Fix type issue

copy googles changes. Fix tests. Improve LLM file
2026-10-20 17:05:04 +02:00 · 2024-12-09 15:27:36 -05:00 · 2024-12-09 15:18:44 -05:00
74 changed files with 11299 additions and 955 deletions
@@ -13,4 +13,4 @@ jobs:
          pip install ruff

      - name: Run Ruff Linter
-        run: ruff check
+        run: ruff check --exclude "templates","__init__.py"
@@ -1,10 +1,5 @@
 name: Mark stale issues and pull requests

-permissions:
-  contents: write
-  issues: write
-  pull-requests: write
-
 on:
  schedule:
    - cron: '10 12 * * *'
@@ -13,6 +8,9 @@ on:
 jobs:
  stale:
    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
    steps:
    - uses: actions/stale@v9
      with:
@@ -1,7 +1,9 @@
 repos:
  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.2
+    rev: v0.4.4
    hooks:
      - id: ruff
        args: ["--fix"]
+        exclude: "templates"
      - id: ruff-format
+        exclude: "templates"
@@ -1,9 +0,0 @@
-exclude = [
-    "templates",
-    "__init__.py",
-]
-
-[lint]
-select = [
-    "I", # isort rules
-]
@@ -32,6 +32,7 @@ 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.                                                                                                                                                                                        |
@@ -43,81 +43,6 @@ Here's a detailed breakdown of supported models and their capabilities, you can
      1 token ≈ 4 characters in English. For example, 8,192 tokens ≈ 32,768 characters or about 6,000 words.
    </Note>
  </Tab>
-  <Tab title="Nvidia NIM">
-    | Model | Context Window | Best For |
-    |-------|---------------|-----------|
-    | nvidia/mistral-nemo-minitron-8b-8k-instruct | 8,192 tokens | State-of-the-art small language model delivering superior accuracy for chatbot, virtual assistants, and content generation. |
-    | nvidia/nemotron-4-mini-hindi-4b-instruct| 4,096 tokens | A bilingual Hindi-English SLM for on-device inference, tailored specifically for Hindi Language. |
-    | "nvidia/llama-3.1-nemotron-70b-instruct | 128k tokens | Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA in order to improve the helpfulness of LLM generated responses. |
-    | nvidia/llama3-chatqa-1.5-8b | 128k tokens | Advanced LLM to generate high-quality, context-aware responses for chatbots and search engines. |
-    | nvidia/llama3-chatqa-1.5-70b | 128k tokens | Advanced LLM to generate high-quality, context-aware responses for chatbots and search engines. |
-    | nvidia/vila | 128k tokens | Multi-modal vision-language model that understands text/img/video and creates informative responses |
-    | nvidia/neva-22| 4,096 tokens | Multi-modal vision-language model that understands text/images and generates informative responses |
-    | nvidia/nemotron-mini-4b-instruct | 8,192 tokens | General-purpose tasks |
-    | nvidia/usdcode-llama3-70b-instruct | 128k tokens | State-of-the-art LLM that answers OpenUSD knowledge queries and generates USD-Python code. |
-    | nvidia/nemotron-4-340b-instruct | 4,096 tokens | Creates diverse synthetic data that mimics the characteristics of real-world data. |
-    | meta/codellama-70b | 100k tokens | LLM capable of generating code from natural language and vice versa. |
-    | meta/llama2-70b | 4,096 tokens | Cutting-edge large language AI model capable of generating text and code in response to prompts. |
-    | meta/llama3-8b-instruct | 8,192 tokens | Advanced state-of-the-art LLM with language understanding, superior reasoning, and text generation. |
-    | meta/llama3-70b-instruct | 8,192 tokens | Powers complex conversations with superior contextual understanding, reasoning and text generation. |
-    | meta/llama-3.1-8b-instruct | 128k tokens | Advanced state-of-the-art model with language understanding, superior reasoning, and text generation. |
-    | meta/llama-3.1-70b-instruct | 128k tokens | Powers complex conversations with superior contextual understanding, reasoning and text generation. |
-    | meta/llama-3.1-405b-instruct | 128k tokens | Advanced LLM for synthetic data generation, distillation, and inference for chatbots, coding, and domain-specific tasks. |
-    | meta/llama-3.2-1b-instruct | 128k tokens | Advanced state-of-the-art small language model with language understanding, superior reasoning, and text generation. |
-    | meta/llama-3.2-3b-instruct | 128k tokens | Advanced state-of-the-art small language model with language understanding, superior reasoning, and text generation. |
-    | meta/llama-3.2-11b-vision-instruct | 128k tokens | Advanced state-of-the-art small language model with language understanding, superior reasoning, and text generation. |
-    | meta/llama-3.2-90b-vision-instruct | 128k tokens | Advanced state-of-the-art small language model with language understanding, superior reasoning, and text generation. |
-    | meta/llama-3.1-70b-instruct | 128k tokens | Powers complex conversations with superior contextual understanding, reasoning and text generation. |
-    | google/gemma-7b | 8,192 tokens | Cutting-edge text generation model text understanding, transformation, and code generation. |
-    | google/gemma-2b | 8,192 tokens | Cutting-edge text generation model text understanding, transformation, and code generation. |
-    | google/codegemma-7b | 8,192 tokens | Cutting-edge model built on Google's Gemma-7B specialized for code generation and code completion. |
-    | google/codegemma-1.1-7b | 8,192 tokens | Advanced programming model for code generation, completion, reasoning, and instruction following. |
-    | google/recurrentgemma-2b | 8,192 tokens | Novel recurrent architecture based language model for faster inference when generating long sequences. |
-    | google/gemma-2-9b-it | 8,192 tokens | Cutting-edge text generation model text understanding, transformation, and code generation. |
-    | google/gemma-2-27b-it | 8,192 tokens | Cutting-edge text generation model text understanding, transformation, and code generation. |
-    | google/gemma-2-2b-it | 8,192 tokens | Cutting-edge text generation model text understanding, transformation, and code generation. |
