1e0def78df
# CrewAI Integration
crewai-arcade enables you to add Arcade tools and Arcade Auth into your
CrewAI applications. Just create an `ArcadeToolManager` and add your
tools to your CrewAI Agent/Tasks.
## Initializing the ArcadeToolManager
There are two main ways to initialize your `ArcadeToolManager`
1. Default handling of tool authorization and execution:
```py
"""
When you provide a user id to the ArcadeToolManger,
it will handle the tool authorization and tool execution for you
"""
manager = ArcadeToolManager(default_user_id="me@example.com,
api_key="...")
```
2. Custom handling of tool authorization and execution
```py
"""
Provide a callback function to the `ArcadeToolManager` that handles
tool authorization and tool execution. The callback function will be
called whenever your CrewAI
application wants to call a tool.
"""
def custom_tool_executor(
manager: ArcadeToolManager, tool_name: str, **tool_input: dict[str, Any]
) -> Any:
"""Custom tool executor for the ArcadeToolManager
ArcadeToolManager's default executor handles authorization and tool
execution.
This function overrides the default executor to handle authorization and
tool execution
in a custom way.
"""
# Your custom tool auth logic goes here
# Your custom tool execution logic goes here
...
manager = ArcadeToolManager(executor=custom_tool_executor,
api_key="...")
```
## Tool Registration
1. Initialize the tools in the manager
```py
"""
Clears any existing tools in the manager and replaces them with tools
and toolkits that are provided.
"""
manager.init_tools(tools=["Google.ListEmails"], toolkits=["Slack"])
```
2. Add tools to the manager
```py
"""
Adds tools and toolkits to the manager's internal tool list.
"""
manager.add_tools(tools=["Google.ListEmails"], toolkits=["Slack"])
```
3. Retrieve tools and toolkits from the manager
```py
"""
Retrieves the provided tools and toolkits as CrewAI StructuredTools.
"""
manager.get_tools(tools=["Google.ListEmails"], toolkits=["Slack"])
```
## Auth Helpers
The `ArcadeToolManager` provides multiple helper methods for when you
need to create
a custom auth flow.
1. `authorize_tool` handles the whole authorization flow for you. This
is used internally when a custom auth flow is not needed.
2. `requires_auth(tool_name)` checks if the provided tool has
authorization requirements.
3. `authorize(tool_name, user_id)` authorizes the use of the provided
tool for the provided user ID
4. `is_authorized(tool_name, user_id)` checks if a tool is authorized
for use by the provided user ID
5. `wait_for_auth(auth_response)` waits for an authorization process to
complete before returning
## Tool Execution Helpers
1. `execute_tool` handles the whole tool execution flow for you. This is
used internally when a custom tool execution flow is not needed.
---------
Co-authored-by: lgesuellip <lgesuellipinto@uade.edu.ar>
Co-authored-by: lpetralli <123559656+lpetralli@users.noreply.github.com>
Co-authored-by: lgesuellip <102637283+lgesuellip@users.noreply.github.com>
Co-authored-by: “lgesuellip” <“lgesuellipinto@uade.edu.ar”>
54 lines
1.8 KiB
Python
54 lines
1.8 KiB
Python
from textwrap import dedent
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from typing import Any, Callable, Optional
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from crewai.tools.base_tool import BaseTool
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from pydantic import BaseModel as PydanticBaseModel
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class StructuredTool(BaseTool): # type: ignore[no-any-unimported]
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"""A tool that executes functions with structured inputs using a schema."""
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func: Callable[..., Any]
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"""The callable function that implements the tool's functionality."""
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def _run(self, *args: Any, **kwargs: Any) -> Any:
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"""Execute the tool's function with the provided arguments."""
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return self.func(*args, **kwargs)
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@classmethod
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def from_function(
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cls,
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func: Callable,
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args_schema: type[PydanticBaseModel],
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name: Optional[str] = None,
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description: Optional[str] = None,
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**kwargs: Any,
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) -> "StructuredTool":
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"""Create a new StructuredTool instance from a function.
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Args:
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func: Function to wrap as a CrewAI tool
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name: Custom name for the tool
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description: Custom description of the tool's functionality
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args_schema: Pydantic model defining the expected argument structure
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**kwargs: Additional tool configuration parameters, like cache_function
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Returns:
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StructuredTool: A new tool instance wrapping the provided function
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"""
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name = name or func.__name__
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if description is None:
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description = func.__doc__
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if description is None:
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raise ValueError("Function must have a docstring if description not provided.")
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# Clean up docstring
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description = dedent(description).strip()
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return cls(
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func=func,
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args_schema=args_schema,
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name=name,
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description=description,
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**kwargs,
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)
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