pguso/rag-from-scratch
Demystify RAG by building it from scratch. Local LLMs, no black boxes - real understanding of embeddings, vector search, retrieval, and context-augmented generation.
Implements a modular, JavaScript-based RAG pipeline with progressive learning examples covering embeddings, in-memory vector indexing, and retrieval strategies including hybrid search, multi-query decomposition, and query rewriting with LLM fallbacks. Built entirely with local models (via node-llama-cpp) and includes reusable library components for caching, normalization, and result fusion techniques like reciprocal rank fusion.
1,239 stars. Actively maintained with 3 commits in the last 30 days.
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1,239
Forks
135
Language
JavaScript
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
3
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