Awesome
<div align="center"> <div align="left">crewAI Tools
This document provides a comprehensive guide for setting up sophisticated tools for crewAI agents, facilitating the creation of bespoke tooling to empower your AI solutions.
In the realm of CrewAI agents, tools are pivotal for enhancing functionality. This guide outlines the steps to equip your agents with an arsenal of ready-to-use tools and the methodology to craft your own.
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</h3> </div>Table of contents
Creating Your Tools
Tools are always expect to return strings, as they are meant to be used by the agents to generate responses.
There are three ways to create tools for crewAI agents:
Subclassing BaseTool
from crewai_tools import BaseTool
class MyCustomTool(BaseTool):
name: str = "Name of my tool"
description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
def _run(self, argument: str) -> str:
# Implementation goes here
pass
Define a new class inheriting from BaseTool
, specifying name
, description
, and the _run
method for operational logic.
Utilizing the tool
Decorator
For a simpler approach, create a Tool
object directly with the required attributes and a functional logic.
from crewai_tools import tool
@tool("Name of my tool")
def my_tool(question: str) -> str:
"""Clear description for what this tool is useful for, you agent will need this information to use it."""
# Function logic here
The tool
decorator simplifies the process, transforming functions into tools with minimal overhead.
Contribution Guidelines
We eagerly welcome contributions to enrich this toolset. To contribute:
- Fork the Repository: Begin with forking the repository to your GitHub account.
- Feature Branch: Create a new branch in your fork for the feature or improvement.
- Implement Your Feature: Add your contribution to the new branch.
- Pull Request: Submit a pull request from your feature branch to the main repository.
Your contributions are greatly appreciated and will help enhance this project.
Development Setup
Installing Dependencies:
poetry install
Activating Virtual Environment:
poetry shell
Setting Up Pre-commit Hooks:
pre-commit install
Running Tests:
poetry run pytest
Static Type Checking:
poetry run pyright
Packaging:
poetry build
Local Installation:
pip install dist/*.tar.gz
Thank you for your interest in enhancing the capabilities of AI agents through advanced tooling. Your contributions make a significant impact.