mirror of
https://github.com/crewAIInc/crewAI.git
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111 lines
3.2 KiB
Python
111 lines
3.2 KiB
Python
from abc import ABC, abstractmethod
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from typing import Any, Callable, cast, Optional, Type
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from pydantic import BaseModel, model_validator
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from pydantic.v1 import BaseModel as V1BaseModel
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from langchain_core.tools import StructuredTool
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class BaseTool(BaseModel, ABC):
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name: str
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"""The unique name of the tool that clearly communicates its purpose."""
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description: str
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"""Used to tell the model how/when/why to use the tool."""
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args_schema: Optional[Type[V1BaseModel]] = None
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"""The schema for the arguments that the tool accepts."""
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@model_validator(mode="after")
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def _check_args_schema(self):
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self._set_args_schema()
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return self
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def run(
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self,
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*args: Any,
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**kwargs: Any,
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) -> Any:
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print(f"Using Tool: {self.name}")
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return self._run(*args, **kwargs)
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@abstractmethod
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def _run(
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self,
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*args: Any,
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**kwargs: Any,
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) -> Any:
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"""Here goes the actual implementation of the tool."""
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def to_langchain(self) -> StructuredTool:
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self._set_args_schema()
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return StructuredTool(
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name=self.name,
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description=self.description,
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args_schema=self.args_schema,
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func=self._run,
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)
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def _set_args_schema(self):
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if self.args_schema is None:
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class_name = f"{self.__class__.__name__}Schema"
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self.args_schema = type(
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class_name,
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(V1BaseModel,),
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{
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"__annotations__": {
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k: v for k, v in self._run.__annotations__.items() if k != 'return'
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},
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},
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)
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class Tool(BaseTool):
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func: Callable
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"""The function that will be executed when the tool is called."""
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def _run(self, *args: Any, **kwargs: Any) -> Any:
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return self.func(*args, **kwargs)
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def to_langchain(
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tools: list[BaseTool | StructuredTool],
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) -> list[StructuredTool]:
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return [t.to_langchain() if isinstance(t, BaseTool) else t for t in tools]
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def tool(*args):
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"""
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Decorator to create a tool from a function.
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"""
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def _make_with_name(tool_name: str) -> Callable:
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def _make_tool(f: Callable) -> BaseTool:
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if f.__doc__ is None:
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raise ValueError("Function must have a docstring")
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args_schema = None
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if f.__annotations__:
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class_name = "".join(tool_name.split()).title()
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args_schema = type(
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class_name,
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(V1BaseModel,),
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{
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"__annotations__": {
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k: v for k, v in f.__annotations__.items() if k != 'return'
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},
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},
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)
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return Tool(
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name=tool_name,
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description=f.__doc__,
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func=f,
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args_schema=args_schema,
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)
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return _make_tool
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if len(args) == 1 and callable(args[0]):
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return _make_with_name(args[0].__name__)(args[0])
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if len(args) == 1 and isinstance(args[0], str):
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return _make_with_name(args[0])
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raise ValueError("Invalid arguments") |