatted_crew_outputs = self._format_crew_outputs(all_stage_outputs)
-
-        return [
-            PipelineKickoffResult(
-                token_usage=token_usage,
-                trace=formatted_trace,
-                raw=crews_outputs[-1].raw,
-                pydantic=crews_outputs[-1].pydantic,
-                json_dict=crews_outputs[-1].json_dict,
-                crews_outputs=crews_outputs,
-            )
-            for crews_outputs, formatted_trace in zip(
-                formatted_crew_outputs, formatted_traces
-            )
-        ]
-
-    def _format_traces(
-        self, traces: List[List[Union[str, Dict[str, Any]]]]
-    ) -> List[List[Trace]]:
-        """
-        Formats the traces of a pipeline run.
-
-        Args:
-            traces (List[List[Union[str, Dict[str, Any]]]]): The traces to format.
-
-        Returns:
-            List[List[Trace]]: The formatted traces.
-        """
-        formatted_traces: List[Trace] = self._format_single_trace(traces[:-1])
-        return self._format_multiple_traces(formatted_traces, traces[-1])
-
-    def _format_single_trace(
-        self, traces: List[List[Union[str, Dict[str, Any]]]]
-    ) -> List[Trace]:
-        """
-        Formats single traces.
-
-        Args:
-            traces (List[List[Union[str, Dict[str, Any]]]]): The traces to format.
-
-        Returns:
-            List[Trace]: The formatted single traces.
-        """
-        formatted_traces: List[Trace] = []
-        for trace in traces:
-            formatted_traces.append(trace[0] if len(trace) == 1 else trace)
-        return formatted_traces
-
-    def _format_multiple_traces(
-        self,
-        formatted_traces: List[Trace],
-        final_trace: List[Union[str, Dict[str, Any]]],
-    ) -> List[List[Trace]]:
-        """
-        Formats multiple traces.
-
-        Args:
-            formatted_traces (List[Trace]): The formatted single traces.
-            final_trace (List[Union[str, Dict[str, Any]]]): The final trace to format.
-
-        Returns:
-            List[List[Trace]]: The formatted multiple traces.
-        """
-        traces_to_return: List[List[Trace]] = []
-        if len(final_trace) == 1:
-            formatted_traces.append(final_trace[0])
-            traces_to_return.append(formatted_traces)
-        else:
-            for trace in final_trace:
-                copied_traces = formatted_traces.copy()
-                copied_traces.append(trace)
-                traces_to_return.append(copied_traces)
-        return traces_to_return
-
-    def _format_crew_outputs(
-        self, all_stage_outputs: List[List[CrewOutput]]
-    ) -> List[List[CrewOutput]]:
-        """
-        Formats the outputs of all stages into a list of crew outputs.
-
-        Args:
-            all_stage_outputs (List[List[CrewOutput]]): All stage outputs.
-
-        Returns:
-            List[List[CrewOutput]]: Formatted crew outputs.
-        """
-        crew_outputs: List[CrewOutput] = [
-            output
-            for stage_outputs in all_stage_outputs[:-1]
-            for output in stage_outputs
-        ]
-        return [crew_outputs + [output] for output in all_stage_outputs[-1]]
-
-    def _copy_stages(self):
-        """Create a deep copy of the Pipeline's stages."""
-        new_stages = []
-        for stage in self.stages:
-            if isinstance(stage, list):
-                new_stages.append(
-                    [
-                        crew.copy() if hasattr(crew, "copy") else copy.deepcopy(crew)
-                        for crew in stage
-                    ]
-                )
-            elif hasattr(stage, "copy"):
-                new_stages.append(stage.copy())
-            else:
-                new_stages.append(copy.deepcopy(stage))
-
-        return new_stages
-
-    def __rshift__(self, other: PipelineStage) -> "Pipeline":
-        """
-        Implements the >> operator to add another Stage (Crew or List[Crew]) to an existing Pipeline.
-
-        Args:
-            other (Any): The stage to add.
-
-        Returns:
-            Pipeline: A new pipeline with the added stage.
-        """
-        if isinstance(other, (Crew, Router)) or (
-            isinstance(other, list) and all(isinstance(item, Crew) for item in other)
-        ):
-            return type(self)(stages=self.stages + [other])
-        else:
-            raise TypeError(
-                f"Unsupported operand type for >>: '{type(self).__name__}' and '{type(other).__name__}'"
-            )
diff --git a/src/crewai/pipeline/pipeline_kickoff_result.py b/src/crewai/pipeline/pipeline_kickoff_result.py
deleted file mode 100644
index 7bde238cd..000000000
--- a/src/crewai/pipeline/pipeline_kickoff_result.py
+++ /dev/null
@@ -1,61 +0,0 @@
-import json
-import uuid
-from typing import Any, Dict, List, Optional, Union
-
-from pydantic import UUID4, BaseModel, Field
-
-from crewai.crews.crew_output import CrewOutput
-from crewai.types.usage_metrics import UsageMetrics
-
-
-class PipelineKickoffResult(BaseModel):
-    """Class that represents the result of a pipeline run."""
-
-    id: UUID4 = Field(
-        default_factory=uuid.uuid4,
-        frozen=True,
-        description="Unique identifier for the object, not set by user.",
-    )
-    raw: str = Field(description="Raw output of the pipeline run", default="")
-    pydantic: Any = Field(
-        description="Pydantic output of the pipeline run", default=None
-    )
-    json_dict: Union[Dict[str, Any], None] = Field(
-        description="JSON dict output of the pipeline run", default={}
-    )
-
-    token_usage: Dict[str, UsageMetrics] = Field(
-        description="Token usage for each crew in the run"
-    )
-    trace: List[Any] = Field(
-        description="Trace of the journey of inputs through the run"
-    )
-    crews_outputs: List[CrewOutput] = Field(
-        description="Output from each crew in the run",
-        default=[],
-    )
-
-    @property
-    def json(self) -> Optional[str]:
-        if self.crews_outputs[-1].tasks_output[-1].output_format != "json":
-            raise ValueError(
-                "No JSON output found in the final task of the final crew. Please make sure to set the output_json property in the final task in your crew."
-            )
-
-        return json.dumps(self.json_dict)
-
-    def to_dict(self) -> Dict[str, Any]:
-        """Convert json_output and pydantic_output to a dictionary."""
-        output_dict = {}
-        if self.json_dict:
-            output_dict.update(self.json_dict)
-        elif self.pydantic:
-            output_dict.update(self.pydantic.model_dump())
-        return output_dict
-
-    def __str__(self):
-        if self.pydantic:
-            return str(self.pydantic)
-        if self.json_dict:
-            return str(self.json_dict)
-        return self.raw
diff --git a/src/crewai/pipeline/pipeline_output.py b/src/crewai/pipeline/pipeline_output.py
deleted file mode 100644
index d9875b64a..000000000
--- a/src/crewai/pipeline/pipeline_output.py
+++ /dev/null
@@ -1,20 +0,0 @@
-import uuid
-from typing import List
-
-from pydantic import UUID4, BaseModel, Field
-
-from crewai.pipeline.pipeline_kickoff_result import PipelineKickoffResult
-
-
-class PipelineOutput(BaseModel):
-    id: UUID4 = Field(
-        default_factory=uuid.uuid4,
-        frozen=True,
-        description="Unique identifier for the object, not set by user.",
-    )
-    run_results: List[PipelineKickoffResult] = Field(
-        description="List of results for each run through the pipeline", default=[]
-    )
-
-    def add_run_result(self, result: PipelineKickoffResult):
-        self.run_results.append(result)
diff --git a/src/crewai/project/__init__.py b/src/crewai/project/__init__.py
index 25f6f5e04..d60212153 100644
--- a/src/crewai/project/__init__.py
+++ b/src/crewai/project/__init__.py
@@ -8,12 +8,10 @@ from .annotations import (
     llm,
     output_json,
     output_pydantic,
-    pipeline,
     task,
     tool,
 )
 from .crew_base import CrewBase
-from .pipeline_base import PipelineBase
 
 __all__ = [
     "agent",
@@ -24,10 +22,8 @@ __all__ = [
     "tool",
     "callback",
     "CrewBase",
-    "PipelineBase",
     "llm",
     "cache_handler",
-    "pipeline",
     "before_kickoff",
     "after_kickoff",
 ]
diff --git a/src/crewai/project/annotations.py b/src/crewai/project/annotations.py
index 83e396a4c..be4710b2b 100644
--- a/src/crewai/project/annotations.py
+++ b/src/crewai/project/annotations.py
@@ -65,21 +65,6 @@ def cache_handler(func):
     return memoize(func)
 
 
-def stage(func):
-    func.is_stage = True
-    return memoize(func)
-
-
-def router(func):
-    func.is_router = True
-    return memoize(func)
-
-
-def pipeline(func):
-    func.is_pipeline = True
-    return memoize(func)
-
-
 def crew(func) -> Callable[..., Crew]:
     def wrapper(self, *args, **kwargs) -> Crew:
         instantiated_tasks = []
diff --git a/src/crewai/project/pipeline_base.py b/src/crewai/project/pipeline_base.py
deleted file mode 100644
index 268cb3901..000000000
--- a/src/crewai/project/pipeline_base.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from typing import Any, Callable, Dict, List, Type, Union
-
-from crewai.crew import Crew
-from crewai.pipeline.pipeline import Pipeline
-from crewai.routers.router import Router
-
-PipelineStage = Union[Crew, List[Crew], Router]
-
-
-# TODO: Could potentially remove. Need to check with @joao and @gui if this is needed for CrewAI+
-def PipelineBase(cls: Type[Any]) -> Type[Any]:
-    class WrappedClass(cls):
-        is_pipeline_class: bool = True  # type: ignore
-        stages: List[PipelineStage]
-
-        def __init__(self, *args: Any, **kwargs: Any) -> None:
-            super().__init__(*args, **kwargs)
-            self.stages = []
-            self._map_pipeline_components()
-
-        def _get_all_functions(self) -> Dict[str, Callable[..., Any]]:
-            return {
-                name: getattr(self, name)
-                for name in dir(self)
-                if callable(getattr(self, name))
-            }
-
-        def _filter_functions(
-            self, functions: Dict[str, Callable[..., Any]], attribute: str
-        ) -> Dict[str, Callable[..., Any]]:
-            return {
-                name: func
-                for name, func in functions.items()
-                if hasattr(func, attribute)
-            }
-
-        def _map_pipeline_components(self) -> None:
-            all_functions = self._get_all_functions()
-            crew_functions = self._filter_functions(all_functions, "is_crew")
-            router_functions = self._filter_functions(all_functions, "is_router")
-
-            for stage_attr in dir(self):
-                stage = getattr(self, stage_attr)
-                if isinstance(stage, (Crew, Router)):
-                    self.stages.append(stage)
-                elif callable(stage) and hasattr(stage, "is_crew"):
-                    self.stages.append(crew_functions[stage_attr]())
-                elif callable(stage) and hasattr(stage, "is_router"):
-                    self.stages.append(router_functions[stage_attr]())
-                elif isinstance(stage, list) and all(
-                    isinstance(item, Crew) for item in stage
-                ):
-                    self.stages.append(stage)
-
-        def build_pipeline(self) -> Pipeline:
-            return Pipeline(stages=self.stages)
-
-    return WrappedClass
diff --git a/src/crewai/routers/__init__.py b/src/crewai/routers/__init__.py
deleted file mode 100644
index c53802bef..000000000
--- a/src/crewai/routers/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-from crewai.routers.router import Router
-
-__all__ = ["Router"]
diff --git a/src/crewai/routers/router.py b/src/crewai/routers/router.py
deleted file mode 100644
index e85ce2256..000000000
--- a/src/crewai/routers/router.py
+++ /dev/null
@@ -1,84 +0,0 @@
-from copy import deepcopy
-from typing import Any, Callable, Dict, Tuple
-
-from pydantic import BaseModel, Field, PrivateAttr
-
-
-class Route(BaseModel):
-    condition: Callable[[Dict[str, Any]], bool]
-    pipeline: Any
-
-
-class Router(BaseModel):
-    routes: Dict[str, Route] = Field(
-        default_factory=dict,
-        description="Dictionary of route names to (condition, pipeline) tuples",
-    )
-    default: Any = Field(..., description="Default pipeline if no conditions are met")
-    _route_types: Dict[str, type] = PrivateAttr(default_factory=dict)
-
-    class Config:
-        arbitrary_types_allowed = True
-
-    def __init__(self, routes: Dict[str, Route], default: Any, **data):
-        super().__init__(routes=routes, default=default, **data)
-        self._check_copyable(default)
-        for name, route in routes.items():
-            self._check_copyable(route.pipeline)
-            self._route_types[name] = type(route.pipeline)
-
-    @staticmethod
-    def _check_copyable(obj: Any) -> None:
-        if not hasattr(obj, "copy") or not callable(getattr(obj, "copy")):
-            raise ValueError(f"Object of type {type(obj)} must have a 'copy' method")
-
-    def add_route(
-        self,
-        name: str,
-        condition: Callable[[Dict[str, Any]], bool],
-        pipeline: Any,
-    ) -> "Router":
-        """
-        Add a named route with its condition and corresponding pipeline to the router.
-
-        Args:
-            name: A unique name for this route
-            condition: A function that takes a dictionary input and returns a boolean
-            pipeline: The Pipeline to execute if the condition is met
-
-        Returns:
-            The Router instance for method chaining
-        """
-        self._check_copyable(pipeline)
-        self.routes[name] = Route(condition=condition, pipeline=pipeline)
-        self._route_types[name] = type(pipeline)
-        return self
-
-    def route(self, input_data: Dict[str, Any]) -> Tuple[Any, str]:
-        """
-        Evaluate the input against the conditions and return the appropriate pipeline.
-
-        Args:
-            input_data: The input dictionary to be evaluated
-
-        Returns:
-            A tuple containing the next Pipeline to be executed and the name of the route taken
-        """
-        for name, route in self.routes.items():
-            if route.condition(input_data):
-                return route.pipeline, name
-
-        return self.default, "default"
-
-    def copy(self) -> "Router":
-        """Create a deep copy of the Router."""
-        new_routes = {
-            name: Route(
-                condition=deepcopy(route.condition),
-                pipeline=route.pipeline.copy(),
-            )
-            for name, route in self.routes.items()
-        }
-        new_default = self.default.copy()
-
-        return Router(routes=new_routes, default=new_default)
diff --git a/tests/pipeline/test_pipeline.py b/tests/pipeline/test_pipeline.py
deleted file mode 100644
index bd0a38183..000000000
--- a/tests/pipeline/test_pipeline.py
+++ /dev/null
@@ -1,921 +0,0 @@
-import json
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from crewai.agent import Agent
-from crewai.crew import Crew
-from crewai.crews.crew_output import CrewOutput
-from crewai.pipeline.pipeline import Pipeline
-from crewai.pipeline.pipeline_kickoff_result import PipelineKickoffResult
-from crewai.process import Process
-from crewai.routers.router import Route, Router
-from crewai.task import Task
-from crewai.tasks.task_output import TaskOutput
-from crewai.types.usage_metrics import UsageMetrics
-from pydantic import BaseModel, ValidationError
-
-DEFAULT_TOKEN_USAGE = UsageMetrics(
-    total_tokens=100, prompt_tokens=50, completion_tokens=50, successful_requests=3
-)
-
-
-@pytest.fixture
-def mock_crew_factory():
-    def _create_mock_crew(name: str, output_json_dict=None, pydantic_output=None):
-        MockCrewClass = type("MockCrew", (MagicMock, Crew), {})
-
-        class MockCrew(MockCrewClass):
-            def __deepcopy__(self):
-                result = MockCrewClass()
-                result.kickoff_async = self.kickoff_async
-                result.name = self.name
-                return result
-
-            def copy(
-                self,
-            ):
-                return self
-
-        crew = MockCrew()
-        crew.name = name
-        crew.knowledge = None
-
-        task_output = TaskOutput(
-            description="Test task", raw="Task output", agent="Test Agent"
-        )
-        crew_output = CrewOutput(
-            raw="Test output",
-            tasks_output=[task_output],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict=output_json_dict if output_json_dict else None,
-            pydantic=pydantic_output,
-        )
-
-        async def kickoff_async(inputs=None):
-            return crew_output
-
-        # Create an AsyncMock for kickoff_async
-        crew.kickoff_async = AsyncMock(side_effect=kickoff_async)
-
-        # Mock the synchronous kickoff method
-        crew.kickoff = MagicMock(return_value=crew_output)
-
-        # Add more attributes that Procedure might be expecting
-        crew.verbose = False
-        crew.output_log_file = None
-        crew.max_rpm = None
-        crew.memory = False
-        crew.process = Process.sequential
-        crew.config = None
-        crew.cache = True
-        crew.embedder = None
-
-        # Add non-empty agents and tasks
-        mock_agent = MagicMock(spec=Agent)
-        mock_task = MagicMock(spec=Task)
-        mock_task.agent = mock_agent
-        mock_task.async_execution = False
-        mock_task.context = None
-
-        crew.agents = [mock_agent]
-        crew.tasks = [mock_task]
-
-        return crew
-
-    return _create_mock_crew
-
-
-@pytest.fixture
-def mock_router_factory(mock_crew_factory):
-    def _create_mock_router():
-        crew1 = mock_crew_factory(name="Crew 1", output_json_dict={"output": "crew1"})
-        crew2 = mock_crew_factory(name="Crew 2", output_json_dict={"output": "crew2"})
-        crew3 = mock_crew_factory(name="Crew 3", output_json_dict={"output": "crew3"})
-
-        MockRouterClass = type("MockRouter", (MagicMock, Router), {})
-
-        class MockRouter(MockRouterClass):
-            def __deepcopy__(self, memo):
-                result = MockRouterClass()
-                result.route = self.route
-                return result
-
-        mock_router = MockRouter()
-        mock_router.route = MagicMock(
-            side_effect=lambda x: (
-                (
-                    Pipeline(stages=[crew1])
-                    if x.get("score", 0) > 80
-                    else (
-                        Pipeline(stages=[crew2])
-                        if x.get("score", 0) > 50
-                        else Pipeline(stages=[crew3])
-                    )
-                ),
-                (
-                    "route1"
-                    if x.get("score", 0) > 80
-                    else "route2"
-                    if x.get("score", 0) > 50
-                    else "default"
-                ),
-            )
-        )
-
-        return mock_router
-
-    return _create_mock_router
-
-
-def test_pipeline_initialization(mock_crew_factory):
-    """
-    Test that a Pipeline is correctly initialized with the given stages.
-    """
-    crew1 = mock_crew_factory(name="Crew 1")
-    crew2 = mock_crew_factory(name="Crew 2")
-
-    pipeline = Pipeline(stages=[crew1, crew2])
-    assert len(pipeline.stages) == 2
-    assert pipeline.stages[0] == crew1
-    assert pipeline.stages[1] == crew2
-
-
-@pytest.mark.asyncio
-async def test_pipeline_with_empty_input(mock_crew_factory):
-    """
-    Ensure the pipeline handles an empty input list correctly.
-    """
-    crew = mock_crew_factory(name="Test Crew")
-    pipeline = Pipeline(stages=[crew])
-
-    input_data = []
-    pipeline_results = await pipeline.kickoff(input_data)
-
-    assert (
-        len(pipeline_results) == 0
-    ), "Pipeline should return empty results for empty input"
-
-
-agent = Agent(
-    role="Test Role",
-    goal="Test Goal",
-    backstory="Test Backstory",
-    allow_delegation=False,
-    verbose=False,
-)
-task = Task(
-    description="Return: Test output",
-    expected_output="Test output",
-    agent=agent,
-    async_execution=False,
-    context=None,
-)
-
-
-@pytest.mark.asyncio
-async def test_pipeline_process_streams_single_input():
-    """
-    Test that Pipeline.process_streams() correctly processes a single input
-    and returns the expected CrewOutput.
-    """
-    crew_name = "Test Crew"
-    mock_crew = Crew(
-        agents=[agent],
-        tasks=[task],
-        process=Process.sequential,
-    )
-    mock_crew.name = crew_name
-    pipeline = Pipeline(stages=[mock_crew])
-    input_data = [{"key": "value"}]
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        task_output = TaskOutput(
-            description="Test task", raw="Task output", agent="Test Agent"
-        )
-        mock_kickoff.return_value = CrewOutput(
-            raw="Test output",
-            tasks_output=[task_output],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict=None,
-            pydantic=None,
-        )
-        pipeline_results = await pipeline.kickoff(input_data)
-        mock_crew.kickoff_async.assert_called_once_with(inputs={"key": "value"})
-
-        for pipeline_result in pipeline_results:
-            assert isinstance(pipeline_result, PipelineKickoffResult)
-            assert pipeline_result.raw == "Test output"
-            assert len(pipeline_result.crews_outputs) == 1
-            assert pipeline_result.token_usage == {crew_name: DEFAULT_TOKEN_USAGE}
-            assert pipeline_result.trace == [input_data[0], "Test Crew"]
-
-
-@pytest.mark.asyncio
-async def test_pipeline_result_ordering():
-    """
-    Ensure that results are returned in the same order as the inputs, especially with parallel processing.
-    """
-    crew1 = Crew(
-        name="Crew 1",
-        agents=[agent],
-        tasks=[task],
-    )
-    crew2 = Crew(
-        name="Crew 2",
-        agents=[agent],
-        tasks=[task],
-    )
-    crew3 = Crew(
-        name="Crew 3",
-        agents=[agent],
-        tasks=[task],
-    )
-
-    pipeline = Pipeline(
-        stages=[crew1, [crew2, crew3]]
-    )  # Parallel stage to test ordering
-    input_data = [{"id": 1}, {"id": 2}, {"id": 3}]
-
-    def create_crew_output(crew_name):
-        return CrewOutput(
-            raw=f"Test output from {crew_name}",
-            tasks_output=[
-                TaskOutput(
-                    description="Test task",
-                    raw=f"Task output from {crew_name}",
-                    agent="Test Agent",
-                )
-            ],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict={"output": crew_name.lower().replace(" ", "")},
-            pydantic=None,
-        )
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.side_effect = [
-            create_crew_output("Crew 1"),
-            create_crew_output("Crew 2"),
-            create_crew_output("Crew 3"),
-        ] * 3
-        pipeline_results = await pipeline.kickoff(input_data)
-        mock_kickoff.call_count = 3
-
-    assert (
-        len(pipeline_results) == 6
-    ), "Should have 2 results for each input due to the parallel final stage"
-
-    # Group results by their original input id
-    grouped_results = {}
-    for result in pipeline_results:
-        input_id = result.trace[0]["id"]
-        if input_id not in grouped_results:
-            grouped_results[input_id] = []
-        grouped_results[input_id].append(result)
-
-    # Check that we have the correct number of groups and results per group
-    assert len(grouped_results) == 3, "Should have results for each of the 3 inputs"
-    for input_id, results in grouped_results.items():
-        assert (
-            len(results) == 2
-        ), f"Each input should have 2 results, but input {input_id} has {len(results)}"
-
-    # Check the ordering and content of the results
-    for input_id in range(1, 4):
-        group = grouped_results[input_id]
-        assert group[0].trace == [
-            {"id": input_id},
-            "Crew 1",
-            "Crew 2",
-        ], f"Unexpected trace for first result of input {input_id}"
-        assert group[1].trace == [
-            {"id": input_id},
-            "Crew 1",
-            "Crew 3",
-        ], f"Unexpected trace for second result of input {input_id}"
-
-
-class TestPydanticOutput(BaseModel):
-    key: str
-    value: int
-
-
-@pytest.mark.asyncio
-@pytest.mark.vcr(filter_headers=["authorization"])
-async def test_pipeline_process_streams_single_input_pydantic_output():
-    crew_name = "Test Crew"
-    task = Task(
-        description="Return: Key:value",
-        expected_output="Key:Value",
-        agent=agent,
-        async_execution=False,
-        context=None,
-        output_pydantic=TestPydanticOutput,
-    )
-    mock_crew = Crew(
-        name=crew_name,
-        agents=[agent],
-        tasks=[task],
-    )
-
-    pipeline = Pipeline(stages=[mock_crew])
-    input_data = [{"key": "value"}]
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_crew_output = CrewOutput(
-            raw="Test output",
-            tasks_output=[
-                TaskOutput(
-                    description="Return: Key:value", raw="Key:Value", agent="Test Agent"
-                )
-            ],
-            token_usage=UsageMetrics(
-                total_tokens=171,
-                prompt_tokens=154,
-                completion_tokens=17,
-                successful_requests=1,
-            ),
-            pydantic=TestPydanticOutput(key="test", value=42),
-        )
-        mock_kickoff.return_value = mock_crew_output
-        pipeline_results = await pipeline.kickoff(input_data)
-
-    assert len(pipeline_results) == 1
-    pipeline_result = pipeline_results[0]
-
-    assert isinstance(pipeline_result, PipelineKickoffResult)
-    assert pipeline_result.raw == "Test output"
-    assert len(pipeline_result.crews_outputs) == 1
-    assert pipeline_result.token_usage == {
-        crew_name: UsageMetrics(
-            total_tokens=171,
-            prompt_tokens=154,
-            completion_tokens=17,
-            successful_requests=1,
-        )
-    }
-
-    assert pipeline_result.trace == [input_data[0], "Test Crew"]
-    assert isinstance(pipeline_result.pydantic, TestPydanticOutput)
-    assert pipeline_result.pydantic.key == "test"
-    assert pipeline_result.pydantic.value == 42
-    assert pipeline_result.json_dict is None
-
-
-@pytest.mark.asyncio
-async def test_pipeline_preserves_original_input(mock_crew_factory):
-    crew_name = "Test Crew"
-    mock_crew = mock_crew_factory(
-        name=crew_name,
-        output_json_dict={"new_key": "new_value"},
-    )
-    pipeline = Pipeline(stages=[mock_crew])
-
-    # Create a deep copy of the input data to ensure we're not comparing references
-    original_input_data = [{"key": "value", "nested": {"a": 1}}]
-    input_data = json.loads(json.dumps(original_input_data))
-
-    await pipeline.kickoff(input_data)
-
-    # Assert that the original input hasn't been modified
-    assert (
-        input_data == original_input_data
-    ), "The original input data should not be modified"
-
-    # Ensure that even nested structures haven't been modified
-    assert (
-        input_data[0]["nested"] == original_input_data[0]["nested"]
-    ), "Nested structures should not be modified"
-
-    # Verify that adding new keys to the crew output doesn't affect the original input
-    assert (
-        "new_key" not in input_data[0]
-    ), "New keys from crew output should not be added to the original input"
-
-
-@pytest.mark.asyncio
-async def test_pipeline_process_streams_multiple_inputs():
-    """
-    Test that Pipeline.process_streams() correctly processes multiple inputs
-    and returns the expected CrewOutputs.
-    """
-    mock_crew = Crew(name="Test Crew", tasks=[task], agents=[agent])
-    pipeline = Pipeline(stages=[mock_crew])
-    input_data = [{"key1": "value1"}, {"key2": "value2"}]
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.return_value = CrewOutput(
-            raw="Test output",
-            tasks_output=[
-                TaskOutput(
-                    description="Test task", raw="Task output", agent="Test Agent"
-                )
-            ],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict=None,
-            pydantic=None,
-        )
-        pipeline_results = await pipeline.kickoff(input_data)
-        assert mock_kickoff.call_count == 2
-        assert len(pipeline_results) == 2
-
-    for pipeline_result in pipeline_results:
-        assert all(
-            isinstance(crew_output, CrewOutput)
-            for crew_output in pipeline_result.crews_outputs
-        )
-
-
-@pytest.mark.asyncio
-async def test_pipeline_with_parallel_stages():
-    """
-    Test that Pipeline correctly handles parallel stages.
-    """
-    crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
-    crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
-    crew3 = Crew(name="Crew 3", tasks=[task], agents=[agent])
-
-    pipeline = Pipeline(stages=[crew1, [crew2, crew3]])
-    input_data = [{"initial": "data"}]
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.return_value = CrewOutput(
-            raw="Test output",
-            tasks_output=[
-                TaskOutput(
-                    description="Test task", raw="Task output", agent="Test Agent"
-                )
-            ],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict=None,
-            pydantic=None,
-        )
-        pipeline_result = await pipeline.kickoff(input_data)
-        mock_kickoff.assert_called_with(inputs={"initial": "data"})
-
-    assert len(pipeline_result) == 2
-    pipeline_result_1, pipeline_result_2 = pipeline_result
-
-    pipeline_result_1.trace = [
-        "Crew 1",
-        "Crew 2",
-    ]
-    pipeline_result_2.trace = [
-        "Crew 1",
-        "Crew 3",
-    ]
-
-    expected_token_usage = {
-        "Crew 1": DEFAULT_TOKEN_USAGE,
-        "Crew 2": DEFAULT_TOKEN_USAGE,
-        "Crew 3": DEFAULT_TOKEN_USAGE,
-    }
-
-    assert pipeline_result_1.token_usage == expected_token_usage
-    assert pipeline_result_2.token_usage == expected_token_usage
-
-
-@pytest.mark.asyncio
-async def test_pipeline_with_parallel_stages_end_in_single_stage(mock_crew_factory):
-    """
-    Test that Pipeline correctly handles parallel stages.
-    """
-    crew1 = mock_crew_factory(name="Crew 1")
-    crew2 = mock_crew_factory(name="Crew 2")
-    crew3 = mock_crew_factory(name="Crew 3")
-    crew4 = mock_crew_factory(name="Crew 4")
-
-    pipeline = Pipeline(stages=[crew1, [crew2, crew3], crew4])
-    input_data = [{"initial": "data"}]
-
-    pipeline_result = await pipeline.kickoff(input_data)
-
-    crew1.kickoff_async.assert_called_once_with(inputs={"initial": "data"})
-
-    assert len(pipeline_result) == 1
-    pipeline_result_1 = pipeline_result[0]
-
-    pipeline_result_1.trace = [
-        input_data[0],
-        "Crew 1",
-        ["Crew 2", "Crew 3"],
-        "Crew 4",
-    ]
-
-    expected_token_usage = {
-        "Crew 1": DEFAULT_TOKEN_USAGE,
-        "Crew 2": DEFAULT_TOKEN_USAGE,
-        "Crew 3": DEFAULT_TOKEN_USAGE,
-        "Crew 4": DEFAULT_TOKEN_USAGE,
-    }
-
-    assert pipeline_result_1.token_usage == expected_token_usage
-
-
-def test_pipeline_rshift_operator(mock_crew_factory):
-    """
-    Test that the >> operator correctly creates a Pipeline from Crews and lists of Crews.
-    """
-    crew1 = mock_crew_factory(name="Crew 1")
-    crew2 = mock_crew_factory(name="Crew 2")
-    crew3 = mock_crew_factory(name="Crew 3")
-
-    # Test single crew addition
-    pipeline = Pipeline(stages=[]) >> crew1
-    assert len(pipeline.stages) == 1
-    assert pipeline.stages[0] == crew1
-
-    # Test adding a list of crews
-    pipeline = Pipeline(stages=[crew1])
-    pipeline = pipeline >> [crew2, crew3]
-    assert len(pipeline.stages) == 2
-    assert pipeline.stages[1] == [crew2, crew3]
-
-    # Test error case: trying to shift with non-Crew object
-    with pytest.raises(TypeError):
-        pipeline >> "not a crew"
-
-
-@pytest.mark.asyncio
-@pytest.mark.vcr(filter_headers=["authorization"])
-async def test_pipeline_parallel_crews_to_parallel_crews():
-    """
-    Test that feeding parallel crews to parallel crews works correctly.
-    """
-    crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
-    crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
-    crew3 = Crew(name="Crew 3", tasks=[task], agents=[agent])
-    crew4 = Crew(name="Crew 4", tasks=[task], agents=[agent])
-    #  output_json_dict={"output1": "crew1"}
-    pipeline = Pipeline(stages=[[crew1, crew2], [crew3, crew4]])
-
-    input_data = [{"input": "test"}]
-
-    def create_crew_output(crew_name):
-        return CrewOutput(
-            raw=f"Test output from {crew_name}",
-            tasks_output=[
-                TaskOutput(
-                    description="Test task",
-                    raw=f"Task output from {crew_name}",
-                    agent="Test Agent",
-                )
-            ],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict={"output": crew_name.lower().replace(" ", "")},
-            pydantic=None,
-        )
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.side_effect = [
-            create_crew_output(crew_name)
-            for crew_name in ["Crew 1", "Crew 2", "Crew 3", "Crew 4"]
-        ]
-        pipeline_results = await pipeline.kickoff(input_data)
-
-    assert len(pipeline_results) == 2, "Should have 2 results for final parallel stage"
-
-    pipeline_result_1, pipeline_result_2 = pipeline_results
-
-    # Check the outputs
-    assert pipeline_result_1.json_dict == {"output": "crew3"}
-    assert pipeline_result_2.json_dict == {"output": "crew4"}
-
-    # Check the traces
-    expected_traces = [
-        [{"input": "test"}, ["Crew 1", "Crew 2"], "Crew 3"],
-        [{"input": "test"}, ["Crew 1", "Crew 2"], "Crew 4"],
-    ]
-
-    for result, expected_trace in zip(pipeline_results, expected_traces):
-        assert result.trace == expected_trace, f"Unexpected trace: {result.trace}"
-
-
-def test_pipeline_double_nesting_not_allowed(mock_crew_factory):
-    """
-    Test that double nesting in pipeline stages is not allowed.
-    """
-    crew1 = mock_crew_factory(name="Crew 1")
-    crew2 = mock_crew_factory(name="Crew 2")
-    crew3 = mock_crew_factory(name="Crew 3")
-    crew4 = mock_crew_factory(name="Crew 4")
-
-    with pytest.raises(ValidationError) as exc_info:
-        Pipeline(stages=[crew1, [[crew2, crew3], crew4]])
-
-    error_msg = str(exc_info.value)
-
-    assert (
-        "Double nesting is not allowed in pipeline stages" in error_msg
-    ), f"Unexpected error message: {error_msg}"
-
-
-def test_pipeline_invalid_crew(mock_crew_factory):
-    """
-    Test that non-Crew objects are not allowed in pipeline stages.
-    """
-    crew1 = mock_crew_factory(name="Crew 1")
-    not_a_crew = "This is not a crew"
-
-    with pytest.raises(ValidationError) as exc_info:
-        Pipeline(stages=[crew1, not_a_crew])
-
-    error_msg = str(exc_info.value)
-    assert (
-        "Expected Crew instance, Router instance, or list of Crews, got <class 'str'>"
-        in error_msg
-    ), f"Unexpected error message: {error_msg}"
-
-
-"""
-TODO: Figure out what is the proper output for a pipeline with multiple stages
-
-Options:
-- Should the final output only include the last stage's output?
-- Should the final output include the accumulation of previous stages' outputs?
-"""
-
-
-@pytest.mark.asyncio
-async def test_pipeline_data_accumulation(mock_crew_factory):
-    crew1 = mock_crew_factory(name="Crew 1", output_json_dict={"key1": "value1"})
-    crew2 = mock_crew_factory(name="Crew 2", output_json_dict={"key2": "value2"})
-
-    pipeline = Pipeline(stages=[crew1, crew2])
-    input_data = [{"initial": "data"}]
-    results = await pipeline.kickoff(input_data)
-
-    # Check that crew1 was called with only the initial input
-    crew1.kickoff_async.assert_called_once_with(inputs={"initial": "data"})
-
-    # Check that crew2 was called with the combined input from the initial data and crew1's output
-    crew2.kickoff_async.assert_called_once_with(
-        inputs={"initial": "data", "key1": "value1"}
-    )
-
-    # Check the final output
-    assert len(results) == 1
-    final_result = results[0]
-    assert final_result.json_dict == {"key2": "value2"}
-
-    # Check that the trace includes all stages
-    assert final_result.trace == [{"initial": "data"}, "Crew 1", "Crew 2"]
-
-    # Check that crews_outputs contain the correct information
-    assert len(final_result.crews_outputs) == 2
-    assert final_result.crews_outputs[0].json_dict == {"key1": "value1"}
-    assert final_result.crews_outputs[1].json_dict == {"key2": "value2"}
-
-
-@pytest.mark.asyncio
-@pytest.mark.vcr(filter_headers=["authorization"])
-async def test_pipeline_with_router():
-    crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
-    crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
-    crew3 = Crew(name="Crew 3", tasks=[task], agents=[agent])
-    routes = {
-        "route1": Route(
-            condition=lambda x: x.get("score", 0) > 80,
-            pipeline=Pipeline(stages=[crew1]),
-        ),
-        "route2": Route(
-            condition=lambda x: 50 < x.get("score", 0) <= 80,
-            pipeline=Pipeline(stages=[crew2]),
-        ),
-    }
-    router = Router(
-        routes=routes,
-        default=Pipeline(stages=[crew3]),
-    )
-    # Test high score route
-    pipeline = Pipeline(stages=[router])
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.return_value = CrewOutput(
-            raw="Test output from Crew 1",
-            tasks_output=[],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict={"output": "crew1"},
-            pydantic=None,
-        )
-        result_high = await pipeline.kickoff([{"score": 90}])
-
-        assert len(result_high) == 1
-        assert result_high[0].json_dict is not None
-        assert result_high[0].json_dict["output"] == "crew1"
-        assert result_high[0].trace == [
-            {"score": 90},
-            {"route_taken": "route1"},
-            "Crew 1",
-        ]
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.return_value = CrewOutput(
-            raw="Test output from Crew 2",
-            tasks_output=[],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict={"output": "crew2"},
-            pydantic=None,
-        )
-        # Test medium score route
-        pipeline = Pipeline(stages=[router])
-        result_medium = await pipeline.kickoff([{"score": 60}])
-        assert len(result_medium) == 1
-        assert result_medium[0].json_dict is not None
-        assert result_medium[0].json_dict["output"] == "crew2"
-        assert result_medium[0].trace == [
-            {"score": 60},
-            {"route_taken": "route2"},
-            "Crew 2",
-        ]
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.return_value = CrewOutput(
-            raw="Test output from Crew 3",
-            tasks_output=[],
-            token_usage=DEFAULT_TOKEN_USAGE,
-            json_dict={"output": "crew3"},
-            pydantic=None,
-        )
-        # Test low score route
-        pipeline = Pipeline(stages=[router])
-        result_low = await pipeline.kickoff([{"score": 30}])
-        assert len(result_low) == 1
-        assert result_low[0].json_dict is not None
-        assert result_low[0].json_dict["output"] == "crew3"
-        assert result_low[0].trace == [
-            {"score": 30},
-            {"route_taken": "default"},
-            "Crew 3",
-        ]
-
-
-@pytest.mark.asyncio
-@pytest.mark.vcr(filter_headers=["authorization"])
-async def test_router_with_multiple_inputs():
-    crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
-    crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
-    crew3 = Crew(name="Crew 3", tasks=[task], agents=[agent])
-    router = Router(
-        routes={
-            "route1": Route(
-                condition=lambda x: x.get("score", 0) > 80,
-                pipeline=Pipeline(stages=[crew1]),
-            ),
-            "route2": Route(
-                condition=lambda x: 50 < x.get("score", 0) <= 80,
-                pipeline=Pipeline(stages=[crew2]),
-            ),
-        },
-        default=Pipeline(stages=[crew3]),
-    )
-    pipeline = Pipeline(stages=[router])
-
-    inputs = [{"score": 90}, {"score": 60}, {"score": 30}]
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.side_effect = [
-            CrewOutput(
-                raw="Test output from Crew 1",
-                tasks_output=[],
-                token_usage=DEFAULT_TOKEN_USAGE,
-                json_dict={"output": "crew1"},
-                pydantic=None,
-            ),
-            CrewOutput(
-                raw="Test output from Crew 2",
-                tasks_output=[],
-                token_usage=DEFAULT_TOKEN_USAGE,
-                json_dict={"output": "crew2"},
-                pydantic=None,
-            ),
-            CrewOutput(
-                raw="Test output from Crew 3",
-                tasks_output=[],
-                token_usage=DEFAULT_TOKEN_USAGE,
-                json_dict={"output": "crew3"},
-                pydantic=None,
-            ),
-        ]
-        results = await pipeline.kickoff(inputs)
-
-    assert len(results) == 3
-    assert results[0].json_dict is not None
-    assert results[0].json_dict["output"] == "crew1"
-    assert results[1].json_dict is not None
-    assert results[1].json_dict["output"] == "crew2"
-    assert results[2].json_dict is not None
-    assert results[2].json_dict["output"] == "crew3"
-
-    assert results[0].trace[1]["route_taken"] == "route1"
-    assert results[1].trace[1]["route_taken"] == "route2"
-    assert results[2].trace[1]["route_taken"] == "default"
-
-
-@pytest.mark.asyncio
-@pytest.mark.vcr(filter_headers=["authorization"])
-async def test_pipeline_with_multiple_routers():
-    crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
-    crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
-    router1 = Router(
-        routes={
-            "route1": Route(
-                condition=lambda x: x.get("score", 0) > 80,
-                pipeline=Pipeline(stages=[crew1]),
-            ),
-        },
-        default=Pipeline(stages=[crew2]),
-    )
-    router2 = Router(
-        routes={
-            "route2": Route(
-                condition=lambda x: 50 < x.get("score", 0) <= 80,
-                pipeline=Pipeline(stages=[crew2]),
-            ),
-        },
-        default=Pipeline(stages=[crew2]),
-    )
-    final_crew = Crew(name="Final Crew", tasks=[task], agents=[agent])
-
-    pipeline = Pipeline(stages=[router1, router2, final_crew])
-
-    with patch.object(Crew, "kickoff_async") as mock_kickoff:
-        mock_kickoff.side_effect = [
-            CrewOutput(
-                raw="Test output from Crew 1",
-                tasks_output=[],
-                token_usage=DEFAULT_TOKEN_USAGE,
-                json_dict={"output": "crew1"},
-                pydantic=None,
-            ),
-            CrewOutput(
-                raw="Test output from Crew 2",
-                tasks_output=[],
-                token_usage=DEFAULT_TOKEN_USAGE,
-                json_dict={"output": "crew2"},
-                pydantic=None,
-            ),
-            CrewOutput(
-                raw="Test output from Final Crew",
-                tasks_output=[],
-                token_usage=DEFAULT_TOKEN_USAGE,
-                json_dict={"output": "final"},
-                pydantic=None,
-            ),
-        ]
-        result = await pipeline.kickoff([{"score": 75}])
-
-    assert len(result) == 1
-    assert result[0].json_dict is not None
-    assert result[0].json_dict["output"] == "final"
-    assert (
-        len(result[0].trace) == 6
-    )  # Input, Router1, Crew2, Router2, Crew2, Final Crew
-    assert result[0].trace[1]["route_taken"] == "default"
-    assert result[0].trace[3]["route_taken"] == "route2"
-
-
-@pytest.mark.asyncio
-async def test_router_default_route(mock_crew_factory):
-    default_crew = mock_crew_factory(
-        name="Default Crew", output_json_dict={"output": "default"}
-    )
-    router = Router(
-        routes={
-            "route1": Route(
-                condition=lambda x: False,
-                pipeline=Pipeline(stages=[mock_crew_factory(name="Never Used")]),
-            ),
-        },
-        default=Pipeline(stages=[default_crew]),
-    )
-
-    pipeline = Pipeline(stages=[router])
-    result = await pipeline.kickoff([{"score": 100}])
-
-    assert len(result) == 1
-    assert result[0].json_dict is not None
-    assert result[0].json_dict["output"] == "default"
-    assert result[0].trace[1]["route_taken"] == "default"
-
-
-@pytest.mark.asyncio
-@pytest.mark.vcr(filter_headers=["authorization"])
-async def test_router_with_empty_input():
-    crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
-    crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
-    crew3 = Crew(name="Crew 3", tasks=[task], agents=[agent])
-    router = Router(
-        routes={
-            "route1": Route(
-                condition=lambda x: x.get("score", 0) > 80,
-                pipeline=Pipeline(stages=[crew1]),
-            ),
-            "route2": Route(
-                condition=lambda x: 50 < x.get("score", 0) <= 80,
-                pipeline=Pipeline(stages=[crew2]),
-            ),
-        },
-        default=Pipeline(stages=[crew3]),
-    )
-    pipeline = Pipeline(stages=[router])
-
-    result = await pipeline.kickoff([{}])
-
-    assert len(result) == 1
-    assert result[0].trace[1]["route_taken"] == "default"

