AI API calls are expensive and slow. Redis caching dramatically reduces both by storing AI responses for reuse. Here's a complete implementation guide. Why Cache AI Responses? Without Cache With Cache Every request → AI API Cache hit → Return immediately 1-3s latency per request < 10ms for cache hits Full API cost per request Pay only for cache misses Rate limit pressure Rate limit relief Semantic Caching vs Exact Match `python Exact match caching (simple) cache_key = hash(messages) # Only matches identical prompts Semantic caching (smart) cachekey = generateembeddinghash(userprompt) # Matches similar prompts ` This guide covers exact match caching first, then semantic.…