-    | google/deplot | 512 tokens | One-shot visual language understanding model that translates images of plots into tables. |
-    | google/paligemma | 8,192 tokens | Vision language model adept at comprehending text and visual inputs to produce informative responses. |
-    | mistralai/mistral-7b-instruct-v0.2 | 32k tokens | This LLM follows instructions, completes requests, and generates creative text. |
-    | mistralai/mixtral-8x7b-instruct-v0.1 | 8,192 tokens | An MOE LLM that follows instructions, completes requests, and generates creative text. |
-    | mistralai/mistral-large | 4,096 tokens | Creates diverse synthetic data that mimics the characteristics of real-world data. |
-    | mistralai/mixtral-8x22b-instruct-v0.1 | 8,192 tokens | Creates diverse synthetic data that mimics the characteristics of real-world data. |
-    | mistralai/mistral-7b-instruct-v0.3 | 32k tokens | This LLM follows instructions, completes requests, and generates creative text. |
-    | nv-mistralai/mistral-nemo-12b-instruct | 128k tokens | Most advanced language model for reasoning, code, multilingual tasks; runs on a single GPU. |
-    | mistralai/mamba-codestral-7b-v0.1 | 256k tokens | Model for writing and interacting with code across a wide range of programming languages and tasks. |
-    | microsoft/phi-3-mini-128k-instruct | 128K tokens | Lightweight, state-of-the-art open LLM with strong math and logical reasoning skills. |
-    | microsoft/phi-3-mini-4k-instruct | 4,096 tokens | Lightweight, state-of-the-art open LLM with strong math and logical reasoning skills. |
-    | microsoft/phi-3-small-8k-instruct | 8,192 tokens | Lightweight, state-of-the-art open LLM with strong math and logical reasoning skills. |
-    | microsoft/phi-3-small-128k-instruct | 128K tokens | Lightweight, state-of-the-art open LLM with strong math and logical reasoning skills. |
-    | microsoft/phi-3-medium-4k-instruct | 4,096 tokens | Lightweight, state-of-the-art open LLM with strong math and logical reasoning skills. |
-    | microsoft/phi-3-medium-128k-instruct | 128K tokens | Lightweight, state-of-the-art open LLM with strong math and logical reasoning skills. |
-    | microsoft/phi-3.5-mini-instruct | 128K tokens | Lightweight multilingual LLM powering AI applications in latency bound, memory/compute constrained environments |
-    | microsoft/phi-3.5-moe-instruct | 128K tokens | Advanced LLM based on Mixture of Experts architecure to deliver compute efficient content generation |
-    | microsoft/kosmos-2 | 1,024 tokens | Groundbreaking multimodal model designed to understand and reason about visual elements in images. |
-    | microsoft/phi-3-vision-128k-instruct | 128k tokens | Cutting-edge open multimodal model exceling in high-quality reasoning from images. |
-    | microsoft/phi-3.5-vision-instruct | 128k tokens | Cutting-edge open multimodal model exceling in high-quality reasoning from images. |
-    | databricks/dbrx-instruct | 12k tokens | A general-purpose LLM with state-of-the-art performance in language understanding, coding, and RAG. |
-    | snowflake/arctic | 1,024 tokens | Delivers high efficiency inference for enterprise applications focused on SQL generation and coding. |
-    | aisingapore/sea-lion-7b-instruct | 4,096 tokens | LLM to represent and serve the linguistic and cultural diversity of Southeast Asia |
-    | ibm/granite-8b-code-instruct | 4,096 tokens | Software programming LLM for code generation, completion, explanation, and multi-turn conversion. |
-    | ibm/granite-34b-code-instruct | 8,192 tokens | Software programming LLM for code generation, completion, explanation, and multi-turn conversion. |
-    | ibm/granite-3.0-8b-instruct | 4,096 tokens | Advanced Small Language Model supporting RAG, summarization, classification, code, and agentic AI |
-    | ibm/granite-3.0-3b-a800m-instruct | 4,096 tokens | Highly efficient Mixture of Experts model for RAG, summarization, entity extraction, and classification |
-    | mediatek/breeze-7b-instruct | 4,096 tokens | Creates diverse synthetic data that mimics the characteristics of real-world data. |
-    | upstage/solar-10.7b-instruct | 4,096 tokens | Excels in NLP tasks, particularly in instruction-following, reasoning, and mathematics. |
-    | writer/palmyra-med-70b-32k | 32k tokens | Leading LLM for accurate, contextually relevant responses in the medical domain. |
-    | writer/palmyra-med-70b | 32k tokens | Leading LLM for accurate, contextually relevant responses in the medical domain. |
-    | writer/palmyra-fin-70b-32k | 32k tokens | Specialized LLM for financial analysis, reporting, and data processing |
-    | 01-ai/yi-large | 32k tokens | Powerful model trained on English and Chinese for diverse tasks including chatbot and creative writing. |
-    | deepseek-ai/deepseek-coder-6.7b-instruct | 2k tokens | Powerful coding model offering advanced capabilities in code generation, completion, and infilling |
-    | rakuten/rakutenai-7b-instruct | 1,024 tokens | Advanced state-of-the-art LLM with language understanding, superior reasoning, and text generation. |
-    | rakuten/rakutenai-7b-chat | 1,024 tokens | Advanced state-of-the-art LLM with language understanding, superior reasoning, and text generation. |
-    | baichuan-inc/baichuan2-13b-chat | 4,096 tokens | Support Chinese and English chat, coding, math, instruction following, solving quizzes |
-
-    <Note>
-      NVIDIA's NIM support for models is expanding continuously! For the most up-to-date list of available models, please visit build.nvidia.com.
-    </Note>
-  </Tab>
  <Tab title="Gemini">
    | Model | Context Window | Best For |
    |-------|---------------|-----------|
@@ -503,20 +428,6 @@ Learn how to get the most out of your LLM configuration:
    ```
  </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="Groq">
    ```python Code
    GROQ_API_KEY=<your-api-key>
@@ -607,6 +518,20 @@ Learn how to get the most out of your LLM configuration:
    ```
  </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>
@@ -26,10 +26,9 @@ dependencies = [
    "uv>=0.4.25",
    "tomli-w>=1.1.0",
    "tomli>=2.0.2",
-    "chromadb>=0.5.23",
+    "chromadb>=0.5.18",
    "pdfplumber>=0.11.4",
    "openpyxl>=3.1.5",
-    "blinker>=1.9.0",
 ]

