def from_documents(
        cls: Type[OraLlamaVS],
        docs: List[TextNode],
        table_name: str = "llama_index",
        **kwargs: Any,
    ) -> OraLlamaVS:
        """Return VectorStore initialized from texts and embeddings."""
        _client = kwargs.get("client")
        if _client is None:
            raise ValueError("client parameter is required...")
        params = kwargs.get("params")
        distance_strategy = kwargs.get("distance_strategy")
        drop_table_purge(_client, table_name)

        vss = cls(
            _client=_client,
            table_name=table_name,
            params=params,
            distance_strategy=distance_strategy,
        )
        vss.add(nodes=docs)
        return vss
Return VectorStore initialized from texts and embeddings.
llama-index-integrations/vector_stores/llama-index-vector-stores-oracledb/llama_index/vector_stores/oracledb/base.py