rag-from-scratch and production-rag
The "rag-from-scratch" tool, focused on demystifying RAG by building it from the ground up, could serve as an educational complement to "production-rag," which aims to enhance retrieval accuracy with a production-ready system integrating semantic and lexical search, as the former provides the foundational understanding necessary to effectively implement and troubleshoot the advanced features of the latter.
About rag-from-scratch
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.
About production-rag
mahdidjemaci/production-rag
🔍 Enhance retrieval accuracy with a production-ready RAG system that integrates semantic and lexical search for optimal results.
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