langchain.js
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    Class to parse the output of an LLM call to a list.

    Hierarchy (View Summary)

    Index

    Constructors

    Properties

    lc_kwargs: SerializedFields
    lc_namespace: string[] = ...

    A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.

    lc_runnable: boolean = true
    lc_serializable: boolean = true
    name?: string
    re: RegExp = ...

    Accessors

    • get lc_aliases(): undefined | { [key: string]: string }

      A map of aliases for constructor args. Keys are the attribute names, e.g. "foo". Values are the alias that will replace the key in serialization. This is used to eg. make argument names match Python.

      Returns undefined | { [key: string]: string }

    • get lc_attributes(): undefined | SerializedFields

      A map of additional attributes to merge with constructor args. Keys are the attribute names, e.g. "foo". Values are the attribute values, which will be serialized. These attributes need to be accepted by the constructor as arguments.

      Returns undefined | SerializedFields

    • get lc_id(): string[]

      The final serialized identifier for the module.

      Returns string[]

    • get lc_secrets(): undefined | { [key: string]: string }

      A map of secrets, which will be omitted from serialization. Keys are paths to the secret in constructor args, e.g. "foo.bar.baz". Values are the secret ids, which will be used when deserializing.

      Returns undefined | { [key: string]: string }

    • get lc_serializable_keys(): undefined | string[]

      A manual list of keys that should be serialized. If not overridden, all fields passed into the constructor will be serialized.

      Returns undefined | string[]

    Methods

    • Internal method that handles batching and configuration for a runnable It takes a function, input values, and optional configuration, and returns a promise that resolves to the output values.

      Type Parameters

      Parameters

      Returns Promise<(string[] | Error)[]>

      A promise that resolves to the output values.

    • Type Parameters

      Parameters

      • func:
            | ((input: T) => Promise<string[]>)
            | (
                (
                    input: T,
                    config?: Partial<RunnableConfig<Record<string, any>>>,
                    runManager?: CallbackManagerForChainRun,
                ) => Promise<string[]>
            )
      • input: T
      • Optionaloptions: Partial<RunnableConfig<Record<string, any>>> & { runType?: string }

      Returns Promise<string[]>

    • Type Parameters

      Parameters

      • options: Partial<O> | Partial<O>[]
      • length: number = 0

      Returns Partial<O>[]

    • Helper method to transform an Iterator of Input values into an Iterator of Output values, with callbacks. Use this to implement stream() or transform() in Runnable subclasses.

      Type Parameters

      Parameters

      • inputGenerator: AsyncGenerator<I>
      • transformer: (
            generator: AsyncGenerator<I>,
            runManager?: CallbackManagerForChainRun,
            options?: Partial<RunnableConfig<Record<string, any>>>,
        ) => AsyncGenerator<O>
      • Optionaloptions: Partial<RunnableConfig<Record<string, any>>> & { runType?: string }

      Returns AsyncGenerator<O>

    • Return the string type key uniquely identifying this class of parser

      Returns string

    • Assigns new fields to the dict output of this runnable. Returns a new runnable.

      Parameters

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

      Returns Runnable

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

      Parameters

      • inputs: (string | BaseMessage<MessageStructure, MessageType>)[]

        Array of inputs to each batch call.

      • Optionaloptions:
            | Partial<RunnableConfig<Record<string, any>>>
            | Partial<RunnableConfig<Record<string, any>>>[]

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

      • OptionalbatchOptions: RunnableBatchOptions & { returnExceptions?: false }
        • OptionalmaxConcurrency?: number

          Pass in via the standard runnable config object instead

        • OptionalreturnExceptions?: boolean
        • OptionalreturnExceptions?: false

          Whether to return errors rather than throwing on the first one

      Returns Promise<string[][]>

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

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

      Parameters

      • inputs: (string | BaseMessage<MessageStructure, MessageType>)[]

        Array of inputs to each batch call.

      • Optionaloptions:
            | Partial<RunnableConfig<Record<string, any>>>
            | Partial<RunnableConfig<Record<string, any>>>[]

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

      • OptionalbatchOptions: RunnableBatchOptions & { returnExceptions: true }
        • OptionalmaxConcurrency?: number

          Pass in via the standard runnable config object instead

        • OptionalreturnExceptions?: boolean
        • returnExceptions: true

          Whether to return errors rather than throwing on the first one

      Returns Promise<(string[] | Error)[]>

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

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

      Parameters

      • inputs: (string | BaseMessage<MessageStructure, MessageType>)[]

        Array of inputs to each batch call.

      • Optionaloptions:
            | Partial<RunnableConfig<Record<string, any>>>
            | Partial<RunnableConfig<Record<string, any>>>[]

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

      • OptionalbatchOptions: RunnableBatchOptions
        • OptionalmaxConcurrency?: number

          Pass in via the standard runnable config object instead

        • OptionalreturnExceptions?: boolean

      Returns Promise<(string[] | Error)[]>

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

    • Return a string describing the format of the output.

      Returns string

      Format instructions.

