Boost Your RAG Systems with Semantic Caching

For retrieval-augmented generation (RAG) AI applications, semantic caching offers a powerful optimization to handle repetitive user queries efficiently. This technique involves storing embeddings of previously asked questions along with their answers in a high-speed cache.

How Semantic Caching Works

Instead of following the full RAG pipeline for every query, the system first checks the semantic cache. If a similar question is found based on embedding similarity, it retrieves the corresponding cached answer…