 [project.urls]
@@ -38,7 +37,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"

 [project.optional-dependencies]
-tools = ["crewai-tools>=0.17.0"]
+tools = ["crewai-tools>=0.14.0"]
 agentops = ["agentops>=0.3.0"]
 fastembed = ["fastembed>=0.4.1"]
 pdfplumber = [
@@ -54,7 +53,7 @@ mem0 = ["mem0ai>=0.1.29"]

 [tool.uv]
 dev-dependencies = [
-    "ruff>=0.8.2",
+    "ruff>=0.4.10",
    "mypy>=1.10.0",
    "pre-commit>=3.6.0",
    "mkdocs>=1.4.3",
@@ -64,7 +63,7 @@ dev-dependencies = [
    "mkdocs-material-extensions>=1.3.1",
    "pillow>=10.2.0",
    "cairosvg>=2.7.1",
-    "crewai-tools>=0.17.0",
+    "crewai-tools>=0.14.0",
    "pytest>=8.0.0",
    "pytest-vcr>=1.0.2",
    "python-dotenv>=1.0.0",
@@ -23,19 +23,27 @@ from crewai.utilities.converter import generate_model_description
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler

-agentops = None

-try:
-    import agentops  # type: ignore # Name "agentops" is already defined
-    from agentops import track_agent  # type: ignore
-except ImportError:
-
-    def track_agent():
+def mock_agent_ops_provider():
+    def track_agent(*args, **kwargs):
        def noop(f):
            return f

        return noop

+    return track_agent
+
+
+agentops = None
+
+if os.environ.get("AGENTOPS_API_KEY"):
+    try:
+        from agentops import track_agent
+    except ImportError:
+        track_agent = mock_agent_ops_provider()
+else:
+    track_agent = mock_agent_ops_provider()
+

@track_agent()
 class Agent(BaseAgent):
@@ -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
@@ -413,6 +413,7 @@ 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)
@@ -1,6 +1,5 @@
 import re
 from typing import Any, Union
-
 from json_repair import repair_json

 from crewai.utilities import I18N
@@ -5,10 +5,9 @@ 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()

@@ -80,9 +79,7 @@ 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"):
@@ -1,9 +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
+
+
@@ -1,7 +1,7 @@
-from importlib.metadata import version as get_version
 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
@@ -25,7 +25,7 @@ from .update_crew import update_crew


@click.group()
-@click.version_option(get_version("crewai"))
+@click.version_option(pkg_resources.get_distribution("crewai").version)
 def crewai():
    """Top-level command group for crewai."""

