Beyond Prompt Caching: 5 More Things You Should Cache in RAG Pipelines

The article provides a practical guide to optimizing Retrieval-Augmented Generation (RAG) pipelines through strategic caching at various stages, including query embeddings and full query-response pairs. This approach aims to enhance efficiency by reducing redundant computations and latency, thereby improving the overall performance of RAG systems. Implementing these caching layers enables more scalable and responsive AI applications, especially in scenarios requiring frequent or real-time data retrieval and generation.