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**Description:** Databricks Vector Search recently added support for hybrid keyword-similarity search. See [usage examples](https://docs.databricks.com/en/generative-ai/create-query-vector-search.html#query-a-vector-search-endpoint) from their documentation. This PR updates the Langchain vectorstore interface for Databricks to enable the user to pass the *query_type* parameter to *similarity_search* to make use of this functionality. By default, there will not be any changes for existing users of this interface. To use the new hybrid search feature, it is now possible to do ```python # ... dvs = DatabricksVectorSearch(index) dvs.similarity_search("my search query", query_type="HYBRID") ``` Or using the retriever: ```python retriever = dvs.as_retriever( search_kwargs={ "query_type": "HYBRID", } ) retriever.invoke("my search query") ``` --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Erick Friis <erick@langchain.dev> |
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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 the Contributing Guide.