@@ -52,16 +52,16 @@ def create(type, name, provider, skip_provider=False):
 def version(tools):
    """Show the installed version of crewai."""
    try:
-        crewai_version = get_version("crewai")
+        crewai_version = pkg_resources.get_distribution("crewai").version
    except Exception:
        crewai_version = "unknown version"
    click.echo(f"crewai version: {crewai_version}")

    if tools:
        try:
-            tools_version = get_version("crewai")
+            tools_version = pkg_resources.get_distribution("crewai-tools").version
            click.echo(f"crewai tools version: {tools_version}")
-        except Exception:
+        except pkg_resources.DistributionNotFound:
            click.echo("crewai tools not installed")


@@ -1,9 +1,8 @@
 import requests
 from requests.exceptions import JSONDecodeError
 from rich.console import Console
-
-from crewai.cli.authentication.token import get_auth_token
 from crewai.cli.plus_api import PlusAPI
+from crewai.cli.authentication.token import get_auth_token
 from crewai.telemetry.telemetry import Telemetry

 console = Console()
@@ -1,19 +1,13 @@
 import json
 from pathlib import Path
-from typing import Optional
-
 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"
-    )
+    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):
@@ -1,10 +1,8 @@
-from os import getenv
 from typing import Optional
-from urllib.parse import urljoin
-
 import requests
-
+from os import getenv
 from crewai.cli.version import get_crewai_version
+from urllib.parse import urljoin


 class PlusAPI:
@@ -1,12 +1,11 @@
 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(
@@ -10,7 +10,7 @@ class MyCustomToolInput(BaseModel):
 class MyCustomTool(BaseTool):
    name: str = "Name of my tool"
    description: str = (
-        "Clear description for what this tool is useful for, your agent will need this information to use it."
+        "Clear description for what this tool is useful for, you agent will need this information to use it."
    )
    args_schema: Type[BaseModel] = MyCustomToolInput

@@ -13,7 +13,7 @@ class MyCustomToolInput(BaseModel):
 class MyCustomTool(BaseTool):
    name: str = "Name of my tool"
    description: str = (
-        "Clear description for what this tool is useful for, your agent will need this information to use it."
+        "Clear description for what this tool is useful for, you agent will need this information to use it."
    )
    args_schema: Type[BaseModel] = MyCustomToolInput

@@ -117,7 +117,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):

        published_handle = publish_response.json()["handle"]
        console.print(
-            f"Successfully published {published_handle} ({project_version}).\nInstall it in other projects with crewai tool install {published_handle}",
+            f"Succesfully 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"Successfully installed {handle}", style="bold green")
+        console.print(f"Succesfully installed {handle}", style="bold green")

    def login(self):
        login_response = self.plus_api_client.login_to_tool_repository()
@@ -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")
+
@@ -1,5 +1,6 @@
 import asyncio
 import json
+import os
 import uuid
 import warnings
 from concurrent.futures import Future
@@ -48,10 +49,12 @@ from crewai.utilities.planning_handler import CrewPlanner
 from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
 from crewai.utilities.training_handler import CrewTrainingHandler

-try:
-    import agentops  # type: ignore
-except ImportError:
-    agentops = None
+agentops = None
+if os.environ.get("AGENTOPS_API_KEY"):
+    try:
+        import agentops  # type: ignore
+    except ImportError:
+        pass


 warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
@@ -1029,7 +1032,6 @@ class Crew(BaseModel):
            agentops.end_session(
                end_state="Success",
                end_state_reason="Finished Execution",
-                is_auto_end=True,
            )
        self._telemetry.end_crew(self, final_string_output)

@@ -14,15 +14,8 @@ 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
@@ -166,7 +159,6 @@ 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
@@ -261,14 +253,6 @@ 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())
@@ -283,6 +267,8 @@ 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")

@@ -299,19 +285,11 @@ class Flow(Generic[T], metaclass=FlowMeta):
        # Run all start methods concurrently
        await asyncio.gather(*tasks)

-        # 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
+        # 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

    async def _execute_start_method(self, start_method_name: str) -> None:
        result = await self._execute_method(
@@ -374,16 +352,6 @@ 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())

