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TL;DR: You’re building a semantic caching system using Spring AI and Redis to improve LLM application performance. Unlike traditional caching that requires exact query matches, semantic caching understands the meaning behind queries and can return cached responses for semantically similar questions. It works by storing query-response pairs as vector embeddings in Redis, allowing your application to…