@property
    def embeddings(self) -> Embeddings:
        return self._embedding
[docs]    def add_texts(
        self,
        texts: Iterable[str],
        metadatas: Optional[List[Dict[Any, Any]]] = None,
        ids: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> List[str]:
        ids = ids or [str(uuid.uuid4()) for _ in texts]
        docs = self._texts_to_documents(texts, metadatas)
        vectors = self._embedding.embed_documents(list(texts))
        return self.add_vectors(vectors, docs, ids)
[docs]    @classmethod
    def from_texts(
        cls: Type["SupabaseVectorStore"],
        texts: List[str],
        embedding: Embeddings,
        metadatas: Optional[List[dict]] = None,
        client: Optional[supabase.client.Client] = None,
        table_name: Optional[str] = "documents",
        query_name: Union[str, None] = "match_documents",
        ids: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> "SupabaseVectorStore":
        """Return VectorStore initialized from texts and embeddings."""
        if not client:
            raise ValueError("Supabase client is required.")
        if not table_name:
            raise ValueError("Supabase document table_name is required.")
        embeddings = embedding.embed_documents(texts)
        ids = [str(uuid.uuid4()) for _ in texts]
        docs = cls._texts_to_documents(texts, metadatas)
        cls._add_vectors(client, table_name, embeddings, docs, ids)
        return cls(
            client=client,
            embedding=embedding,
            table_name=table_name,