RAG Evaluation
RAG QA Command Center
Retrieval diagnostics · trace inspection · configuration comparison.
Diagnoses RAG failures through retrieval metrics, trace inspection, configuration comparison, and review-policy simulation.
Problem
RAG systems are hard to trust when retrieval failures, hallucination exposure, and configuration trade-offs are hidden inside raw logs.
Approach
- Turns QA logs and retrieval traces into an operator review flow covering quality posture, retrieval diagnostics, risk slices, configuration comparison, and trace review.
- Uses policy simulation to inspect how review thresholds change workload and quality posture before rollout decisions.
- Exports evidence-style artifacts so RAG quality review can be repeated and shared instead of judged from isolated examples.
Design Decisions & Trade-offs
- Offline evaluation is kept separate from live serving so retrieval, hallucination, configuration, and review-policy changes can be compared reproducibly before rollout.
- Packaged evaluation artifacts are validated fail-fast at startup so incomplete or inconsistent evidence does not silently produce misleading diagnostics.
- The project deliberately favors deterministic, inspectable offline review over live ingestion, production vector infrastructure, authentication, alerting, or incident automation.
Signals & Results
- Evaluation scale: 3,824 offline QA evaluation runs and 93,375 retrieval events.
- Offline review system with data-contract validation, retrieval diagnostics, configuration comparison, trace inspection, policy simulation, evidence exports, Docker, and CI.
- Explicit scope boundary: evaluation workspace over bundled offline artifacts, not a live RAG serving or ingestion platform.