Create Custom Tools
Creating and Utilizing Tools in crewAI¶
This guide provides detailed instructions on creating custom tools for the crewAI framework and how to efficiently manage and utilize these tools, incorporating the latest functionalities such as tool delegation, error handling, and dynamic tool calling. It also highlights the importance of collaboration tools, enabling agents to perform a wide range of actions.
Prerequisites¶
Before creating your own tools, ensure you have the crewAI extra tools package installed:
Subclassing BaseTool
¶
To create a personalized tool, inherit from BaseTool
and define the necessary attributes and the _run
method.
from crewai_tools import BaseTool
class MyCustomTool(BaseTool):
name: str = "Name of my tool"
description: str = "What this tool does. It's vital for effective utilization."
def _run(self, argument: str) -> str:
# Your tool's logic here
return "Tool's result"
Using the tool
Decorator¶
Alternatively, use the tool
decorator for a direct approach to create tools. This requires specifying attributes and the tool's logic within a function.
from crewai_tools import tool
@tool("Tool Name")
def my_simple_tool(question: str) -> str:
"""Tool description for clarity."""
# Tool logic here
return "Tool output"
Defining a Cache Function for the Tool¶
To optimize tool performance with caching, define custom caching strategies using the cache_function
attribute.
@tool("Tool with Caching")
def cached_tool(argument: str) -> str:
"""Tool functionality description."""
return "Cachable result"
def my_cache_strategy(arguments: dict, result: str) -> bool:
# Define custom caching logic
return True if some_condition else False
cached_tool.cache_function = my_cache_strategy
By adhering to these guidelines and incorporating new functionalities and collaboration tools into your tool creation and management processes, you can leverage the full capabilities of the crewAI framework, enhancing both the development experience and the efficiency of your AI agents.