@@ -399,15 +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)

-            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:
@@ -1,33 +0,0 @@
-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
@@ -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 it's inside the knowledge directory, use the relative path.",
+                    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}")
@@ -46,5 +46,4 @@ class BaseKnowledgeSource(BaseModel, ABC):
        Save the documents to the storage.
        This method should be called after the chunks and embeddings are generated.
        """
-        print("CHUNKS: ", self.chunks)
        self.storage.save(self.chunks)
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Any, Dict, List, Optional
+from typing import Dict, Any, List, Optional


 class BaseKnowledgeStorage(ABC):
@@ -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
@@ -124,60 +124,43 @@ class KnowledgeStorage(BaseKnowledgeStorage):
        documents: List[str],
        metadata: Optional[Union[Dict[str, Any], List[Dict[str, Any]]]] = None,
    ):
-        if not self.collection:
+        if self.collection:
+            try:
+                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
+                ]
+
+                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")

-        try:
-            # Create a dictionary to store unique documents
-            unique_docs = {}
-
-            # Generate IDs and create a mapping of id -> (document, metadata)
-            for idx, doc in enumerate(documents):
-                doc_id = hashlib.sha256(doc.encode("utf-8")).hexdigest()
-                doc_metadata = None
-                if metadata is not None:
-                    if isinstance(metadata, list):
-                        doc_metadata = metadata[idx]
-                    else:
-                        doc_metadata = metadata
-                unique_docs[doc_id] = (doc, doc_metadata)
-
-            # Prepare filtered lists for ChromaDB
-            filtered_docs = []
-            filtered_metadata = []
-            filtered_ids = []
-
-            # Build the filtered lists
-            for doc_id, (doc, meta) in unique_docs.items():
-                filtered_docs.append(doc)
-                filtered_metadata.append(meta)
-                filtered_ids.append(doc_id)
-
-            # If we have no metadata at all, set it to None
-            final_metadata: Optional[OneOrMany[chromadb.Metadata]] = (
-                None if all(m is None for m in filtered_metadata) else filtered_metadata
-            )
-
-            self.collection.upsert(
-                documents=filtered_docs,
-                metadatas=final_metadata,
-                ids=filtered_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
-
    def _create_default_embedding_function(self):
        from chromadb.utils.embedding_functions.openai_embedding_function import (
            OpenAIEmbeddingFunction,
@@ -1,4 +1,4 @@
-from typing import Any, Dict, Optional
+from typing import Optional, Dict, Any

 from crewai.memory import EntityMemory, LongTermMemory, ShortTermMemory, UserMemory

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, Optional, List

 from crewai.memory.storage.rag_storage import RAGStorage

@@ -1,5 +1,4 @@
 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
@@ -33,10 +32,7 @@ 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)
@@ -2,7 +2,6 @@ import os
 from typing import Any, Dict, List

 from mem0 import MemoryClient
-
 from crewai.memory.storage.interface import Storage


@@ -1,6 +1,5 @@
 from functools import wraps

-
 def memoize(func):
    cache = {}

@@ -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
@@ -6,7 +6,6 @@ import os
 import platform
 import warnings
 from contextlib import contextmanager
-from importlib.metadata import version
 from typing import TYPE_CHECKING, Any, Optional


@@ -17,10 +16,12 @@ def suppress_warnings():
        yield


+with suppress_warnings():
+    import pkg_resources
+
+
 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
@@ -103,7 +104,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(span, "python_version", platform.python_version())
            self._add_attribute(span, "crew_key", crew.key)
@@ -305,7 +306,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(span, "tool_name", tool_name)
            self._add_attribute(span, "attempts", attempts)
@@ -325,7 +326,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(span, "tool_name", tool_name)
            self._add_attribute(span, "attempts", attempts)
@@ -345,7 +346,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            if llm:
                self._add_attribute(span, "llm", llm.model)
@@ -364,7 +365,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(span, "crew_key", crew.key)
            self._add_attribute(span, "crew_id", str(crew.id))
@@ -390,7 +391,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(span, "crew_key", crew.key)
            self._add_attribute(span, "crew_id", str(crew.id))
@@ -471,7 +472,7 @@ class Telemetry:
            self._add_attribute(
                span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(span, "crew_key", crew.key)
            self._add_attribute(span, "crew_id", str(crew.id))
@@ -540,7 +541,7 @@ class Telemetry:
            self._add_attribute(
                crew._execution_span,
                "crewai_version",
-                version("crewai"),
+                pkg_resources.get_distribution("crewai").version,
            )
            self._add_attribute(
                crew._execution_span, "crew_output", final_string_output
@@ -1,9 +1,9 @@
-from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.tools.base_tool import BaseTool
+from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.utilities import I18N

