redis-vector-search
Redis Vector Search
Guidance for storing and searching embeddings in Redis. Covers index configuration, algorithm selection, hybrid filtering, and the RAG retrieval pattern with RedisVL.
When to apply
- Defining a
VECTORfield inFT.CREATE(raw RQE) or a RedisVLIndexSchema. - Choosing HNSW vs FLAT and tuning HNSW parameters.
- Adding category, date, or tenant filters to a vector query.
- Building a retrieval-augmented generation (RAG) pipeline on top of Redis.
This skill builds on the redis-query-engine skill — vector fields live inside RQE indexes and share the same FT.CREATE / FT.SEARCH machinery.
1. Configure the vector index properly
Three settings must match the embedding model:
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