Enables calls to the Google Cloud's Vertex AI API to access Large Language Models in a chat-like fashion.

To use, you will need to have one of the following authentication methods in place:

  • You are logged into an account permitted to the Google Cloud project using Vertex AI.
  • You are running this on a machine using a service account permitted to the Google Cloud project using Vertex AI.
  • The GOOGLE_APPLICATION_CREDENTIALS environment variable is set to the path of a credentials file for a service account permitted to the Google Cloud project using Vertex AI.

Example

const model = new ChatGoogleVertexAI({
temperature: 0.7,
});
const result = await model.invoke("What is the capital of France?");

Hierarchy

  • BaseChatGoogleVertexAI<GoogleAuthOptions>
    • ChatGoogleVertexAI

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.

connection: GoogleVertexAILLMConnection<BaseLanguageModelCallOptions, GoogleVertexAIChatInstance, GoogleVertexAIChatPrediction, GoogleAuthOptions<JSONClient>>
examples: ChatExample[] = []
maxOutputTokens: number = 1024
model: string = "chat-bison"
streamedConnection: GoogleVertexAILLMConnection<BaseLanguageModelCallOptions, GoogleVertexAIChatInstance, GoogleVertexAIChatPrediction, GoogleAuthOptions<JSONClient>>
temperature: number = 0.2
topK: number = 40
topP: number = 0.8
verbose: boolean

Whether to print out response text.

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

Accessors

  • get callKeys(): string[]
  • Keys that the language model accepts as call options.

    Returns string[]

Methods

  • Makes a single call to the chat model.

    Parameters

    Returns Promise<BaseMessage>

    A Promise that resolves to a BaseMessage.

  • Makes a single call to the chat model with a prompt value.

    Parameters

    Returns Promise<BaseMessage>

    A Promise that resolves to a BaseMessage.

  • Generates chat based on the input messages.

    Parameters

    Returns Promise<LLMResult>

    A Promise that resolves to an LLMResult.

  • Generates a prompt based on the input prompt values.

    Parameters

    Returns Promise<LLMResult>

    A Promise that resolves to an LLMResult.

  • Parameters

    Returns Promise<number>

  • Get the parameters used to invoke the model

    Parameters

    Returns any

  • Invokes the chat model with a single input.

    Parameters

    Returns Promise<BaseMessageChunk>

    A Promise that resolves to a BaseMessageChunk.

  • 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

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

    A new runnable sequence.

  • Predicts the next message based on a text input.

    Parameters

    • text: string

      The text input.

    • Optional options: string[] | BaseLanguageModelCallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<string>

    A Promise that resolves to a string.

  • Predicts the next message based on the input messages.

    Parameters

    Returns Promise<BaseMessage>

    A Promise that resolves to a BaseMessage.

  • Returns SerializedLLM

    Deprecated

    Return a json-like object representing this LLM.

  • 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

    Returns AsyncGenerator<RunLogPatch, any, unknown>

  • Returns Serialized

  • 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

    Returns AsyncGenerator<BaseMessageChunk, 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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