-from .ask_question_tool import AskQuestionTool
 from .delegate_work_tool import DelegateWorkTool
+from .ask_question_tool import AskQuestionTool


 class AgentTools:
@@ -1,8 +1,6 @@
-from typing import Optional
-
-from pydantic import BaseModel, Field
-
 from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
+from typing import Optional
+from pydantic import BaseModel, Field


 class AskQuestionToolSchema(BaseModel):
@@ -1,10 +1,9 @@
 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


@@ -45,14 +44,14 @@ class BaseAgentTool(BaseTool):
                if available_agent.role.casefold().replace("\n", "") == agent_name
            ]
        except Exception as _:
-            return self.i18n.errors("agent_tool_unexisting_coworker").format(
+            return self.i18n.errors("agent_tool_unexsiting_coworker").format(
                coworkers="\n".join(
                    [f"- {agent.role.casefold()}" for agent in self.agents]
                )
            )

        if not agent:
-            return self.i18n.errors("agent_tool_unexisting_coworker").format(
+            return self.i18n.errors("agent_tool_unexsiting_coworker").format(
                coworkers="\n".join(
                    [f"- {agent.role.casefold()}" for agent in self.agents]
                )
@@ -1,9 +1,8 @@
+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")
@@ -1,5 +1,6 @@
 import ast
 import datetime
+import os
 import time
 from difflib import SequenceMatcher
 from textwrap import dedent
@@ -14,10 +15,12 @@ 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

-try:
-    import agentops  # type: ignore
-except ImportError:
-    agentops = None
+agentops = None
+if os.environ.get("AGENTOPS_API_KEY"):
+    try:
+        import agentops  # type: ignore
+    except ImportError:
+        pass

 OPENAI_BIGGER_MODELS = ["gpt-4", "gpt-4o", "o1-preview", "o1-mini"]

@@ -1,7 +1,6 @@
-from datetime import datetime
 from typing import Any, Dict
-
 from pydantic import BaseModel
+from datetime import datetime


 class ToolUsageEvent(BaseModel):
@@ -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_unexisting_coworker": "\nError executing tool. coworker mentioned not found, it must be one of the following options:\n{coworkers}\n",
+    "agent_tool_unexsiting_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.",
@@ -1,9 +1,8 @@
+from datetime import datetime, date
 import json
-from datetime import date, datetime
-from decimal import Decimal
 from uuid import UUID
-
 from pydantic import BaseModel
+from decimal import Decimal


 class CrewJSONEncoder(json.JSONEncoder):
@@ -1,10 +1,9 @@
 import json
+import regex
 from typing import Any, Type

-import regex
-from pydantic import BaseModel, ValidationError
-
 from crewai.agents.parser import OutputParserException
+from pydantic import BaseModel, ValidationError


 class CrewPydanticOutputParser:
@@ -1,7 +1,6 @@
 import os
 from typing import Any, Dict, cast
-
-from chromadb import Documents, EmbeddingFunction, Embeddings
+from chromadb import EmbeddingFunction, Documents, Embeddings
 from chromadb.api.types import validate_embedding_function


@@ -1,14 +1,13 @@
 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):
@@ -1,3 +1,4 @@
+import os
 from typing import List

 from pydantic import BaseModel, Field
@@ -5,17 +6,27 @@ from pydantic import BaseModel, Field
 from crewai.utilities import Converter
 from crewai.utilities.pydantic_schema_parser import PydanticSchemaParser

-agentops = None
-try:
-    from agentops import track_agent  # type: ignore
-except ImportError:

-    def track_agent(name):
+def mock_agent_ops_provider():
+    def track_agent(*args, **kwargs):
        def noop(f):
            return f

        return noop

+    return track_agent
+
+
+agentops = None
+
+if os.environ.get("AGENTOPS_API_KEY"):
+    try:
+        from agentops import track_agent
+    except ImportError:
+        track_agent = mock_agent_ops_provider()
+else:
+    track_agent = mock_agent_ops_provider()
+

 class Entity(BaseModel):
    name: str = Field(description="The name of the entity.")
@@ -1,8 +1,8 @@
+from typing import Any, Callable, Generic, List, Dict, Type, TypeVar
 from functools import wraps
-from typing import Any, Callable, Dict, Generic, List, Type, TypeVar
-
 from pydantic import BaseModel

+
 T = TypeVar("T")
 EVT = TypeVar("EVT", bound=BaseModel)

@@ -1,5 +1,4 @@
 from typing import Any, List, Optional
-
 from pydantic import BaseModel, Field

 from crewai.agent import Agent
@@ -1,7 +1,5 @@
-from typing import Any, Optional
-
 from pydantic import BaseModel, Field
-
+from typing import Any, Optional
 from crewai.utilities import I18N