From 48bb8ef775392b67aba84ad04f6c7f8beda0802d Mon Sep 17 00:00:00 2001
From: Rashmi Pawar <168514198+raspawar@users.noreply.github.com>
Date: Thu, 5 Dec 2024 02:08:46 +0530
Subject: [PATCH 100/126] docs: add nvidia as provider (#1632)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/how-to/llm-connections.mdx | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/how-to/llm-connections.mdx b/docs/how-to/llm-connections.mdx
index a2fc540cc..a69aa4c86 100644
--- a/docs/how-to/llm-connections.mdx
+++ b/docs/how-to/llm-connections.mdx
@@ -32,6 +32,7 @@ LiteLLM supports a wide range of providers, including but not limited to:
 - Cloudflare Workers AI
 - DeepInfra
 - Groq
+- [NVIDIA NIMs](https://docs.api.nvidia.com/nim/reference/models-1)
 - And many more!
 
 For a complete and up-to-date list of supported providers, please refer to the [LiteLLM Providers documentation](https://docs.litellm.ai/docs/providers).

From fa373f9660410b766c2f81ea33fbfd864bae4f47 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Thu, 5 Dec 2024 09:49:44 -0500
Subject: [PATCH 101/126] add knowledge demo + improve knowledge docs (#1706)

---
 docs/concepts/knowledge.mdx | 370 +++++++++++++++++++++++-------------
 1 file changed, 234 insertions(+), 136 deletions(-)

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index a00b2c2f0..06c2eb947 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -1,6 +1,6 @@
 ---
 title: Knowledge
-description: Understand what knowledge is in CrewAI and how to effectively use it.
+description: What is knowledge in CrewAI and how to use it.
 icon: book
 ---
 
@@ -8,7 +8,8 @@ icon: book
 
 ## What is Knowledge?
 
-Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks. Think of it as giving your agents a reference library they can consult while working.
+Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks. 
+Think of it as giving your agents a reference library they can consult while working. 
 
 <Info>
   Key benefits of using Knowledge:
@@ -37,151 +38,275 @@ CrewAI supports various types of knowledge sources out of the box:
 
 ## Quick Start
 
-Here's a simple example using string-based knowledge:
+Here's an example using string-based knowledge:
 
-```python
-from crewai import Agent, Task, Crew
-from crewai.knowledge import StringKnowledgeSource
+```python Code
+from crewai import Agent, Task, Crew, Process, LLM
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 
-# 1. Create a knowledge source
-product_info = StringKnowledgeSource(
-    content="""Our product X1000 has the following features:
-    - 10-hour battery life
-    - Water-resistant
-    - Available in black and silver
-    Price: $299.99""",
-    metadata={"category": "product"}
+# Create a knowledge source
+content = "Users name is John. He is 30 years old and lives in San Francisco."
+string_source = StringKnowledgeSource(
+    content=content, 
+    metadata={"preference": "personal"}
 )
 
-# 2. Create an agent with knowledge
-sales_agent = Agent(
-    role="Sales Representative",
-    goal="Accurately answer customer questions about products",
-    backstory="Expert in product features and customer service",
-    knowledge_sources=[product_info]  # Attach knowledge to agent
+# Create an LLM with a temperature of 0 to ensure deterministic outputs
+llm = LLM(model="gpt-4o-mini", temperature=0)
+
+# Create an agent with the knowledge store
+agent = Agent(
+    role="About User",
+    goal="You know everything about the user.",
+    backstory="""You are a master at understanding people and their preferences.""",
+    verbose=True,
+    allow_delegation=False,
+    llm=llm,
+)
+task = Task(
+    description="Answer the following questions about the user: {question}",
+    expected_output="An answer to the question.",
+    agent=agent,
 )
 
-# 3. Create a task
-answer_task = Task(
-    description="Answer: What colors is the X1000 available in and how much does it cost?",
-    agent=sales_agent
-)
-
-# 4. Create and run the crew
 crew = Crew(
-    agents=[sales_agent],
-    tasks=[answer_task]
+    agents=[agent],
+    tasks=[task],
+    verbose=True,
+    process=Process.sequential,
+    knowledge={
+      "sources": [string_source], 
+      "metadata": {"preference": "personal"}
+    }, # Enable knowledge by adding the sources here. You can also add more sources to the sources list.
 )
 
-result = crew.kickoff()
+result = crew.kickoff(inputs={"question": "What city does John live in and how old is he?"})
 ```
 
 ## Knowledge Configuration
 
-### Collection Names
-
-Knowledge sources are organized into collections for better management:
-
-```python
-# Create knowledge sources with specific collections
-tech_specs = StringKnowledgeSource(
-    content="Technical specifications...",
-    collection_name="product_tech_specs"
-)
-
-pricing_info = StringKnowledgeSource(
-    content="Pricing information...",
-    collection_name="product_pricing"
-)
-```
-
 ### Metadata and Filtering
 
-Add metadata to organize and filter knowledge:
+Knowledge sources support metadata for better organization and filtering. Metadata is used to filter the knowledge sources when querying the knowledge store.
 
-```python
+```python Code
 knowledge_source = StringKnowledgeSource(
-    content="Product details...",
-    metadata={
-        "category": "electronics",
-        "product_line": "premium",
-        "last_updated": "2024-03"
-    }
+    content="Users name is John. He is 30 years old and lives in San Francisco.",
+    metadata={"preference": "personal"} # Metadata is used to filter the knowledge sources
 )
 ```
 
 ### Chunking Configuration
 
-Control how your content is split for processing:
+Control how content is split for processing by setting the chunk size and overlap.
 
-```python
-knowledge_source = PDFKnowledgeSource(
-    file_path="product_manual.pdf",
-    chunk_size=2000,     # Characters per chunk
-    chunk_overlap=200    # Overlap between chunks
+```python Code
+knowledge_source = StringKnowledgeSource(
+    content="Long content...",
+    chunk_size=4000,     # Characters per chunk (default)
+    chunk_overlap=200    # Overlap between chunks (default)
 )
 ```
 
-## Advanced Usage
+## Embedder Configuration
 
-### Custom Knowledge Sources
+You can also configure the embedder for the knowledge store. This is useful if you want to use a different embedder for the knowledge store than the one used for the agents.
 
-Create your own knowledge source by extending the base class:
+```python Code
+...
+string_source = StringKnowledgeSource(
+    content="Users name is John. He is 30 years old and lives in San Francisco.",
+    metadata={"preference": "personal"}
+)
+crew = Crew(
+    ...
+    knowledge={
+        "sources": [string_source],
+        "metadata": {"preference": "personal"},
+        "embedder_config": {
+          "provider": "openai", # Default embedder provider; can be "ollama", "gemini", e.t.c.
+          "config": {"model": "text-embedding-3-small"} # Default embedder model; can be "mxbai-embed-large", "nomic-embed-tex", e.t.c.
+        },
+    },
+)
+```
 
-```python
-from crewai.knowledge.source import BaseKnowledgeSource
+## Custom Knowledge Sources
 
-class APIKnowledgeSource(BaseKnowledgeSource):
-    def __init__(self, api_endpoint: str, **kwargs):
-        super().__init__(**kwargs)
-        self.api_endpoint = api_endpoint
+CrewAI allows you to create custom knowledge sources for any type of data by extending the `BaseKnowledgeSource` class. Let's create a practical example that fetches and processes space news articles.
+
+#### Space News Knowledge Source Example
+
+<CodeGroup>
+
+```python Code
+from crewai import Agent, Task, Crew, Process, LLM
+from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+import requests
+from datetime import datetime
+from typing import Dict, Any
+from pydantic import BaseModel, Field
+
+class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
+    """Knowledge source that fetches data from Space News API."""
     
-    def load_content(self):
-        # Implement API data fetching
-        response = requests.get(self.api_endpoint)
-        return response.json()
+    api_endpoint: str = Field(description="API endpoint URL")
+    limit: int = Field(default=10, description="Number of articles to fetch")
     
-    def add(self):
+    def load_content(self) -> Dict[Any, str]:
+        """Fetch and format space news articles."""
+        try:
+            response = requests.get(
+                f"{self.api_endpoint}?limit={self.limit}"
+            )
+            response.raise_for_status()
+            
+            data = response.json()
+            articles = data.get('results', [])
+            
+            formatted_data = self._format_articles(articles)
+            return {self.api_endpoint: formatted_data}
+        except Exception as e:
+            raise ValueError(f"Failed to fetch space news: {str(e)}")
+    
+    def _format_articles(self, articles: list) -> str:
+        """Format articles into readable text."""
+        formatted = "Space News Articles:\n\n"
+        for article in articles:
+            formatted += f"""
+Title: {article['title']}
+Published: {article['published_at']}
+Summary: {article['summary']}
+News Site: {article['news_site']}
+URL: {article['url']}
+-------------------"""
+        return formatted
+
+    def add(self) -> None:
+        """Process and store the articles."""
         content = self.load_content()
-        # Process and store content
-        self.save_documents({"source": "api"})
-```
+        for _, text in content.items():
+            chunks = self._chunk_text(text)
+            self.chunks.extend(chunks)
+        
+        self.save_documents(metadata={
+            "source": "space_news_api",
+            "timestamp": datetime.now().isoformat(),
+            "article_count": self.limit
+        })
 
-### Embedder Configuration
+# Create knowledge source
+recent_news = SpaceNewsKnowledgeSource(
+    api_endpoint="https://api.spaceflightnewsapi.net/v4/articles",
+    limit=10,
+    metadata={"category": "recent_news", "source": "spaceflight_news"}
+)
 
-Customize the embedding process:
+# Create specialized agent
+space_analyst = Agent(
+    role="Space News Analyst",
+    goal="Answer questions about space news accurately and comprehensively",
+    backstory="""You are a space industry analyst with expertise in space exploration, 
+    satellite technology, and space industry trends. You excel at answering questions
+    about space news and providing detailed, accurate information.""",
+    knowledge_sources=[recent_news],
+    llm=LLM(model="gpt-4", temperature=0.0)
+)
 
-```python
+# Create task that handles user questions
+analysis_task = Task(
+    description="Answer this question about space news: {user_question}",
+    expected_output="A detailed answer based on the recent space news articles",
+    agent=space_analyst
+)
+
+# Create and run the crew
 crew = Crew(
-    agents=[agent],
-    tasks=[task],
-    knowledge_sources=[source],
-    embedder={
-        "provider": "ollama",
-        "config": {"model": "nomic-embed-text:latest"},
-    }
+    agents=[space_analyst],
+    tasks=[analysis_task],
+    verbose=True,
+    process=Process.sequential
+)
+
+# Example usage
+result = crew.kickoff(
+    inputs={"user_question": "What are the latest developments in space exploration?"}
 )
 ```
+```output Output
+# Agent: Space News Analyst
+## Task: Answer this question about space news: What are the latest developments in space exploration?
 
