) -> None:
            super().__init__(criteria=criteria, **kwargs)
[docs]    class LabeledCriteria(EvalConfig):
        """Configuration for a labeled (with references) criteria evaluator.
        Parameters
        ----------
        criteria : Optional[CRITERIA_TYPE]
            The criteria to evaluate.
        llm : Optional[BaseLanguageModel]
            The language model to use for the evaluation chain.
        """
        criteria: Optional[CRITERIA_TYPE] = None
        llm: Optional[BaseLanguageModel] = None
        evaluator_type: EvaluatorType = EvaluatorType.LABELED_CRITERIA
        def __init__(
            self, criteria: Optional[CRITERIA_TYPE] = None, **kwargs: Any
        ) -> None:
            super().__init__(criteria=criteria, **kwargs)
[docs]    class EmbeddingDistance(EvalConfig):
        """Configuration for an embedding distance evaluator.
        Parameters
        ----------
        embeddings : Optional[Embeddings]
            The embeddings to use for computing the distance.
        distance_metric : Optional[EmbeddingDistanceEnum]
            The distance metric to use for computing the distance.
        """
        evaluator_type: EvaluatorType = EvaluatorType.EMBEDDING_DISTANCE
        embeddings: Optional[Embeddings] = None
        distance_metric: Optional[EmbeddingDistanceEnum] = None
        class Config:
            arbitrary_types_allowed = True
[docs]    class StringDistance(EvalConfig):
        """Configuration for a string distance evaluator.
        Parameters
        ----------
        distance : Optional[StringDistanceEnum]
            The string distance metric to use.
        """
        evaluator_type: EvaluatorType = EvaluatorType.STRING_DISTANCE
        distance: Optional[StringDistanceEnum] = None