init() — langchain Function Reference

Architecture documentation for the __init__() function in base.py from the langchain codebase.

Function python LangChainCore Runnables

Entity Profile

LangChainCore→ Runnables→ __init__() — langchain Function Reference

Dependency Diagram

graph TD
  ec934977_7e1f_106e_289e_bc5d17bc0941["__init__()"]
  9a777f9f_fc96_a4c7_ebd5_632b655b53ae["RunnableBindingBase"]
  ec934977_7e1f_106e_289e_bc5d17bc0941 -->|defined in| 9a777f9f_fc96_a4c7_ebd5_632b655b53ae
  style ec934977_7e1f_106e_289e_bc5d17bc0941 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/runnables/base.py lines 5577–5621

    def __init__(
        self,
        *,
        bound: Runnable[Input, Output],
        kwargs: Mapping[str, Any] | None = None,
        config: RunnableConfig | None = None,
        config_factories: list[Callable[[RunnableConfig], RunnableConfig]]
        | None = None,
        custom_input_type: type[Input] | BaseModel | None = None,
        custom_output_type: type[Output] | BaseModel | None = None,
        **other_kwargs: Any,
    ) -> None:
        """Create a `RunnableBinding` from a `Runnable` and kwargs.

        Args:
            bound: The underlying `Runnable` that this `Runnable` delegates calls
                to.
            kwargs: optional kwargs to pass to the underlying `Runnable`, when running
                the underlying `Runnable` (e.g., via `invoke`, `batch`,
                `transform`, or `stream` or async variants)

            config: optional config to bind to the underlying `Runnable`.

            config_factories: optional list of config factories to apply to the
                config before binding to the underlying `Runnable`.

            custom_input_type: Specify to override the input type of the underlying
                `Runnable` with a custom type.
            custom_output_type: Specify to override the output type of the underlying
                `Runnable` with a custom type.
            **other_kwargs: Unpacked into the base class.
        """
        super().__init__(
            bound=bound,
            kwargs=kwargs or {},
            config=config or {},
            config_factories=config_factories or [],
            custom_input_type=custom_input_type,
            custom_output_type=custom_output_type,
            **other_kwargs,
        )
        # if we don't explicitly set config to the TypedDict here,
        # the pydantic init above will strip out any of the "extra"
        # fields even though total=False on the typed dict.
        self.config = config or {}