Class RunnableParallel

libs/core/langchain_core/runnables/base.py:2912–3338

Runnable that runs a mapping of Runnables in parallel, and returns a mapping of their outputs. RunnableParallel is one of the two main composition primitives for the LCEL, alongside RunnableSequence. It invokes Runnables concurrently, providing the same input to each. A Runnabl

class RunnableParallel(RunnableSerializable[Input, Dict[str, Any]]):
    """Runnable that runs a mapping of Runnables in parallel, and returns a mapping
    of their outputs.

    RunnableParallel is one of the two main composition primitives for the LCEL,
    alongside RunnableSequence. It invokes Runnables concurrently, providing the same
    input to each.

    A RunnableParallel can be instantiated directly or by using a dict literal within a
    sequence.

    Here is a simple example that uses functions to illustrate the use of
    RunnableParallel:

        .. code-block:: python

            from langchain_core.runnables import RunnableLambda

            def add_one(x: int) -> int:
                return x + 1

            def mul_two(x: int) -> int:
                return x * 2

            def mul_three(x: int) -> int:
                return x * 3

            runnable_1 = RunnableLambda(add_one)
            runnable_2 = RunnableLambda(mul_two)
            runnable_3 = RunnableLambda(mul_three)

            sequence = runnable_1 | {  # this dict is coerced to a RunnableParallel
                "mul_two": runnable_2,
                "mul_three": runnable_3,
            }
            # Or equivalently:
            # sequence = runnable_1 | RunnableParallel(
            #     {"mul_two": runnable_2, "mul_three": runnable_3}
            # )
            # Also equivalently:
            # sequence = runnable_1 | RunnableParallel(
            #     mul_two=runnable_2,
            #     mul_three=runnable_3,
            # )

            sequence.invoke(1)
            await sequence.ainvoke(1)

            sequence.batch([1, 2, 3])
            await sequence.abatch([1, 2, 3])

    RunnableParallel makes it easy to run Runnables in parallel. In the below example,
    we simultaneously stream output from two different Runnables:

        .. code-block:: python

            from langchain_core.prompts import ChatPromptTemplate
            from langchain_core.runnables import RunnableParallel