-### Referencing Sources
 
-You can reference knowledge sources by their collection name or metadata.
+# Agent: Space News Analyst
+## Final Answer: 
+The latest developments in space exploration, based on recent space news articles, include the following:
 
-* Add a directory to your crew project called `knowledge`:
-* File paths in knowledge can be referenced relative to the `knowledge` directory.
+1. SpaceX has received the final regulatory approvals to proceed with the second integrated Starship/Super Heavy launch, scheduled for as soon as the morning of Nov. 17, 2023. This is a significant step in SpaceX's ambitious plans for space exploration and colonization. [Source: SpaceNews](https://spacenews.com/starship-cleared-for-nov-17-launch/)
 
-Example:
-A file inside the `knowledge` directory called `example.txt` can be referenced as `example.txt`.
+2. SpaceX has also informed the US Federal Communications Commission (FCC) that it plans to begin launching its first next-generation Starlink Gen2 satellites. This represents a major upgrade to the Starlink satellite internet service, which aims to provide high-speed internet access worldwide. [Source: Teslarati](https://www.teslarati.com/spacex-first-starlink-gen2-satellite-launch-2022/)
 
+3. AI startup Synthetaic has raised $15 million in Series B funding. The company uses artificial intelligence to analyze data from space and air sensors, which could have significant applications in space exploration and satellite technology. [Source: SpaceNews](https://spacenews.com/ai-startup-synthetaic-raises-15-million-in-series-b-funding/)
+
+4. The Space Force has formally established a unit within the U.S. Indo-Pacific Command, marking a permanent presence in the Indo-Pacific region. This could have significant implications for space security and geopolitics. [Source: SpaceNews](https://spacenews.com/space-force-establishes-permanent-presence-in-indo-pacific-region/)
+
+5. Slingshot Aerospace, a space tracking and data analytics company, is expanding its network of ground-based optical telescopes to increase coverage of low Earth orbit. This could improve our ability to track and analyze objects in low Earth orbit, including satellites and space debris. [Source: SpaceNews](https://spacenews.com/slingshots-space-tracking-network-to-extend-coverage-of-low-earth-orbit/)
+
+6. The National Natural Science Foundation of China has outlined a five-year project for researchers to study the assembly of ultra-large spacecraft. This could lead to significant advancements in spacecraft technology and space exploration capabilities. [Source: SpaceNews](https://spacenews.com/china-researching-challenges-of-kilometer-scale-ultra-large-spacecraft/)
+
+7. The Center for AEroSpace Autonomy Research (CAESAR) at Stanford University is focusing on spacecraft autonomy. The center held a kickoff event on May 22, 2024, to highlight the industry, academia, and government collaboration it seeks to foster. This could lead to significant advancements in autonomous spacecraft technology. [Source: SpaceNews](https://spacenews.com/stanford-center-focuses-on-spacecraft-autonomy/)
+``` 
+</CodeGroup>
+#### Key Components Explained
+
+1. **Custom Knowledge Source (`SpaceNewsKnowledgeSource`)**:
+   - Extends `BaseKnowledgeSource` for integration with CrewAI
+   - Configurable API endpoint and article limit
+   - Implements three key methods:
+     - `load_content()`: Fetches articles from the API
+     - `_format_articles()`: Structures the articles into readable text
+     - `add()`: Processes and stores the content with metadata
+
+2. **Agent Configuration**:
+   - Specialized role as a Space News Analyst
+   - Uses the knowledge source to access space news
+
+3. **Task Setup**:
+   - Takes a user question as input through `{user_question}`
+   - Designed to provide detailed answers based on the knowledge source
+
+4. **Crew Orchestration**:
+   - Manages the workflow between agent and task
+   - Handles input/output through the kickoff method
+
+This example demonstrates how to:
+- Create a custom knowledge source that fetches real-time data
+- Process and format external data for AI consumption
+- Use the knowledge source to answer specific user questions
+- Integrate everything seamlessly with CrewAI's agent system
+
+#### About the Spaceflight News API
+
+The example uses the [Spaceflight News API](https://api.spaceflightnewsapi.net/v4/documentation), which:
+- Provides free access to space-related news articles
+- Requires no authentication
+- Returns structured data about space news
+- Supports pagination and filtering
+
+You can customize the API query by modifying the endpoint URL:
 ```python
-source = TextFileKnowledgeSource(
-    file_path="example.txt", # or /example.txt
-    collection_name="example"
+# Fetch more articles
+recent_news = SpaceNewsKnowledgeSource(
+    api_endpoint="https://api.spaceflightnewsapi.net/v4/articles",
+    limit=20,  # Increase the number of articles
+    metadata={"category": "recent_news"}
 )
-crew = Crew(
-    agents=[agent],
-    tasks=[task],
-    knowledge_sources=[source],
+
+# Add search parameters
+recent_news = SpaceNewsKnowledgeSource(
+    api_endpoint="https://api.spaceflightnewsapi.net/v4/articles?search=NASA", # Search for NASA news
+    limit=10,
+    metadata={"category": "nasa_news"}
 )
 ```
 
@@ -189,43 +314,16 @@ crew = Crew(
 
 <AccordionGroup>
   <Accordion title="Content Organization">
-    - Use meaningful collection names
-    - Add detailed metadata for filtering
-    - Keep chunk sizes appropriate for your content
+    - Use descriptive metadata for better filtering
+    - Keep chunk sizes appropriate for your content type
     - Consider content overlap for context preservation
+    - Organize related information into separate knowledge sources
   </Accordion>
   
   <Accordion title="Performance Tips">
-    - Use smaller chunk sizes for precise retrieval
-    - Implement metadata filtering for faster searches
-    - Choose appropriate embedding models for your use case
-    - Cache frequently accessed knowledge
+    - Use metadata filtering to narrow search scope
+    - Adjust chunk sizes based on content complexity
+    - Configure appropriate embedding models
+    - Consider using local embedding providers for faster processing
   </Accordion>
-  
-  <Accordion title="Error Handling">
-    - Validate knowledge source content
-    - Handle missing or corrupted files
-    - Monitor embedding generation
-    - Implement fallback options
-  </Accordion>
-</AccordionGroup>
-
-## Common Issues and Solutions
-
-<AccordionGroup>
-  <Accordion title="Content Not Found">
-    If agents can't find relevant information:
-    - Check chunk sizes
-    - Verify knowledge source loading
-    - Review metadata filters
-    - Test with simpler queries first
-  </Accordion>
-  
-  <Accordion title="Performance Issues">
-    If knowledge retrieval is slow:
-    - Reduce chunk sizes
-    - Optimize metadata filtering
-    - Consider using a lighter embedding model
-    - Cache frequently accessed content
-  </Accordion>
-</AccordionGroup>
+</AccordionGroup>
\ No newline at end of file

From 611526596a026a68f9657ca47479d546a80d6ca6 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Thu, 5 Dec 2024 10:14:04 -0500
Subject: [PATCH 102/126] Brandon/cre 509 hitl multiple rounds of followup
 (#1702)

* v1 of HITL working

* Drop print statements

* HITL code more robust. Still needs to be refactored.

* refactor and more clear messages

* Fix type issue

* fix tests

* Fix test again

* Drop extra print
---
 .../base_agent_executor_mixin.py              |  14 +-
 src/crewai/agents/crew_agent_executor.py      | 123 +++++--
 src/crewai/translations/en.json               |   3 +-
 src/crewai/utilities/constants.py             |   1 +
 tests/agent_test.py                           |  30 +-
 tests/cassettes/test_agent_human_input.yaml   | 321 +++++++++++++++---
 6 files changed, 403 insertions(+), 89 deletions(-)

diff --git a/src/crewai/agents/agent_builder/base_agent_executor_mixin.py b/src/crewai/agents/agent_builder/base_agent_executor_mixin.py
index c452848e8..19d5401a3 100644
--- a/src/crewai/agents/agent_builder/base_agent_executor_mixin.py
+++ b/src/crewai/agents/agent_builder/base_agent_executor_mixin.py
@@ -3,16 +3,15 @@ from typing import TYPE_CHECKING, Optional
 
 from crewai.memory.entity.entity_memory_item import EntityMemoryItem
 from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
+from crewai.utilities import I18N
 from crewai.utilities.converter import ConverterError
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
-from crewai.utilities import I18N
 from crewai.utilities.printer import Printer
 
-
 if TYPE_CHECKING:
+    from crewai.agents.agent_builder.base_agent import BaseAgent
     from crewai.crew import Crew
     from crewai.task import Task
-    from crewai.agents.agent_builder.base_agent import BaseAgent
 
 
 class CrewAgentExecutorMixin:
@@ -100,14 +99,19 @@ class CrewAgentExecutorMixin:
                 print(f"Failed to add to long term memory: {e}")
                 pass
 
-    def _ask_human_input(self, final_answer: dict) -> str:
+    def _ask_human_input(self, final_answer: str) -> str:
         """Prompt human input for final decision making."""
         self._printer.print(
             content=f"\033[1m\033[95m ## Final Result:\033[00m \033[92m{final_answer}\033[00m"
         )
 
         self._printer.print(
-            content="\n\n=====\n## Please provide feedback on the Final Result and the Agent's actions:",
+            content=(
+                "\n\n=====\n"
+                "## Please provide feedback on the Final Result and the Agent's actions. "
+                "Respond with 'looks good' or a similar phrase when you're satisfied.\n"
+                "=====\n"
+            ),
             color="bold_yellow",
         )
         return input()
diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index 2c880a634..00545e760 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -16,7 +16,7 @@ from crewai.agents.tools_handler import ToolsHandler
 from crewai.tools.base_tool import BaseTool
 from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
 from crewai.utilities import I18N, Printer
-from crewai.utilities.constants import TRAINING_DATA_FILE
+from crewai.utilities.constants import MAX_LLM_RETRY, TRAINING_DATA_FILE
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -90,7 +90,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         if "system" in self.prompt:
             system_prompt = self._format_prompt(self.prompt.get("system", ""), inputs)
             user_prompt = self._format_prompt(self.prompt.get("user", ""), inputs)
-
             self.messages.append(self._format_msg(system_prompt, role="system"))
             self.messages.append(self._format_msg(user_prompt))
         else:
@@ -103,17 +102,8 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         formatted_answer = self._invoke_loop()
 
         if self.ask_for_human_input:
-            human_feedback = self._ask_human_input(formatted_answer.output)
-            if self.crew and self.crew._train:
-                self._handle_crew_training_output(formatted_answer, human_feedback)
+            formatted_answer = self._handle_human_feedback(formatted_answer)
 
-            # Making sure we only ask for it once, so disabling for the next thought loop
-            self.ask_for_human_input = False
-            self.messages.append(self._format_msg(f"Feedback: {human_feedback}"))
-            formatted_answer = self._invoke_loop()
-
-            if self.crew and self.crew._train:
-                self._handle_crew_training_output(formatted_answer)
         self._create_short_term_memory(formatted_answer)
         self._create_long_term_memory(formatted_answer)
         return {"output": formatted_answer.output}
@@ -326,16 +316,14 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
     def _handle_context_length(self) -> None:
         if self.respect_context_window:
-            self._logger.log(
-                "debug",
-                "Context length exceeded. Summarizing content to fit the model context window.",
+            self._printer.print(
+                content="Context length exceeded. Summarizing content to fit the model context window.",
                 color="yellow",
             )
             self._summarize_messages()
         else:
-            self._logger.log(
-                "debug",
-                "Context length exceeded. Consider using smaller text or RAG tools from crewai_tools.",
+            self._printer.print(
+                content="Context length exceeded. Consider using smaller text or RAG tools from crewai_tools.",
                 color="red",
             )
             raise SystemExit(
@@ -362,15 +350,13 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                     ] = result.output
                     training_handler.save(training_data)
                 else:
-                    self._logger.log(
-                        "error",
-                        "Invalid train iteration type or agent_id not in training data.",
+                    self._printer.print(
+                        content="Invalid train iteration type or agent_id not in training data.",
                         color="red",
                     )
             else:
-                self._logger.log(
-                    "error",
-                    "Crew is None or does not have _train_iteration attribute.",
+                self._printer.print(
+                    content="Crew is None or does not have _train_iteration attribute.",
                     color="red",
                 )
 
@@ -388,15 +374,13 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         train_iteration, agent_id, training_data
                     )
                 else:
-                    self._logger.log(
-                        "error",
-                        "Invalid train iteration type. Expected int.",
+                    self._printer.print(
+                        content="Invalid train iteration type. Expected int.",
                         color="red",
                     )
             else:
-                self._logger.log(
-                    "error",
-                    "Crew is None or does not have _train_iteration attribute.",
+                self._printer.print(
+                    content="Crew is None or does not have _train_iteration attribute.",
                     color="red",
                 )
 
@@ -412,3 +396,82 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
     def _format_msg(self, prompt: str, role: str = "user") -> Dict[str, str]:
         prompt = prompt.rstrip()
         return {"role": role, "content": prompt}
+
+    def _handle_human_feedback(self, formatted_answer: AgentFinish) -> AgentFinish:
+        """
+        Handles the human feedback loop, allowing the user to provide feedback
+        on the agent's output and determining if additional iterations are needed.
+
+        Parameters:
+            formatted_answer (AgentFinish): The initial output from the agent.
+
+        Returns:
+            AgentFinish: The final output after incorporating human feedback.
+        """
+        while self.ask_for_human_input:
+            human_feedback = self._ask_human_input(formatted_answer.output)
+            print("Human feedback: ", human_feedback)
+
+            if self.crew and self.crew._train:
+                self._handle_crew_training_output(formatted_answer, human_feedback)
+
+            # Make an LLM call to verify if additional changes are requested based on human feedback
+            additional_changes_prompt = self._i18n.slice(
+                "human_feedback_classification"
+            ).format(feedback=human_feedback)
+
+            retry_count = 0
+            llm_call_successful = False
+            additional_changes_response = None
+
+            while retry_count < MAX_LLM_RETRY and not llm_call_successful:
+                try:
+                    additional_changes_response = (
+                        self.llm.call(
+                            [
+                                self._format_msg(
+                                    additional_changes_prompt, role="system"
+                                )
+                            ],
+                            callbacks=self.callbacks,
+                        )
+                        .strip()
+                        .lower()
+                    )
+                    llm_call_successful = True
+                except Exception as e:
+                    retry_count += 1
+
+                    self._printer.print(
+                        content=f"Error during LLM call to classify human feedback: {e}. Retrying... ({retry_count}/{MAX_LLM_RETRY})",
+                        color="red",
+                    )
+
+            if not llm_call_successful:
+                self._printer.print(
+                    content="Error processing feedback after multiple attempts.",
+                    color="red",
+                )
+                self.ask_for_human_input = False
+                break
+
+            if additional_changes_response == "false":
+                self.ask_for_human_input = False
+            elif additional_changes_response == "true":
+                self.ask_for_human_input = True
+                # Add human feedback to messages
+                self.messages.append(self._format_msg(f"Feedback: {human_feedback}"))
+                # Invoke the loop again with updated messages
+                formatted_answer = self._invoke_loop()
+
+                if self.crew and self.crew._train:
+                    self._handle_crew_training_output(formatted_answer)
+            else:
+                # Unexpected response
+                self._printer.print(
+                    content=f"Unexpected response from LLM: '{additional_changes_response}'. Assuming no additional changes requested.",
+                    color="red",
+                )
+                self.ask_for_human_input = False
+
+        return formatted_answer
diff --git a/src/crewai/translations/en.json b/src/crewai/translations/en.json
index d79076bb7..d30606dc0 100644
--- a/src/crewai/translations/en.json
+++ b/src/crewai/translations/en.json
@@ -22,7 +22,8 @@
     "sumamrize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
     "summary": "This is a summary of our conversation so far:\n{merged_summary}",
     "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
-    "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python."
+    "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",
+    "human_feedback_classification": "Determine if the following feedback indicates that the user is satisfied or if further changes are needed. Respond with 'True' if further changes are needed, or 'False' if the user is satisfied. **Important** Do not include any additional commentary outside of your 'True' or 'False' response.\n\nFeedback: \"{feedback}\""
   },
   "errors": {
     "force_final_answer_error": "You can't keep going, this was the best you could do.\n {formatted_answer.text}",
diff --git a/src/crewai/utilities/constants.py b/src/crewai/utilities/constants.py
index 97fadda48..3578b7ece 100644
--- a/src/crewai/utilities/constants.py
+++ b/src/crewai/utilities/constants.py
@@ -2,3 +2,4 @@ TRAINING_DATA_FILE = "training_data.pkl"
 TRAINED_AGENTS_DATA_FILE = "trained_agents_data.pkl"
 DEFAULT_SCORE_THRESHOLD = 0.35
 KNOWLEDGE_DIRECTORY = "knowledge"
+MAX_LLM_RETRY = 3
diff --git a/tests/agent_test.py b/tests/agent_test.py
index 1f4b62fd0..46f6edc29 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -3,19 +3,20 @@
 import os
 from unittest import mock
 from unittest.mock import patch
+
 import pytest
 
 from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.llm import LLM
 from crewai.tools import tool
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
 from crewai.tools.tool_usage_events import ToolUsageFinished
 from crewai.utilities import RPMController
-from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.utilities.events import Emitter
 
 
@@ -985,8 +986,7 @@ def test_agent_definition_based_on_dict():
 # test for human input
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_human_input():
-    from unittest.mock import patch
-
+    # Agent configuration
     config = {
         "role": "test role",
         "goal": "test goal",
@@ -995,6 +995,7 @@ def test_agent_human_input():
 
     agent = Agent(**config)
 
+    # Task configuration with human input enabled
     task = Task(
         agent=agent,
         description="Say the word: Hi",
@@ -1002,11 +1003,26 @@ def test_agent_human_input():
         human_input=True,
     )
 
-    with patch.object(CrewAgentExecutor, "_ask_human_input") as mock_human_input:
-        mock_human_input.return_value = "Don't say hi, say Hello instead!"
+    # Side effect function for _ask_human_input to simulate multiple feedback iterations
+    feedback_responses = iter(
+        [
+            "Don't say hi, say Hello instead!",  # First feedback
+            "looks good",  # Second feedback to exit loop
+        ]
+    )
+
+    def ask_human_input_side_effect(*args, **kwargs):
+        return next(feedback_responses)
+
+    with patch.object(
+        CrewAgentExecutor, "_ask_human_input", side_effect=ask_human_input_side_effect
+    ) as mock_human_input:
+        # Execute the task
         output = agent.execute_task(task)
-        mock_human_input.assert_called_once()
-        assert output == "Hello"
+
+        # Assertions to ensure the agent behaves correctly
+        assert mock_human_input.call_count == 2  # Should have asked for feedback twice
+        assert output.strip().lower() == "hello"  # Final output should be 'Hello'
 
 
 def test_interpolate_inputs():
diff --git a/tests/cassettes/test_agent_human_input.yaml b/tests/cassettes/test_agent_human_input.yaml
index 4a336247e..16b9ac9a5 100644
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From b0f1d1fcf0a89f21cf537af211fbb1e3d8f2d9f6 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Thu, 5 Dec 2024 11:23:20 -0500
Subject: [PATCH 103/126] =?UTF-8?q?New=20docs=20about=20yaml=20crew=20with?=
 =?UTF-8?q?=20decorators.=20Simplify=20template=20crew=20with=E2=80=A6=20(?=
 =?UTF-8?q?#1701)?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* New docs about yaml crew with decorators. Simplify template crew with links

* Fix spelling issues.
---
 docs/concepts/crews.mdx                       | 151 +++++++++++++++++-
 src/crewai/cli/templates/crew/crew.py         |  43 ++---
 .../flow/crews/poem_crew/poem_crew.py         |  62 ++++---
 3 files changed, 203 insertions(+), 53 deletions(-)

diff --git a/docs/concepts/crews.mdx b/docs/concepts/crews.mdx
index ec0f190de..3225b48b6 100644
--- a/docs/concepts/crews.mdx
+++ b/docs/concepts/crews.mdx
@@ -41,6 +41,155 @@ A crew in crewAI represents a collaborative group of agents working together to
 **Crew Max RPM**: The `max_rpm` attribute sets the maximum number of requests per minute the crew can perform to avoid rate limits and will override individual agents' `max_rpm` settings if you set it.
 </Tip>
 
+## Creating Crews
+
+There are two ways to create crews in CrewAI: using **YAML configuration (recommended)** or defining them **directly in code**.
+
+### YAML Configuration (Recommended)
+
+Using YAML configuration provides a cleaner, more maintainable way to define crews and is consistent with how agents and tasks are defined in CrewAI projects.
+
+After creating your CrewAI project as outlined in the [Installation](/installation) section, you can define your crew in a class that inherits from `CrewBase` and uses decorators to define agents, tasks, and the crew itself.
+
+#### Example Crew Class with Decorators
+
+```python code
+from crewai import Agent, Crew, Task, Process
+from crewai.project import CrewBase, agent, task, crew, before_kickoff, after_kickoff
+
+
+@CrewBase
+class YourCrewName:
+    """Description of your crew"""
+
+    # Paths to your YAML configuration files
+    # To see an example agent and task defined in YAML, checkout the following:
+    # - Task: https://docs.crewai.com/concepts/tasks#yaml-configuration-recommended
+    # - Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended
+    agents_config = 'config/agents.yaml' 
+    tasks_config = 'config/tasks.yaml' 
+
+    @before_kickoff
+    def prepare_inputs(self, inputs):
+        # Modify inputs before the crew starts
+        inputs['additional_data'] = "Some extra information"
+        return inputs
+
+    @after_kickoff
+    def process_output(self, output):
+        # Modify output after the crew finishes
+        output.raw += "\nProcessed after kickoff."
+        return output
+
+    @agent
+    def agent_one(self) -> Agent:
+        return Agent(
+            config=self.agents_config['agent_one'],
+            verbose=True
+        )
+
+    @agent
+    def agent_two(self) -> Agent:
+        return Agent(
+            config=self.agents_config['agent_two'],
+            verbose=True
+        )
+
+    @task
+    def task_one(self) -> Task:
+        return Task(
+            config=self.tasks_config['task_one']
+        )
+
+    @task
+    def task_two(self) -> Task:
+        return Task(
+            config=self.tasks_config['task_two']
+        )
+
+    @crew
+    def crew(self) -> Crew:
+        return Crew(
+            agents=self.agents,  # Automatically collected by the @agent decorator
+            tasks=self.tasks,    # Automatically collected by the @task decorator. 
+            process=Process.sequential,
+            verbose=True,
+        )
+```
+
+<Note>
+Tasks will be executed in the order they are defined.
+</Note>
+
+The `CrewBase` class, along with these decorators, automates the collection of agents and tasks, reducing the need for manual management.
+
+#### Decorators overview from `annotations.py`
+
+CrewAI provides several decorators in the `annotations.py` file that are used to mark methods within your crew class for special handling:
+
+- `@CrewBase`: Marks the class as a crew base class.
+- `@agent`: Denotes a method that returns an `Agent` object.
+- `@task`: Denotes a method that returns a `Task` object.
+- `@crew`: Denotes the method that returns the `Crew` object.
+- `@before_kickoff`: (Optional) Marks a method to be executed before the crew starts.
+- `@after_kickoff`: (Optional) Marks a method to be executed after the crew finishes.
+
+These decorators help in organizing your crew's structure and automatically collecting agents and tasks without manually listing them.
+
+### Direct Code Definition (Alternative)
+
+Alternatively, you can define the crew directly in code without using YAML configuration files.
+
+```python code
+from crewai import Agent, Crew, Task, Process
+from crewai_tools import YourCustomTool
+
+class YourCrewName:
+    def agent_one(self) -> Agent:
+        return Agent(
+            role="Data Analyst",
+            goal="Analyze data trends in the market",
+            backstory="An experienced data analyst with a background in economics",
+            verbose=True,
+            tools=[YourCustomTool()]
+        )
+
+    def agent_two(self) -> Agent:
+        return Agent(
+            role="Market Researcher",
+            goal="Gather information on market dynamics",
+            backstory="A diligent researcher with a keen eye for detail",
+            verbose=True
+        )
+
+    def task_one(self) -> Task:
+        return Task(
+            description="Collect recent market data and identify trends.",
+            expected_output="A report summarizing key trends in the market.",
+            agent=self.agent_one()
+        )
+
+    def task_two(self) -> Task:
+        return Task(
+            description="Research factors affecting market dynamics.",
+            expected_output="An analysis of factors influencing the market.",
+            agent=self.agent_two()
+        )
+
+    def crew(self) -> Crew:
+        return Crew(
+            agents=[self.agent_one(), self.agent_two()],
+            tasks=[self.task_one(), self.task_two()],
+            process=Process.sequential,
+            verbose=True
+        )
+```
+
+In this example:
+
+- Agents and tasks are defined directly within the class without decorators.
+- We manually create and manage the list of agents and tasks.
+- This approach provides more control but can be less maintainable for larger projects.
 
