"""
        self.embedding = embedding
        self.distance_strategy = distance_strategy
        self.table_name = self._sanitize_input(table_name)
        self.content_field = self._sanitize_input(content_field)
        self.metadata_field = self._sanitize_input(metadata_field)
        self.vector_field = self._sanitize_input(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"] = "1.0.1"
        # 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 _sanitize_input(self, input_str: str) -> str:
        # Remove characters that are not alphanumeric or underscores
        return re.sub(r"[^a-zA-Z0-9_]", "", input_str)
    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 {}