feat(vector): add Elasticsearch backend with hybrid similarity search#164
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vigneshn16 wants to merge 1 commit into
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feat(vector): add Elasticsearch backend with hybrid similarity search#164vigneshn16 wants to merge 1 commit into
vigneshn16 wants to merge 1 commit into
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- Updated factory to support new vector store - Modified document routes to integrate vector logic - Adjusted config settings to support Elasticsearch backend - Updated .gitignore and requirements files accordingly
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Elasticsearch as a vector store backend, enabling hybrid search functionality — combining both semantic vector similarity and text-based scoring. It enhances document retrieval quality, especially when dealing with large documents or unstructured data chunks.
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