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pydantic_ai.ext

tool_from_langchain 

tool_from_langchain(langchain_tool: LangChainTool) -> Tool

Creates a Pydantic AI tool proxy from a LangChain tool.

Parameters:

Name Type Description Default
langchain_tool LangChainTool

The LangChain tool to wrap.

 required

Returns:

Type Description
Tool

A Pydantic AI tool that corresponds to the LangChain tool.
Source code in pydantic_ai_slim/pydantic_ai/ext/langchain.py 
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def tool_from_langchain(langchain_tool: LangChainTool) -> Tool:
    """Creates a Pydantic AI tool proxy from a LangChain tool.

    Args:
        langchain_tool: The LangChain tool to wrap.

    Returns:
        A Pydantic AI tool that corresponds to the LangChain tool.
    """
    function_name = langchain_tool.name
    function_description = langchain_tool.description
    inputs = langchain_tool.args.copy()
    required = sorted({name for name, detail in inputs.items() if 'default' not in detail})
    schema: JsonSchemaValue = langchain_tool.get_input_jsonschema()
    if 'additionalProperties' not in schema:
        schema['additionalProperties'] = False
    if required:
        schema['required'] = required

    defaults = {name: detail['default'] for name, detail in inputs.items() if 'default' in detail}

    # restructures the arguments to match langchain tool run
    def proxy(*args: Any, **kwargs: Any) -> str:
        assert not args, 'This should always be called with kwargs'
        kwargs = defaults | kwargs
        return langchain_tool.run(kwargs)

    return Tool.from_schema(
        function=proxy,
        name=function_name,
        description=function_description,
        json_schema=schema,
    )

LangChainToolset

Bases: FunctionToolset

A toolset that wraps LangChain tools.

Source code in pydantic_ai_slim/pydantic_ai/ext/langchain.py 
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class LangChainToolset(FunctionToolset):
    """A toolset that wraps LangChain tools."""

    def __init__(self, tools: list[LangChainTool], *, id: str | None = None):
        super().__init__([tool_from_langchain(tool) for tool in tools], id=id)