Base class for chat models. It extends the BaseLanguageModel class and provides methods for generating chat based on input messages.

Hierarchy

Constructors

Properties

ParsedCallOptions: Omit<BaseLanguageModelCallOptions, never>
caller: AsyncCaller

The async caller should be used by subclasses to make any async calls, which will thus benefit from the concurrency and retry logic.

verbose: boolean

Whether to print out response text.

callbacks?: Callbacks
metadata?: Record<string, unknown>
name?: string
tags?: string[]

Accessors

Methods

  • 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.

    event name chunk input output
    on_llm_start [model name] {'input': 'hello'}
    on_llm_stream [model name] 'Hello' OR AIMessageChunk("hello")
    on_llm_end [model name] 'Hello human!'
    on_chain_start format_docs
    on_chain_stream format_docs "hello world!, goodbye world!"
    on_chain_end format_docs [Document(...)] "hello world!, goodbye world!"
    on_tool_start some_tool {"x": 1, "y": "2"}
    on_tool_stream some_tool {"x": 1, "y": "2"}
    on_tool_end some_tool {"x": 1, "y": "2"}
    on_retriever_start [retriever name] {"query": "hello"}
    on_retriever_chunk [retriever name] {documents: [...]}
    on_retriever_end [retriever name] {"query": "hello"} {documents: [...]}
    on_prompt_start [template_name] {"question": "hello"}
    on_prompt_end [template_name] {"question": "hello"} ChatPromptValue(messages: [SystemMessage, ...])

    Parameters

    Returns AsyncGenerator<StreamEvent, any, unknown>

  • 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<BaseLanguageModelInput, BaseMessageChunk, BaseLanguageModelCallOptions>

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