RAG QA Cache and FAQ Generation
Extract common questions, add a QA cache layer, and publish curated FAQs on top of RAG systems.
The Problem
Most RAG systems treat every user query as new. In practice:
Without an explicit QA layer, RAG systems cannot distinguish between known questions and open-ended queries.
Two Complementary Notebooks
This use case is implemented through two connected notebooks, each addressing a different part of the problem.
Notebook 1 — RAG QA Cache
Focuses on capturing and reusing known questions.
Extract common questions
From logs or datasets.
Cluster & deduplicate
Semantically similar questions.
Evaluate quality
Consistency and correctness checks.
Store as cache
Reusable QA pairs.
Outcome: Reduced latency, lower cost, consistent answers, clear known/unknown boundary.
Notebook 2 — FAQ Generation
Builds on curated questions to generate publishable FAQs.
Select representative questions
High-quality, commonly asked.
Generate user-facing answers
Clear and polished responses.
Structured FAQ set
Aligned with real usage patterns.
FAQs are: Grounded in actual questions, consistent with system behavior, easy to maintain.
Why This Matters
Combining QA caching and FAQ generation turns RAG from a purely reactive system into a question-aware system. You gain: