from_existing_collection

from_existing_collection(
  cls: type[QdrantVectorStore],
  collection_name: str,
  embedding: Embeddings | None = None,
  retrieval_mode: RetrievalMode = RetrievalMode.DENSE,
  location: str | None = None,
  url: str | None = None,
  port: int | None = 6333,
  grpc_port: int = 6334,
  prefer_grpc: bool = False,
  https: bool | None = None,
  api_key: str | None = None,
  prefix: str | None = None,
  timeout: int | None = None,
  host: str | None = None,
  path: 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,
  sparse_embedding: SparseEmbeddings | None = None,
  validate_embeddings: bool = True,
  validate_collection_config: bool = True,
  **kwargs: Any = {}
) -> QdrantVectorStore