 ## Crew Output
 
@@ -188,4 +337,4 @@ Then, to replay from a specific task, use:
 crewai replay -t <task_id>
 ```
 
-These commands let you replay from your latest kickoff tasks, still retaining context from previously executed tasks.
\ No newline at end of file
+These commands let you replay from your latest kickoff tasks, still retaining context from previously executed tasks.
diff --git a/src/crewai/cli/templates/crew/crew.py b/src/crewai/cli/templates/crew/crew.py
index 0a8c7481a..383bfac48 100644
--- a/src/crewai/cli/templates/crew/crew.py
+++ b/src/crewai/cli/templates/crew/crew.py
@@ -1,37 +1,26 @@
 from crewai import Agent, Crew, Process, Task
-from crewai.project import CrewBase, agent, crew, task, before_kickoff, after_kickoff
-# Uncomment the following line to use an example of a custom tool
-# from {{folder_name}}.tools.custom_tool import MyCustomTool
-# Uncomment the following line to use an example of a knowledge source
-# from crewai.knowledge.source.text_file_knowledge_source import TextFileKnowledgeSource
+from crewai.project import CrewBase, agent, crew, task
 
-# Check our tools documentations for more information on how to use them
-# from crewai_tools import SerperDevTool
+# If you want to run a snippet of code before or after the crew starts, 
+# you can use the @before_kickoff and @after_kickoff decorators
+# https://docs.crewai.com/concepts/crews#example-crew-class-with-decorators
 
 @CrewBase
 class {{crew_name}}():
 	"""{{crew_name}} crew"""
 
+	# Learn more about YAML configuration files here:
+	# Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended
+	# Tasks: https://docs.crewai.com/concepts/tasks#yaml-configuration-recommended
 	agents_config = 'config/agents.yaml'
 	tasks_config = 'config/tasks.yaml'
 
-	@before_kickoff # Optional hook to be executed before the crew starts
-	def pull_data_example(self, inputs):
-		# Example of pulling data from an external API, dynamically changing the inputs
-		inputs['extra_data'] = "This is extra data"
-		return inputs
-
-	@after_kickoff # Optional hook to be executed after the crew has finished
-	def log_results(self, output):
-		# Example of logging results, dynamically changing the output
-		print(f"Results: {output}")
-		return output
-
+	# If you would like to add tools to your agents, you can learn more about it here:
+	# https://docs.crewai.com/concepts/agents#agent-tools
 	@agent
 	def researcher(self) -> Agent:
 		return Agent(
 			config=self.agents_config['researcher'],
-			# tools=[MyCustomTool()], # Example of custom tool, loaded on the beginning of file
 			verbose=True
 		)
 
@@ -42,6 +31,9 @@ class {{crew_name}}():
 			verbose=True
 		)
 
+	# To learn more about structured task outputs, 
+	# task dependencies, and task callbacks, check out the documentation:
+	# https://docs.crewai.com/concepts/tasks#overview-of-a-task
 	@task
 	def research_task(self) -> Task:
 		return Task(
@@ -58,14 +50,8 @@ class {{crew_name}}():
 	@crew
 	def crew(self) -> Crew:
 		"""Creates the {{crew_name}} crew"""
-		# You can add knowledge sources here
-		# knowledge_path = "user_preference.txt"
-		# sources = [
-		# 	TextFileKnowledgeSource(
-		# 		file_path="knowledge/user_preference.txt",
-		# 		metadata={"preference": "personal"}
-		# 	),
-		# ]
+		# To learn how to add knowledge sources to your crew, check out the documentation:
+		# https://docs.crewai.com/concepts/knowledge#what-is-knowledge
 
 		return Crew(
 			agents=self.agents, # Automatically created by the @agent decorator
@@ -73,5 +59,4 @@ class {{crew_name}}():
 			process=Process.sequential,
 			verbose=True,
 			# process=Process.hierarchical, # In case you wanna use that instead https://docs.crewai.com/how-to/Hierarchical/
-			# knowledge_sources=sources, # In the case you want to add knowledge sources
 		)
diff --git a/src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py b/src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py
index cc3ce7150..5e978d985 100644
--- a/src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py
+++ b/src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py
@@ -1,31 +1,47 @@
 from crewai import Agent, Crew, Process, Task
 from crewai.project import CrewBase, agent, crew, task
 
+# If you want to run a snippet of code before or after the crew starts,
+# you can use the @before_kickoff and @after_kickoff decorators
+# https://docs.crewai.com/concepts/crews#example-crew-class-with-decorators
+
+
 @CrewBase
-class PoemCrew():
-	"""Poem Crew"""
+class PoemCrew:
+    """Poem Crew"""
 
-	agents_config = 'config/agents.yaml'
-	tasks_config = 'config/tasks.yaml'
+    # Learn more about YAML configuration files here:
+    # Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended
+    # Tasks: https://docs.crewai.com/concepts/tasks#yaml-configuration-recommended
+    agents_config = "config/agents.yaml"
+    tasks_config = "config/tasks.yaml"
 
-	@agent
-	def poem_writer(self) -> Agent:
-		return Agent(
-			config=self.agents_config['poem_writer'],
-		)
+    # If you would lik to add tools to your crew, you can learn more about it here:
+    # https://docs.crewai.com/concepts/agents#agent-tools
+    @agent
+    def poem_writer(self) -> Agent:
+        return Agent(
+            config=self.agents_config["poem_writer"],
+        )
 
-	@task
-	def write_poem(self) -> Task:
-		return Task(
-			config=self.tasks_config['write_poem'],
-		)
+    # To learn more about structured task outputs,
+    # task dependencies, and task callbacks, check out the documentation:
+    # https://docs.crewai.com/concepts/tasks#overview-of-a-task
+    @task
+    def write_poem(self) -> Task:
+        return Task(
+            config=self.tasks_config["write_poem"],
+        )
 
-	@crew
-	def crew(self) -> Crew:
-		"""Creates the Research Crew"""
-		return Crew(
-			agents=self.agents, # Automatically created by the @agent decorator
-			tasks=self.tasks, # Automatically created by the @task decorator
-			process=Process.sequential,
-			verbose=True,
-		)
+    @crew
+    def crew(self) -> Crew:
+        """Creates the Research Crew"""
+        # To learn how to add knowledge sources to your crew, check out the documentation:
+        # https://docs.crewai.com/concepts/knowledge#what-is-knowledge
+
+        return Crew(
+            agents=self.agents,  # Automatically created by the @agent decorator
+            tasks=self.tasks,  # Automatically created by the @task decorator
+            process=Process.sequential,
+            verbose=True,
+        )

From 2c85e8e23a912ef963c9348d31f49e9ad91f33b2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Thu, 5 Dec 2024 13:51:09 -0300
Subject: [PATCH 104/126] updating tools

---
 pyproject.toml | 2 +-
 uv.lock        | 9 ++++-----
 2 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 86891294c..e82e5e6c9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,7 +15,7 @@ dependencies = [
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
     "instructor>=1.3.3",
     "regex>=2024.9.11",
-    "crewai-tools>=0.14.0",
+    "crewai-tools>=0.17.0",
     "click>=8.1.7",
     "python-dotenv>=1.0.0",
     "appdirs>=1.4.4",
diff --git a/uv.lock b/uv.lock
index 900e730da..bca7a9c03 100644
--- a/uv.lock
+++ b/uv.lock
@@ -685,7 +685,7 @@ requires-dist = [
     { name = "auth0-python", specifier = ">=4.7.1" },
     { name = "chromadb", specifier = ">=0.5.18" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", specifier = ">=0.14.0" },
+    { name = "crewai-tools", specifier = ">=0.17.0" },
     { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.14.0" },
     { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
     { name = "instructor", specifier = ">=1.3.3" },
@@ -733,7 +733,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.14.0"
+version = "0.17.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "beautifulsoup4" },
@@ -742,7 +742,6 @@ dependencies = [
     { name = "docx2txt" },
     { name = "embedchain" },
     { name = "lancedb" },
-    { name = "langchain" },
     { name = "openai" },
     { name = "pydantic" },
     { name = "pyright" },
@@ -751,9 +750,9 @@ dependencies = [
     { name = "requests" },
     { name = "selenium" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/9b/6d/4fa91b481b120f83bb58f365203d8aa8564e8ced1035d79f8aedb7d71e2f/crewai_tools-0.14.0.tar.gz", hash = "sha256:510f3a194bcda4fdae4314bd775521964b5f229ddbe451e5d9e0216cae57f4e3", size = 815892 }
+sdist = { url = "https://files.pythonhosted.org/packages/cc/15/365f74e0e8313e7a3399bf01d908aa73575c823275f9196ec14c23159878/crewai_tools-0.17.0.tar.gz", hash = "sha256:2a2986000775c76bad45b9f3a2be857d293cf5daffe5f316abc052e630b1e5ce", size = 818983 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c8/ed/9f4e64e1507062957b0118085332d38b621c1000874baef2d1c4069bfd97/crewai_tools-0.14.0-py3-none-any.whl", hash = "sha256:0a804a828c29869c3af3253f4fc4c3967a3f80f06dab22e9bbe9526608a31564", size = 462980 },
+    { url = "https://files.pythonhosted.org/packages/f4/1d/976adc2a4e5237cb03625de412cd051dea7d524084ed442adedfda871526/crewai_tools-0.17.0-py3-none-any.whl", hash = "sha256:85cf15286684ecad579b5a497888c6bf8a079ca443f7dd63a52bf1709655e4a3", size = 467975 },
 ]
 
 [[package]]

From 3daba0c79e3ca377a1f57fde6852793136cbea54 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Moura?= <joaomdmoura@gmail.com>
Date: Thu, 5 Dec 2024 13:53:10 -0300
Subject: [PATCH 105/126] curting new verson

---
 pyproject.toml                                  |  2 +-
 src/crewai/__init__.py                          |  2 +-
 src/crewai/cli/templates/crew/pyproject.toml    |  2 +-
 src/crewai/cli/templates/flow/pyproject.toml    |  2 +-
 .../cli/templates/pipeline/pyproject.toml       | 17 +++++++++++++++++
 src/crewai/cli/templates/tool/pyproject.toml    |  2 +-
 uv.lock                                         |  2 +-
 7 files changed, 23 insertions(+), 6 deletions(-)
 create mode 100644 src/crewai/cli/templates/pipeline/pyproject.toml

diff --git a/pyproject.toml b/pyproject.toml
index e82e5e6c9..cac8bab9b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.85.0"
+version = "0.86.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index a6ec565e9..0833afd58 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,7 +14,7 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.85.0"
+__version__ = "0.86.0"
 __all__ = [
     "Agent",
     "Crew",
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index e45732685..d9ac06cd0 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.85.0,<1.0.0"
+    "crewai[tools]>=0.86.0,<1.0.0"
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index d981987c8..ba4f4a823 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.85.0,<1.0.0",
+    "crewai[tools]>=0.86.0,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
new file mode 100644
index 000000000..97abd41a5
--- /dev/null
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -0,0 +1,17 @@
+[tool.poetry]
+name = "{{folder_name}}"
+version = "0.1.0"
+description = "{{name}} using crewAI"
+authors = ["Your Name <you@example.com>"]
+
+[tool.poetry.dependencies]
+python = ">=3.10,<=3.13"
+crewai = { extras = ["tools"], version = ">=0.86.0,<1.0.0" }
+asyncio = "*"
+
+[tool.poetry.scripts]
+{{folder_name}} = "{{folder_name}}.main:main"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
\ No newline at end of file
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 33dabd38e..585bbef38 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<=3.13"
 dependencies = [
-    "crewai[tools]>=0.85.0"
+    "crewai[tools]>=0.86.0"
 ]
 
diff --git a/uv.lock b/uv.lock
index bca7a9c03..42fb38424 100644
--- a/uv.lock
+++ b/uv.lock
@@ -608,7 +608,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.85.0"
+version = "0.86.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },

From 7b276e67978b82ae7a160ee0762072da94ead8a2 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Thu, 5 Dec 2024 12:17:23 -0500
Subject: [PATCH 106/126] Incorporate Stale PRs that have feedback (#1693)

* incorporate #1683

* add in --version flag to cli. closes #1679.

* Fix env issue

* Add in suggestions from @caike to make sure ragstorage doesnt exceed os file limit. Also, included additional checks to support windows.

* remove poetry.lock as pointed out by @sanders41 in #1574.

* Incorporate feedback from crewai reviewer

* Incorporate @lorenzejay feedback
---
 src/crewai/agent.py                      | 21 ++++++------------
 src/crewai/cli/cli.py                    |  6 +++++-
 src/crewai/cli/constants.py              |  3 +++
 src/crewai/memory/storage/rag_storage.py | 27 ++++++++++++++++++++----
 src/crewai/utilities/constants.py        |  1 +
 tests/cli/cli_test.py                    |  7 ++++++
 6 files changed, 45 insertions(+), 20 deletions(-)

diff --git a/src/crewai/agent.py b/src/crewai/agent.py
index abe678db1..8c79c6eb8 100644
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -8,7 +8,7 @@ from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 from crewai.agents import CacheHandler
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
-from crewai.cli.constants import ENV_VARS
+from crewai.cli.constants import ENV_VARS, LITELLM_PARAMS
 from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.knowledge.utils.knowledge_utils import extract_knowledge_context
@@ -181,20 +181,11 @@ class Agent(BaseAgent):
                         if key_name and key_name not in unaccepted_attributes:
                             env_value = os.environ.get(key_name)
                             if env_value:
-                                # Map key names containing "API_KEY" to "api_key"
-                                key_name = (
-                                    "api_key" if "API_KEY" in key_name else key_name
-                                )
-                                # Map key names containing "API_BASE" to "api_base"
-                                key_name = (
-                                    "api_base" if "API_BASE" in key_name else key_name
-                                )
-                                # Map key names containing "API_VERSION" to "api_version"
-                                key_name = (
-                                    "api_version"
-                                    if "API_VERSION" in key_name
-                                    else key_name
-                                )
+                                key_name = key_name.lower()
+                                for pattern in LITELLM_PARAMS:
+                                    if pattern in key_name:
+                                        key_name = pattern
+                                        break
                                 llm_params[key_name] = env_value
                         # Check for default values if the environment variable is not set
                         elif env_var.get("default", False):
diff --git a/src/crewai/cli/cli.py b/src/crewai/cli/cli.py
index 6e8560133..43dc90eed 100644
--- a/src/crewai/cli/cli.py
+++ b/src/crewai/cli/cli.py
@@ -25,6 +25,7 @@ from .update_crew import update_crew
 
 
 @click.group()
+@click.version_option(pkg_resources.get_distribution("crewai").version)
 def crewai():
     """Top-level command group for crewai."""
 
@@ -50,7 +51,10 @@ def create(type, name, provider, skip_provider=False):
 )
 def version(tools):
     """Show the installed version of crewai."""
-    crewai_version = pkg_resources.get_distribution("crewai").version
+    try:
+        crewai_version = pkg_resources.get_distribution("crewai").version
+    except Exception:
+        crewai_version = "unknown version"
     click.echo(f"crewai version: {crewai_version}")
 
     if tools:
diff --git a/src/crewai/cli/constants.py b/src/crewai/cli/constants.py
index e13349155..13279f8d3 100644
--- a/src/crewai/cli/constants.py
+++ b/src/crewai/cli/constants.py
@@ -159,3 +159,6 @@ MODELS = {
 }
 
 JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
+
+
+LITELLM_PARAMS = ["api_key", "api_base", "api_version"]
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index ded340a19..bf40aee96 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -4,12 +4,14 @@ import logging
 import os
 import shutil
 import uuid
-
 from typing import Any, Dict, List, Optional
+
 from chromadb.api import ClientAPI
+
 from crewai.memory.storage.base_rag_storage import BaseRAGStorage
-from crewai.utilities.paths import db_storage_path
 from crewai.utilities import EmbeddingConfigurator
+from crewai.utilities.constants import MAX_FILE_NAME_LENGTH
+from crewai.utilities.paths import db_storage_path
 
 
 @contextlib.contextmanager
@@ -37,12 +39,15 @@ class RAGStorage(BaseRAGStorage):
 
     app: ClientAPI | None = None
 
-    def __init__(self, type, allow_reset=True, embedder_config=None, crew=None, path=None):
+    def __init__(
+        self, type, allow_reset=True, embedder_config=None, crew=None, path=None
+    ):
         super().__init__(type, allow_reset, embedder_config, crew)
         agents = crew.agents if crew else []
         agents = [self._sanitize_role(agent.role) for agent in agents]
         agents = "_".join(agents)
         self.agents = agents
+        self.storage_file_name = self._build_storage_file_name(type, agents)
 
         self.type = type
 
@@ -60,7 +65,7 @@ class RAGStorage(BaseRAGStorage):
 
         self._set_embedder_config()
         chroma_client = chromadb.PersistentClient(
-            path=self.path if self.path else f"{db_storage_path()}/{self.type}/{self.agents}",
+            path=self.path if self.path else self.storage_file_name,
             settings=Settings(allow_reset=self.allow_reset),
         )
 
@@ -81,6 +86,20 @@ class RAGStorage(BaseRAGStorage):
         """
         return role.replace("\n", "").replace(" ", "_").replace("/", "_")
 
+    def _build_storage_file_name(self, type: str, file_name: str) -> str:
+        """
+        Ensures file name does not exceed max allowed by OS
+        """
+        base_path = f"{db_storage_path()}/{type}"
+
+        if len(file_name) > MAX_FILE_NAME_LENGTH:
+            logging.warning(
+                f"Trimming file name from {len(file_name)} to {MAX_FILE_NAME_LENGTH} characters."
+            )
+            file_name = file_name[:MAX_FILE_NAME_LENGTH]
+
+        return f"{base_path}/{file_name}"
+
     def save(self, value: Any, metadata: Dict[str, Any]) -> None:
         if not hasattr(self, "app") or not hasattr(self, "collection"):
             self._initialize_app()
diff --git a/src/crewai/utilities/constants.py b/src/crewai/utilities/constants.py
index 3578b7ece..096bb7c8c 100644
--- a/src/crewai/utilities/constants.py
+++ b/src/crewai/utilities/constants.py
@@ -3,3 +3,4 @@ TRAINED_AGENTS_DATA_FILE = "trained_agents_data.pkl"
 DEFAULT_SCORE_THRESHOLD = 0.35
 KNOWLEDGE_DIRECTORY = "knowledge"
 MAX_LLM_RETRY = 3
+MAX_FILE_NAME_LENGTH = 255
diff --git a/tests/cli/cli_test.py b/tests/cli/cli_test.py
index 05e1cf03a..15ed81637 100644
--- a/tests/cli/cli_test.py
+++ b/tests/cli/cli_test.py
@@ -131,6 +131,13 @@ def test_reset_no_memory_flags(runner):
     )
 
 
+def test_version_flag(runner):
+    result = runner.invoke(version)
+
+    assert result.exit_code == 0
+    assert "crewai version:" in result.output
+
+
 def test_version_command(runner):
     result = runner.invoke(version)
 

From c7c0647dd225d655d928ec9cc96c6b933ad77e0e Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Thu, 5 Dec 2024 14:59:52 -0500
Subject: [PATCH 107/126] drop metadata requirement (#1712)

* drop metadata requirement

* fix linting

* Update docs for new knowledge

* more linting

* more linting

* make save_documents private

* update docs to the new way we use knowledge and include clearing memory
---
 docs/concepts/knowledge.mdx                   | 67 +++++++------------
 src/crewai/knowledge/knowledge.py             |  9 +--
 .../source/base_file_knowledge_source.py      |  9 ++-
 .../knowledge/source/base_knowledge_source.py |  8 +--
 .../knowledge/source/csv_knowledge_source.py  |  4 +-
 .../source/excel_knowledge_source.py          |  5 +-
 .../knowledge/source/json_knowledge_source.py |  4 +-
 .../knowledge/source/pdf_knowledge_source.py  |  4 +-
 .../source/string_knowledge_source.py         |  2 +-
 .../source/text_file_knowledge_source.py      |  4 +-
 .../knowledge/storage/knowledge_storage.py    | 25 ++++---
 11 files changed, 63 insertions(+), 78 deletions(-)

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index 06c2eb947..96200b356 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -48,7 +48,6 @@ from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSourc
 content = "Users name is John. He is 30 years old and lives in San Francisco."
 string_source = StringKnowledgeSource(
     content=content, 
-    metadata={"preference": "personal"}
 )
 
 # Create an LLM with a temperature of 0 to ensure deterministic outputs
@@ -74,10 +73,7 @@ crew = Crew(
     tasks=[task],
     verbose=True,
     process=Process.sequential,
-    knowledge={
-      "sources": [string_source], 
-      "metadata": {"preference": "personal"}
-    }, # Enable knowledge by adding the sources here. You can also add more sources to the sources list.
+    knowledge_sources=[string_source], # Enable knowledge by adding the sources here. You can also add more sources to the sources list.
 )
 
 result = crew.kickoff(inputs={"question": "What city does John live in and how old is he?"})
@@ -85,17 +81,6 @@ result = crew.kickoff(inputs={"question": "What city does John live in and how o
 
 ## Knowledge Configuration
 
-### Metadata and Filtering
-
-Knowledge sources support metadata for better organization and filtering. Metadata is used to filter the knowledge sources when querying the knowledge store.
-
-```python Code
-knowledge_source = StringKnowledgeSource(
-    content="Users name is John. He is 30 years old and lives in San Francisco.",
-    metadata={"preference": "personal"} # Metadata is used to filter the knowledge sources
-)
-```
-
 ### Chunking Configuration
 
 Control how content is split for processing by setting the chunk size and overlap.
@@ -116,21 +101,28 @@ You can also configure the embedder for the knowledge store. This is useful if y
 ...
 string_source = StringKnowledgeSource(
     content="Users name is John. He is 30 years old and lives in San Francisco.",
-    metadata={"preference": "personal"}
 )
 crew = Crew(
     ...
-    knowledge={
-        "sources": [string_source],
-        "metadata": {"preference": "personal"},
-        "embedder_config": {
-          "provider": "openai", # Default embedder provider; can be "ollama", "gemini", e.t.c.
-          "config": {"model": "text-embedding-3-small"} # Default embedder model; can be "mxbai-embed-large", "nomic-embed-tex", e.t.c.
-        },
+    knowledge_sources=[string_source],
+    embedder={
+        "provider": "openai",
+        "config": {"model": "text-embedding-3-small"},
     },
 )
 ```
 
+## Clearing Knowledge
+
+If you need to clear the knowledge stored in CrewAI, you can use the `crewai reset-memories` command with the `--knowledge` option.
+
+```bash Command
+crewai reset-memories --knowledge
+```
+
+This is useful when you've updated your knowledge sources and want to ensure that the agents are using the most recent information.
+
+
 ## Custom Knowledge Sources
 
 CrewAI allows you to create custom knowledge sources for any type of data by extending the `BaseKnowledgeSource` class. Let's create a practical example that fetches and processes space news articles.
@@ -174,12 +166,12 @@ class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
         formatted = "Space News Articles:\n\n"
         for article in articles:
             formatted += f"""
-Title: {article['title']}
-Published: {article['published_at']}
-Summary: {article['summary']}
-News Site: {article['news_site']}
-URL: {article['url']}
--------------------"""
+                Title: {article['title']}
+                Published: {article['published_at']}
+                Summary: {article['summary']}
+                News Site: {article['news_site']}
+                URL: {article['url']}
+                -------------------"""
         return formatted
 
     def add(self) -> None:
@@ -189,17 +181,12 @@ URL: {article['url']}
             chunks = self._chunk_text(text)
             self.chunks.extend(chunks)
         
-        self.save_documents(metadata={
-            "source": "space_news_api",
-            "timestamp": datetime.now().isoformat(),
-            "article_count": self.limit
-        })
+        self._save_documents()
 
 # Create knowledge source
 recent_news = SpaceNewsKnowledgeSource(
     api_endpoint="https://api.spaceflightnewsapi.net/v4/articles",
     limit=10,
-    metadata={"category": "recent_news", "source": "spaceflight_news"}
 )
 
 # Create specialized agent
@@ -265,7 +252,7 @@ The latest developments in space exploration, based on recent space news article
    - Implements three key methods:
      - `load_content()`: Fetches articles from the API
      - `_format_articles()`: Structures the articles into readable text
-     - `add()`: Processes and stores the content with metadata
+     - `add()`: Processes and stores the content
 
 2. **Agent Configuration**:
    - Specialized role as a Space News Analyst
@@ -299,14 +286,12 @@ You can customize the API query by modifying the endpoint URL:
 recent_news = SpaceNewsKnowledgeSource(
     api_endpoint="https://api.spaceflightnewsapi.net/v4/articles",
     limit=20,  # Increase the number of articles
-    metadata={"category": "recent_news"}
 )
 
