batch() — langchain Function Reference

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

Function python LangChainCore LanguageModelBase calls 1

Entity Profile

LangChainCore→ LanguageModelBase→ batch() — langchain Function Reference

Dependency Diagram

graph TD
  c4fe32ba_8c1c_519f_8a80_8c795b6f614a["batch()"]
  74f697e6_2555_becc_640e_6f41ea707eba["_ConfigurableModel"]
  c4fe32ba_8c1c_519f_8a80_8c795b6f614a -->|defined in| 74f697e6_2555_becc_640e_6f41ea707eba
  4d79fd76_22aa_8160_64a3_c62bd0bfe875["_model()"]
  c4fe32ba_8c1c_519f_8a80_8c795b6f614a -->|calls| 4d79fd76_22aa_8160_64a3_c62bd0bfe875
  style c4fe32ba_8c1c_519f_8a80_8c795b6f614a fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain_v1/langchain/chat_models/base.py lines 747–773

    def batch(
        self,
        inputs: list[LanguageModelInput],
        config: RunnableConfig | list[RunnableConfig] | None = None,
        *,
        return_exceptions: bool = False,
        **kwargs: Any | None,
    ) -> list[Any]:
        config = config or None
        # If <= 1 config use the underlying models batch implementation.
        if config is None or isinstance(config, dict) or len(config) <= 1:
            if isinstance(config, list):
                config = config[0]
            return self._model(config).batch(
                inputs,
                config=config,
                return_exceptions=return_exceptions,
                **kwargs,
            )
        # If multiple configs default to Runnable.batch which uses executor to invoke
        # in parallel.
        return super().batch(
            inputs,
            config=config,
            return_exceptions=return_exceptions,
            **kwargs,
        )