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Update QdrantComponent build method to handle pre-existing vector-stores

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This commit is contained in:
Ricardo Henriques 2024-02-14 15:58:30 +00:00
commit 79e472772e
1 changed files with 50 additions and 23 deletions
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73
src/backend/langflow/components/vectorstores/Qdrant.py
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@ -15,7 +15,7 @@ class QdrantComponent(CustomComponent):
return { return {
"documents": {"display_name": "Documents"}, "documents": {"display_name": "Documents"},
"embedding": {"display_name": "Embedding"}, "embedding": {"display_name": "Embedding"},
"api_key": {"display_name": "API Key", "password": True}, "api_key": {"display_name": "API Key", "password": True, "advanced": True},
"collection_name": {"display_name": "Collection Name"}, "collection_name": {"display_name": "Collection Name"},
"content_payload_key": {"display_name": "Content Payload Key", "advanced": True}, "content_payload_key": {"display_name": "Content Payload Key", "advanced": True},
"distance_func": {"display_name": "Distance Function", "advanced": True}, "distance_func": {"display_name": "Distance Function", "advanced": True},
@ -36,7 +36,7 @@ class QdrantComponent(CustomComponent):
def build( def build(
self, self,
embedding: Embeddings, embedding: Embeddings,
documents: List[Document], documents: Optional[Document] = None,
api_key: Optional[str] = None, api_key: Optional[str] = None,
collection_name: Optional[str] = None, collection_name: Optional[str] = None,
content_payload_key: str = "page_content", content_payload_key: str = "page_content",
@ -44,7 +44,7 @@ class QdrantComponent(CustomComponent):
grpc_port: Optional[int] = 6334, grpc_port: Optional[int] = 6334,
host: Optional[str] = None, host: Optional[str] = None,
https: bool = False, https: bool = False,
location: str = ":memory:", location: Optional[str] = None,
metadata_payload_key: str = "metadata", metadata_payload_key: str = "metadata",
path: Optional[str] = None, path: Optional[str] = None,
port: Optional[int] = 6333, port: Optional[int] = 6333,
@ -54,23 +54,50 @@ class QdrantComponent(CustomComponent):
timeout: Optional[float] = None, timeout: Optional[float] = None,
url: Optional[str] = None, url: Optional[str] = None,
) -> Union[VectorStore, Qdrant, BaseRetriever]: ) -> Union[VectorStore, Qdrant, BaseRetriever]:
return Qdrant.from_documents( if documents is None:
documents=documents, from qdrant_client import QdrantClient
embedding=embedding, client = QdrantClient(
api_key=api_key, location=location,
collection_name=collection_name, url=host,
content_payload_key=content_payload_key, port=port,
distance_func=distance_func, grpc_port=grpc_port,
grpc_port=grpc_port, https=https,
host=host, prefix=prefix,
https=https, timeout=timeout,
location=location, prefer_grpc=prefer_grpc,
metadata_payload_key=metadata_payload_key, metadata_payload_key=metadata_payload_key,
path=path, content_payload_key=content_payload_key,
port=port, api_key=api_key,
prefer_grpc=prefer_grpc, collection_name=collection_name,
prefix=prefix, host=host,
search_kwargs=search_kwargs, path=path,
timeout=timeout, )
url=url, vs = Qdrant(client=client,
) collection_name=collection_name,
embeddings=embedding,
search_kwargs=search_kwargs,
distance_func=distance_func,
)
return vs
else:
vs = Qdrant.from_documents(
documents=documents,
embedding=embedding,
api_key=api_key,
collection_name=collection_name,
content_payload_key=content_payload_key,
distance_func=distance_func,
grpc_port=grpc_port,
host=host,
https=https,
location=location,
metadata_payload_key=metadata_payload_key,
path=path,
port=port,
prefer_grpc=prefer_grpc,
prefix=prefix,
search_kwargs=search_kwargs,
timeout=timeout,
url=url,
)
return vs