construct_instance

construct_instance(
  cls: type[QdrantVectorStore],
  embedding: Embeddings | None = None,
  retrieval_mode: RetrievalMode = RetrievalMode.DENSE,
  sparse_embedding: SparseEmbeddings | None = None,
  client_options: dict[str, Any] | None = None,
  collection_name: str | None = None,
  distance: models.Distance = models.Distance.COSINE,
  content_payload_key: str = CONTENT_KEY,
  metadata_payload_key: str = METADATA_KEY,
  vector_name: str = VECTOR_NAME,
  sparse_vector_name: str = SPARSE_VECTOR_NAME,
  force_recreate: bool = False,
  collection_create_options: dict[str, Any] | None = None,
  vector_params: dict[str, Any] | None = None,
  sparse_vector_params: dict[str, Any] | None = None,
  validate_embeddings: bool = True,
  validate_collection_config: bool = True
) -> QdrantVectorStore