batch() — langchain Function Reference

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

Function python LangChainCore Runnables calls 3 called by 4

Entity Profile

LangChainCore→ Runnables→ batch() — langchain Function Reference

Dependency Diagram

graph TD
  2826dfcf_5024_bd4d_0268_8f909fbbae0c["batch()"]
  4a62481c_02cb_a5de_1833_50669d5351a6["Runnable"]
  2826dfcf_5024_bd4d_0268_8f909fbbae0c -->|defined in| 4a62481c_02cb_a5de_1833_50669d5351a6
  e9999cfb_b051_7cee_27e4_2e2746488c79["batch()"]
  e9999cfb_b051_7cee_27e4_2e2746488c79 -->|calls| 2826dfcf_5024_bd4d_0268_8f909fbbae0c
  6623b4f5_0477_1322_996c_6a66715eb7c1["batch()"]
  6623b4f5_0477_1322_996c_6a66715eb7c1 -->|calls| 2826dfcf_5024_bd4d_0268_8f909fbbae0c
  0ceb56af_9929_a187_7b84_2584155e0d7b["pipe()"]
  0ceb56af_9929_a187_7b84_2584155e0d7b -->|calls| 2826dfcf_5024_bd4d_0268_8f909fbbae0c
  d7c8b78b_bd8b_c15c_ce21_97525a7a5764["_invoke()"]
  d7c8b78b_bd8b_c15c_ce21_97525a7a5764 -->|calls| 2826dfcf_5024_bd4d_0268_8f909fbbae0c
  e2ca1dd3_4ae9_2ab3_37d2_60242857703f["invoke()"]
  2826dfcf_5024_bd4d_0268_8f909fbbae0c -->|calls| e2ca1dd3_4ae9_2ab3_37d2_60242857703f
  cb51eea6_993b_93b2_5bc8_da36e6fac2df["map()"]
  2826dfcf_5024_bd4d_0268_8f909fbbae0c -->|calls| cb51eea6_993b_93b2_5bc8_da36e6fac2df
  6623b4f5_0477_1322_996c_6a66715eb7c1["batch()"]
  2826dfcf_5024_bd4d_0268_8f909fbbae0c -->|calls| 6623b4f5_0477_1322_996c_6a66715eb7c1
  style 2826dfcf_5024_bd4d_0268_8f909fbbae0c fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/runnables/base.py lines 867–915

    def batch(
        self,
        inputs: list[Input],
        config: RunnableConfig | list[RunnableConfig] | None = None,
        *,
        return_exceptions: bool = False,
        **kwargs: Any | None,
    ) -> list[Output]:
        """Default implementation runs invoke in parallel using a thread pool executor.

        The default implementation of batch works well for IO bound runnables.

        Subclasses must override this method if they can batch more efficiently;
        e.g., if the underlying `Runnable` uses an API which supports a batch mode.

        Args:
            inputs: A list of inputs to the `Runnable`.
            config: A config to use when invoking the `Runnable`. The config supports
                standard keys like `'tags'`, `'metadata'` for
                tracing purposes, `'max_concurrency'` for controlling how much work
                to do in parallel, and other keys.

                Please refer to `RunnableConfig` for more details.
            return_exceptions: Whether to return exceptions instead of raising them.
            **kwargs: Additional keyword arguments to pass to the `Runnable`.

        Returns:
            A list of outputs from the `Runnable`.
        """
        if not inputs:
            return []

        configs = get_config_list(config, len(inputs))

        def invoke(input_: Input, config: RunnableConfig) -> Output | Exception:
            if return_exceptions:
                try:
                    return self.invoke(input_, config, **kwargs)
                except Exception as e:
                    return e
            else:
                return self.invoke(input_, config, **kwargs)

        # If there's only one input, don't bother with the executor
        if len(inputs) == 1:
            return cast("list[Output]", [invoke(inputs[0], configs[0])])

        with get_executor_for_config(configs[0]) as executor:
            return cast("list[Output]", list(executor.map(invoke, inputs, configs)))