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LLM Apps in Production (RAG + Vector DB + Caching) · Lesson

Semantic Caching for LLM Responses

Learn how semantic caching reuses answers for similar queries by matching on meaning rather than exact text, cutting LLM cost and latency dramatically.

Beyond Exact-Match Caching

A normal cache only hits when the key is byte-identical. But 'What is your refund policy?' and 'How do refunds work?' mean the same thing yet miss an exact cache.

Semantic caching matches on meaning, so paraphrases reuse the same answer.

How It Works

The flow:

  • Embed the incoming query into a vector
  • Search the cache for a near-by stored query
  • If similarity exceeds a threshold, return the cached answer
  • Otherwise call the LLM and store the new pair

All lessons in this course

  1. Distributed Caching with Redis/Memcached
  2. Session Management and Context Persistence
  3. Advanced Cache Invalidation Strategies
  4. Semantic Caching for LLM Responses
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