      {
      "foo": "bar"
      }
    • Parameters

      • Optionalsuffix: string

      Returns string

    • Calls the parser with a given input and optional configuration options. If the input is a string, it creates a generation with the input as text and calls parseResult. If the input is a BaseMessage, it creates a generation with the input as a message and the content of the input as text, and then calls parseResult.

      Parameters

      Returns Promise<string[]>

      A promise of the parsed output.

    • Parse the output of an LLM call.

      Parameters

      • text: string

        LLM output to parse.

      Returns Promise<string[]>

      Parsed output.

    • Parses the result of an LLM call. This method is meant to be implemented by subclasses to define how the output from the LLM should be parsed.

      Parameters

      Returns Promise<string[]>

      A promise of the parsed output.

    • Pick keys from the dict output of this runnable. Returns a new runnable.

      Parameters

      • keys: string | string[]

      Returns Runnable

    • Generate a stream of events emitted by the internal steps of the runnable.

      Use to create an iterator over StreamEvents that provide real-time information about the progress of the runnable, including StreamEvents from intermediate results.

      A StreamEvent is a dictionary with the following schema:

      • event: string - Event names are of the format: on_[runnable_type]_(start|stream|end).
      • name: string - The name of the runnable that generated the event.
      • run_id: string - Randomly generated ID associated with the given execution of the runnable that emitted the event. A child runnable that gets invoked as part of the execution of a parent runnable is assigned its own unique ID.
      • tags: string[] - The tags of the runnable that generated the event.
      • metadata: Record<string, any> - The metadata of the runnable that generated the event.
      • data: Record<string, any>

      Below is a table that illustrates some events that might be emitted by various chains. Metadata fields have been omitted from the table for brevity. Chain definitions have been included after the table.

      ATTENTION This reference table is for the V2 version of the schema.

      +----------------------+-----------------------------+------------------------------------------+
      | event                | input                       | output/chunk                             |
      +======================+=============================+==========================================+
      | on_chat_model_start  | {"messages": BaseMessage[]} |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chat_model_stream |                             | AIMessageChunk("hello")                  |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chat_model_end    | {"messages": BaseMessage[]} | AIMessageChunk("hello world")            |
      +----------------------+-----------------------------+------------------------------------------+
      | on_llm_start         | {'input': 'hello'}          |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_llm_stream        |                             | 'Hello'                                  |
      +----------------------+-----------------------------+------------------------------------------+
      | on_llm_end           | 'Hello human!'              |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chain_start       |                             |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chain_stream      |                             | "hello world!"                           |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chain_end         | [Document(...)]             | "hello world!, goodbye world!"           |
      +----------------------+-----------------------------+------------------------------------------+
      | on_tool_start        | {"x": 1, "y": "2"}          |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_tool_end          |                             | {"x": 1, "y": "2"}                       |
      +----------------------+-----------------------------+------------------------------------------+
      | on_retriever_start   | {"query": "hello"}          |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_retriever_end     | {"query": "hello"}          | [Document(...), ..]                      |
      +----------------------+-----------------------------+------------------------------------------+
      | on_prompt_start      | {"question": "hello"}       |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_prompt_end        | {"question": "hello"}       | ChatPromptValue(messages: BaseMessage[]) |
      +----------------------+-----------------------------+------------------------------------------+
      

      The "on_chain_*" events are the default for Runnables that don't fit one of the above categories.

      In addition to the standard events above, users can also dispatch custom events.

      Custom events will be only be surfaced with in the v2 version of the API!

      A custom event has following format:

      +-----------+------+------------------------------------------------------------+
      | Attribute | Type | Description                                                |
      +===========+======+============================================================+
      | name      | str  | A user defined name for the event.                         |
      +-----------+------+------------------------------------------------------------+
      | data      | Any  | The data associated with the event. This can be anything.  |
      +-----------+------+------------------------------------------------------------+
      

      Here's an example:

      import { RunnableLambda } from "@langchain/core/runnables";
      import { dispatchCustomEvent } from "@langchain/core/callbacks/dispatch";
      // Use this import for web environments that don't support "async_hooks"
      // and manually pass config to child runs.
      // import { dispatchCustomEvent } from "@langchain/core/callbacks/dispatch/web";

      const slowThing = RunnableLambda.from(async (someInput: string) => {
      // Placeholder for some slow operation
      await new Promise((resolve) => setTimeout(resolve, 100));
      await dispatchCustomEvent("progress_event", {
      message: "Finished step 1 of 2",
      });
      await new Promise((resolve) => setTimeout(resolve, 100));
      return "Done";
      });

      const eventStream = await slowThing.streamEvents("hello world", {
      version: "v2",
      });

      for await (const event of eventStream) {
      if (event.event === "on_custom_event") {
      console.log(event);
      }
      }

      Parameters

      Returns IterableReadableStream<StreamEvent>

    • Generate a stream of events emitted by the internal steps of the runnable.

      Use to create an iterator over StreamEvents that provide real-time information about the progress of the runnable, including StreamEvents from intermediate results.

