Class RunnablePassthrough<RunInput>

A runnable to passthrough inputs unchanged or with additional keys.

This runnable behaves almost like the identity function, except that it can be configured to add additional keys to the output, if the input is an object.

The example below demonstrates how to use RunnablePassthrough to passthrough the input from the .invoke()`

@example

const chain = RunnableSequence.from([
{
question: new RunnablePassthrough(),
context: async () => loadContextFromStore(),
},
prompt,
llm,
outputParser,
]);
const response = await chain.invoke(
"I can pass a single string instead of an object since I'm using `RunnablePassthrough`."
);

Type Parameters

  • RunInput

Hierarchy

  • Runnable<RunInput, RunInput>
    • RunnablePassthrough

Constructors

  • Type Parameters

    • RunInput

    Parameters

    • Optional kwargs: SerializedFields
    • Rest ..._args: never[]

    Returns RunnablePassthrough<RunInput>

Methods

  • Default implementation of batch, which calls invoke N times. Subclasses should override this method if they can batch more efficiently.

    Parameters

    • inputs: RunInput[]

      Array of inputs to each batch call.

    • Optional options: Partial<RunnableConfig> | Partial<RunnableConfig>[]

      Either a single call options object to apply to each batch call or an array for each call.

    • Optional batchOptions: RunnableBatchOptions & {
          returnExceptions?: false;
      }

    Returns Promise<RunInput[]>

    An array of RunOutputs, or mixed RunOutputs and errors if batchOptions.returnExceptions is set

  • Parameters

    Returns Promise<(Error | RunInput)[]>

  • Parameters

    Returns Promise<(Error | RunInput)[]>

  • Bind arguments to a Runnable, returning a new Runnable.

    Parameters

    Returns Runnable<RunInput, RunInput, RunnableConfig>

    A new RunnableBinding that, when invoked, will apply the bound args.

  • Parameters

    Returns Promise<RunInput>

  • Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input.

    Returns Runnable<RunInput[], RunInput[], RunnableConfig>

  • Create a new runnable sequence that runs each individual runnable in series, piping the output of one runnable into another runnable or runnable-like.

    Type Parameters

    • NewRunOutput

    Parameters

    • coerceable: RunnableLike<RunInput, NewRunOutput>

      A runnable, function, or object whose values are functions or runnables.

    Returns RunnableSequence<RunInput, Exclude<NewRunOutput, Error>>

    A new runnable sequence.

  • Stream output in chunks.

    Parameters

    Returns Promise<IterableReadableStream<RunInput>>

    A readable stream that is also an iterable.

  • Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops can be applied in order to construct state.

    Parameters

    • input: RunInput
    • Optional options: Partial<RunnableConfig>
    • Optional streamOptions: Omit<LogStreamCallbackHandlerInput, "autoClose">

    Returns AsyncGenerator<RunLogPatch, any, unknown>

  • Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated.

    Parameters

    • generator: AsyncGenerator<RunInput, any, unknown>
    • options: Partial<RunnableConfig>

    Returns AsyncGenerator<RunInput, any, unknown>

  • Create a new runnable from the current one that will try invoking other passed fallback runnables if the initial invocation fails.

    Parameters

    Returns RunnableWithFallbacks<RunInput, RunInput>

    A new RunnableWithFallbacks.

  • Bind lifecycle listeners to a Runnable, returning a new Runnable. The Run object contains information about the run, including its id, type, input, output, error, startTime, endTime, and any tags or metadata added to the run.

    Parameters

    • params: {
          onEnd?: ((run, config?) => void | Promise<void>);
          onError?: ((run, config?) => void | Promise<void>);
          onStart?: ((run, config?) => void | Promise<void>);
      }

      The object containing the callback functions.

      • Optional onEnd?: ((run, config?) => void | Promise<void>)
          • (run, config?): void | Promise<void>
          • Called after the runnable finishes running, with the Run object.

            Parameters

            Returns void | Promise<void>

      • Optional onError?: ((run, config?) => void | Promise<void>)
          • (run, config?): void | Promise<void>
          • Called if the runnable throws an error, with the Run object.

            Parameters

            Returns void | Promise<void>

      • Optional onStart?: ((run, config?) => void | Promise<void>)
          • (run, config?): void | Promise<void>
          • Called before the runnable starts running, with the Run object.

            Parameters

            Returns void | Promise<void>

    Returns Runnable<RunInput, RunInput, RunnableConfig>

  • A runnable that assigns key-value pairs to the input.

    The example below shows how you could use it with an inline function.

    Parameters

    • mapping: RunnableMapLike<Record<string, unknown>, Record<string, unknown>>

    Returns RunnableAssign<Record<string, unknown>, Record<string, unknown>, RunnableConfig>

    Example

    const prompt =
    PromptTemplate.fromTemplate(`Write a SQL query to answer the question using the following schema: {schema}
    Question: {question}
    SQL Query:`);

    // The `RunnablePassthrough.assign()` is used here to passthrough the input from the `.invoke()`
    // call (in this example it's the question), along with any inputs passed to the `.assign()` method.
    // In this case, we're passing the schema.
    const sqlQueryGeneratorChain = RunnableSequence.from([
    RunnablePassthrough.assign({
    schema: async () => db.getTableInfo(),
    }),
    prompt,
    new ChatOpenAI({}).bind({ stop: ["\nSQLResult:"] }),
    new StringOutputParser(),
    ]);
    const result = await sqlQueryGeneratorChain.invoke({
    question: "How many employees are there?",
    });

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