EvaluatorType.AGENT_TRAJECTORY: TrajectoryEvalChain,
    EvaluatorType.CRITERIA: CriteriaEvalChain,
    EvaluatorType.LABELED_CRITERIA: LabeledCriteriaEvalChain,
    EvaluatorType.STRING_DISTANCE: StringDistanceEvalChain,
    EvaluatorType.PAIRWISE_STRING_DISTANCE: PairwiseStringDistanceEvalChain,
    EvaluatorType.EMBEDDING_DISTANCE: EmbeddingDistanceEvalChain,
    EvaluatorType.PAIRWISE_EMBEDDING_DISTANCE: PairwiseEmbeddingDistanceEvalChain,
    EvaluatorType.JSON_VALIDITY: JsonValidityEvaluator,
    EvaluatorType.JSON_EQUALITY: JsonEqualityEvaluator,
    EvaluatorType.JSON_EDIT_DISTANCE: JsonEditDistanceEvaluator,
    EvaluatorType.JSON_SCHEMA_VALIDATION: JsonSchemaEvaluator,
    EvaluatorType.REGEX_MATCH: RegexMatchStringEvaluator,
    EvaluatorType.EXACT_MATCH: ExactMatchStringEvaluator,
}
[docs]def load_evaluator(
    evaluator: EvaluatorType,
    *,
    llm: Optional[BaseLanguageModel] = None,
    **kwargs: Any,
) -> Union[Chain, StringEvaluator]:
    """Load the requested evaluation chain specified by a string.
    Parameters
    ----------
    evaluator : EvaluatorType
        The type of evaluator to load.
    llm : BaseLanguageModel, optional
        The language model to use for evaluation, by default None
    **kwargs : Any
        Additional keyword arguments to pass to the evaluator.
    Returns
    -------
    Chain
        The loaded evaluation chain.
    Examples
    --------
    >>> from langchain.evaluation import load_evaluator, EvaluatorType
    >>> evaluator = load_evaluator(EvaluatorType.QA)
    """
    if evaluator not in _EVALUATOR_MAP: