Vector search
Vector search yana gano content ta ma'ana maimakon exact words. Ana juya rubutu zuwa high-dimensional embeddings, sannan similarity metric kamar cosine distance yana rank stored vectors bisa kusancinsu da query vector, yana dawo da passages masu alaka ta concept ko da keywords ba su yi match ba.
Kalmomi masu kama: semantic search, similarity search, nearest-neighbor search, embedding search
Vector search yana karfafa semantic retrieval: maimakon matching strings, yana matching meaning. Ana embed query cikin vector space iri daya da indexed content, sannan index ya dawo da vectors mafi kusa bisa distance metric. Domin kasancewa fast at scale, production systems suna amfani da approximate nearest-neighbor indexes da ke karbar kananan accuracy trade-offs don manyan latency wins. Vector search ya fi tasiri idan an hada shi da keyword search a hybrid retriever, don exact identifiers kada su bace cikin pure semantic matching.