@@ -1,4 +1,4 @@
-from typing import Type, Union, get_args, get_origin
+from typing import Type, get_args, get_origin, Union

 from pydantic import BaseModel

@@ -1,8 +1,6 @@
-from datetime import datetime
-from typing import Any, Dict, List, Optional
-
 from pydantic import BaseModel, Field
-
+from datetime import datetime
+from typing import Dict, Any, Optional, List
 from crewai.memory.storage.kickoff_task_outputs_storage import (
    KickoffTaskOutputsSQLiteStorage,
 )
@@ -1,6 +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


@@ -12,7 +11,7 @@ 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)
@@ -1595,15 +1595,19 @@ def test_agent_execute_task_with_ollama():
@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 red and he likes Mexican food."
-    string_source = StringKnowledgeSource(content=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}]
+        mock_knowledge_instance.query.return_value = [
+            {"content": content, "metadata": {"preference": "personal"}}
+        ]

        agent = Agent(
            role="Information Agent",
@@ -1624,4 +1628,4 @@ def test_agent_with_knowledge_sources():
        result = crew.kickoff()

        # Assert that the agent provides the correct information
-        assert "red" in result.raw.lower()
+        assert "blue" in result.raw.lower()
@@ -1,10 +1,9 @@
 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):
@@ -1,11 +1,10 @@
 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
@@ -1,6 +1,6 @@
 interactions:
 - request:
-    body: '{"input": ["Brandon''s favorite color is red and he likes Mexican food."],
+    body: '{"input": ["Brandon''s favorite color is blue and he likes Mexican food."],
      "model": "text-embedding-3-small", "encoding_format": "base64"}'
    headers:
      accept:
@@ -10,7 +10,7 @@ interactions:
      connection:
      - keep-alive
      content-length:
-      - '137'
+      - '138'
      content-type:
      - application/json
      host:
@@ -32,19 +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:
    content: "{\n  \"object\": \"list\",\n  \"data\": [\n    {\n      \"object\":
-      \"embedding\",\n      \"index\": 0,\n      \"embedding\": 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 from unittest.mock import MagicMock, patch

 import requests
-
 from crewai.cli.authentication.main import AuthenticationCommand


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    @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 = {
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        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")
@@ -3,9 +3,8 @@ import unittest
 from datetime import datetime, timedelta
 from unittest.mock import MagicMock, patch

-from cryptography.fernet import Fernet
-
 from crewai.cli.authentication.utils import TokenManager, validate_token
+from cryptography.fernet import Fernet


 class TestValidateToken(unittest.TestCase):
@@ -1,12 +1,10 @@
-import json
-import shutil
-import tempfile
 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())
@@ -22,7 +20,8 @@ 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)
@@ -38,23 +37,22 @@ 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()

@@ -69,7 +67,8 @@ 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()

@@ -80,7 +79,10 @@ 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:
@@ -1,6 +1,5 @@
-import pytest
-
 from crewai.cli.git import Repository
+import pytest


@pytest.fixture()
@@ -1,7 +1,6 @@
 import os
 import unittest
 from unittest.mock import MagicMock, patch
-
 from crewai.cli.plus_api import PlusAPI


@@ -1,9 +1,7 @@
-import os
+import pytest
 import shutil
 import tempfile
-
-import pytest
-
+import os
 from crewai.cli import utils


@@ -85,7 +85,7 @@ def test_install_success(mock_get, mock_subprocess_run):
        env=unittest.mock.ANY
    )

-    assert "Successfully installed sample-tool" in output
+    assert "Succesfully installed sample-tool" in output


@patch("crewai.cli.plus_api.PlusAPI.get_tool")
@@ -3,7 +3,6 @@
 import asyncio

 import pytest
-
 from crewai.flow.flow import Flow, and_, listen, or_, router, start


@@ -3,8 +3,6 @@
 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
@@ -12,6 +10,8 @@ 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():
@@ -1,7 +1,5 @@
-from unittest.mock import patch
-
 import pytest
-
+from unittest.mock import patch
 from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
@@ -6,13 +6,12 @@ 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():
@@ -686,7 +685,7 @@ def test_increment_tool_errors():
    with patch.object(Task, "increment_tools_errors") as increment_tools_errors:
        increment_tools_errors.return_value = None
        crew.kickoff()
-        assert len(increment_tools_errors.mock_calls) > 0
+        assert len(increment_tools_errors.mock_calls) == 12


 def test_task_definition_based_on_dict():
@@ -6,14 +6,14 @@ 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, your agent will need this information to use it."""
+        """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, your agent will need this information to use it."
+        == "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"}
@@ -27,7 +27,7 @@ def test_creating_a_tool_using_annotation():

    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, your agent will need this information to use it."
+        == "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"}
@@ -41,7 +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, your 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
@@ -52,7 +52,7 @@ def test_creating_a_tool_using_baseclass():

