github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-07-04 04:07:54 +00:00
Code Issues Packages Projects Releases Wiki Activity

Add async search with relevance score (#4558)

Browse Source 
Add the async version for the search with relevance score

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
This commit is contained in:
Jiaping(JP) Zhang 2023-05-19 13:05:24 -07:00 committed by GitHub
parent 616e9a93e0
commit 22d844dc07
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 18 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

18
langchain/vectorstores/base.py
View File

@ -166,6 +166,17 @@ class VectorStore(ABC):
"""
raise NotImplementedError
async def asimilarity_search_with_relevance_scores(
self, query: str, k: int = 4, **kwargs: Any
) -> List[Tuple[Document, float]]:
"""Return docs most similar to query."""
# This is a temporary workaround to make the similarity search
# asynchronous. The proper solution is to make the similarity search
# asynchronous in the vector store implementations.
func = partial(self.similarity_search_with_relevance_scores, query, k, **kwargs)
return await asyncio.get_event_loop().run_in_executor(None, func)
async def asimilarity_search(
self, query: str, k: int = 4, **kwargs: Any
) -> List[Document]:
@ -384,6 +395,13 @@ class VectorStoreRetriever(BaseRetriever, BaseModel):
docs = await self.vectorstore.asimilarity_search(
query, **self.search_kwargs
)
elif self.search_type == "similarity_score_threshold":
docs_and_similarities = (
await self.vectorstore.asimilarity_search_with_relevance_scores(
query, **self.search_kwargs
)
)
docs = [doc for doc, _ in docs_and_similarities]
elif self.search_type == "mmr":
docs = await self.vectorstore.amax_marginal_relevance_search(
query, **self.search_kwargs