_run_chain() — langchain Function Reference

Architecture documentation for the _run_chain() function in runner_utils.py from the langchain codebase.

Function python LangChainCore ApiManagement called by 1

Entity Profile

LangChainCore→ ApiManagement→ _run_chain() — langchain Function Reference

Dependency Diagram

graph TD
  732636c1_f8cb_78e1_d81d_6611b0b6e364["_run_chain()"]
  8253c602_7d0c_9195_a7e1_3e9b19304131["runner_utils.py"]
  732636c1_f8cb_78e1_d81d_6611b0b6e364 -->|defined in| 8253c602_7d0c_9195_a7e1_3e9b19304131
  385c1e91_d947_1192_8746_ee1dd66ceb54["_run_llm_or_chain()"]
  385c1e91_d947_1192_8746_ee1dd66ceb54 -->|calls| 732636c1_f8cb_78e1_d81d_6611b0b6e364
  style 732636c1_f8cb_78e1_d81d_6611b0b6e364 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/smith/evaluation/runner_utils.py lines 929–962

def _run_chain(
    chain: Chain | Runnable,
    inputs: dict[str, Any],
    callbacks: Callbacks,
    *,
    tags: list[str] | None = None,
    input_mapper: Callable[[dict], Any] | None = None,
    metadata: dict[str, Any] | None = None,
) -> dict | str:
    """Run a chain on inputs."""
    inputs_ = inputs if input_mapper is None else input_mapper(inputs)
    if (
        isinstance(chain, Chain)
        and isinstance(inputs_, dict)
        and len(inputs_) == 1
        and chain.input_keys
    ):
        val = next(iter(inputs_.values()))
        output = chain.invoke(
            val,
            config=RunnableConfig(
                callbacks=callbacks,
                tags=tags or [],
                metadata=metadata or {},
            ),
        )
    else:
        runnable_config = RunnableConfig(
            tags=tags or [],
            callbacks=callbacks,
            metadata=metadata or {},
        )
        output = chain.invoke(inputs_, config=runnable_config)
    return output