 # Add search parameters
 recent_news = SpaceNewsKnowledgeSource(
     api_endpoint="https://api.spaceflightnewsapi.net/v4/articles?search=NASA", # Search for NASA news
     limit=10,
-    metadata={"category": "nasa_news"}
 )
 ```
 
@@ -314,16 +299,14 @@ recent_news = SpaceNewsKnowledgeSource(
 
 <AccordionGroup>
   <Accordion title="Content Organization">
-    - Use descriptive metadata for better filtering
     - Keep chunk sizes appropriate for your content type
     - Consider content overlap for context preservation
     - Organize related information into separate knowledge sources
   </Accordion>
   
   <Accordion title="Performance Tips">
-    - Use metadata filtering to narrow search scope
     - Adjust chunk sizes based on content complexity
     - Configure appropriate embedding models
     - Consider using local embedding providers for faster processing
   </Accordion>
-</AccordionGroup>
\ No newline at end of file
+</AccordionGroup>
diff --git a/src/crewai/knowledge/knowledge.py b/src/crewai/knowledge/knowledge.py
index 4a1331799..f9f55a517 100644
--- a/src/crewai/knowledge/knowledge.py
+++ b/src/crewai/knowledge/knowledge.py
@@ -1,11 +1,10 @@
 import os
+from typing import Any, Dict, List, Optional
 
-from typing import List, Optional, Dict, Any
 from pydantic import BaseModel, ConfigDict, Field
 
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
-from crewai.utilities.constants import DEFAULT_SCORE_THRESHOLD
 
 os.environ["TOKENIZERS_PARALLELISM"] = "false"  # removes logging from fastembed
 
@@ -46,9 +45,7 @@ class Knowledge(BaseModel):
             source.storage = self.storage
             source.add()
 
-    def query(
-        self, query: List[str], limit: int = 3, preference: Optional[str] = None
-    ) -> List[Dict[str, Any]]:
+    def query(self, query: List[str], limit: int = 3) -> List[Dict[str, Any]]:
         """
         Query across all knowledge sources to find the most relevant information.
         Returns the top_k most relevant chunks.
@@ -57,8 +54,6 @@ class Knowledge(BaseModel):
         results = self.storage.search(
             query,
             limit,
-            filter={"preference": preference} if preference else None,
-            score_threshold=DEFAULT_SCORE_THRESHOLD,
         )
         return results
 
diff --git a/src/crewai/knowledge/source/base_file_knowledge_source.py b/src/crewai/knowledge/source/base_file_knowledge_source.py
index 9cb9ec2a2..7f078b4a4 100644
--- a/src/crewai/knowledge/source/base_file_knowledge_source.py
+++ b/src/crewai/knowledge/source/base_file_knowledge_source.py
@@ -1,13 +1,13 @@
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Union, List, Dict, Any
+from typing import Dict, List, Union
 
 from pydantic import Field
 
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
-from crewai.utilities.logger import Logger
 from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
 from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
+from crewai.utilities.logger import Logger
 
 
 class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
@@ -49,10 +49,9 @@ class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
                     color="red",
                 )
 
-    def save_documents(self, metadata: Dict[str, Any]):
+    def _save_documents(self):
         """Save the documents to the storage."""
-        chunk_metadatas = [metadata.copy() for _ in self.chunks]
-        self.storage.save(self.chunks, chunk_metadatas)
+        self.storage.save(self.chunks)
 
     def convert_to_path(self, path: Union[Path, str]) -> Path:
         """Convert a path to a Path object."""
diff --git a/src/crewai/knowledge/source/base_knowledge_source.py b/src/crewai/knowledge/source/base_knowledge_source.py
index 6be76ca40..07a9a0f25 100644
--- a/src/crewai/knowledge/source/base_knowledge_source.py
+++ b/src/crewai/knowledge/source/base_knowledge_source.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import List, Dict, Any, Optional
+from typing import Any, Dict, List, Optional
 
 import numpy as np
 from pydantic import BaseModel, ConfigDict, Field
@@ -17,7 +17,7 @@ class BaseKnowledgeSource(BaseModel, ABC):
 
     model_config = ConfigDict(arbitrary_types_allowed=True)
     storage: KnowledgeStorage = Field(default_factory=KnowledgeStorage)
-    metadata: Dict[str, Any] = Field(default_factory=dict)
+    metadata: Dict[str, Any] = Field(default_factory=dict)  # Currently unused
     collection_name: Optional[str] = Field(default=None)
 
     @abstractmethod
@@ -41,9 +41,9 @@ class BaseKnowledgeSource(BaseModel, ABC):
             for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
         ]
 
-    def save_documents(self, metadata: Dict[str, Any]):
+    def _save_documents(self):
         """
         Save the documents to the storage.
         This method should be called after the chunks and embeddings are generated.
         """
-        self.storage.save(self.chunks, metadata)
+        self.storage.save(self.chunks)
diff --git a/src/crewai/knowledge/source/csv_knowledge_source.py b/src/crewai/knowledge/source/csv_knowledge_source.py
index 117cbe32f..3bb0714d9 100644
--- a/src/crewai/knowledge/source/csv_knowledge_source.py
+++ b/src/crewai/knowledge/source/csv_knowledge_source.py
@@ -1,6 +1,6 @@
 import csv
-from typing import Dict, List
 from pathlib import Path
+from typing import Dict, List
 
 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
 
@@ -30,7 +30,7 @@ class CSVKnowledgeSource(BaseFileKnowledgeSource):
         )
         new_chunks = self._chunk_text(content_str)
         self.chunks.extend(new_chunks)
-        self.save_documents(metadata=self.metadata)
+        self._save_documents()
 
     def _chunk_text(self, text: str) -> List[str]:
         """Utility method to split text into chunks."""
diff --git a/src/crewai/knowledge/source/excel_knowledge_source.py b/src/crewai/knowledge/source/excel_knowledge_source.py
index 5484e59d5..d379c2763 100644
--- a/src/crewai/knowledge/source/excel_knowledge_source.py
+++ b/src/crewai/knowledge/source/excel_knowledge_source.py
@@ -1,5 +1,6 @@
-from typing import Dict, List
 from pathlib import Path
+from typing import Dict, List
+
 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
 
 
@@ -44,7 +45,7 @@ class ExcelKnowledgeSource(BaseFileKnowledgeSource):
 
         new_chunks = self._chunk_text(content_str)
         self.chunks.extend(new_chunks)
-        self.save_documents(metadata=self.metadata)
+        self._save_documents()
 
     def _chunk_text(self, text: str) -> List[str]:
         """Utility method to split text into chunks."""
diff --git a/src/crewai/knowledge/source/json_knowledge_source.py b/src/crewai/knowledge/source/json_knowledge_source.py
index ed6eec86d..b02d438e6 100644
--- a/src/crewai/knowledge/source/json_knowledge_source.py
+++ b/src/crewai/knowledge/source/json_knowledge_source.py
@@ -1,6 +1,6 @@
 import json
-from typing import Any, Dict, List
 from pathlib import Path
+from typing import Any, Dict, List
 
 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
 
@@ -42,7 +42,7 @@ class JSONKnowledgeSource(BaseFileKnowledgeSource):
         )
         new_chunks = self._chunk_text(content_str)
         self.chunks.extend(new_chunks)
-        self.save_documents(metadata=self.metadata)
+        self._save_documents()
 
     def _chunk_text(self, text: str) -> List[str]:
         """Utility method to split text into chunks."""
diff --git a/src/crewai/knowledge/source/pdf_knowledge_source.py b/src/crewai/knowledge/source/pdf_knowledge_source.py
index e6733d78b..38cd67807 100644
--- a/src/crewai/knowledge/source/pdf_knowledge_source.py
+++ b/src/crewai/knowledge/source/pdf_knowledge_source.py
@@ -1,5 +1,5 @@
-from typing import List, Dict
 from pathlib import Path
+from typing import Dict, List
 
 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
 
@@ -43,7 +43,7 @@ class PDFKnowledgeSource(BaseFileKnowledgeSource):
         for _, text in self.content.items():
             new_chunks = self._chunk_text(text)
             self.chunks.extend(new_chunks)
-        self.save_documents(metadata=self.metadata)
+        self._save_documents()
 
     def _chunk_text(self, text: str) -> List[str]:
         """Utility method to split text into chunks."""
diff --git a/src/crewai/knowledge/source/string_knowledge_source.py b/src/crewai/knowledge/source/string_knowledge_source.py
index 7336fd3ea..1d40ac4b8 100644
--- a/src/crewai/knowledge/source/string_knowledge_source.py
+++ b/src/crewai/knowledge/source/string_knowledge_source.py
@@ -24,7 +24,7 @@ class StringKnowledgeSource(BaseKnowledgeSource):
         """Add string content to the knowledge source, chunk it, compute embeddings, and save them."""
         new_chunks = self._chunk_text(self.content)
         self.chunks.extend(new_chunks)
-        self.save_documents(metadata=self.metadata)
+        self._save_documents()
 
     def _chunk_text(self, text: str) -> List[str]:
         """Utility method to split text into chunks."""
diff --git a/src/crewai/knowledge/source/text_file_knowledge_source.py b/src/crewai/knowledge/source/text_file_knowledge_source.py
index 1ceb02843..ddb1f2516 100644
--- a/src/crewai/knowledge/source/text_file_knowledge_source.py
+++ b/src/crewai/knowledge/source/text_file_knowledge_source.py
@@ -1,5 +1,5 @@
-from typing import Dict, List
 from pathlib import Path
+from typing import Dict, List
 
 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
 
@@ -24,7 +24,7 @@ class TextFileKnowledgeSource(BaseFileKnowledgeSource):
         for _, text in self.content.items():
             new_chunks = self._chunk_text(text)
             self.chunks.extend(new_chunks)
-        self.save_documents(metadata=self.metadata)
+        self._save_documents()
 
     def _chunk_text(self, text: str) -> List[str]:
         """Utility method to split text into chunks."""
diff --git a/src/crewai/knowledge/storage/knowledge_storage.py b/src/crewai/knowledge/storage/knowledge_storage.py
index 79aa385a8..e0e36f4a7 100644
--- a/src/crewai/knowledge/storage/knowledge_storage.py
+++ b/src/crewai/knowledge/storage/knowledge_storage.py
@@ -1,18 +1,20 @@
 import contextlib
+import hashlib
 import io
 import logging
-import chromadb
 import os
+from typing import Any, Dict, List, Optional, Union, cast
 
+import chromadb
 import chromadb.errors
-from crewai.utilities.paths import db_storage_path
-from typing import Optional, List, Dict, Any, Union
-from crewai.utilities import EmbeddingConfigurator
-from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
-import hashlib
-from chromadb.config import Settings
 from chromadb.api import ClientAPI
+from chromadb.api.types import OneOrMany
+from chromadb.config import Settings
+
+from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
+from crewai.utilities import EmbeddingConfigurator
 from crewai.utilities.logger import Logger
+from crewai.utilities.paths import db_storage_path
 
 
 @contextlib.contextmanager
@@ -116,11 +118,16 @@ class KnowledgeStorage(BaseKnowledgeStorage):
     def save(
         self,
         documents: List[str],
-        metadata: Union[Dict[str, Any], List[Dict[str, Any]]],
+        metadata: Optional[Union[Dict[str, Any], List[Dict[str, Any]]]] = None,
     ):
         if self.collection:
             try:
-                metadatas = [metadata] if isinstance(metadata, dict) else metadata
+                if metadata is None:
+                    metadatas: Optional[OneOrMany[chromadb.Metadata]] = None
+                elif isinstance(metadata, list):
+                    metadatas = [cast(chromadb.Metadata, m) for m in metadata]
+                else:
+                    metadatas = cast(chromadb.Metadata, metadata)
 
                 ids = [
                     hashlib.sha256(doc.encode("utf-8")).hexdigest() for doc in documents

From 6930b6848460dc7d9b1ca7d5629286fc559123cd Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Fri, 6 Dec 2024 13:57:28 -0500
Subject: [PATCH 108/126] add support for langfuse with litellm (#1721)

---
 src/crewai/llm.py | 38 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 38 insertions(+)

diff --git a/src/crewai/llm.py b/src/crewai/llm.py
index bfdaa4418..d860a8907 100644
--- a/src/crewai/llm.py
+++ b/src/crewai/llm.py
@@ -1,4 +1,5 @@
 import logging
+import os
 import sys
 import threading
 import warnings
@@ -128,6 +129,7 @@ class LLM:
         litellm.drop_params = True
         litellm.set_verbose = False
         self.set_callbacks(callbacks)
+        self.set_env_callbacks()
 
     def call(self, messages: List[Dict[str, str]], callbacks: List[Any] = []) -> str:
         with suppress_warnings():
@@ -202,3 +204,39 @@ class LLM:
                 litellm._async_success_callback.remove(callback)
 
         litellm.callbacks = callbacks
+
+    def set_env_callbacks(self):
+        """
+        Sets the success and failure callbacks for the LiteLLM library from environment variables.
+
+        This method reads the `LITELLM_SUCCESS_CALLBACKS` and `LITELLM_FAILURE_CALLBACKS`
+        environment variables, which should contain comma-separated lists of callback names.
+        It then assigns these lists to `litellm.success_callback` and `litellm.failure_callback`,
+        respectively.
+
+        If the environment variables are not set or are empty, the corresponding callback lists
+        will be set to empty lists.
+
+        Example:
+            LITELLM_SUCCESS_CALLBACKS="langfuse,langsmith"
+            LITELLM_FAILURE_CALLBACKS="langfuse"
+
+        This will set `litellm.success_callback` to ["langfuse", "langsmith"] and
+        `litellm.failure_callback` to ["langfuse"].
+        """
+        success_callbacks_str = os.environ.get("LITELLM_SUCCESS_CALLBACKS", "")
+        success_callbacks = []
+        if success_callbacks_str:
+            success_callbacks = [
+                callback.strip() for callback in success_callbacks_str.split(",")
+            ]
+
+        failure_callbacks_str = os.environ.get("LITELLM_FAILURE_CALLBACKS", "")
+        failure_callbacks = []
+        if failure_callbacks_str:
+            failure_callbacks = [
+                callback.strip() for callback in failure_callbacks_str.split(",")
+            ]
+
+        litellm.success_callback = success_callbacks
+        litellm.failure_callback = failure_callbacks

From 11a3d4b8401159b4c8d6bb150aca3cc0ef4ced0b Mon Sep 17 00:00:00 2001
From: Eduardo Chiarotti <dudumelgaco@hotmail.com>
Date: Mon, 9 Dec 2024 11:42:36 -0300
Subject: [PATCH 109/126] docs: Add quotes to agentops installing command
 (#1729)

* docs: Add quotes to agentops installing command

* feat: Add ContextualMemory to __init__

* feat: remove import due to circular improt

* feat: update tasks config main template typos
---
 docs/how-to/agentops-observability.mdx          | 2 +-
 src/crewai/cli/templates/crew/config/tasks.yaml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/how-to/agentops-observability.mdx b/docs/how-to/agentops-observability.mdx
index ce50d1fc5..b6ade320e 100644
--- a/docs/how-to/agentops-observability.mdx
+++ b/docs/how-to/agentops-observability.mdx
@@ -57,7 +57,7 @@ This feature is useful for debugging and understanding how agents interact with
    <Step title="Install AgentOps">
       Install AgentOps with:
       ```bash
-      pip install crewai[agentops]
+      pip install 'crewai[agentops]'
       ```
       or
       ```bash
diff --git a/src/crewai/cli/templates/crew/config/tasks.yaml b/src/crewai/cli/templates/crew/config/tasks.yaml
index f30820855..e6c0870a2 100644
--- a/src/crewai/cli/templates/crew/config/tasks.yaml
+++ b/src/crewai/cli/templates/crew/config/tasks.yaml
@@ -12,6 +12,6 @@ reporting_task:
     Review the context you got and expand each topic into a full section for a report.
     Make sure the report is detailed and contains any and all relevant information.
   expected_output: >
-    A fully fledge reports with the mains topics, each with a full section of information.
+    A fully fledged report with the main topics, each with a full section of information.
     Formatted as markdown without '```'
   agent: reporting_analyst

From bc2a86d66a6ecd53e3524de52a3d0f287c258f28 Mon Sep 17 00:00:00 2001
From: Frieda Huang <124417784+frieda-huang@users.noreply.github.com>
Date: Mon, 9 Dec 2024 10:05:54 -0500
Subject: [PATCH 110/126] Fixed output_file not respecting system path (#1726)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 src/crewai/task.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/src/crewai/task.py b/src/crewai/task.py
index af5b34c54..cedb73c09 100644
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -1,6 +1,6 @@
 import datetime
 import json
-import os
+from pathlib import Path
 import threading
 import uuid
 from concurrent.futures import Future
@@ -393,12 +393,13 @@ class Task(BaseModel):
         if self.output_file is None:
             raise ValueError("output_file is not set.")
 
-        directory = os.path.dirname(self.output_file)  # type: ignore # Value of type variable "AnyOrLiteralStr" of "dirname" cannot be "str | None"
+        resolved_path = Path(self.output_file).expanduser().resolve()
+        directory = resolved_path.parent
 
-        if directory and not os.path.exists(directory):
-            os.makedirs(directory)
+        if not directory.exists():
+            directory.mkdir(parents=True, exist_ok=True)
 
-        with open(self.output_file, "w", encoding="utf-8") as file:
+        with resolved_path.open("w", encoding="utf-8") as file:
             if isinstance(result, dict):
                 import json
 

From 46be5e8097a4e18fd9ab05e630b784658e7da2a6 Mon Sep 17 00:00:00 2001
From: Archkon <180910180+Archkon@users.noreply.github.com>
Date: Mon, 9 Dec 2024 23:53:55 +0800
Subject: [PATCH 111/126] fix:typo error (#1732)

* Update crew_agent_executor.py

typo error

* Update en.json

typo error
---
 src/crewai/agents/crew_agent_executor.py | 2 +-
 src/crewai/translations/en.json          | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index 00545e760..649360e30 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -299,7 +299,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         self._i18n.slice("summarizer_system_message"), role="system"
                     ),
                     self._format_msg(
-                        self._i18n.slice("sumamrize_instruction").format(group=group),
+                        self._i18n.slice("summarize_instruction").format(group=group),
                     ),
                 ],
                 callbacks=self.callbacks,
diff --git a/src/crewai/translations/en.json b/src/crewai/translations/en.json
index d30606dc0..7353cfc33 100644
--- a/src/crewai/translations/en.json
+++ b/src/crewai/translations/en.json
@@ -19,7 +19,7 @@
     "human_feedback": "You got human feedback on your work, re-evaluate it and give a new Final Answer when ready.\n {human_feedback}",
     "getting_input": "This is the agent's final answer: {final_answer}\n\n",
     "summarizer_system_message": "You are a helpful assistant that summarizes text.",
-    "sumamrize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
+    "summarize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
     "summary": "This is a summary of our conversation so far:\n{merged_summary}",
     "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
     "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",

From 5a7a323f3a450fb9df986a4b5bec1c6b93b97978 Mon Sep 17 00:00:00 2001
From: Rok Benko <ksjeno@gmail.com>
Date: Mon, 9 Dec 2024 16:41:29 +0100
Subject: [PATCH 112/126] Fix Knowledge docs Spaceflight News API dead link

---
 docs/concepts/knowledge.mdx | 65 +++++++++++++++++++------------------
 1 file changed, 33 insertions(+), 32 deletions(-)

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index 96200b356..16ac586d6 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -8,15 +8,13 @@ icon: book
 
 ## What is Knowledge?
 
-Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks. 
-Think of it as giving your agents a reference library they can consult while working. 
+Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks.
+Think of it as giving your agents a reference library they can consult while working.
 
 <Info>
-  Key benefits of using Knowledge:
-  - Enhance agents with domain-specific information
-  - Support decisions with real-world data
-  - Maintain context across conversations
-  - Ground responses in factual information
+  Key benefits of using Knowledge: - Enhance agents with domain-specific
+  information - Support decisions with real-world data - Maintain context across
+  conversations - Ground responses in factual information
 </Info>
 
 ## Supported Knowledge Sources
@@ -25,14 +23,10 @@ CrewAI supports various types of knowledge sources out of the box:
 
 <CardGroup cols={2}>
   <Card title="Text Sources" icon="text">
-    - Raw strings
-    - Text files (.txt)
-    - PDF documents
+    - Raw strings - Text files (.txt) - PDF documents
   </Card>
   <Card title="Structured Data" icon="table">
-    - CSV files
-    - Excel spreadsheets
-    - JSON documents
+    - CSV files - Excel spreadsheets - JSON documents
   </Card>
 </CardGroup>
 
@@ -47,7 +41,7 @@ from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSourc
 # Create a knowledge source
 content = "Users name is John. He is 30 years old and lives in San Francisco."
 string_source = StringKnowledgeSource(
-    content=content, 
+    content=content,
 )
 
 # Create an LLM with a temperature of 0 to ensure deterministic outputs
@@ -122,7 +116,6 @@ crewai reset-memories --knowledge
 
 This is useful when you've updated your knowledge sources and want to ensure that the agents are using the most recent information.
 
-
 ## Custom Knowledge Sources
 
 CrewAI allows you to create custom knowledge sources for any type of data by extending the `BaseKnowledgeSource` class. Let's create a practical example that fetches and processes space news articles.
@@ -141,10 +134,10 @@ from pydantic import BaseModel, Field
 
 class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
     """Knowledge source that fetches data from Space News API."""
-    
+
     api_endpoint: str = Field(description="API endpoint URL")
     limit: int = Field(default=10, description="Number of articles to fetch")
-    
+
     def load_content(self) -> Dict[Any, str]:
         """Fetch and format space news articles."""
         try:
@@ -152,15 +145,15 @@ class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
                 f"{self.api_endpoint}?limit={self.limit}"
             )
             response.raise_for_status()
-            
+
             data = response.json()
             articles = data.get('results', [])
-            
+
             formatted_data = self._format_articles(articles)
             return {self.api_endpoint: formatted_data}
         except Exception as e:
             raise ValueError(f"Failed to fetch space news: {str(e)}")
-    
+
     def _format_articles(self, articles: list) -> str:
         """Format articles into readable text."""
         formatted = "Space News Articles:\n\n"
@@ -180,7 +173,7 @@ class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
         for _, text in content.items():
             chunks = self._chunk_text(text)
             self.chunks.extend(chunks)
-        
+
         self._save_documents()
 
 # Create knowledge source
@@ -193,7 +186,7 @@ recent_news = SpaceNewsKnowledgeSource(
 space_analyst = Agent(
     role="Space News Analyst",
     goal="Answer questions about space news accurately and comprehensively",
-    backstory="""You are a space industry analyst with expertise in space exploration, 
+    backstory="""You are a space industry analyst with expertise in space exploration,
     satellite technology, and space industry trends. You excel at answering questions
     about space news and providing detailed, accurate information.""",
     knowledge_sources=[recent_news],
@@ -220,13 +213,14 @@ result = crew.kickoff(
     inputs={"user_question": "What are the latest developments in space exploration?"}
 )
 ```
+
 ```output Output
 # Agent: Space News Analyst
 ## Task: Answer this question about space news: What are the latest developments in space exploration?
 
 
 # Agent: Space News Analyst
-## Final Answer: 
+## Final Answer:
 The latest developments in space exploration, based on recent space news articles, include the following:
 
 1. SpaceX has received the final regulatory approvals to proceed with the second integrated Starship/Super Heavy launch, scheduled for as soon as the morning of Nov. 17, 2023. This is a significant step in SpaceX's ambitious plans for space exploration and colonization. [Source: SpaceNews](https://spacenews.com/starship-cleared-for-nov-17-launch/)
@@ -242,11 +236,13 @@ The latest developments in space exploration, based on recent space news article
 6. The National Natural Science Foundation of China has outlined a five-year project for researchers to study the assembly of ultra-large spacecraft. This could lead to significant advancements in spacecraft technology and space exploration capabilities. [Source: SpaceNews](https://spacenews.com/china-researching-challenges-of-kilometer-scale-ultra-large-spacecraft/)
 
 7. The Center for AEroSpace Autonomy Research (CAESAR) at Stanford University is focusing on spacecraft autonomy. The center held a kickoff event on May 22, 2024, to highlight the industry, academia, and government collaboration it seeks to foster. This could lead to significant advancements in autonomous spacecraft technology. [Source: SpaceNews](https://spacenews.com/stanford-center-focuses-on-spacecraft-autonomy/)
-``` 
+```
+
 </CodeGroup>
 #### Key Components Explained
 
 1. **Custom Knowledge Source (`SpaceNewsKnowledgeSource`)**:
+
    - Extends `BaseKnowledgeSource` for integration with CrewAI
    - Configurable API endpoint and article limit
    - Implements three key methods:
@@ -255,10 +251,12 @@ The latest developments in space exploration, based on recent space news article
      - `add()`: Processes and stores the content
 
 2. **Agent Configuration**:
+
    - Specialized role as a Space News Analyst
    - Uses the knowledge source to access space news
 
 3. **Task Setup**:
+
    - Takes a user question as input through `{user_question}`
    - Designed to provide detailed answers based on the knowledge source
 
@@ -267,6 +265,7 @@ The latest developments in space exploration, based on recent space news article
    - Handles input/output through the kickoff method
 
 This example demonstrates how to:
+
 - Create a custom knowledge source that fetches real-time data
 - Process and format external data for AI consumption
 - Use the knowledge source to answer specific user questions
@@ -274,13 +273,15 @@ This example demonstrates how to:
 
 #### About the Spaceflight News API
 
-The example uses the [Spaceflight News API](https://api.spaceflightnewsapi.net/v4/documentation), which:
+The example uses the [Spaceflight News API](https://api.spaceflightnewsapi.net/v4/docs/), which:
+
 - Provides free access to space-related news articles
 - Requires no authentication
 - Returns structured data about space news
 - Supports pagination and filtering
 
 You can customize the API query by modifying the endpoint URL:
+
 ```python
 # Fetch more articles
 recent_news = SpaceNewsKnowledgeSource(
@@ -299,14 +300,14 @@ recent_news = SpaceNewsKnowledgeSource(
 
 <AccordionGroup>
   <Accordion title="Content Organization">
-    - Keep chunk sizes appropriate for your content type
-    - Consider content overlap for context preservation
-    - Organize related information into separate knowledge sources
+    - Keep chunk sizes appropriate for your content type - Consider content
+    overlap for context preservation - Organize related information into
+    separate knowledge sources
   </Accordion>
-  
+
   <Accordion title="Performance Tips">
-    - Adjust chunk sizes based on content complexity
-    - Configure appropriate embedding models
-    - Consider using local embedding providers for faster processing
+    - Adjust chunk sizes based on content complexity - Configure appropriate
+    embedding models - Consider using local embedding providers for faster
+    processing
   </Accordion>
 </AccordionGroup>

From e01c0a0f4cc2990c5a772040917fad8014414a71 Mon Sep 17 00:00:00 2001
From: Aviral Jain <avi.aviral140@gmail.com>
Date: Mon, 9 Dec 2024 21:37:52 +0530
Subject: [PATCH 113/126] call storage.search in user context search instead of
 memory.search (#1692)

Co-authored-by: Eduardo Chiarotti <dudumelgaco@hotmail.com>
---
 src/crewai/memory/user/user_memory.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/crewai/memory/user/user_memory.py b/src/crewai/memory/user/user_memory.py
index 25e36617c..24e5fe035 100644
--- a/src/crewai/memory/user/user_memory.py
+++ b/src/crewai/memory/user/user_memory.py
@@ -37,7 +37,7 @@ class UserMemory(Memory):
         limit: int = 3,
         score_threshold: float = 0.35,
     ):
-        results = super().search(
+        results = self.storage.search(
             query=query,
             limit=limit,
             score_threshold=score_threshold,

From 1261ce513ff2b707c506c6ff65e326fc6e9627c7 Mon Sep 17 00:00:00 2001
From: lgesuellip <102637283+lgesuellip@users.noreply.github.com>
Date: Mon, 9 Dec 2024 13:34:07 -0300
Subject: [PATCH 114/126] Add doc structured tool (#1713)

