from_function() — langchain Function Reference

Source Code

libs/core/langchain_core/tools/structured.py lines 133–252

    def from_function(
        cls,
        func: Callable | None = None,
        coroutine: Callable[..., Awaitable[Any]] | None = None,
        name: str | None = None,
        description: str | None = None,
        return_direct: bool = False,  # noqa: FBT001,FBT002
        args_schema: ArgsSchema | None = None,
        infer_schema: bool = True,  # noqa: FBT001,FBT002
        *,
        response_format: Literal["content", "content_and_artifact"] = "content",
        parse_docstring: bool = False,
        error_on_invalid_docstring: bool = False,
        **kwargs: Any,
    ) -> StructuredTool:
        """Create tool from a given function.

        A classmethod that helps to create a tool from a function.

        Args:
            func: The function from which to create a tool.
            coroutine: The async function from which to create a tool.
            name: The name of the tool.

                Defaults to the function name.
            description: The description of the tool.

                Defaults to the function docstring.
            return_direct: Whether to return the result directly or as a callback.
            args_schema: The schema of the tool's input arguments.
            infer_schema: Whether to infer the schema from the function's signature.
            response_format: The tool response format.

                If `'content'` then the output of the tool is interpreted as the
                contents of a `ToolMessage`. If `'content_and_artifact'` then the output
                is expected to be a two-tuple corresponding to the `(content, artifact)`
                of a `ToolMessage`.
            parse_docstring: If `infer_schema` and `parse_docstring`, will attempt
                to parse parameter descriptions from Google Style function docstrings.
            error_on_invalid_docstring: if `parse_docstring` is provided, configure
                whether to raise `ValueError` on invalid Google Style docstrings.
            **kwargs: Additional arguments to pass to the tool

        Returns:
            The tool.

        Raises:
            ValueError: If the function is not provided.
            ValueError: If the function does not have a docstring and description
                is not provided.
            TypeError: If the `args_schema` is not a `BaseModel` or dict.

        Examples:
            ```python
            def add(a: int, b: int) -> int:
                \"\"\"Add two numbers\"\"\"
                return a + b
            tool = StructuredTool.from_function(add)
            tool.run(1, 2) # 3

            ```
        """
        if func is not None:
            source_function = func
        elif coroutine is not None:
            source_function = coroutine
        else:
            msg = "Function and/or coroutine must be provided"
            raise ValueError(msg)
        name = name or source_function.__name__
        if args_schema is None and infer_schema:
            # schema name is appended within function
            args_schema = create_schema_from_function(
                name,
                source_function,
                parse_docstring=parse_docstring,
                error_on_invalid_docstring=error_on_invalid_docstring,
                filter_args=_filter_schema_args(source_function),
            )
        description_ = description
        if description is None and not parse_docstring: