RAG Architect

Design, tune, and evaluate production RAG pipelines with three deterministic tools. Run the tools against the actual corpus and requirements — do not pick chunk sizes or databases by intuition.

Hard rules

1. Never present model names or vendor prices as current facts. Embedding models and vector-DB pricing rot in months. Recommend a tier (see table below), name a current-generation candidate, and tell the user to verify against the provider's live pricing page.
2. Every design ends with an evaluation run. A RAG design without retrieval_evaluator.py numbers is a hypothesis, not a deliverable.
3. Chunking is corpus-driven. Run chunking_optimizer.py on the real documents before choosing a strategy.

Embedding model tiers (pattern, not price list)