Example:

from chromadb import Search, K, Knn, Rrf

Create RRF ranking with text query

hybrid_rank = Rrf( ranks=[ Knn(query="query", return_rank=True, limit=300), Knn(query="query learning applications", key="sparse_embedding") ], weights=[2.0, 1.0], # Dense 2x more important k=60 )

Build complete the search strategy

search = (Search() .where( (K("language") == "en") & (K("year") >= 2020) ) .rank(hybrid_rank) .limit(10) .select(K.DOCUMENT, K.SCORE, "title", "year") )

results = vector_store.hybrid_search(search)