    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, your agent will need this information to use it."
+        == "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"}
@@ -64,7 +64,7 @@ def test_creating_a_tool_using_baseclass():

    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, your agent will need this information to use it."
+        == "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"}
@@ -78,7 +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, your 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:
@@ -92,7 +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, your 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
@@ -6,8 +6,8 @@ import pytest
 from pydantic import BaseModel, Field

 from crewai import Agent, Task
-from crewai.tools import BaseTool
 from crewai.tools.tool_usage import ToolUsage
+from crewai.tools import BaseTool


 class RandomNumberToolInput(BaseModel):
@@ -1,7 +1,6 @@
 from unittest import mock

 import pytest
-
 from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.task import Task
@@ -26,7 +26,7 @@
  },
  "errors": {
    "force_final_answer": "Lorem ipsum dolor sit amet",
-    "agent_tool_unexisting_coworker": "Lorem ipsum dolor sit amet",
+    "agent_tool_unexsiting_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",
@@ -272,15 +272,6 @@ wheels = [
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 ]

-[[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"
@@ -479,7 +470,7 @@ wheels = [

 [[package]]
 name = "chromadb"
-version = "0.5.23"
+version = "0.5.18"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "bcrypt" },
@@ -511,9 +502,9 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uvicorn", extra = ["standard"] },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/42/64/28daa773f784bcd18de944fe26ed301de844d6ee17188e26a9d6b4baf122/chromadb-0.5.23.tar.gz", hash = "sha256:360a12b9795c5a33cb1f839d14410ccbde662ef1accd36153b0ae22312edabd1", size = 33700455 }
+sdist = { url = "https://files.pythonhosted.org/packages/15/95/d1a3f14c864e37d009606b82bd837090902b5e5a8e892fcab07eeaec0438/chromadb-0.5.18.tar.gz", hash = "sha256:cfbb3e5aeeb1dd532b47d80ed9185e8a9886c09af41c8e6123edf94395d76aec", size = 33620708 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/92/8c/a9eb95a28e6c35a0122417976a9d435eeaceb53f596a8973e33b3dd4cfac/chromadb-0.5.23-py3-none-any.whl", hash = "sha256:ffe5bdd7276d12cb682df0d38a13aa37573e6a3678e71889ac45f539ae05ad7e", size = 628347 },
+    { url = "https://files.pythonhosted.org/packages/82/85/4d2f8b9202153105ad4514ae09e9fe6f3b353a45e44e0ef7eca03dd8b9dc/chromadb-0.5.18-py3-none-any.whl", hash = "sha256:9dd3827b5e04b4ff0a5ea0df28a78bac88a09f45be37fcd7fe20f879b57c43cf", size = 615499 },
 ]

 [[package]]
@@ -577,7 +568,6 @@ source = { editable = "." }
 dependencies = [
    { name = "appdirs" },
    { name = "auth0-python" },
-    { name = "blinker" },
    { name = "chromadb" },
    { name = "click" },
    { name = "instructor" },
@@ -647,10 +637,9 @@ 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 = ">=0.5.23" },
+    { name = "chromadb", specifier = ">=0.5.18" },
    { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", marker = "extra == '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" },
    { name = "json-repair", specifier = ">=0.25.2" },
@@ -678,7 +667,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
    { name = "cairosvg", specifier = ">=2.7.1" },
-    { name = "crewai-tools", specifier = ">=0.17.0" },
+    { 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" },
@@ -692,7 +681,7 @@ 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 = ">=0.8.2" },
+    { name = "ruff", specifier = ">=0.4.10" },
 ]

 [[package]]
@@ -3876,27 +3865,27 @@ wheels = [

 [[package]]
 name = "ruff"
-version = "0.8.2"
+version = "0.7.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/5e/2b/01245f4f3a727d60bebeacd7ee6d22586c7f62380a2597ddb22c2f45d018/ruff-0.8.2.tar.gz", hash = "sha256:b84f4f414dda8ac7f75075c1fa0b905ac0ff25361f42e6d5da681a465e0f78e5", size = 3349020 }
+sdist = { url = "https://files.pythonhosted.org/packages/2c/c7/f3367d1da5d568192968c5c9e7f3d51fb317b9ac04828493b23d8fce8ce6/ruff-0.7.0.tar.gz", hash = "sha256:47a86360cf62d9cd53ebfb0b5eb0e882193fc191c6d717e8bef4462bc3b9ea2b", size = 3146645 }
 wheels = [
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 [[package]]
Author	SHA1	Message	Date
Brandon Hancock	c89f475c4c	Fix type issue	2024-12-09 15:27:36 -05:00
Brandon Hancock	0c5789f1e8	copy googles changes. Fix tests. Improve LLM file	2024-12-09 15:18:44 -05:00