* Add doc structured tool

* Fix example

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/concepts/tools.mdx | 42 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/docs/concepts/tools.mdx b/docs/concepts/tools.mdx
index 9b9c6a32e..8abe0f4e6 100644
--- a/docs/concepts/tools.mdx
+++ b/docs/concepts/tools.mdx
@@ -172,6 +172,48 @@ def my_tool(question: str) -> str:
     return "Result from your custom tool"
 ```
 
+### Structured Tools
+
+The `StructuredTool` class wraps functions as tools, providing flexibility and validation while reducing boilerplate. It supports custom schemas and dynamic logic for seamless integration of complex functionalities.
+
+#### Example:
+Using `StructuredTool.from_function`, you can wrap a function that interacts with an external API or system, providing a structured interface. This enables robust validation and consistent execution, making it easier to integrate complex functionalities into your applications as demonstrated in the following example:
+
+```python
+from crewai.tools.structured_tool import CrewStructuredTool
+from pydantic import BaseModel
+
+# Define the schema for the tool's input using Pydantic
+class APICallInput(BaseModel):
+    endpoint: str
+    parameters: dict
+
+# Wrapper function to execute the API call
+def tool_wrapper(*args, **kwargs):
+    # Here, you would typically call the API using the parameters
+    # For demonstration, we'll return a placeholder string
+    return f"Call the API at {kwargs['endpoint']} with parameters {kwargs['parameters']}"
+
+# Create and return the structured tool
+def create_structured_tool():
+    return CrewStructuredTool.from_function(
+        name='Wrapper API',
+        description="A tool to wrap API calls with structured input.",
+        args_schema=APICallInput,
+        func=tool_wrapper,
+    )
+
+# Example usage
+structured_tool = create_structured_tool()
+
+# Execute the tool with structured input
+result = structured_tool._run(**{
+    "endpoint": "https://example.com/api",
+    "parameters": {"key1": "value1", "key2": "value2"}
+})
+print(result)  # Output: Call the API at https://example.com/api with parameters {'key1': 'value1', 'key2': 'value2'}
+```
+
 ### Custom Caching Mechanism
 
 <Tip>

From 8c90db04b5439bed4682b8575fe28db37deb7898 Mon Sep 17 00:00:00 2001
From: fuckqqcom <9391575+fuckqqcom@users.noreply.github.com>
Date: Tue, 10 Dec 2024 00:37:54 +0800
Subject: [PATCH 115/126] =?UTF-8?q?=5Fexecute=5Ftool=5Fand=5Fcheck=5Ffinal?=
 =?UTF-8?q?ity=20=E7=BB=93=E6=9E=9C=E7=BB=99=E5=9B=9E=E8=B0=83=E5=8F=82?=
 =?UTF-8?q?=E6=95=B0=EF=BC=8C=E8=BF=99=E6=A0=B7=E5=B0=B1=E5=8F=AF=E4=BB=A5?=
 =?UTF-8?q?=E6=8F=90=E5=89=8D=E6=8B=BF=E5=88=B0=E7=BB=93=E6=9E=9C=E4=BF=A1?=
 =?UTF-8?q?=E6=81=AF=EF=BC=8C=E5=8E=BB=E5=81=9A=E6=95=B0=E6=8D=AE=E8=A7=A3?=
 =?UTF-8?q?=E6=9E=90=E5=88=A4=E6=96=AD=E5=81=9A=E9=A2=84=E5=88=A4=20(#1716?=
 =?UTF-8?q?)?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: xiaohan <fuck@qq.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 src/crewai/agents/crew_agent_executor.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index 649360e30..83ca06e41 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -143,6 +143,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         tool_result = self._execute_tool_and_check_finality(
                             formatted_answer
                         )
+                        if self.step_callback:
+                          self.step_callback(tool_result)
+
                         formatted_answer.text += f"\nObservation: {tool_result.result}"
                         formatted_answer.result = tool_result.result
                         if tool_result.result_as_answer:

From 236e42d0bc4e1e79013e110c5f4502a54b338799 Mon Sep 17 00:00:00 2001
From: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
Date: Mon, 9 Dec 2024 11:40:01 -0500
Subject: [PATCH 116/126] format bullet points (#1734)

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 docs/concepts/knowledge.mdx | 28 +++++++++++++++++-----------
 1 file changed, 17 insertions(+), 11 deletions(-)

diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
index 16ac586d6..8af9b70a2 100644
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -12,9 +12,11 @@ Knowledge in CrewAI is a powerful system that allows AI agents to access and uti
 Think of it as giving your agents a reference library they can consult while working.
 
 <Info>
-  Key benefits of using Knowledge: - Enhance agents with domain-specific
-  information - Support decisions with real-world data - Maintain context across
-  conversations - Ground responses in factual information
+  Key benefits of using Knowledge:
+  - Enhance agents with domain-specific information
+  - Support decisions with real-world data
+  - Maintain context across conversations
+  - Ground responses in factual information
 </Info>
 
 ## Supported Knowledge Sources
@@ -23,10 +25,14 @@ CrewAI supports various types of knowledge sources out of the box:
 
 <CardGroup cols={2}>
   <Card title="Text Sources" icon="text">
-    - Raw strings - Text files (.txt) - PDF documents
+    - Raw strings
+    - Text files (.txt)
+    - PDF documents
   </Card>
   <Card title="Structured Data" icon="table">
-    - CSV files - Excel spreadsheets - JSON documents
+    - CSV files
+    - Excel spreadsheets
+    - JSON documents
   </Card>
 </CardGroup>
 
@@ -300,14 +306,14 @@ recent_news = SpaceNewsKnowledgeSource(
 
 <AccordionGroup>
   <Accordion title="Content Organization">
-    - Keep chunk sizes appropriate for your content type - Consider content
-    overlap for context preservation - Organize related information into
-    separate knowledge sources
+    - Keep chunk sizes appropriate for your content type
+    - Consider content overlap for context preservation
+    - Organize related information into separate knowledge sources
   </Accordion>
 
   <Accordion title="Performance Tips">
-    - Adjust chunk sizes based on content complexity - Configure appropriate
-    embedding models - Consider using local embedding providers for faster
-    processing
+    - Adjust chunk sizes based on content complexity 
+    - Configure appropriate embedding models
+    - Consider using local embedding providers for faster processing
   </Accordion>
 </AccordionGroup>

From c4f7eaf2599c5709260d660d48e810aae7a8c124 Mon Sep 17 00:00:00 2001
From: Piotr Mardziel <piotrm@gmail.com>
Date: Mon, 9 Dec 2024 08:51:12 -0800
Subject: [PATCH 117/126] Add missing @functools.wraps when wrapping functions
 and preserve wrapped class name in @CrewBase. (#1560)

* Update annotations.py

* Update utils.py

* Update crew_base.py

* Update utils.py

* Update crew_base.py

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 src/crewai/project/annotations.py | 2 ++
 src/crewai/project/crew_base.py   | 4 ++++
 src/crewai/project/utils.py       | 4 +++-
 3 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/src/crewai/project/annotations.py b/src/crewai/project/annotations.py
index be4710b2b..bf0051c4d 100644
--- a/src/crewai/project/annotations.py
+++ b/src/crewai/project/annotations.py
@@ -66,6 +66,8 @@ def cache_handler(func):
 
 
 def crew(func) -> Callable[..., Crew]:
+
+    @wraps(func)
     def wrapper(self, *args, **kwargs) -> Crew:
         instantiated_tasks = []
         instantiated_agents = []
diff --git a/src/crewai/project/crew_base.py b/src/crewai/project/crew_base.py
index e93452a6e..0b43882f2 100644
--- a/src/crewai/project/crew_base.py
+++ b/src/crewai/project/crew_base.py
@@ -213,4 +213,8 @@ def CrewBase(cls: T) -> T:
                     callback_functions[callback]() for callback in callbacks
                 ]
 
+    # Include base class (qual)name in the wrapper class (qual)name.
+    WrappedClass.__name__ = CrewBase.__name__ + "(" + cls.__name__ + ")"
+    WrappedClass.__qualname__ = CrewBase.__qualname__ + "(" + cls.__name__ + ")"
+  
     return cast(T, WrappedClass)
diff --git a/src/crewai/project/utils.py b/src/crewai/project/utils.py
index be3f757d9..2e95c755d 100644
--- a/src/crewai/project/utils.py
+++ b/src/crewai/project/utils.py
@@ -1,11 +1,13 @@
+from functools import wraps
+
 def memoize(func):
     cache = {}
 
+    @wraps(func)
     def memoized_func(*args, **kwargs):
         key = (args, tuple(kwargs.items()))
         if key not in cache:
             cache[key] = func(*args, **kwargs)
         return cache[key]
 
-    memoized_func.__dict__.update(func.__dict__)
     return memoized_func

From 6b87d22a7084897d243f47da5a9218786994d72f Mon Sep 17 00:00:00 2001
From: Carlos Souza <caike@users.noreply.github.com>
Date: Mon, 9 Dec 2024 13:30:51 -0500
Subject: [PATCH 118/126] Fix disk I/O error when resetting short-term memory.
 (#1724)

* Fix disk I/O error when resetting short-term memory.

Reset chromadb client and nullifies references before
removing directory.

* Nit for clarity

* did the same for knowledge_storage

* cleanup

* cleanup order

* Cleanup after the rm of the directories

---------

Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
---
 src/crewai/knowledge/storage/knowledge_storage.py | 14 +++++++++-----
 src/crewai/memory/storage/rag_storage.py          |  4 +++-
 2 files changed, 12 insertions(+), 6 deletions(-)

diff --git a/src/crewai/knowledge/storage/knowledge_storage.py b/src/crewai/knowledge/storage/knowledge_storage.py
index e0e36f4a7..acbbe75a1 100644
--- a/src/crewai/knowledge/storage/knowledge_storage.py
+++ b/src/crewai/knowledge/storage/knowledge_storage.py
@@ -3,6 +3,7 @@ import hashlib
 import io
 import logging
 import os
+import shutil
 from typing import Any, Dict, List, Optional, Union, cast
 
 import chromadb
@@ -15,6 +16,7 @@ from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
 from crewai.utilities import EmbeddingConfigurator
 from crewai.utilities.logger import Logger
 from crewai.utilities.paths import db_storage_path
+from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
 
 
 @contextlib.contextmanager
@@ -105,15 +107,17 @@ class KnowledgeStorage(BaseKnowledgeStorage):
             raise Exception("Failed to create or get collection")
 
     def reset(self):
-        if self.app:
-            self.app.reset()
-        else:
-            base_path = os.path.join(db_storage_path(), "knowledge")
+        base_path = os.path.join(db_storage_path(), KNOWLEDGE_DIRECTORY)
+        if not self.app:
             self.app = chromadb.PersistentClient(
                 path=base_path,
                 settings=Settings(allow_reset=True),
             )
-            self.app.reset()
+
+        self.app.reset()
+        shutil.rmtree(base_path)
+        self.app = None
+        self.collection = None
 
     def save(
         self,
diff --git a/src/crewai/memory/storage/rag_storage.py b/src/crewai/memory/storage/rag_storage.py
index bf40aee96..fd4c77838 100644
--- a/src/crewai/memory/storage/rag_storage.py
+++ b/src/crewai/memory/storage/rag_storage.py
@@ -150,9 +150,11 @@ class RAGStorage(BaseRAGStorage):
 
     def reset(self) -> None:
         try:
-            shutil.rmtree(f"{db_storage_path()}/{self.type}")
             if self.app:
                 self.app.reset()
+                shutil.rmtree(f"{db_storage_path()}/{self.type}")
+                self.app = None
+                self.collection = None
         except Exception as e:
             if "attempt to write a readonly database" in str(e):
                 # Ignore this specific error

From 54ebd6cf90c8ab3785ead34cc23f5f52724869fe Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 9 Dec 2024 14:00:18 -0500
Subject: [PATCH 119/126] restrict python version compatibility (#1731)

* drop 3.13

* revert

* Drop test cassette that was causing error

* trying to fix failing test

* adding thiago changes

* resolve final tests

* Drop skip
---
 .github/ISSUE_TEMPLATE/bug_report.yml         |   3 +-
 .github/workflows/tests.yml                   |   2 +-
 README.md                                     |   2 +-
 docs/installation.mdx                         |   2 +-
 pyproject.toml                                |   2 +-
 src/crewai/cli/templates/crew/README.md       |   2 +-
 src/crewai/cli/templates/crew/pyproject.toml  |   2 +-
 src/crewai/cli/templates/flow/README.md       |   2 +-
 src/crewai/cli/templates/flow/pyproject.toml  |   2 +-
 .../cli/templates/pipeline/pyproject.toml     |   4 +-
 src/crewai/cli/templates/tool/README.md       |   2 +-
 src/crewai/cli/templates/tool/pyproject.toml  |   2 +-
 src/crewai/cli/utils.py                       |  22 +-
 .../test_agent_with_knowledge_sources.yaml    | 313 +++-------------
 .../test_crew_kickoff_usage_metrics.yaml      | 182 +++++-----
 .../test_llm_callback_replacement.yaml        | 118 +++---
 tests/cli/deploy/test_deploy_main.py          |  15 +-
 tests/crew_test.py                            |  24 +-
 uv.lock                                       | 338 +-----------------
 19 files changed, 243 insertions(+), 796 deletions(-)

diff --git a/.github/ISSUE_TEMPLATE/bug_report.yml b/.github/ISSUE_TEMPLATE/bug_report.yml
index 45272c3ab..8a71dc247 100644
--- a/.github/ISSUE_TEMPLATE/bug_report.yml
+++ b/.github/ISSUE_TEMPLATE/bug_report.yml
@@ -65,7 +65,6 @@ body:
         - '3.10'
         - '3.11'
         - '3.12'
-        - '3.13'
     validations:
       required: true
   - type: input
@@ -113,4 +112,4 @@ body:
       label: Additional context
       description: Add any other context about the problem here.
     validations:
-      required: true
\ No newline at end of file
+      required: true
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 76ef2a611..f655dcc64 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -23,7 +23,7 @@ jobs:
 
 
       - name: Set up Python
-        run: uv python install 3.11.9
+        run: uv python install 3.12.8
 
       - name: Install the project
         run: uv sync --dev --all-extras
diff --git a/README.md b/README.md
index 706dc065a..b6d950a3b 100644
--- a/README.md
+++ b/README.md
@@ -44,7 +44,7 @@ To get started with CrewAI, follow these simple steps:
 
 ### 1. Installation
 
-Ensure you have Python >=3.10 <=3.13 installed on your system. CrewAI uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
+Ensure you have Python >=3.10 <=3.12 installed on your system. CrewAI uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
 
 First, install CrewAI:
 
diff --git a/docs/installation.mdx b/docs/installation.mdx
index ab3bf341b..ca330e9ca 100644
--- a/docs/installation.mdx
+++ b/docs/installation.mdx
@@ -7,7 +7,7 @@ icon: wrench
 <Note>
   **Python Version Requirements**
   
-  CrewAI requires `Python >=3.10 and <=3.13`. Here's how to check your version:
+  CrewAI requires `Python >=3.10 and <=3.12`. Here's how to check your version:
   ```bash
   python3 --version
   ```
diff --git a/pyproject.toml b/pyproject.toml
index cac8bab9b..44207ca44 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,7 +3,7 @@ name = "crewai"
 version = "0.86.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
-requires-python = ">=3.10,<=3.13"
+requires-python = ">=3.10,<=3.12"
 authors = [
     { name = "Joao Moura", email = "joao@crewai.com" }
 ]
diff --git a/src/crewai/cli/templates/crew/README.md b/src/crewai/cli/templates/crew/README.md
index e6f94d95f..ca3cbd3eb 100644
--- a/src/crewai/cli/templates/crew/README.md
+++ b/src/crewai/cli/templates/crew/README.md
@@ -4,7 +4,7 @@ Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.co
 
 ## Installation
 
-Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
+Ensure you have Python >=3.10 <=3.12 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
 
 First, if you haven't already, install uv:
 
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index d9ac06cd0..29014881b 100644
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/src/crewai/cli/templates/crew/pyproject.toml
@@ -3,7 +3,7 @@ name = "{{folder_name}}"
 version = "0.1.0"
 description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
-requires-python = ">=3.10,<=3.13"
+requires-python = ">=3.10,<=3.12"
 dependencies = [
     "crewai[tools]>=0.86.0,<1.0.0"
 ]
diff --git a/src/crewai/cli/templates/flow/README.md b/src/crewai/cli/templates/flow/README.md
index 2cde7892b..fead65ece 100644
--- a/src/crewai/cli/templates/flow/README.md
+++ b/src/crewai/cli/templates/flow/README.md
@@ -4,7 +4,7 @@ Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.co
 
 ## Installation
 
-Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
+Ensure you have Python >=3.10 <=3.12 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
 
 First, if you haven't already, install uv:
 
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index ba4f4a823..a20653eff 100644
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/src/crewai/cli/templates/flow/pyproject.toml
@@ -3,7 +3,7 @@ name = "{{folder_name}}"
 version = "0.1.0"
 description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
-requires-python = ">=3.10,<=3.13"
+requires-python = ">=3.10,<=3.12"
 dependencies = [
     "crewai[tools]>=0.86.0,<1.0.0",
 ]
diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
index 97abd41a5..d74764742 100644
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ b/src/crewai/cli/templates/pipeline/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = ["Your Name <you@example.com>"]
 
 [tool.poetry.dependencies]
-python = ">=3.10,<=3.13"
+python = ">=3.10,<=3.12"
 crewai = { extras = ["tools"], version = ">=0.86.0,<1.0.0" }
 asyncio = "*"
 
@@ -14,4 +14,4 @@ asyncio = "*"
 
 [build-system]
 requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
\ No newline at end of file
+build-backend = "poetry.core.masonry.api"
diff --git a/src/crewai/cli/templates/tool/README.md b/src/crewai/cli/templates/tool/README.md
index 43b1d721a..1291ff6a6 100644
--- a/src/crewai/cli/templates/tool/README.md
+++ b/src/crewai/cli/templates/tool/README.md
@@ -5,7 +5,7 @@ custom tools to power up your crews.
 
 ## Installing
 
-Ensure you have Python >=3.10 <=3.13 installed on your system. This project
+Ensure you have Python >=3.10 <=3.12 installed on your system. This project
 uses [UV](https://docs.astral.sh/uv/) for dependency management and package
 handling, offering a seamless setup and execution experience.
 
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 585bbef38..a1557bd7f 100644
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/src/crewai/cli/templates/tool/pyproject.toml
@@ -3,7 +3,7 @@ name = "{{folder_name}}"
 version = "0.1.0"
 description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
-requires-python = ">=3.10,<=3.13"
+requires-python = ">=3.10,<=3.12"
 dependencies = [
     "crewai[tools]>=0.86.0"
 ]
diff --git a/src/crewai/cli/utils.py b/src/crewai/cli/utils.py
index 2daba4111..a385e1f37 100644
--- a/src/crewai/cli/utils.py
+++ b/src/crewai/cli/utils.py
@@ -33,26 +33,6 @@ def copy_template(src, dst, name, class_name, folder_name):
     click.secho(f"  - Created {dst}", fg="green")
 
 
-# Drop the simple_toml_parser when we move to python3.11
-def simple_toml_parser(content):
-    result = {}
-    current_section = result
-    for line in content.split("\n"):
-        line = line.strip()
-        if line.startswith("[") and line.endswith("]"):
-            # New section
-            section = line[1:-1].split(".")
-            current_section = result
-            for key in section:
-                current_section = current_section.setdefault(key, {})
-        elif "=" in line:
-            key, value = line.split("=", 1)
-            key = key.strip()
-            value = value.strip().strip('"')
-            current_section[key] = value
-    return result
-
-
 def read_toml(file_path: str = "pyproject.toml"):
     """Read the content of a TOML file and return it as a dictionary."""
     with open(file_path, "rb") as f:
@@ -63,7 +43,7 @@ def read_toml(file_path: str = "pyproject.toml"):
 def parse_toml(content):
     if sys.version_info >= (3, 11):
         return tomllib.loads(content)
-    return simple_toml_parser(content)
+    return tomli.loads(content)
 
 
 def get_project_name(
diff --git a/tests/cassettes/test_agent_with_knowledge_sources.yaml b/tests/cassettes/test_agent_with_knowledge_sources.yaml
index fdc9f912e..ed3a8b31f 100644
--- a/tests/cassettes/test_agent_with_knowledge_sources.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_sources.yaml
@@ -32,126 +32,19 @@ interactions:
       x-stainless-runtime:
       - CPython
       x-stainless-runtime-version:
-      - 3.11.9
+      - 3.12.7
     method: POST
     uri: https://api.openai.com/v1/embeddings
   response:
-    body:
-      string: !!binary |
-        H4sIAAAAAAAAA1R6SxOyurrmfP+KVWtKn5KLkGTNuIuABAFRu7q6QJGLIAKSQE6d/96l367T3RMH
-        EEpI8j63N//5r7/++rvPm+L2+fufv/5u6+nz9//4Xrtnn+zvf/76n//666+//vrP3+//N7Lo8uJ+
-        r1/lb/jvZv26F8vf//zF//eV/zvon7/+jq6vjKh9O4J16w0pDD6Sje2RqsYS44hDcWl9cPKQzIYP
-        H8KK5NDZkVu+3eVi0B0ntNmvzxlIl3fM8DMLoM+bIy5Ux2e0iE4p2g/aRIr0JXu0ntIb1N1dFLDx
-        vowUa0+I7jsjmhXu9AKr4lIODLV4wOaJfUaWM6xD7yWLWAN5O64qLkxZGDl1trNOzJmJMxdZUpbh
-        AEQuW8BVVtEHpGdsyZmZi5p5NBE+0gc+HuXJmyk6l1ADg42tKQ9y0Xw/fPh63+7EZnXH2OF8HODb
-        G0ZiuboPWMlffRCXuw/WsMAD5omxiNpX0c7bfPUNcYtoClEq74JJuHfjcnknNjrPtoEjd5FZ9zjC
-        AVrdxyOH6fUEzJUVBxl740z2mWwCQRrXHp128E5uN6UxlmI1IcJucCR76ebE0t6UAiW/imdsTI9P
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-      - Linux
+      - MacOS
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diff --git a/tests/cli/deploy/test_deploy_main.py b/tests/cli/deploy/test_deploy_main.py
index bf1198a0b..00e355a62 100644
--- a/tests/cli/deploy/test_deploy_main.py
+++ b/tests/cli/deploy/test_deploy_main.py
@@ -228,17 +228,18 @@ class TestDeployCommand(unittest.TestCase):
         "builtins.open",
         new_callable=unittest.mock.mock_open,
         read_data="""
-    [project]
-    name = "test_project"
-    version = "0.1.0"
-    requires-python = ">=3.10,<=3.13"
-    dependencies = ["crewai"]
-    """,
+        [project]
+        name = "test_project"
+        version = "0.1.0"
+        requires-python = ">=3.10,<=3.12"
+        dependencies = ["crewai"]
+        """,
     )
     def test_get_project_name_python_310(self, mock_open):
         from crewai.cli.utils import get_project_name
 
         project_name = get_project_name()
+        print("project_name", project_name)
         self.assertEqual(project_name, "test_project")
 
     @unittest.skipIf(sys.version_info < (3, 11), "Requires Python 3.11+")
@@ -249,7 +250,7 @@ class TestDeployCommand(unittest.TestCase):
     [project]
     name = "test_project"
     version = "0.1.0"
-    requires-python = ">=3.10,<=3.13"
+    requires-python = ">=3.10,<=3.12"
     dependencies = ["crewai"]
     """,
     )
diff --git a/tests/crew_test.py b/tests/crew_test.py
index 5f31061ec..caecf4524 100644
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -1285,7 +1285,7 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
         prompt_tokens=1562,
         completion_tokens=111,
         successful_requests=3,
-        cached_prompt_tokens=0
+        cached_prompt_tokens=0,
     )
 
 
@@ -1785,16 +1785,18 @@ def test_crew_train_success(
     crew_training_handler.assert_any_call("trained_agents_data.pkl")
     crew_training_handler().load.assert_called()
 
-    crew_training_handler().save_trained_data.assert_has_calls([
-        mock.call(
-            agent_id="Researcher",
-            trained_data=task_evaluator().evaluate_training_data().model_dump(),
-        ),
-        mock.call(
-            agent_id="Senior Writer",
-            trained_data=task_evaluator().evaluate_training_data().model_dump(),
-        )
-    ])
+    crew_training_handler().save_trained_data.assert_has_calls(
+        [
+            mock.call(
+                agent_id="Researcher",
+                trained_data=task_evaluator().evaluate_training_data().model_dump(),
+            ),
+            mock.call(
+                agent_id="Senior Writer",
+                trained_data=task_evaluator().evaluate_training_data().model_dump(),
+            ),
+        ]
+    )
 
 
 def test_crew_train_error():
diff --git a/uv.lock b/uv.lock
index 42fb38424..e6481f89f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,13 +1,9 @@
 version = 1
-requires-python = ">=3.10, <=3.13"
+requires-python = ">=3.10, <=3.12"
 resolution-markers = [
-    "python_full_version < '3.11' and platform_python_implementation == 'PyPy'",
-    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy'",
-    "python_full_version < '3.11' and platform_python_implementation != 'PyPy'",
-    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4'",
-    "python_full_version >= '3.12.4' and python_full_version < '3.13'",
-    "python_full_version >= '3.13'",
+    "python_full_version < '3.11'",
+    "python_full_version == '3.11.*'",
+    "python_full_version >= '3.12'",
 ]
 
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     { url = "https://files.pythonhosted.org/packages/fb/f7/87a32867ddc1a9817018bfd6109ee57646a543acf0d272843d8393e575f9/yarl-1.16.0-py3-none-any.whl", hash = "sha256:e6980a558d8461230c457218bd6c92dfc1d10205548215c2c21d79dc8d0a96f3", size = 43746 },
 ]
 

From c1df7c410e6c08c4dbd2ec77761f7529703931bf Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 9 Dec 2024 14:07:57 -0500
Subject: [PATCH 120/126] Bugfix/restrict python version compatibility (#1736)

* drop 3.13

* revert

* Drop test cassette that was causing error

* trying to fix failing test

* adding thiago changes

* resolve final tests

* Drop skip

* drop pipeline
---
 .../cli/templates/pipeline/pyproject.toml       | 17 -----------------
 1 file changed, 17 deletions(-)
 delete mode 100644 src/crewai/cli/templates/pipeline/pyproject.toml

diff --git a/src/crewai/cli/templates/pipeline/pyproject.toml b/src/crewai/cli/templates/pipeline/pyproject.toml
deleted file mode 100644
index d74764742..000000000
--- a/src/crewai/cli/templates/pipeline/pyproject.toml
+++ /dev/null
@@ -1,17 +0,0 @@
-[tool.poetry]
-name = "{{folder_name}}"
-version = "0.1.0"
-description = "{{name}} using crewAI"
-authors = ["Your Name <you@example.com>"]
-
-[tool.poetry.dependencies]
-python = ">=3.10,<=3.12"
-crewai = { extras = ["tools"], version = ">=0.86.0,<1.0.0" }
-asyncio = "*"
-
-[tool.poetry.scripts]
-{{folder_name}} = "{{folder_name}}.main:main"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

From 2f9a2afd9ec118221273fcfcd82e2785df932109 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Mon, 9 Dec 2024 14:17:46 -0500
Subject: [PATCH 121/126] Update pyproject.toml and uv.lock to drop
 crewai-tools as a default requirement (#1711)

---
 pyproject.toml | 1 -
 uv.lock        | 2 --
 2 files changed, 3 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 44207ca44..ea684cec6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,7 +15,6 @@ dependencies = [
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
     "instructor>=1.3.3",
     "regex>=2024.9.11",
-    "crewai-tools>=0.17.0",
     "click>=8.1.7",
     "python-dotenv>=1.0.0",
     "appdirs>=1.4.4",
diff --git a/uv.lock b/uv.lock
index e6481f89f..26be5064d 100644
--- a/uv.lock
+++ b/uv.lock
@@ -570,7 +570,6 @@ dependencies = [
     { name = "auth0-python" },
     { name = "chromadb" },
     { name = "click" },
-    { name = "crewai-tools" },
     { name = "instructor" },
     { name = "json-repair" },
     { name = "jsonref" },
@@ -640,7 +639,6 @@ requires-dist = [
     { name = "auth0-python", specifier = ">=4.7.1" },
     { name = "chromadb", specifier = ">=0.5.18" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", specifier = ">=0.17.0" },
     { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.14.0" },
     { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
     { name = "instructor", specifier = ">=1.3.3" },

From d932b20c6ef1efd4dba8d625dab20807b0f30319 Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Tue, 10 Dec 2024 11:14:37 -0500
Subject: [PATCH 122/126] copy googles changes. Fix tests. Improve LLM file
 (#1737)

* copy googles changes. Fix tests. Improve LLM file

* Fix type issue
---
 docs/concepts/llms.mdx | 26 +++++++++++++++++++++-----
 src/crewai/llm.py      | 19 ++++++++++++++++++-
 2 files changed, 39 insertions(+), 6 deletions(-)

diff --git a/docs/concepts/llms.mdx b/docs/concepts/llms.mdx
index 1f01ca0eb..8f895ca61 100644
