def add(self, nodes: List[BaseNode], **add_kwargs: Any) -> List[str]:
        """
        Add nodes to index.

        Args:
            nodes: List[BaseNode]: list of nodes with embeddings

        """
        if len(nodes) > 0 and not self._collection_initialized:
            self._create_collection(
                collection_name=self.collection_name,
                vector_size=len(nodes[0].get_embedding()),
            )

        if self._collection_initialized and self._legacy_vector_format is None:
            self._detect_vector_format(self.collection_name)

        points, ids = self._build_points(nodes, self.sparse_vector_name)

        self._client.upload_points(
            collection_name=self.collection_name,
            points=points,
            batch_size=self.batch_size,
            parallel=self.parallel,
            max_retries=self.max_retries,
            wait=True,
        )

        return ids

        Add nodes to index.

        Args:
            nodes: List[BaseNode]: list of nodes with embeddings

        
llama-index-integrations/vector_stores/llama-index-vector-stores-qdrant/llama_index/vector_stores/qdrant/base.py