Class EmbeddingDistanceEvalChain

Use embedding distances to score semantic difference between a prediction and reference.

Hierarchy

  • StringEvaluator
    • EmbeddingDistanceEvalChain

Implements

Constructors

Properties

distanceMetric: EmbeddingDistanceType = "cosine"

The distance metric to use for comparing the embeddings.

outputKey: string = "score"
requiresInput: boolean = false
requiresReference: boolean = true
verbose: boolean

Whether to print out response text.

callbacks?: Callbacks
embedding?: Embeddings

The embedding objects to vectorize the outputs.

evaluationName?: string = ...

The name of the evaluation.

memory?: BaseMemory
metadata?: Record<string, unknown>
skipInputWarning?: string = ...
skipReferenceWarning?: string = ...
tags?: string[]
lc_runnable: boolean = true

Accessors

Methods

  • Check if the evaluation arguments are valid.

    Parameters

    • Optional reference: string

      The reference label.

    • Optional input: string

      The input string.

    Returns void

    Throws

    If the evaluator requires an input string but none is provided, or if the evaluator requires a reference label but none is provided.

  • Evaluate Chain or LLM output, based on optional input and label.

    Parameters

    Returns Promise<ChainValues>

    The evaluation results containing the score or value. It is recommended that the dictionary contain the following keys:

    • score: the score of the evaluation, if applicable.
    • value: the string value of the evaluation, if applicable.
    • reasoning: the reasoning for the evaluation, if applicable.
  • Invoke the chain with the provided input and returns the output.

    Parameters

    Returns Promise<ChainValues>

    Promise that resolves with the output of the chain run.

  • 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<ChainValues, any, unknown>

  • Parameters

    • values: ChainValues & {
          signal?: AbortSignal;
          timeout?: number;
      }

    Returns Promise<ChainValues & {
        signal?: AbortSignal;
        timeout?: number;
    }>

  • 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: BaseCallbackConfig & {
          runType?: string;
      }

    Returns AsyncGenerator<O, any, unknown>

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