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -29,7 +29,7 @@ Large Language Models (LLMs) are the core intelligence behind CrewAI agents. The
 
 ## Available Models and Their Capabilities
 
-Here's a detailed breakdown of supported models and their capabilities:
+Here's a detailed breakdown of supported models and their capabilities, you can compare performance at [lmarena.ai](https://lmarena.ai/):
 
 <Tabs>
   <Tab title="OpenAI">
@@ -43,6 +43,17 @@ Here's a detailed breakdown of supported models and their capabilities:
       1 token ≈ 4 characters in English. For example, 8,192 tokens ≈ 32,768 characters or about 6,000 words.
     </Note>
   </Tab>
+  <Tab title="Gemini">
+    | Model | Context Window | Best For |
+    |-------|---------------|-----------|
+    | Gemini 1.5 Flash | 1M tokens | Balanced multimodal model, good for most tasks |
+    | Gemini 1.5 Flash 8B | 1M tokens | Fastest, most cost-efficient, good for high-frequency tasks |
+    | Gemini 1.5 Pro | 2M tokens | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration |
+
+    <Tip>
+      Google's Gemini models are all multimodal, supporting audio, images, video and text, supporting context caching, json schema, function calling, etc.
+    </Tip>
+  </Tab>
   <Tab title="Groq">
     | Model | Context Window | Best For |
     |-------|---------------|-----------|
@@ -128,10 +139,10 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
         # llm: anthropic/claude-2.1
         # llm: anthropic/claude-2.0
 
-        # Google Models - Good for general tasks
-        # llm: gemini/gemini-pro
+        # Google Models - Strong reasoning, large cachable context window, multimodal
         # llm: gemini/gemini-1.5-pro-latest
-        # llm: gemini/gemini-1.0-pro-latest
+        # llm: gemini/gemini-1.5-flash-latest
+        # llm: gemini/gemini-1.5-flash-8b-latest
 
         # AWS Bedrock Models - Enterprise-grade
         # llm: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
@@ -350,13 +361,18 @@ Learn how to get the most out of your LLM configuration:
 
   <Accordion title="Google">
     ```python Code
+    # Option 1. Gemini accessed with an API key.
+    # https://ai.google.dev/gemini-api/docs/api-key
     GEMINI_API_KEY=<your-api-key>
+
+    # Option 2. Vertex AI IAM credentials for Gemini, Anthropic, and anything in the Model Garden.
+    # https://cloud.google.com/vertex-ai/generative-ai/docs/overview
     ```
 
     Example usage:
     ```python Code
     llm = LLM(
-        model="gemini/gemini-pro",
+        model="gemini/gemini-1.5-pro-latest",
         temperature=0.7
     )
     ```
diff --git a/src/crewai/llm.py b/src/crewai/llm.py
index d860a8907..058589056 100644
--- a/src/crewai/llm.py
+++ b/src/crewai/llm.py
@@ -43,6 +43,10 @@ LLM_CONTEXT_WINDOW_SIZES = {
     "gpt-4-turbo": 128000,
     "o1-preview": 128000,
     "o1-mini": 128000,
+    # gemini
+    "gemini-1.5-pro": 2097152,
+    "gemini-1.5-flash": 1048576,
+    "gemini-1.5-flash-8b": 1048576,
     # deepseek
     "deepseek-chat": 128000,
     # groq
@@ -61,6 +65,9 @@ LLM_CONTEXT_WINDOW_SIZES = {
     "mixtral-8x7b-32768": 32768,
 }
 
+DEFAULT_CONTEXT_WINDOW_SIZE = 8192
+CONTEXT_WINDOW_USAGE_RATIO = 0.75
+
 
 @contextmanager
 def suppress_warnings():
@@ -124,6 +131,7 @@ class LLM:
         self.api_version = api_version
         self.api_key = api_key
         self.callbacks = callbacks
+        self.context_window_size = 0
         self.kwargs = kwargs
 
         litellm.drop_params = True
@@ -191,7 +199,16 @@ class LLM:
 
     def get_context_window_size(self) -> int:
         # Only using 75% of the context window size to avoid cutting the message in the middle
-        return int(LLM_CONTEXT_WINDOW_SIZES.get(self.model, 8192) * 0.75)
+        if self.context_window_size != 0:
+            return self.context_window_size
+
+        self.context_window_size = int(
+            DEFAULT_CONTEXT_WINDOW_SIZE * CONTEXT_WINDOW_USAGE_RATIO
+        )
+        for key, value in LLM_CONTEXT_WINDOW_SIZES.items():
+            if self.model.startswith(key):
+                self.context_window_size = int(value * CONTEXT_WINDOW_USAGE_RATIO)
+        return self.context_window_size
 
     def set_callbacks(self, callbacks: List[Any]):
         callback_types = [type(callback) for callback in callbacks]

From da4f356fab81e3f3077f2e746464f6abb791fc84 Mon Sep 17 00:00:00 2001
From: Archkon <180910180+Archkon@users.noreply.github.com>
Date: Wed, 11 Dec 2024 00:18:45 +0800
Subject: [PATCH 123/126] fix:typo error (#1738)

* Update base_agent_tools.py

typo error

* Update main.py

typo error

* Update base_file_knowledge_source.py

typo error

* Update test_main.py

typo error

* Update en.json

* Update prompts.json

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
---
 src/crewai/cli/tools/main.py                              | 4 ++--
 src/crewai/knowledge/source/base_file_knowledge_source.py | 2 +-
 src/crewai/tools/agent_tools/base_agent_tools.py          | 4 ++--
 src/crewai/translations/en.json                           | 2 +-
 tests/cli/tools/test_main.py                              | 2 +-
 tests/utilities/prompts.json                              | 2 +-
 6 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/src/crewai/cli/tools/main.py b/src/crewai/cli/tools/main.py
index 35652a1ec..b2d2cec99 100644
--- a/src/crewai/cli/tools/main.py
+++ b/src/crewai/cli/tools/main.py
@@ -117,7 +117,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
 
         published_handle = publish_response.json()["handle"]
         console.print(
-            f"Succesfully published {published_handle} ({project_version}).\nInstall it in other projects with crewai tool install {published_handle}",
+            f"Successfully published {published_handle} ({project_version}).\nInstall it in other projects with crewai tool install {published_handle}",
             style="bold green",
         )
 
@@ -138,7 +138,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
 
         self._add_package(get_response.json())
 
-        console.print(f"Succesfully installed {handle}", style="bold green")
+        console.print(f"Successfully installed {handle}", style="bold green")
 
     def login(self):
         login_response = self.plus_api_client.login_to_tool_repository()
diff --git a/src/crewai/knowledge/source/base_file_knowledge_source.py b/src/crewai/knowledge/source/base_file_knowledge_source.py
index 7f078b4a4..ae9b3bf71 100644
--- a/src/crewai/knowledge/source/base_file_knowledge_source.py
+++ b/src/crewai/knowledge/source/base_file_knowledge_source.py
@@ -38,7 +38,7 @@ class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC):
             if not path.exists():
                 self._logger.log(
                     "error",
-                    f"File not found: {path}. Try adding sources to the knowledge directory. If its inside the knowledge directory, use the relative path.",
+                    f"File not found: {path}. Try adding sources to the knowledge directory. If it's inside the knowledge directory, use the relative path.",
                     color="red",
                 )
                 raise FileNotFoundError(f"File not found: {path}")
diff --git a/src/crewai/tools/agent_tools/base_agent_tools.py b/src/crewai/tools/agent_tools/base_agent_tools.py
index bedb2aed6..4311be6a3 100644
--- a/src/crewai/tools/agent_tools/base_agent_tools.py
+++ b/src/crewai/tools/agent_tools/base_agent_tools.py
@@ -44,14 +44,14 @@ class BaseAgentTool(BaseTool):
                 if available_agent.role.casefold().replace("\n", "") == agent_name
             ]
         except Exception as _:
-            return self.i18n.errors("agent_tool_unexsiting_coworker").format(
+            return self.i18n.errors("agent_tool_unexisting_coworker").format(
                 coworkers="\n".join(
                     [f"- {agent.role.casefold()}" for agent in self.agents]
                 )
             )
 
         if not agent:
-            return self.i18n.errors("agent_tool_unexsiting_coworker").format(
+            return self.i18n.errors("agent_tool_unexisting_coworker").format(
                 coworkers="\n".join(
                     [f"- {agent.role.casefold()}" for agent in self.agents]
                 )
diff --git a/src/crewai/translations/en.json b/src/crewai/translations/en.json
index 7353cfc33..2b8fec44b 100644
--- a/src/crewai/translations/en.json
+++ b/src/crewai/translations/en.json
@@ -28,7 +28,7 @@
   "errors": {
     "force_final_answer_error": "You can't keep going, this was the best you could do.\n {formatted_answer.text}",
     "force_final_answer": "Now it's time you MUST give your absolute best final answer. You'll ignore all previous instructions, stop using any tools, and just return your absolute BEST Final answer.",
-    "agent_tool_unexsiting_coworker": "\nError executing tool. coworker mentioned not found, it must be one of the following options:\n{coworkers}\n",
+    "agent_tool_unexisting_coworker": "\nError executing tool. coworker mentioned not found, it must be one of the following options:\n{coworkers}\n",
     "task_repeated_usage": "I tried reusing the same input, I must stop using this action input. I'll try something else instead.\n\n",
     "tool_usage_error": "I encountered an error: {error}",
     "tool_arguments_error": "Error: the Action Input is not a valid key, value dictionary.",
diff --git a/tests/cli/tools/test_main.py b/tests/cli/tools/test_main.py
index 3804fb9b4..10c29b920 100644
--- a/tests/cli/tools/test_main.py
+++ b/tests/cli/tools/test_main.py
@@ -85,7 +85,7 @@ def test_install_success(mock_get, mock_subprocess_run):
         env=unittest.mock.ANY
     )
 
-    assert "Succesfully installed sample-tool" in output
+    assert "Successfully installed sample-tool" in output
 
 
 @patch("crewai.cli.plus_api.PlusAPI.get_tool")
diff --git a/tests/utilities/prompts.json b/tests/utilities/prompts.json
index 55bbfae8f..a51203dbc 100644
--- a/tests/utilities/prompts.json
+++ b/tests/utilities/prompts.json
@@ -26,7 +26,7 @@
   },
   "errors": {
     "force_final_answer": "Lorem ipsum dolor sit amet",
-    "agent_tool_unexsiting_coworker": "Lorem ipsum dolor sit amet",
+    "agent_tool_unexisting_coworker": "Lorem ipsum dolor sit amet",
     "task_repeated_usage": "Lorem ipsum dolor sit amet",
     "tool_usage_error": "Lorem ipsum dolor sit amet",
     "tool_arguments_error": "Lorem ipsum dolor sit amet",

From da9220fa81121ff8ffa5c7aa53123c7be03f9851 Mon Sep 17 00:00:00 2001
From: Paul Cowgill <pauldavidcowgill@gmail.com>
Date: Wed, 11 Dec 2024 09:13:57 -0600
Subject: [PATCH 124/126] Remove manager_callbacks reference (#1741)

---
 docs/concepts/crews.mdx | 1 -
 1 file changed, 1 deletion(-)

diff --git a/docs/concepts/crews.mdx b/docs/concepts/crews.mdx
index 3225b48b6..58511b07c 100644
--- a/docs/concepts/crews.mdx
+++ b/docs/concepts/crews.mdx
@@ -32,7 +32,6 @@ A crew in crewAI represents a collaborative group of agents working together to
 | **Share Crew** _(optional)_           | `share_crew`           | Whether you want to share the complete crew information and execution with the crewAI team to make the library better, and allow us to train models.                                                                                                      |
 | **Output Log File** _(optional)_      | `output_log_file`      | Whether you want to have a file with the complete crew output and execution. You can set it using True and it will default to the folder you are currently in and it will be called logs.txt or passing a string with the full path and name of the file. |
 | **Manager Agent** _(optional)_        | `manager_agent`        | `manager` sets a custom agent that will be used as a manager.                                                                                                                                                                                             |
-| **Manager Callbacks** _(optional)_    | `manager_callbacks`    | `manager_callbacks` takes a list of callback handlers to be executed by the manager agent when a hierarchical process is used.                                                                                                                            |
 | **Prompt File** _(optional)_          | `prompt_file`          | Path to the prompt JSON file to be used for the crew.                                                                                                                                                                                                     |
 | **Planning** *(optional)*             | `planning`             | Adds planning ability to the Crew. When activated before each Crew iteration, all Crew data is sent to an AgentPlanner that will plan the tasks and this plan will be added to each task description.                                                     |
 | **Planning LLM** *(optional)*         | `planning_llm`         | The language model used by the AgentPlanner in a planning process.                                                                                                                                                                                        |

From 1df61aba4c4e24060ce6d4049f7848d9caa41d3b Mon Sep 17 00:00:00 2001
From: "Brandon Hancock (bhancock_ai)"
 <109994880+bhancockio@users.noreply.github.com>
Date: Wed, 11 Dec 2024 10:16:05 -0500
Subject: [PATCH 125/126] include event emitter in flows (#1740)

* include event emitter in flows

* Clean up

* Fix linter
---
 pyproject.toml                           |  1 +
 src/crewai/agents/crew_agent_executor.py |  3 +-
 src/crewai/flow/flow.py                  | 55 +++++++++++++++++++++---
 src/crewai/flow/flow_events.py           | 33 ++++++++++++++
 uv.lock                                  | 11 +++++
 5 files changed, 94 insertions(+), 9 deletions(-)
 create mode 100644 src/crewai/flow/flow_events.py

diff --git a/pyproject.toml b/pyproject.toml
index ea684cec6..f90110e85 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -29,6 +29,7 @@ dependencies = [
     "chromadb>=0.5.18",
     "pdfplumber>=0.11.4",
     "openpyxl>=3.1.5",
+    "blinker>=1.9.0",
 ]
 
 [project.urls]
diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py
index 83ca06e41..eb0ff7c5a 100644
--- a/src/crewai/agents/crew_agent_executor.py
+++ b/src/crewai/agents/crew_agent_executor.py
@@ -144,7 +144,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                             formatted_answer
                         )
                         if self.step_callback:
-                          self.step_callback(tool_result)
+                            self.step_callback(tool_result)
 
                         formatted_answer.text += f"\nObservation: {tool_result.result}"
                         formatted_answer.result = tool_result.result
@@ -413,7 +413,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         """
         while self.ask_for_human_input:
             human_feedback = self._ask_human_input(formatted_answer.output)
-            print("Human feedback: ", human_feedback)
 
             if self.crew and self.crew._train:
                 self._handle_crew_training_output(formatted_answer, human_feedback)
diff --git a/src/crewai/flow/flow.py b/src/crewai/flow/flow.py
index fa0902594..ccc76dc95 100644
--- a/src/crewai/flow/flow.py
+++ b/src/crewai/flow/flow.py
@@ -14,8 +14,15 @@ from typing import (
     cast,
 )
 
+from blinker import Signal
 from pydantic import BaseModel, ValidationError
 
+from crewai.flow.flow_events import (
+    FlowFinishedEvent,
+    FlowStartedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionStartedEvent,
+)
 from crewai.flow.flow_visualizer import plot_flow
 from crewai.flow.utils import get_possible_return_constants
 from crewai.telemetry import Telemetry
@@ -159,6 +166,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
     _routers: Dict[str, str] = {}
     _router_paths: Dict[str, List[str]] = {}
     initial_state: Union[Type[T], T, None] = None
+    event_emitter = Signal("event_emitter")
 
     def __class_getitem__(cls: Type["Flow"], item: Type[T]) -> Type["Flow"]:
         class _FlowGeneric(cls):  # type: ignore
@@ -253,6 +261,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
         Returns:
             The final output from the flow execution.
         """
+        self.event_emitter.send(
+            self,
+            event=FlowStartedEvent(
+                type="flow_started",
+                flow_name=self.__class__.__name__,
+            ),
+        )
+
         if inputs is not None:
             self._initialize_state(inputs)
         return asyncio.run(self.kickoff_async())
@@ -267,8 +283,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
         Returns:
             The final output from the flow execution.
         """
-        if inputs is not None:
-            self._initialize_state(inputs)
         if not self._start_methods:
             raise ValueError("No start method defined")
 
@@ -285,11 +299,19 @@ class Flow(Generic[T], metaclass=FlowMeta):
         # Run all start methods concurrently
         await asyncio.gather(*tasks)
 
-        # Return the final output (from the last executed method)
-        if self._method_outputs:
-            return self._method_outputs[-1]
-        else:
-            return None  # Or raise an exception if no methods were executed
+        # Determine the final output (from the last executed method)
+        final_output = self._method_outputs[-1] if self._method_outputs else None
+
+        self.event_emitter.send(
+            self,
+            event=FlowFinishedEvent(
+                type="flow_finished",
+                flow_name=self.__class__.__name__,
+                result=final_output,
+            ),
+        )
+
+        return final_output
 
     async def _execute_start_method(self, start_method_name: str) -> None:
         result = await self._execute_method(
@@ -352,6 +374,16 @@ class Flow(Generic[T], metaclass=FlowMeta):
     async def _execute_single_listener(self, listener_name: str, result: Any) -> None:
         try:
             method = self._methods[listener_name]
+
+            self.event_emitter.send(
+                self,
+                event=MethodExecutionStartedEvent(
+                    type="method_execution_started",
+                    method_name=listener_name,
+                    flow_name=self.__class__.__name__,
+                ),
+            )
+
             sig = inspect.signature(method)
             params = list(sig.parameters.values())
 
@@ -367,6 +399,15 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 # If listener does not expect parameters, call without arguments
                 listener_result = await self._execute_method(listener_name, method)
 
+            self.event_emitter.send(
+                self,
+                event=MethodExecutionFinishedEvent(
+                    type="method_execution_finished",
+                    method_name=listener_name,
+                    flow_name=self.__class__.__name__,
+                ),
+            )
+
             # Execute listeners of this listener
             await self._execute_listeners(listener_name, listener_result)
         except Exception as e:
diff --git a/src/crewai/flow/flow_events.py b/src/crewai/flow/flow_events.py
new file mode 100644
index 000000000..068005ebe
--- /dev/null
+++ b/src/crewai/flow/flow_events.py
@@ -0,0 +1,33 @@
+from dataclasses import dataclass, field
+from datetime import datetime
+from typing import Any, Optional
+
+
+@dataclass
+class Event:
+    type: str
+    flow_name: str
+    timestamp: datetime = field(init=False)
+
+    def __post_init__(self):
+        self.timestamp = datetime.now()
+
+
+@dataclass
+class FlowStartedEvent(Event):
+    pass
+
+
+@dataclass
+class MethodExecutionStartedEvent(Event):
+    method_name: str
+
+
+@dataclass
+class MethodExecutionFinishedEvent(Event):
+    method_name: str
+
+
+@dataclass
+class FlowFinishedEvent(Event):
+    result: Optional[Any] = None
diff --git a/uv.lock b/uv.lock
index 26be5064d..9fa1a274c 100644
--- a/uv.lock
+++ b/uv.lock
@@ -272,6 +272,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b1/fe/e8c672695b37eecc5cbf43e1d0638d88d66ba3a44c4d321c796f4e59167f/beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed", size = 147925 },
 ]
 
+[[package]]
+name = "blinker"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/21/28/9b3f50ce0e048515135495f198351908d99540d69bfdc8c1d15b73dc55ce/blinker-1.9.0.tar.gz", hash = "sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf", size = 22460 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458 },
+]
+
 [[package]]
 name = "build"
 version = "1.2.2.post1"
@@ -568,6 +577,7 @@ source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
     { name = "auth0-python" },
+    { name = "blinker" },
     { name = "chromadb" },
     { name = "click" },
     { name = "instructor" },
@@ -637,6 +647,7 @@ requires-dist = [
     { name = "agentops", marker = "extra == 'agentops'", specifier = ">=0.3.0" },
     { name = "appdirs", specifier = ">=1.4.4" },
     { name = "auth0-python", specifier = ">=4.7.1" },
+    { name = "blinker", specifier = ">=1.9.0" },
     { name = "chromadb", specifier = ">=0.5.18" },
     { name = "click", specifier = ">=8.1.7" },
     { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.14.0" },

From 0b0f2d30ab072abced49de838d9a4be3065edb62 Mon Sep 17 00:00:00 2001
From: Bowen Liang <liangbowen@gf.com.cn>
Date: Wed, 11 Dec 2024 23:46:53 +0800
Subject: [PATCH 126/126] sort imports with isort rules by ruff linter (#1730)

* sort imports

* update

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
Co-authored-by: Eduardo Chiarotti <dudumelgaco@hotmail.com>
---
 .github/workflows/linter.yml                  |  2 +-
 .pre-commit-config.yaml                       |  4 +-
 .ruff.toml                                    |  9 +++++
 pyproject.toml                                |  2 +-
 src/crewai/agents/parser.py                   |  1 +
 src/crewai/cli/authentication/main.py         |  7 +++-
 src/crewai/cli/authentication/token.py        |  3 +-
 src/crewai/cli/command.py                     |  3 +-
 src/crewai/cli/config.py                      | 12 ++++--
 src/crewai/cli/plus_api.py                    |  8 ++--
 src/crewai/cli/reset_memories_command.py      |  3 +-
 src/crewai/cli/version.py                     |  2 +-
 .../storage/base_knowledge_storage.py         |  2 +-
 .../knowledge/storage/knowledge_storage.py    |  2 +-
 .../memory/contextual/contextual_memory.py    |  2 +-
 src/crewai/memory/memory.py                   |  2 +-
 .../memory/short_term/short_term_memory.py    |  6 ++-
 src/crewai/memory/storage/mem0_storage.py     |  1 +
 src/crewai/project/utils.py                   |  1 +
 src/crewai/task.py                            |  2 +-
 src/crewai/telemetry/telemetry.py             |  4 +-
 src/crewai/tools/agent_tools/agent_tools.py   |  4 +-
 .../tools/agent_tools/ask_question_tool.py    |  4 +-
 .../tools/agent_tools/base_agent_tools.py     |  3 +-
 .../tools/agent_tools/delegate_work_tool.py   |  3 +-
 src/crewai/tools/tool_usage_events.py         |  5 ++-
 src/crewai/utilities/crew_json_encoder.py     |  7 ++--
 .../utilities/crew_pydantic_output_parser.py  |  5 ++-
 .../utilities/embedding_configurator.py       |  3 +-
 .../evaluators/crew_evaluator_handler.py      |  9 +++--
 src/crewai/utilities/events.py                |  4 +-
 src/crewai/utilities/planning_handler.py      |  1 +
 src/crewai/utilities/prompts.py               |  4 +-
 .../utilities/pydantic_schema_parser.py       |  2 +-
 .../utilities/task_output_storage_handler.py  |  6 ++-
 .../utilities/token_counter_callback.py       |  3 +-
 tests/agents/agent_builder/base_agent_test.py |  3 +-
 tests/agents/test_crew_agent_parser.py        |  3 +-
 tests/cli/authentication/test_auth_main.py    |  9 ++++-
 tests/cli/authentication/test_utils.py        |  3 +-
 tests/cli/config_test.py                      | 34 ++++++++--------
 tests/cli/test_git.py                         |  3 +-
 tests/cli/test_plus_api.py                    |  1 +
 tests/cli/test_utils.py                       |  6 ++-
 tests/flow_test.py                            |  1 +
 tests/knowledge/knowledge_test.py             |  4 +-
 tests/memory/short_term_memory_test.py        |  4 +-
 tests/task_test.py                            |  5 ++-
 tests/tools/test_tool_usage.py                |  2 +-
 .../evaluators/test_crew_evaluator_handler.py |  1 +
 uv.lock                                       | 40 +++++++++----------
 51 files changed, 159 insertions(+), 101 deletions(-)
 create mode 100644 .ruff.toml

diff --git a/.github/workflows/linter.yml b/.github/workflows/linter.yml
index 7ced70df9..f9853cf7c 100644
--- a/.github/workflows/linter.yml
+++ b/.github/workflows/linter.yml
@@ -13,4 +13,4 @@ jobs:
           pip install ruff
 
       - name: Run Ruff Linter
-        run: ruff check --exclude "templates","__init__.py"
+        run: ruff check
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index dfa210d60..291f3f871 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,9 +1,7 @@
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.4.4
+    rev: v0.8.2
     hooks:
       - id: ruff
         args: ["--fix"]
-        exclude: "templates"
       - id: ruff-format
-        exclude: "templates"
diff --git a/.ruff.toml b/.ruff.toml
new file mode 100644
index 000000000..acc241bd4
--- /dev/null
+++ b/.ruff.toml
@@ -0,0 +1,9 @@
+exclude = [
+    "templates",
+    "__init__.py",
+]
+
+[lint]
+select = [
+    "I", # isort rules
+]
diff --git a/pyproject.toml b/pyproject.toml
index f90110e85..5885d5c8e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -54,7 +54,7 @@ mem0 = ["mem0ai>=0.1.29"]
 
 [tool.uv]
 dev-dependencies = [
-    "ruff>=0.4.10",
+    "ruff>=0.8.2",
     "mypy>=1.10.0",
     "pre-commit>=3.6.0",
     "mkdocs>=1.4.3",
diff --git a/src/crewai/agents/parser.py b/src/crewai/agents/parser.py
index 2286900c1..b4629a8d2 100644
--- a/src/crewai/agents/parser.py
+++ b/src/crewai/agents/parser.py
@@ -1,5 +1,6 @@
 import re
 from typing import Any, Union
+
 from json_repair import repair_json
 
 from crewai.utilities import I18N
diff --git a/src/crewai/cli/authentication/main.py b/src/crewai/cli/authentication/main.py
index c64045801..5a335e1f2 100644
--- a/src/crewai/cli/authentication/main.py
+++ b/src/crewai/cli/authentication/main.py
@@ -5,9 +5,10 @@ from typing import Any, Dict
 import requests
 from rich.console import Console
 
+from crewai.cli.tools.main import ToolCommand
+
 from .constants import AUTH0_AUDIENCE, AUTH0_CLIENT_ID, AUTH0_DOMAIN
 from .utils import TokenManager, validate_token
-from crewai.cli.tools.main import ToolCommand
 
 console = Console()
 
@@ -79,7 +80,9 @@ class AuthenticationCommand:
                         style="yellow",
                     )
 
-                console.print("\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n")
+                console.print(
+                    "\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n"
+                )
                 return
 
             if token_data["error"] not in ("authorization_pending", "slow_down"):
diff --git a/src/crewai/cli/authentication/token.py b/src/crewai/cli/authentication/token.py
index 889fdc2eb..30a33b4ba 100644
--- a/src/crewai/cli/authentication/token.py
+++ b/src/crewai/cli/authentication/token.py
@@ -1,10 +1,9 @@
 from .utils import TokenManager
 
+
 def get_auth_token() -> str:
     """Get the authentication token."""
     access_token = TokenManager().get_token()
     if not access_token:
         raise Exception()
     return access_token
-
-
diff --git a/src/crewai/cli/command.py b/src/crewai/cli/command.py
index f2af92bf5..2bef8985d 100644
--- a/src/crewai/cli/command.py
+++ b/src/crewai/cli/command.py
@@ -1,8 +1,9 @@
 import requests
 from requests.exceptions import JSONDecodeError
 from rich.console import Console
-from crewai.cli.plus_api import PlusAPI
+
 from crewai.cli.authentication.token import get_auth_token
+from crewai.cli.plus_api import PlusAPI
 from crewai.telemetry.telemetry import Telemetry
 
 console = Console()
diff --git a/src/crewai/cli/config.py b/src/crewai/cli/config.py