      A StreamEvent is a dictionary with the following schema:

      • event: string - Event names are of the format: on_[runnable_type]_(start|stream|end).
      • name: string - The name of the runnable that generated the event.
      • run_id: string - Randomly generated ID associated with the given execution of the runnable that emitted the event. A child runnable that gets invoked as part of the execution of a parent runnable is assigned its own unique ID.
      • tags: string[] - The tags of the runnable that generated the event.
      • metadata: Record<string, any> - The metadata of the runnable that generated the event.
      • data: Record<string, any>

      Below is a table that illustrates some events that might be emitted by various chains. Metadata fields have been omitted from the table for brevity. Chain definitions have been included after the table.

      ATTENTION This reference table is for the V2 version of the schema.

      +----------------------+-----------------------------+------------------------------------------+
      | event                | input                       | output/chunk                             |
      +======================+=============================+==========================================+
      | on_chat_model_start  | {"messages": BaseMessage[]} |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chat_model_stream |                             | AIMessageChunk("hello")                  |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chat_model_end    | {"messages": BaseMessage[]} | AIMessageChunk("hello world")            |
      +----------------------+-----------------------------+------------------------------------------+
      | on_llm_start         | {'input': 'hello'}          |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_llm_stream        |                             | 'Hello'                                  |
      +----------------------+-----------------------------+------------------------------------------+
      | on_llm_end           | 'Hello human!'              |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chain_start       |                             |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chain_stream      |                             | "hello world!"                           |
      +----------------------+-----------------------------+------------------------------------------+
      | on_chain_end         | [Document(...)]             | "hello world!, goodbye world!"           |
      +----------------------+-----------------------------+------------------------------------------+
      | on_tool_start        | {"x": 1, "y": "2"}          |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_tool_end          |                             | {"x": 1, "y": "2"}                       |
      +----------------------+-----------------------------+------------------------------------------+
      | on_retriever_start   | {"query": "hello"}          |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_retriever_end     | {"query": "hello"}          | [Document(...), ..]                      |
      +----------------------+-----------------------------+------------------------------------------+
      | on_prompt_start      | {"question": "hello"}       |                                          |
      +----------------------+-----------------------------+------------------------------------------+
      | on_prompt_end        | {"question": "hello"}       | ChatPromptValue(messages: BaseMessage[]) |
      +----------------------+-----------------------------+------------------------------------------+
      

      The "on_chain_*" events are the default for Runnables that don't fit one of the above categories.

      In addition to the standard events above, users can also dispatch custom events.

      Custom events will be only be surfaced with in the v2 version of the API!

      A custom event has following format:

      +-----------+------+------------------------------------------------------------+
      | Attribute | Type | Description                                                |
      +===========+======+============================================================+
      | name      | str  | A user defined name for the event.                         |
      +-----------+------+------------------------------------------------------------+
      | data      | Any  | The data associated with the event. This can be anything.  |
      +-----------+------+------------------------------------------------------------+
      

      Here's an example:

      import { RunnableLambda } from "@langchain/core/runnables";
      import { dispatchCustomEvent } from "@langchain/core/callbacks/dispatch";
      // Use this import for web environments that don't support "async_hooks"
      // and manually pass config to child runs.
      // import { dispatchCustomEvent } from "@langchain/core/callbacks/dispatch/web";

      const slowThing = RunnableLambda.from(async (someInput: string) => {
      // Placeholder for some slow operation
      await new Promise((resolve) => setTimeout(resolve, 100));
      await dispatchCustomEvent("progress_event", {
      message: "Finished step 1 of 2",
      });
      await new Promise((resolve) => setTimeout(resolve, 100));
      return "Done";
      });

      const eventStream = await slowThing.streamEvents("hello world", {
      version: "v2",
      });

      for await (const event of eventStream) {
      if (event.event === "on_custom_event") {
      console.log(event);
      }
      }

      Parameters

      Returns IterableReadableStream<Uint8Array<ArrayBufferLike>>

    • Transforms an asynchronous generator of input into an asynchronous generator of parsed output.

      Parameters

      Returns AsyncGenerator<string[]>

      An asynchronous generator of parsed output.

    • 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: Run,
                config?: RunnableConfig<Record<string, any>>,
            ) => void | Promise<void>;
            onError?: (
                run: Run,
                config?: RunnableConfig<Record<string, any>>,
            ) => void | Promise<void>;
            onStart?: (
                run: Run,
                config?: RunnableConfig<Record<string, any>>,
            ) => void | Promise<void>;
        }

        The object containing the callback functions.

        • OptionalonEnd?: (run: Run, config?: RunnableConfig<Record<string, any>>) => void | Promise<void>

          Called after the runnable finishes running, with the Run object.

        • OptionalonError?: (run: Run, config?: RunnableConfig<Record<string, any>>) => void | Promise<void>

          Called if the runnable throws an error, with the Run object.

        • OptionalonStart?: (run: Run, config?: RunnableConfig<Record<string, any>>) => void | Promise<void>

          Called before the runnable starts running, with the Run object.

      Returns Runnable<
          string
          | BaseMessage<MessageStructure, MessageType>,
          string[],
          RunnableConfig<Record<string, any>>,
      >

    • The name of the serializable. Override to provide an alias or to preserve the serialized module name in minified environments.

      Implemented as a static method to support loading logic.

      Returns string