EmbeddingDistance: {
    evaluatorType: "embedding_distance";
    feedbackKey: undefined | string;
    formatEvaluatorInputs: EvaluatorInputFormatter;
    agentTools?: undefined | StructuredToolInterface[];
    chainOptions?: undefined | Partial<Omit<LLMEvalChainInput<EvalOutputType, BaseLanguageModelInterface>, "llm">>;
    criteria?: undefined | CriteriaLike;
    distanceMetric?: undefined | EmbeddingDistanceType;
    embedding?: any;
    llm?: any;
}

Configuration to load a "EmbeddingDistanceEvalChain" evaluator, which embeds distances to score semantic difference between a prediction and reference.

Type declaration

  • evaluatorType: "embedding_distance"
  • feedbackKey: undefined | string
  • formatEvaluatorInputs: EvaluatorInputFormatter
  • OptionalagentTools?: undefined | StructuredToolInterface[]

    A list of tools available to the agent, for TrajectoryEvalChain.

  • OptionalchainOptions?: undefined | Partial<Omit<LLMEvalChainInput<EvalOutputType, BaseLanguageModelInterface>, "llm">>
  • Optionalcriteria?: undefined | CriteriaLike

    The criteria to use for the evaluator.

  • OptionaldistanceMetric?: undefined | EmbeddingDistanceType

    The distance metric to use for comparing the embeddings.

  • Optionalembedding?: any

    The embedding objects to vectorize the outputs.

  • Optionalllm?: any
""