Enables calls to the Google Cloud's Vertex AI API to access Large Language Models.

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 GoogleVertexAI({
temperature: 0.7,
});
const stream = await model.stream(
"What would be a good company name for a company that makes colorful socks?",
);
for await (const chunk of stream) {
console.log(chunk);
}

Hierarchy

  • BaseGoogleVertexAI<GoogleAuthOptions>
    • GoogleVertexAI

Constructors

Properties

CallOptions: BaseLLMCallOptions
ParsedCallOptions: Omit<BaseLLMCallOptions, 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.

maxOutputTokens: number = 1024
model: string = "text-bison"
temperature: number = 0.7
topK: number = 40
topP: number = 0.8
verbose: boolean

Whether to print out response text.

callbacks?: Callbacks
metadata?: Record<string, unknown>
tags?: string[]
connection: GoogleVertexAILLMConnection<BaseLanguageModelCallOptions, GoogleVertexAILLMInstance, TextPrediction, GoogleAuthOptions<JSONClient>>
streamedConnection: GoogleVertexAILLMConnection<BaseLanguageModelCallOptions, GoogleVertexAILLMInstance, TextPrediction, GoogleAuthOptions<JSONClient>>

Accessors

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

    Returns string[]

Methods

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

    Parameters

    Returns Promise<string[]>

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

  • Parameters

    Returns Promise<(string | Error)[]>

  • Parameters

    Returns Promise<(string | Error)[]>

  • Convenience wrapper for generate that takes in a single string prompt and returns a single string output.

    Parameters

    Returns Promise<string>

  • Extracts the prediction from the API response.

    Parameters

    • result: GoogleVertexAILLMResponse<TextPrediction>

      The API response from which to extract the prediction.

    Returns TextPrediction

    A TextPrediction object representing the extracted prediction.

  • Formats the input instance for the Google Vertex AI model based on the model type (text or code).

    Parameters

    • prompt: string

      Prompt to be formatted as an instance.

    Returns GoogleVertexAILLMInstance

    A GoogleVertexAILLMInstance object representing the formatted instance.

  • Formats the input instance as a code instance for the Google Vertex AI model.

    Parameters

    • prompt: string

      Prompt to be formatted as a code instance.

    Returns GoogleVertexAILLMInstance

    A GoogleVertexAILLMInstance object representing the formatted code instance.

  • Formats the input instance as a text instance for the Google Vertex AI model.

    Parameters

    • prompt: string

      Prompt to be formatted as a text instance.

    Returns GoogleVertexAILLMInstance

    A GoogleVertexAILLMInstance object representing the formatted text instance.

  • Run the LLM on the given prompts and input, handling caching.

    Parameters

    Returns Promise<LLMResult>

  • This method takes prompt values, options, and callbacks, and generates a result based on the prompts.

    Parameters

    Returns Promise<LLMResult>

    An LLMResult based on the prompts.

  • Parameters

    Returns Promise<number>

  • Get the parameters used to invoke the model

    Parameters

    Returns any

  • This method takes an input and options, and returns a string. It converts the input to a prompt value and generates a result based on the prompt.

    Parameters

    Returns Promise<string>

    A string result based on the prompt.

  • 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<string, NewRunOutput>

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

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

    A new runnable sequence.

  • This method is similar to call, but it's used for making predictions based on the input text.

    Parameters

    • text: string

      Input text for the prediction.

    • Optional options: string[] | BaseLLMCallOptions

      Options for the LLM call.

    • Optional callbacks: Callbacks

      Callbacks for the LLM call.

    Returns Promise<string>

    A prediction based on the input text.

  • This method takes a list of messages, options, and callbacks, and returns a predicted message.

    Parameters

    • messages: BaseMessage[]

      A list of messages for the prediction.

    • Optional options: string[] | BaseLLMCallOptions

      Options for the LLM call.

    • Optional callbacks: Callbacks

      Callbacks for the LLM call.

    Returns Promise<BaseMessage>

    A predicted message based on the list of messages.

  • Returns SerializedLLM

    Deprecated

    Return a json-like object representing this LLM.

  • Stream output in chunks.

    Parameters

    Returns Promise<IterableReadableStream<string>>

    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

    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<string, 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, string, BaseLLMCallOptions>

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