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RAG Architecture Explained: Retrieval-Augmented Generation
RAG gives a language model the right pages to read before it answers. This guide walks through the four stages with a pipeline that runs on a laptop, using open models and public documents, and shows three outcomes: a correct cited answer, a retrieval miss the model admits to, and a question outside the documents.
Retrieval Evaluation: Measuring RAG Quality
You cannot improve a RAG system you have not measured. This guide computes hit rate, MRR and nDCG on 40 real questions, then shows two things most tutorials skip: how wide the uncertainty is on a small test set, and why a retriever that looks better may not be better.