Practice RAG Retrieval Metrics Offline — A Tiny Stdlib Eval Loop (Synthetic Data)

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This post is a walkthrough of a deliberately tiny retrieval eval loop: synthetic docs + QA gold labels a toy lexical retriever (intentionally dumb) precision@k / recall@k / hit@k printed to the terminal Python stdlib-first — no model weights, no API keys I shipped this as two small paid packs (Lite / Pro) on Payhip. Scores on synthetic data are not business scores. Why start with retrieval metrics (not the generator)? Common misreads: High synthetic scores ≠ production readiness. Tiny fake corpora overfit your toy retriever.

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