Two students ask 'how do I reset my password' and 'password reset steps' minutes apart. An exact-match cache treats these as unrelated; a semantic cache — matching by embedding similarity, not exact text — serves the cached answer to both.
The threshold decides everything
Set the similarity threshold too low and you save on API calls but occasionally serve last week's answer to a subtly different question. Set it too high and the cache barely fires. Tune it against real near-duplicate pairs from your own logs, not a default.
- Cache the retrieved context and the final answer separately — sometimes only the retrieval step repeats.
- Invalidate on a time-to-live for anything tied to changing data; never cache answers about live numbers indefinitely.
- Log cache hits and periodically spot-check them for correctness, not just for the hit rate.
See LLM cost control and token budgets for where caching fits in a broader cost strategy.
GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems: RAG pipelines, fine-tuned LLMs, hybrid retrieval and multi-modal apps across vision, speech and OCR, architected end to end from ingestion to deployment. Leads engineering for SCULT INDIA's 14-member team, founded the 500+ member TechVerse Enclave community and has mentored 200+ students. Three hackathon first prizes: Changethon 2025 (IIT Roorkee), Product Genesis at Vividhotsava 2025 (CSJMU Kanpur) and BYTEBATTLE (MeetKats).
Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges. Email pranjulrathour41@gmail.com.
