Merge branch 'main' into feat/add-event-emitters-to-flows

.github/workflows/linter.yml

@@ -13,4 +13,4 @@ jobs:
           pip install ruff
 
       - name: Run Ruff Linter
-        run: ruff check
+        run: ruff check --exclude "templates","__init__.py"

.github/workflows/stale.yml

@@ -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:

.pre-commit-config.yaml

@@ -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"

.ruff.toml

@@ -1,9 +0,0 @@
-exclude = [
-    "templates",
-    "__init__.py",
-]
-
-[lint]
-select = [
-    "I", # isort rules
-]

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:
 

docs/concepts/llms.mdx

@@ -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>

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
   ```

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" }
 ]
@@ -26,7 +26,7 @@ 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",
@@ -38,7 +38,7 @@ 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 +54,7 @@ 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 +64,7 @@ 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",

src/crewai/agent.py

@@ -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):

src/crewai/agents/parser.py

@@ -1,6 +1,5 @@
 import re
 from typing import Any, Union
-
 from json_repair import repair_json
 
 from crewai.utilities import I18N

src/crewai/cli/authentication/main.py

@@ -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"):

src/crewai/cli/authentication/token.py

@@ -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
+
+

src/crewai/cli/cli.py

@@ -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")
 
 

src/crewai/cli/command.py

@@ -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()

src/crewai/cli/config.py

@@ -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):

src/crewai/cli/plus_api.py

@@ -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:

src/crewai/cli/reset_memories_command.py

@@ -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(

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:
 

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"
 ]

src/crewai/cli/templates/crew/tools/custom_tool.py

@@ -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
 

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:
 

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",
 ]

src/crewai/cli/templates/flow/tools/custom_tool.py

@@ -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
 

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.
 

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"
 ]

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")
+

src/crewai/crew.py

@@ -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)
 

src/crewai/knowledge/storage/base_knowledge_storage.py

@@ -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):

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
@@ -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,

src/crewai/memory/contextual/contextual_memory.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, Optional
+from typing import Optional, Dict, Any
 
 from crewai.memory import EntityMemory, LongTermMemory, ShortTermMemory, UserMemory
 

src/crewai/memory/memory.py

@@ -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
 

src/crewai/memory/short_term/short_term_memory.py

@@ -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)

src/crewai/memory/storage/mem0_storage.py

@@ -2,7 +2,6 @@ import os
 from typing import Any, Dict, List
 
 from mem0 import MemoryClient
-
 from crewai.memory.storage.interface import Storage
 
 

src/crewai/project/utils.py

@@ -1,6 +1,5 @@
 from functools import wraps
 
-
 def memoize(func):
     cache = {}
 

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

src/crewai/telemetry/telemetry.py

@@ -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

src/crewai/tools/agent_tools/agent_tools.py

@@ -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:

src/crewai/tools/agent_tools/ask_question_tool.py

@@ -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):

src/crewai/tools/agent_tools/base_agent_tools.py

@@ -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
 
 

src/crewai/tools/agent_tools/delegate_work_tool.py

@@ -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")

src/crewai/tools/tool_usage.py

@@ -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"]
 
@@ -419,10 +422,9 @@ class ToolUsage:
                 elif value.lower() in [
                     "true",
                     "false",
+                    "null",
                 ]:  # Check for boolean and null values
-                    value = value.lower().capitalize()
-                elif value.lower() == "null":
-                    value = "None"
+                    value = value.lower()
                 else:
                     # Assume the value is a string and needs quotes
                     value = '"' + value.replace('"', '\\"') + '"'

src/crewai/tools/tool_usage_events.py

@@ -1,7 +1,6 @@
-from datetime import datetime
 from typing import Any, Dict
-
 from pydantic import BaseModel
+from datetime import datetime
 
 
 class ToolUsageEvent(BaseModel):

src/crewai/utilities/crew_json_encoder.py

@@ -1,17 +1,15 @@
+from datetime import datetime, date
 import json
-from datetime import date, datetime
-from decimal import Decimal
-from enum import Enum
 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) or isinstance(obj, Decimal) or isinstance(obj, Enum):
+        elif isinstance(obj, UUID) or isinstance(obj, Decimal):
             return str(obj)
 
         elif isinstance(obj, datetime) or isinstance(obj, date):

src/crewai/utilities/crew_pydantic_output_parser.py

@@ -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:

src/crewai/utilities/embedding_configurator.py

@@ -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
 
 

src/crewai/utilities/evaluators/crew_evaluator_handler.py

@@ -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):

src/crewai/utilities/evaluators/task_evaluator.py

@@ -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.")

src/crewai/utilities/events.py

@@ -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)
 

src/crewai/utilities/planning_handler.py

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

src/crewai/utilities/prompts.py

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

src/crewai/utilities/pydantic_schema_parser.py

@@ -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
 

src/crewai/utilities/task_output_storage_handler.py

@@ -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,
 )

src/crewai/utilities/token_counter_callback.py

@@ -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)

tests/agent_test.py

@@ -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()

tests/agents/agent_builder/base_agent_test.py

@@ -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):

tests/agents/test_crew_agent_parser.py

@@ -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

tests/cli/authentication/test_auth_main.py

@@ -2,7 +2,6 @@ import unittest
 from unittest.mock import MagicMock, patch
 
 import requests
-
 from crewai.cli.authentication.main import AuthenticationCommand
 
 
@@ -48,9 +47,7 @@ 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 = {
@@ -65,9 +62,7 @@ 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")

tests/cli/authentication/test_utils.py

@@ -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):

tests/cli/config_test.py

@@ -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:

tests/cli/deploy/test_deploy_main.py

@@ -231,7 +231,7 @@ 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"]
         """,
     )
@@ -250,7 +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"]
     """,
     )

tests/cli/test_git.py

@@ -1,6 +1,5 @@
-import pytest
-
 from crewai.cli.git import Repository
+import pytest
 
 
 @pytest.fixture()

tests/cli/test_plus_api.py

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

tests/cli/test_utils.py

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

tests/flow_test.py

@@ -3,7 +3,6 @@
 import asyncio
 
 import pytest
-
 from crewai.flow.flow import Flow, and_, listen, or_, router, start
 
 

tests/knowledge/knowledge_test.py

@@ -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():

tests/memory/short_term_memory_test.py

@@ -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

tests/task_test.py

@@ -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():

tests/tools/test_base_tool.py

@@ -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

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 import BaseTool
 from crewai.tools.tool_usage import ToolUsage
+from crewai.tools import BaseTool
 
 
 class RandomNumberToolInput(BaseModel):

tests/utilities/evaluators/test_crew_evaluator_handler.py

@@ -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

uv.lock

@@ -1,10 +1,9 @@
 version = 1
-requires-python = ">=3.10, <3.13"
+requires-python = ">=3.10, <=3.12"
 resolution-markers = [
     "python_full_version < '3.11'",
     "python_full_version == '3.11.*'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4'",
-    "python_full_version >= '3.12.4'",
+    "python_full_version >= '3.12'",
 ]
 
 [[package]]
@@ -480,7 +479,7 @@ wheels = [
 
 [[package]]
 name = "chromadb"
-version = "0.5.23"
+version = "0.5.18"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "bcrypt" },
@@ -512,9 +511,9 @@ 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]]
@@ -649,9 +648,9 @@ requires-dist = [
     { 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" },
@@ -679,7 +678,7 @@ 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" },
@@ -693,7 +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 = ">=0.8.2" },
+    { name = "ruff", specifier = ">=0.4.10" },
 ]
 
 [[package]]
@@ -3877,27 +3876,27 @@ 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 }
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