AI/dify
1
0
Fork 0
mirror of https://git.mirrors.martin98.com/https://github.com/langgenius/dify.git synced 2025-08-15 11:15:54 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fix the vector retrieval sorting issue (#6431)

Browse Source 
Co-authored-by: weifj <“weifj@tuyuansu.com.cn”>
This commit is contained in:
leoterry 2024-07-18 19:25:41 +08:00 committed by GitHub
parent c0ec40e483
commit dc847ba145
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
3 changed files with 6 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
api/core/rag/datasource/vdb/chroma/chroma_vector.py
View File

@ -111,7 +111,8 @@ class ChromaVector(BaseVector):
metadata=metadata, metadata=metadata,
) )
docs.append(doc) docs.append(doc)
# Sort the documents by score in descending order
docs = sorted(docs, key=lambda x: x.metadata['score'], reverse=True)
return docs return docs
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]: def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:

2
api/core/rag/datasource/vdb/qdrant/qdrant_vector.py
View File

@ -362,6 +362,8 @@ class QdrantVector(BaseVector):
metadata=metadata, metadata=metadata,
) )
docs.append(doc) docs.append(doc)
# Sort the documents by score in descending order
docs = sorted(docs, key=lambda x: x.metadata['score'], reverse=True)
return docs return docs
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]: def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:

3
api/core/rag/datasource/vdb/weaviate/weaviate_vector.py
View File

@ -216,7 +216,8 @@ class WeaviateVector(BaseVector):
if score > score_threshold: if score > score_threshold:
doc.metadata['score'] = score doc.metadata['score'] = score
docs.append(doc) docs.append(doc)
# Sort the documents by score in descending order
docs = sorted(docs, key=lambda x: x.metadata['score'], reverse=True)
return docs return docs
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]: def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]: