- ``tensor_db`` - Hosted Managed Tensor Database for storage
                    and query execution. Only for data in Deep Lake Managed Database.
                        Use runtime = {"db_engine": True} during dataset creation.
            return_score (bool): Return score with document. Default is False.
        Returns:
            Tuple[List[Document], List[Tuple[Document, float]]] - A tuple of two lists.
                The first list contains Documents, and the second list contains
                tuples of Document and float score.
        Raises:
            ValueError: If return_score is True but some condition is not met.
        """
        result = self.vectorstore.search(
            query=tql,
            exec_option=exec_option,
        )
        metadatas = result["metadata"]
        texts = result["text"]
        docs = [
            Document(
                page_content=text,
                metadata=metadata,
            )
            for text, metadata in zip(texts, metadatas)
        ]
        if kwargs:
            unsupported_argument = next(iter(kwargs))
            if kwargs[unsupported_argument] is not False:
                raise ValueError(
                    f"specifying {unsupported_argument} is "
                    "not supported with tql search."
                )
        return docs
    def _search(
        self,
        query: Optional[str] = None,
        embedding: Optional[Union[List[float], np.ndarray]] = None,
        embedding_function: Optional[Callable] = None,
        k: int = 4,
        distance_metric: str = "L2",
        use_maximal_marginal_relevance: bool = False,
        fetch_k: Optional[int] = 20,
        filter: Optional[Union[Dict, Callable]] = None,
        return_score: bool = False,