get_input_schema() — langchain Function Reference

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

Function python LangChainCore Runnables calls 1 called by 3

Entity Profile

LangChainCore→ Runnables→ get_input_schema() — langchain Function Reference

Dependency Diagram

graph TD
  08435009_1486_e4f9_5312_91db7c8545a0["get_input_schema()"]
  4a62481c_02cb_a5de_1833_50669d5351a6["Runnable"]
  08435009_1486_e4f9_5312_91db7c8545a0 -->|defined in| 4a62481c_02cb_a5de_1833_50669d5351a6
  9f10c40d_1a35_2bbe_f0f3_ade9a50ddf54["input_schema()"]
  9f10c40d_1a35_2bbe_f0f3_ade9a50ddf54 -->|calls| 08435009_1486_e4f9_5312_91db7c8545a0
  bb994673_65a8_b98b_ca59_66e1a04c78a4["get_input_jsonschema()"]
  bb994673_65a8_b98b_ca59_66e1a04c78a4 -->|calls| 08435009_1486_e4f9_5312_91db7c8545a0
  0d15d94e_1356_d663_2931_94fce971d5bd["get_graph()"]
  0d15d94e_1356_d663_2931_94fce971d5bd -->|calls| 08435009_1486_e4f9_5312_91db7c8545a0
  255c479b_b9fa_44d8_4de5_2562051e06b5["get_name()"]
  08435009_1486_e4f9_5312_91db7c8545a0 -->|calls| 255c479b_b9fa_44d8_4de5_2562051e06b5
  style 08435009_1486_e4f9_5312_91db7c8545a0 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/runnables/base.py lines 370–409

    def get_input_schema(
        self,
        config: RunnableConfig | None = None,
    ) -> type[BaseModel]:
        """Get a Pydantic model that can be used to validate input to the `Runnable`.

        `Runnable` objects that leverage the `configurable_fields` and
        `configurable_alternatives` methods will have a dynamic input schema that
        depends on which configuration the `Runnable` is invoked with.

        This method allows to get an input schema for a specific configuration.

        Args:
            config: A config to use when generating the schema.

        Returns:
            A Pydantic model that can be used to validate input.
        """
        _ = config
        root_type = self.InputType

        if (
            inspect.isclass(root_type)
            and not isinstance(root_type, GenericAlias)
            and issubclass(root_type, BaseModel)
        ):
            return root_type

        return create_model_v2(
            self.get_name("Input"),
            root=root_type,
            # create model needs access to appropriate type annotations to be
            # able to construct the Pydantic model.
            # When we create the model, we pass information about the namespace
            # where the model is being created, so the type annotations can
            # be resolved correctly as well.
            # self.__class__.__module__ handles the case when the Runnable is
            # being sub-classed in a different module.
            module_name=self.__class__.__module__,
        )