self.sync_client = client.Sync(
            self.service_url,
            self.collection_name,
            self.num_dimensions,
            self._distance_strategy.value.lower(),
            time_partition_interval=self._time_partition_interval,
        )
        self.async_client = client.Async(
            self.service_url,
            self.collection_name,
            self.num_dimensions,
            self._distance_strategy.value.lower(),
            time_partition_interval=self._time_partition_interval,
        )
        self.__post_init__()
    def __post_init__(
        self,
    ) -> None:
        """
        Initialize the store.
        """
        self.sync_client.create_tables()
        if self.pre_delete_collection:
            self.sync_client.delete_all()
    @property
    def embeddings(self) -> Embeddings:
        return self.embedding
[docs]    def drop_tables(self) -> None:
        self.sync_client.drop_table()
    @classmethod
    def __from(
        cls,
        texts: List[str],
        embeddings: List[List[float]],
        embedding: Embeddings,
        metadatas: Optional[List[dict]] = None,
        ids: Optional[List[str]] = None,
        collection_name: str = _LANGCHAIN_DEFAULT_COLLECTION_NAME,
        distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
        service_url: Optional[str] = None,
        pre_delete_collection: bool = False,
        **kwargs: Any,
    ) -> TimescaleVector:
        num_dimensions = len(embeddings[0])
        if ids is None:
            ids = [str(uuid.uuid1()) for _ in texts]
        if not metadatas:
            metadatas = [{} for _ in texts]
        if service_url is None:
            service_url = cls.get_service_url(kwargs)