List of Documents most similar to the query and score for each
        """
        from azure.search.documents.models import Vector
        results = self.client.search(
            search_text="",
            vectors=[
                Vector(
                    value=np.array(
                        self.embedding_function(query), dtype=np.float32
                    ).tolist(),
                    k=k,
                    fields=FIELDS_CONTENT_VECTOR,
                )
            ],
            filter=filters,
        )
        # Convert results to Document objects
        docs = [
            (
                Document(
                    page_content=result.pop(FIELDS_CONTENT),
                    metadata={
                        **(
                            {FIELDS_ID: result.pop(FIELDS_ID)}
                            if FIELDS_ID in result
                            else {}
                        ),
                        **(
                            json.loads(result[FIELDS_METADATA])
                            if FIELDS_METADATA in result
                            else {
                                k: v
                                for k, v in result.items()
                                if k != FIELDS_CONTENT_VECTOR
                            }
                        ),
                    },
                ),
                float(result["@search.score"]),
            )
            for result in results
        ]
        return docs
[docs]    def hybrid_search(self, query: str, k: int = 4, **kwargs: Any) -> List[Document]:
        """
        Returns the most similar indexed documents to the query text.
        Args:
            query (str): The query text for which to find similar documents.
            k (int): The number of documents to return. Default is 4.
        Returns:
            List[Document]: A list of documents that are most similar to the query text.
        """
        docs_and_scores = self.hybrid_search_with_score(
            query, k=k, filters=kwargs.get("filters", None)
        )