📄 中文摘要
在 RAG（检索增强生成）管道中，缓存不仅限于提示缓存，还包括多个关键层次的缓存策略。通过对查询嵌入、文档检索、响应生成等环节的有效缓存，可以显著提高系统的响应速度和效率。具体来说，建议在查询嵌入阶段缓存相似性计算结果，在文档检索中缓存热门文档，以及在响应生成中缓存完整的查询-响应对。此外，利用缓存机制还可以减少重复计算，优化资源使用，从而提升整体性能。这些策略为构建高效的 RAG 系统提供了实用的指导。
超越提示缓存：在 RAG 管道中应缓存的五个内容
出处: Beyond Prompt Caching: 5 More Things You Should Cache in RAG Pipelines
发布: 2026年3月19日
📄 English Summary
Beyond Prompt Caching: 5 More Things You Should Cache in RAG Pipelines
Caching in Retrieval-Augmented Generation (RAG) pipelines extends beyond just prompt caching to encompass several critical layers. Effective caching strategies at various stages, such as query embeddings, document retrieval, and response generation, can significantly enhance system response speed and efficiency. It is recommended to cache similarity computation results at the query embedding stage, cache frequently accessed documents during retrieval, and cache complete query-response pairs in the response generation phase. Additionally, leveraging caching mechanisms can minimize redundant calculations and optimize resource utilization, thereby improving overall performance. These strategies provide practical guidance for building efficient RAG systems.