qdrant-hybrid-search-prefetches

# Different Searches in One Query API Request Each `prefetch` runs exactly one search per one query. Understand if user wants to run several parallel searches on: 1. The same vector representations but different queries or filters. 2. Different vector representations but the same raw query. If first, help user to design logic of constructing query or/and filters on application side and then check [Combining Searches](../combining-searches/SKILL.md). Don't forget to create [indices on filterable payload fields](https://skills.qdrant.tech/md/documentation/manage-data/indexing/?s=payload-index), immediately after collection creation, prior to building HNSW, so filterable HNSW could be constructed. If second, use [named vectors](https://skills.qdrant.tech/md/documentation/manage-data/vectors/?s=named-vectors), which allow to store multiple vector types per point in one collection. Beware that named vectors currently can be configured only at collection creation. To choose vectors, check following recommendations. ## Missed Keyword Matches Use when: pure vector search misses exact term or keyword matches and you need lexical retrieval alongside semantic search. Most likely you need a sparse vector for exact text search alongside the dense one. Qdrant uses sparse vectors for lexical searches, as [payload filtering doesn't provide any ranking score](https://skills.qdrant.tech/md/documentation/search/text-search/?s=filtering-versus-querying). ### Choose a Sparse Vector for T...