Class HuggingFaceInference

Class implementing the Large Language Model (LLM) interface using the Hugging Face Inference API for text generation.

Example

const model = new HuggingFaceInference({
model: "gpt2",
temperature: 0.7,
maxTokens: 50,
});

const res = await model.call(
"Question: What would be a good company name for a company that makes colorful socks?\nAnswer:"
);
console.log({ res });

Hierarchy

  • LLM
    • HuggingFaceInference

Implements

Constructors

Properties

CallOptions: BaseLLMCallOptions
ParsedCallOptions: Omit<BaseLLMCallOptions, never>
apiKey: undefined | string = undefined

API key to use.

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.

endpointUrl: undefined | string = undefined

Custom inference endpoint URL to use

frequencyPenalty: undefined | number = undefined

Penalizes repeated tokens according to frequency

maxTokens: undefined | number = undefined

Maximum number of tokens to generate in the completion.

model: string = "gpt2"

Model to use

temperature: undefined | number = undefined

Sampling temperature to use

topK: undefined | number = undefined

Integer to define the top tokens considered within the sample operation to create new text.

topP: undefined | number = undefined

Total probability mass of tokens to consider at each step

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

  • 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>

  • 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>

  • 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>

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