index 000f1e6d0..8e30767ca 100644
--- a/src/crewai/cli/config.py
+++ b/src/crewai/cli/config.py
@@ -1,13 +1,19 @@
 import json
 from pathlib import Path
-from pydantic import BaseModel, Field
 from typing import Optional
 
+from pydantic import BaseModel, Field
+
 DEFAULT_CONFIG_PATH = Path.home() / ".config" / "crewai" / "settings.json"
 
+
 class Settings(BaseModel):
-    tool_repository_username: Optional[str] = Field(None, description="Username for interacting with the Tool Repository")
-    tool_repository_password: Optional[str] = Field(None, description="Password for interacting with the Tool Repository")
+    tool_repository_username: Optional[str] = Field(
+        None, description="Username for interacting with the Tool Repository"
+    )
+    tool_repository_password: Optional[str] = Field(
+        None, description="Password for interacting with the Tool Repository"
+    )
     config_path: Path = Field(default=DEFAULT_CONFIG_PATH, exclude=True)
 
     def __init__(self, config_path: Path = DEFAULT_CONFIG_PATH, **data):
diff --git a/src/crewai/cli/plus_api.py b/src/crewai/cli/plus_api.py
index 2fce0d6d8..23032ca8f 100644
--- a/src/crewai/cli/plus_api.py
+++ b/src/crewai/cli/plus_api.py
@@ -1,9 +1,11 @@
-from typing import Optional
-import requests
 from os import getenv
-from crewai.cli.version import get_crewai_version
+from typing import Optional
 from urllib.parse import urljoin
 
+import requests
+
+from crewai.cli.version import get_crewai_version
+
 
 class PlusAPI:
     """
diff --git a/src/crewai/cli/reset_memories_command.py b/src/crewai/cli/reset_memories_command.py
index 31624cfc3..554232f52 100644
--- a/src/crewai/cli/reset_memories_command.py
+++ b/src/crewai/cli/reset_memories_command.py
@@ -1,11 +1,12 @@
 import subprocess
+
 import click
 
+from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
 from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
 from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
-from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
 
 
 def reset_memories_command(
diff --git a/src/crewai/cli/version.py b/src/crewai/cli/version.py
index 543be9c32..a7c1087a7 100644
--- a/src/crewai/cli/version.py
+++ b/src/crewai/cli/version.py
@@ -1,6 +1,6 @@
 import importlib.metadata
 
+
 def get_crewai_version() -> str:
     """Get the version number of CrewAI running the CLI"""
     return importlib.metadata.version("crewai")
-
diff --git a/src/crewai/knowledge/storage/base_knowledge_storage.py b/src/crewai/knowledge/storage/base_knowledge_storage.py
index 78d370e04..d4887e85b 100644
--- a/src/crewai/knowledge/storage/base_knowledge_storage.py
+++ b/src/crewai/knowledge/storage/base_knowledge_storage.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Dict, Any, List, Optional
+from typing import Any, Dict, List, Optional
 
 
 class BaseKnowledgeStorage(ABC):
diff --git a/src/crewai/knowledge/storage/knowledge_storage.py b/src/crewai/knowledge/storage/knowledge_storage.py
index acbbe75a1..7f79877ed 100644
--- a/src/crewai/knowledge/storage/knowledge_storage.py
+++ b/src/crewai/knowledge/storage/knowledge_storage.py
@@ -14,9 +14,9 @@ from chromadb.config import Settings
 
 from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
 from crewai.utilities import EmbeddingConfigurator
+from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
 from crewai.utilities.logger import Logger
 from crewai.utilities.paths import db_storage_path
-from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
 
 
 @contextlib.contextmanager
diff --git a/src/crewai/memory/contextual/contextual_memory.py b/src/crewai/memory/contextual/contextual_memory.py
index 9598fe6ee..cdb9cf836 100644
--- a/src/crewai/memory/contextual/contextual_memory.py
+++ b/src/crewai/memory/contextual/contextual_memory.py
@@ -1,4 +1,4 @@
-from typing import Optional, Dict, Any
+from typing import Any, Dict, Optional
 
 from crewai.memory import EntityMemory, LongTermMemory, ShortTermMemory, UserMemory
 
diff --git a/src/crewai/memory/memory.py b/src/crewai/memory/memory.py
index 4869f8e6b..46af2c04d 100644
--- a/src/crewai/memory/memory.py
+++ b/src/crewai/memory/memory.py
@@ -1,4 +1,4 @@
-from typing import Any, Dict, Optional, List
+from typing import Any, Dict, List, Optional
 
 from crewai.memory.storage.rag_storage import RAGStorage
 
diff --git a/src/crewai/memory/short_term/short_term_memory.py b/src/crewai/memory/short_term/short_term_memory.py
index 4ade7eb93..4e5fbbb77 100644
--- a/src/crewai/memory/short_term/short_term_memory.py
+++ b/src/crewai/memory/short_term/short_term_memory.py
@@ -1,4 +1,5 @@
 from typing import Any, Dict, Optional
+
 from crewai.memory.memory import Memory
 from crewai.memory.short_term.short_term_memory_item import ShortTermMemoryItem
 from crewai.memory.storage.rag_storage import RAGStorage
@@ -32,7 +33,10 @@ class ShortTermMemory(Memory):
                 storage
                 if storage
                 else RAGStorage(
-                    type="short_term", embedder_config=embedder_config, crew=crew, path=path
+                    type="short_term",
+                    embedder_config=embedder_config,
+                    crew=crew,
+                    path=path,
                 )
             )
         super().__init__(storage)
diff --git a/src/crewai/memory/storage/mem0_storage.py b/src/crewai/memory/storage/mem0_storage.py
index 34aab9716..e4e84fab4 100644
--- a/src/crewai/memory/storage/mem0_storage.py
+++ b/src/crewai/memory/storage/mem0_storage.py
@@ -2,6 +2,7 @@ import os
 from typing import Any, Dict, List
 
 from mem0 import MemoryClient
+
 from crewai.memory.storage.interface import Storage
 
 
diff --git a/src/crewai/project/utils.py b/src/crewai/project/utils.py
index 2e95c755d..e8876d941 100644
--- a/src/crewai/project/utils.py
+++ b/src/crewai/project/utils.py
@@ -1,5 +1,6 @@
 from functools import wraps
 
+
 def memoize(func):
     cache = {}
 
diff --git a/src/crewai/task.py b/src/crewai/task.py
index cedb73c09..b585e0c69 100644
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -1,11 +1,11 @@
 import datetime
 import json
-from pathlib import Path
 import threading
 import uuid
 from concurrent.futures import Future
 from copy import copy
 from hashlib import md5
+from pathlib import Path
 from typing import Any, Dict, List, Optional, Set, Tuple, Type, Union
 
 from opentelemetry.trace import Span
diff --git a/src/crewai/telemetry/telemetry.py b/src/crewai/telemetry/telemetry.py
index e191f8d4d..aa0f8b9ff 100644
--- a/src/crewai/telemetry/telemetry.py
+++ b/src/crewai/telemetry/telemetry.py
@@ -21,7 +21,9 @@ with suppress_warnings():
 
 
 from opentelemetry import trace  # noqa: E402
-from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter # noqa: E402
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
+    OTLPSpanExporter,  # noqa: E402
+)
 from opentelemetry.sdk.resources import SERVICE_NAME, Resource  # noqa: E402
 from opentelemetry.sdk.trace import TracerProvider  # noqa: E402
 from opentelemetry.sdk.trace.export import BatchSpanProcessor  # noqa: E402
diff --git a/src/crewai/tools/agent_tools/agent_tools.py b/src/crewai/tools/agent_tools/agent_tools.py
index 1db55a29b..08383c244 100644
--- a/src/crewai/tools/agent_tools/agent_tools.py
+++ b/src/crewai/tools/agent_tools/agent_tools.py
@@ -1,9 +1,9 @@
-from crewai.tools.base_tool import BaseTool
 from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.tools.base_tool import BaseTool
 from crewai.utilities import I18N
 
-from .delegate_work_tool import DelegateWorkTool
 from .ask_question_tool import AskQuestionTool
+from .delegate_work_tool import DelegateWorkTool
 
 
 class AgentTools:
diff --git a/src/crewai/tools/agent_tools/ask_question_tool.py b/src/crewai/tools/agent_tools/ask_question_tool.py
index af739b8fc..9294770e5 100644
--- a/src/crewai/tools/agent_tools/ask_question_tool.py
+++ b/src/crewai/tools/agent_tools/ask_question_tool.py
@@ -1,7 +1,9 @@
-from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
 from typing import Optional
+
 from pydantic import BaseModel, Field
 
+from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
+
 
 class AskQuestionToolSchema(BaseModel):
     question: str = Field(..., description="The question to ask")
diff --git a/src/crewai/tools/agent_tools/base_agent_tools.py b/src/crewai/tools/agent_tools/base_agent_tools.py
index 4311be6a3..ea63dd51e 100644
--- a/src/crewai/tools/agent_tools/base_agent_tools.py
+++ b/src/crewai/tools/agent_tools/base_agent_tools.py
@@ -1,9 +1,10 @@
 from typing import Optional, Union
+
 from pydantic import Field
 
-from crewai.tools.base_tool import BaseTool
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.task import Task
+from crewai.tools.base_tool import BaseTool
 from crewai.utilities import I18N
 
 
diff --git a/src/crewai/tools/agent_tools/delegate_work_tool.py b/src/crewai/tools/agent_tools/delegate_work_tool.py
index 7f2007597..9dbf6c920 100644
--- a/src/crewai/tools/agent_tools/delegate_work_tool.py
+++ b/src/crewai/tools/agent_tools/delegate_work_tool.py
@@ -1,8 +1,9 @@
-from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
 from typing import Optional
 
 from pydantic import BaseModel, Field
 
+from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
+
 
 class DelegateWorkToolSchema(BaseModel):
     task: str = Field(..., description="The task to delegate")
diff --git a/src/crewai/tools/tool_usage_events.py b/src/crewai/tools/tool_usage_events.py
index fea9d3f3c..3c1d16113 100644
--- a/src/crewai/tools/tool_usage_events.py
+++ b/src/crewai/tools/tool_usage_events.py
@@ -1,6 +1,7 @@
-from typing import Any, Dict
-from pydantic import BaseModel
 from datetime import datetime
+from typing import Any, Dict
+
+from pydantic import BaseModel
 
 
 class ToolUsageEvent(BaseModel):
diff --git a/src/crewai/utilities/crew_json_encoder.py b/src/crewai/utilities/crew_json_encoder.py
index c3f95fcf6..70c1e9274 100644
--- a/src/crewai/utilities/crew_json_encoder.py
+++ b/src/crewai/utilities/crew_json_encoder.py
@@ -1,8 +1,9 @@
-from datetime import datetime, date
 import json
-from uuid import UUID
-from pydantic import BaseModel
+from datetime import date, datetime
 from decimal import Decimal
+from uuid import UUID
+
+from pydantic import BaseModel
 
 
 class CrewJSONEncoder(json.JSONEncoder):
diff --git a/src/crewai/utilities/crew_pydantic_output_parser.py b/src/crewai/utilities/crew_pydantic_output_parser.py
index 5c5fa0d94..c269f3189 100644
--- a/src/crewai/utilities/crew_pydantic_output_parser.py
+++ b/src/crewai/utilities/crew_pydantic_output_parser.py
@@ -1,10 +1,11 @@
 import json
-import regex
 from typing import Any, Type
 
-from crewai.agents.parser import OutputParserException
+import regex
 from pydantic import BaseModel, ValidationError
 
+from crewai.agents.parser import OutputParserException
+
 
 class CrewPydanticOutputParser:
     """Parses the text into pydantic models"""
diff --git a/src/crewai/utilities/embedding_configurator.py b/src/crewai/utilities/embedding_configurator.py
index f0f77ffca..44e832ec2 100644
--- a/src/crewai/utilities/embedding_configurator.py
+++ b/src/crewai/utilities/embedding_configurator.py
@@ -1,6 +1,7 @@
 import os
 from typing import Any, Dict, cast
-from chromadb import EmbeddingFunction, Documents, Embeddings
+
+from chromadb import Documents, EmbeddingFunction, Embeddings
 from chromadb.api.types import validate_embedding_function
 
 
diff --git a/src/crewai/utilities/evaluators/crew_evaluator_handler.py b/src/crewai/utilities/evaluators/crew_evaluator_handler.py
index e251f76f2..3387d91b3 100644
--- a/src/crewai/utilities/evaluators/crew_evaluator_handler.py
+++ b/src/crewai/utilities/evaluators/crew_evaluator_handler.py
@@ -1,13 +1,14 @@
 from collections import defaultdict
 
+from pydantic import BaseModel, Field
+from rich.box import HEAVY_EDGE
+from rich.console import Console
+from rich.table import Table
+
 from crewai.agent import Agent
 from crewai.task import Task
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
-from pydantic import BaseModel, Field
-from rich.box import HEAVY_EDGE
-from rich.console import Console
-from rich.table import Table
 
 
 class TaskEvaluationPydanticOutput(BaseModel):
diff --git a/src/crewai/utilities/events.py b/src/crewai/utilities/events.py
index 75425fca2..11175e0d2 100644
--- a/src/crewai/utilities/events.py
+++ b/src/crewai/utilities/events.py
@@ -1,7 +1,7 @@
-from typing import Any, Callable, Generic, List, Dict, Type, TypeVar
 from functools import wraps
-from pydantic import BaseModel
+from typing import Any, Callable, Dict, Generic, List, Type, TypeVar
 
+from pydantic import BaseModel
 
 T = TypeVar("T")
 EVT = TypeVar("EVT", bound=BaseModel)
diff --git a/src/crewai/utilities/planning_handler.py b/src/crewai/utilities/planning_handler.py
index 14a9a50a6..590f42389 100644
--- a/src/crewai/utilities/planning_handler.py
+++ b/src/crewai/utilities/planning_handler.py
@@ -1,4 +1,5 @@
 from typing import Any, List, Optional
+
 from pydantic import BaseModel, Field
 
 from crewai.agent import Agent
diff --git a/src/crewai/utilities/prompts.py b/src/crewai/utilities/prompts.py
index cecd6cb71..66909644f 100644
--- a/src/crewai/utilities/prompts.py
+++ b/src/crewai/utilities/prompts.py
@@ -1,5 +1,7 @@
-from pydantic import BaseModel, Field
 from typing import Any, Optional
+
+from pydantic import BaseModel, Field
+
 from crewai.utilities import I18N
 
 
diff --git a/src/crewai/utilities/pydantic_schema_parser.py b/src/crewai/utilities/pydantic_schema_parser.py
index 073280dd2..f4c8c720f 100644
--- a/src/crewai/utilities/pydantic_schema_parser.py
+++ b/src/crewai/utilities/pydantic_schema_parser.py
@@ -1,4 +1,4 @@
-from typing import Type, get_args, get_origin, Union
+from typing import Type, Union, get_args, get_origin
 
 from pydantic import BaseModel
 
diff --git a/src/crewai/utilities/task_output_storage_handler.py b/src/crewai/utilities/task_output_storage_handler.py
index 9970f64b4..34cdaccbb 100644
--- a/src/crewai/utilities/task_output_storage_handler.py
+++ b/src/crewai/utilities/task_output_storage_handler.py
@@ -1,6 +1,8 @@
-from pydantic import BaseModel, Field
 from datetime import datetime
-from typing import Dict, Any, Optional, List
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
 from crewai.memory.storage.kickoff_task_outputs_storage import (
     KickoffTaskOutputsSQLiteStorage,
 )
diff --git a/src/crewai/utilities/token_counter_callback.py b/src/crewai/utilities/token_counter_callback.py
index feaaa4c22..06ad15022 100644
--- a/src/crewai/utilities/token_counter_callback.py
+++ b/src/crewai/utilities/token_counter_callback.py
@@ -1,5 +1,6 @@
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.types.utils import Usage
+
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
 
 
@@ -11,7 +12,7 @@ class TokenCalcHandler(CustomLogger):
         if self.token_cost_process is None:
             return
 
-        usage : Usage = response_obj["usage"]
+        usage: Usage = response_obj["usage"]
         self.token_cost_process.sum_successful_requests(1)
         self.token_cost_process.sum_prompt_tokens(usage.prompt_tokens)
         self.token_cost_process.sum_completion_tokens(usage.completion_tokens)
diff --git a/tests/agents/agent_builder/base_agent_test.py b/tests/agents/agent_builder/base_agent_test.py
index fcd5d58b6..7c0c2f472 100644
--- a/tests/agents/agent_builder/base_agent_test.py
+++ b/tests/agents/agent_builder/base_agent_test.py
@@ -1,9 +1,10 @@
 import hashlib
 from typing import Any, List, Optional
 
+from pydantic import BaseModel
+
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.tools.base_tool import BaseTool
-from pydantic import BaseModel
 
 
 class TestAgent(BaseAgent):
diff --git a/tests/agents/test_crew_agent_parser.py b/tests/agents/test_crew_agent_parser.py
index 6496f7193..4b48e1552 100644
--- a/tests/agents/test_crew_agent_parser.py
+++ b/tests/agents/test_crew_agent_parser.py
@@ -1,10 +1,11 @@
 import pytest
-from crewai.agents.parser import CrewAgentParser
+
 from crewai.agents.crew_agent_executor import (
     AgentAction,
     AgentFinish,
     OutputParserException,
 )
+from crewai.agents.parser import CrewAgentParser
 
 
 @pytest.fixture
diff --git a/tests/cli/authentication/test_auth_main.py b/tests/cli/authentication/test_auth_main.py
index 4466cc999..a0b4fa0d9 100644
--- a/tests/cli/authentication/test_auth_main.py
+++ b/tests/cli/authentication/test_auth_main.py
@@ -2,6 +2,7 @@ import unittest
 from unittest.mock import MagicMock, patch
 
 import requests
+
 from crewai.cli.authentication.main import AuthenticationCommand
 
 
@@ -47,7 +48,9 @@ class TestAuthenticationCommand(unittest.TestCase):
     @patch("crewai.cli.authentication.main.requests.post")
     @patch("crewai.cli.authentication.main.validate_token")
     @patch("crewai.cli.authentication.main.console.print")
-    def test_poll_for_token_success(self, mock_print, mock_validate_token, mock_post, mock_tool):
+    def test_poll_for_token_success(
+        self, mock_print, mock_validate_token, mock_post, mock_tool
+    ):
         mock_response = MagicMock()
         mock_response.status_code = 200
         mock_response.json.return_value = {
@@ -62,7 +65,9 @@ class TestAuthenticationCommand(unittest.TestCase):
         self.auth_command._poll_for_token({"device_code": "123456"})
 
         mock_validate_token.assert_called_once_with("TOKEN")
-        mock_print.assert_called_once_with("\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n")
+        mock_print.assert_called_once_with(
+            "\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n"
+        )
 
     @patch("crewai.cli.authentication.main.requests.post")
     @patch("crewai.cli.authentication.main.console.print")
diff --git a/tests/cli/authentication/test_utils.py b/tests/cli/authentication/test_utils.py
index d634780a8..6da48dcd0 100644
--- a/tests/cli/authentication/test_utils.py
+++ b/tests/cli/authentication/test_utils.py
@@ -3,9 +3,10 @@ import unittest
 from datetime import datetime, timedelta
 from unittest.mock import MagicMock, patch
 
-from crewai.cli.authentication.utils import TokenManager, validate_token
 from cryptography.fernet import Fernet
 
+from crewai.cli.authentication.utils import TokenManager, validate_token
+
 
 class TestValidateToken(unittest.TestCase):
     @patch("crewai.cli.authentication.utils.AsymmetricSignatureVerifier")
diff --git a/tests/cli/config_test.py b/tests/cli/config_test.py
index 1065d4730..95a38c06b 100644
--- a/tests/cli/config_test.py
+++ b/tests/cli/config_test.py
@@ -1,10 +1,12 @@
-import unittest
 import json
-import tempfile
 import shutil
+import tempfile
+import unittest
 from pathlib import Path
+
 from crewai.cli.config import Settings
 
+
 class TestSettings(unittest.TestCase):
     def setUp(self):
         self.test_dir = Path(tempfile.mkdtemp())
@@ -20,8 +22,7 @@ class TestSettings(unittest.TestCase):
 
     def test_initialization_with_data(self):
         settings = Settings(
-            config_path=self.config_path,
-            tool_repository_username="user1"
+            config_path=self.config_path, tool_repository_username="user1"
         )
         self.assertEqual(settings.tool_repository_username, "user1")
         self.assertIsNone(settings.tool_repository_password)
@@ -37,22 +38,23 @@ class TestSettings(unittest.TestCase):
     def test_merge_file_and_input_data(self):
         self.config_path.parent.mkdir(parents=True, exist_ok=True)
         with self.config_path.open("w") as f:
-            json.dump({
-                "tool_repository_username": "file_user",
-                "tool_repository_password": "file_pass"
-            }, f)
+            json.dump(
+                {
+                    "tool_repository_username": "file_user",
+                    "tool_repository_password": "file_pass",
+                },
+                f,
+            )
 
         settings = Settings(
-            config_path=self.config_path,
-            tool_repository_username="new_user"
+            config_path=self.config_path, tool_repository_username="new_user"
         )
         self.assertEqual(settings.tool_repository_username, "new_user")
         self.assertEqual(settings.tool_repository_password, "file_pass")
 
     def test_dump_new_settings(self):
         settings = Settings(
-            config_path=self.config_path,
-            tool_repository_username="user1"
+            config_path=self.config_path, tool_repository_username="user1"
         )
         settings.dump()
 
@@ -67,8 +69,7 @@ class TestSettings(unittest.TestCase):
             json.dump({"existing_setting": "value"}, f)
 
         settings = Settings(
-            config_path=self.config_path,
-            tool_repository_username="user1"
+            config_path=self.config_path, tool_repository_username="user1"
         )
         settings.dump()
 
@@ -79,10 +80,7 @@ class TestSettings(unittest.TestCase):
         self.assertEqual(saved_data["tool_repository_username"], "user1")
 
     def test_none_values(self):
-        settings = Settings(
-            config_path=self.config_path,
-            tool_repository_username=None
-        )
+        settings = Settings(config_path=self.config_path, tool_repository_username=None)
         settings.dump()
 
         with self.config_path.open("r") as f:
diff --git a/tests/cli/test_git.py b/tests/cli/test_git.py
index 1fb1296cd..ccf8f0539 100644
--- a/tests/cli/test_git.py
+++ b/tests/cli/test_git.py
@@ -1,6 +1,7 @@
-from crewai.cli.git import Repository
 import pytest
 
+from crewai.cli.git import Repository
+
 
 @pytest.fixture()
 def repository(fp):
diff --git a/tests/cli/test_plus_api.py b/tests/cli/test_plus_api.py
index e0acf22e3..daefeee42 100644
--- a/tests/cli/test_plus_api.py
+++ b/tests/cli/test_plus_api.py
@@ -1,6 +1,7 @@
 import os
 import unittest
 from unittest.mock import MagicMock, patch
+
 from crewai.cli.plus_api import PlusAPI
 
 
diff --git a/tests/cli/test_utils.py b/tests/cli/test_utils.py
index 616fb3d2f..0270b12fc 100644
--- a/tests/cli/test_utils.py
+++ b/tests/cli/test_utils.py
@@ -1,7 +1,9 @@
-import pytest
+import os
 import shutil
 import tempfile
-import os
+
+import pytest
+
 from crewai.cli import utils
 
 
diff --git a/tests/flow_test.py b/tests/flow_test.py
index ffd82367c..2e2020361 100644
--- a/tests/flow_test.py
+++ b/tests/flow_test.py
@@ -3,6 +3,7 @@
 import asyncio
 
 import pytest
+
 from crewai.flow.flow import Flow, and_, listen, or_, router, start
 
 
diff --git a/tests/knowledge/knowledge_test.py b/tests/knowledge/knowledge_test.py
index 4f506ff16..201ddea12 100644
--- a/tests/knowledge/knowledge_test.py
+++ b/tests/knowledge/knowledge_test.py
@@ -3,6 +3,8 @@
 from pathlib import Path
 from unittest.mock import patch
 
+import pytest
+
 from crewai.knowledge.source.csv_knowledge_source import CSVKnowledgeSource
 from crewai.knowledge.source.excel_knowledge_source import ExcelKnowledgeSource
 from crewai.knowledge.source.json_knowledge_source import JSONKnowledgeSource
@@ -10,8 +12,6 @@ from crewai.knowledge.source.pdf_knowledge_source import PDFKnowledgeSource
 from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.knowledge.source.text_file_knowledge_source import TextFileKnowledgeSource
 
-import pytest
-
 
 @pytest.fixture(autouse=True)
 def mock_vector_db():
diff --git a/tests/memory/short_term_memory_test.py b/tests/memory/short_term_memory_test.py
index c09b22691..6cde2a044 100644
--- a/tests/memory/short_term_memory_test.py
+++ b/tests/memory/short_term_memory_test.py
@@ -1,5 +1,7 @@
-import pytest
 from unittest.mock import patch
+
+import pytest
+
 from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
diff --git a/tests/task_test.py b/tests/task_test.py
index 3b3de0bed..b38b95996 100644
--- a/tests/task_test.py
+++ b/tests/task_test.py
@@ -6,12 +6,13 @@ import os
 from unittest.mock import MagicMock, patch
 
 import pytest
+from pydantic import BaseModel
+from pydantic_core import ValidationError
+
 from crewai import Agent, Crew, Process, Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
 from crewai.utilities.converter import Converter
-from pydantic import BaseModel
-from pydantic_core import ValidationError
 
 
 def test_task_tool_reflect_agent_tools():
diff --git a/tests/tools/test_tool_usage.py b/tests/tools/test_tool_usage.py
index fbe93a628..05b9b23af 100644
--- a/tests/tools/test_tool_usage.py
+++ b/tests/tools/test_tool_usage.py
@@ -6,8 +6,8 @@ import pytest
 from pydantic import BaseModel, Field
 
 from crewai import Agent, Task
-from crewai.tools.tool_usage import ToolUsage
 from crewai.tools import BaseTool
+from crewai.tools.tool_usage import ToolUsage
 
 
 class RandomNumberToolInput(BaseModel):
diff --git a/tests/utilities/evaluators/test_crew_evaluator_handler.py b/tests/utilities/evaluators/test_crew_evaluator_handler.py
index 6c92ffdbc..649c25998 100644
--- a/tests/utilities/evaluators/test_crew_evaluator_handler.py
+++ b/tests/utilities/evaluators/test_crew_evaluator_handler.py
@@ -1,6 +1,7 @@
 from unittest import mock
 
 import pytest
+
 from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.task import Task
diff --git a/uv.lock b/uv.lock
index 9fa1a274c..915111e8c 100644
--- a/uv.lock
+++ b/uv.lock
@@ -692,7 +692,7 @@ dev = [
     { name = "pytest-subprocess", specifier = ">=1.5.2" },
     { name = "pytest-vcr", specifier = ">=1.0.2" },
     { name = "python-dotenv", specifier = ">=1.0.0" },
-    { name = "ruff", specifier = ">=0.4.10" },
+    { name = "ruff", specifier = ">=0.8.2" },
 ]
 
 [[package]]
@@ -3876,27 +3876,27 @@ wheels = [
 
 [[package]]
 name = "ruff"
-version = "0.7.0"
+version = "0.8.2"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/2c/c7/f3367d1da5d568192968c5c9e7f3d51fb317b9ac04828493b23d8fce8ce6/ruff-0.7.0.tar.gz", hash = "sha256:47a86360cf62d9cd53ebfb0b5eb0e882193fc191c6d717e8bef4462bc3b9ea2b", size = 3146645 }
+sdist = { url = "https://files.pythonhosted.org/packages/5e/2b/01245f4f3a727d60bebeacd7ee6d22586c7f62380a2597ddb22c2f45d018/ruff-0.8.2.tar.gz", hash = "sha256:b84f4f414dda8ac7f75075c1fa0b905ac0ff25361f42e6d5da681a465e0f78e5", size = 3349020 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/48/59/a0275a0913f3539498d116046dd679cd657fe3b7caf5afe1733319414932/ruff-0.7.0-py3-none-linux_armv6l.whl", hash = "sha256:0cdf20c2b6ff98e37df47b2b0bd3a34aaa155f59a11182c1303cce79be715628", size = 10434007 },
-    { url = "https://files.pythonhosted.org/packages/cd/94/da0ba5f956d04c90dd899209904210600009dcda039ce840d83eb4298c7d/ruff-0.7.0-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:496494d350c7fdeb36ca4ef1c9f21d80d182423718782222c29b3e72b3512737", size = 10048066 },
-    { url = "https://files.pythonhosted.org/packages/57/1d/e5cc149ecc46e4f203403a79ccd170fad52d316f98b87d0f63b1945567db/ruff-0.7.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:214b88498684e20b6b2b8852c01d50f0651f3cc6118dfa113b4def9f14faaf06", size = 9711389 },
-    { url = "https://files.pythonhosted.org/packages/05/67/fb7ea2c869c539725a16c5bc294e9aa34f8b1b6fe702f1d173a5da517c2b/ruff-0.7.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:630fce3fefe9844e91ea5bbf7ceadab4f9981f42b704fae011bb8efcaf5d84be", size = 10755174 },
-    { url = "https://files.pythonhosted.org/packages/5f/f0/13703bc50536a0613ea3dce991116e5f0917a1f05528c6ab738b33c08d3f/ruff-0.7.0-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:211d877674e9373d4bb0f1c80f97a0201c61bcd1e9d045b6e9726adc42c156aa", size = 10196040 },
-    { url = "https://files.pythonhosted.org/packages/99/c1/77b04ab20324ab03d333522ee55fb0f1c38e3ca0d326b4905f82ce6b6c70/ruff-0.7.0-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:194d6c46c98c73949a106425ed40a576f52291c12bc21399eb8f13a0f7073495", size = 11033684 },
-    { url = "https://files.pythonhosted.org/packages/f2/97/f463334dc4efeea3551cd109163df15561c18a1c3ec13d51643740fd36ba/ruff-0.7.0-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:82c2579b82b9973a110fab281860403b397c08c403de92de19568f32f7178598", size = 11803700 },
-    { url = "https://files.pythonhosted.org/packages/b4/f8/a31d40c4bb92933d376a53e7c5d0245d9b27841357e4820e96d38f54b480/ruff-0.7.0-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9af971fe85dcd5eaed8f585ddbc6bdbe8c217fb8fcf510ea6bca5bdfff56040e", size = 11347848 },
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