if not _check_index_exists(self.client, self.index_name):
            # Define schema
            schema = (
                TextField(name=self.content_key),
                TextField(name=self.metadata_key),
                VectorField(
                    self.vector_key,
                    "FLAT",
                    {
                        "TYPE": "FLOAT32",
                        "DIM": dim,
                        "DISTANCE_METRIC": distance_metric,
                    },
                ),
            )
            prefix = _redis_prefix(self.index_name)
            # Create Redis Index
            self.client.ft(self.index_name).create_index(
                fields=schema,
                definition=IndexDefinition(prefix=[prefix], index_type=IndexType.HASH),
            )
[docs]    def add_texts(
        self,
        texts: Iterable[str],
        metadatas: Optional[List[dict]] = None,
        embeddings: Optional[List[List[float]]] = None,
        keys: Optional[List[str]] = None,
        batch_size: int = 1000,
        **kwargs: Any,
    ) -> List[str]:
        """Add more texts to the vectorstore.
        Args:
            texts (Iterable[str]): Iterable of strings/text to add to the vectorstore.
            metadatas (Optional[List[dict]], optional): Optional list of metadatas.
                Defaults to None.
            embeddings (Optional[List[List[float]]], optional): Optional pre-generated
                embeddings. Defaults to None.
            keys (Optional[List[str]], optional): Optional key values to use as ids.
                Defaults to None.
            batch_size (int, optional): Batch size to use for writes. Defaults to 1000.
        Returns:
            List[str]: List of ids added to the vectorstore
        """
        ids = []
        prefix = _redis_prefix(self.index_name)
rtdocs_stable/api.python.langchain.com/en/stable/_modules/langchain/vectorstores/redis.html