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Khazad

Khazad is a transparent semantic cache for LLM API calls that sits at the transport layer and replays semantically equivalent responses from Redis Vector Sets. Developers can add it without changing application code, then reduce repeated upstream calls, lower latency on cache hits, and cut model spend for workloads with recurring prompts or similar conversations. The README emphasizes model-aware and conversation-aware matching, so cached answers are scoped safely by provider/model and full message history rather than only by the last prompt. That makes Khazad a practical infrastructure tool for AI SaaS teams, internal copilots, RAG systems, and high-volume agent workflows where cost control matters. It was discovered through a fresh Show HN LLM query and verified against its official GitHub repository and PyPI-linked documentation.

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