"similarity",
        "similarity_score_threshold",
        "mmr",
    )
    class Config:
        """Configuration for this pydantic object."""
        arbitrary_types_allowed = True
    @root_validator()
    def validate_search_type(cls, values: Dict) -> Dict:
        """Validate search type."""
        search_type = values["search_type"]
        if search_type not in cls.allowed_search_types:
            raise ValueError(
                f"search_type of {search_type} not allowed. Valid values are: "
                f"{cls.allowed_search_types}"
            )
        if search_type == "similarity_score_threshold":
            score_threshold = values["search_kwargs"].get("score_threshold")
            if (score_threshold is None) or (not isinstance(score_threshold, float)):
                raise ValueError(
                    "`score_threshold` is not specified with a float value(0~1) "
                    "in `search_kwargs`."
                )
        return values
    def _get_relevant_documents(
        self, query: str, *, run_manager: CallbackManagerForRetrieverRun
    ) -> List[Document]:
        if self.search_type == "similarity":
            docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
        elif self.search_type == "similarity_score_threshold":
            docs_and_similarities = (
                self.vectorstore.similarity_search_with_relevance_scores(
                    query, **self.search_kwargs
                )
            )
            docs = [doc for doc, _ in docs_and_similarities]
        elif self.search_type == "mmr":
            docs = self.vectorstore.max_marginal_relevance_search(
                query, **self.search_kwargs
            )
        else: