A type of Large Language Model (LLM) that interacts with the Bedrock service. It extends the base LLM class and implements the BaseBedrockInput interface. The class is designed to authenticate and interact with the Bedrock service, which is a part of Amazon Web Services (AWS). It uses AWS credentials for authentication and can be configured with various parameters such as the model to use, the AWS region, and the maximum number of tokens to generate.

Hierarchy

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.

codec: EventStreamCodec = ...
credentials: CredentialType
fetchFn: ((input, init?) => Promise<Response>)

Type declaration

    • (input, init?): Promise<Response>
    • Parameters

      • input: RequestInfo | URL
      • Optional init: RequestInit

      Returns Promise<Response>

model: string = "amazon.titan-tg1-large"
region: string
streaming: boolean = false
verbose: boolean

Whether to print out response text.

callbacks?: Callbacks
endpointHost?: string
maxTokens?: number = undefined
metadata?: Record<string, unknown>
modelKwargs?: Record<string, unknown>
stopSequences?: string[]

Deprecated

tags?: string[]
temperature?: number = undefined
lc_runnable: boolean = true

Accessors

Methods

  • Get the parameters used to invoke the model

    Parameters

    Returns {
        maxTokens: undefined | number;
        model: string;
        modelKwargs: undefined | Record<string, unknown>;
        region: string;
        stop: undefined | string[];
        temperature: undefined | number;
    }

    • maxTokens: undefined | number
    • model: string
    • modelKwargs: undefined | Record<string, unknown>
    • region: string
    • stop: undefined | string[]
    • temperature: undefined | number
  • 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.

  • 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.

  • 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>

  • 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>

  • 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, any, unknown>
    • transformer: ((generator, runManager?, options?) => AsyncGenerator<O, any, unknown>)
        • (generator, runManager?, options?): AsyncGenerator<O, any, unknown>
        • Parameters

          Returns AsyncGenerator<O, any, unknown>

    • Optional options: BaseLLMCallOptions & {
          runType?: string;
      }

    Returns AsyncGenerator<O, any, unknown>

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