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.

Example

const model = new BedrockChat({
model: "anthropic.claude-v2",
region: "us-east-1",
});
const res = await model.invoke([{ content: "Tell me a joke" }]);
console.log(res);

Hierarchy

Implements

  • BaseBedrockInput

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.

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

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>

  • 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.

  • 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<BaseMessageChunk, any, unknown>

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