Semantic Caching Boosts RAG Efficiency by Reusing Similar Query Results

Semantic caching stores previous RAG query results in memory databases like Redis, allowing semantically similar queries to reuse cached answers without re-querying vector databases or LLMs. This reduces retrieval time, token consumption, and database calls. Cache invalidation strategies must be tailored to data freshness needs.