vectorstore = SingleStoreDB(OpenAIEmbeddings())
        """
        self.embedding = embedding
        self.distance_strategy = distance_strategy
        self.table_name = table_name
        self.content_field = content_field
        self.metadata_field = metadata_field
        self.vector_field = vector_field
        """Pass the rest of the kwargs to the connection."""
        self.connection_kwargs = kwargs
        """Add program name and version to connection attributes."""
        if "conn_attrs" not in self.connection_kwargs:
            self.connection_kwargs["conn_attrs"] = dict()
        self.connection_kwargs["conn_attrs"]["_connector_name"] = "langchain python sdk"
        self.connection_kwargs["conn_attrs"]["_connector_version"] = "1.0.0"
        """Create connection pool."""
        self.connection_pool = QueuePool(
            self._get_connection,
            max_overflow=max_overflow,
            pool_size=pool_size,
            timeout=timeout,
        )
        self._create_table()
    @property
    def embeddings(self) -> Embeddings:
        return self.embedding
    def _select_relevance_score_fn(self) -> Callable[[float], float]:
        return self._max_inner_product_relevance_score_fn
    def _create_table(self: SingleStoreDB) -> None:
        """Create table if it doesn't exist."""
        conn = self.connection_pool.connect()
        try:
            cur = conn.cursor()
            try:
                cur.execute(
                    """CREATE TABLE IF NOT EXISTS {}
                    ({} TEXT CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci,
                    {} BLOB, {} JSON);""".format(
                        self.table_name,
                        self.content_field,
                        self.vector_field,
                        self.metadata_field,
                    ),
                )
            finally:
                cur.close()