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Adds the option for `similarity_score_threshold` when using `MongoDBAtlasVectorSearch` as a vector store retriever. Example use: ``` vector_search = MongoDBAtlasVectorSearch.from_documents(...) qa_retriever = vector_search.as_retriever( search_type="similarity_score_threshold", search_kwargs={ "score_threshold": 0.5, } ) qa = RetrievalQA.from_chain_type( llm=OpenAI(), chain_type="stuff", retriever=qa_retriever, ) docs = qa({"query": "..."}) ``` I've tested this feature locally, using a MongoDB Atlas Cluster with a vector search index. |
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README.md |
🦜️🧑🤝🧑 LangChain Community
Quick Install
pip install langchain-community
What is it?
LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.
For full documentation see the API reference.
📕 Releases & Versioning
langchain-community
is currently on version 0.0.x
All changes will be accompanied by a patch version increase.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see here.