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As long as you use a reranker, which we highly recommend, adding hybrid search has very little impact on performance for most use cases. We're not at all opposed to adding support for it, but that's why it hasn't been a high priority for us.
The project looks amazing. Congrats.
One hot topic is hybrid search, aka combining dense vector (from llm embeddings) with sparse vector (from traditional inverted index like bm25).
Is this something you considered testing, and upstreaming if working ?
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