Shypd.aiThe largest open index of AI toolsrag-from-scratch is an open-source educational resource that demystifies Retrieval-Augmented Generation (RAG). It provides step-by-step guidance to build RAG systems from scratch using local LLMs, focusing on real understanding of embeddings and vector search.
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rag-from-scratch is an open-source project designed to demystify Retrieval-Augmented Generation (RAG) by guiding developers through building it from scratch. It emphasizes local LLMs and avoids black boxes or cloud APIs, fostering a deep understanding of core RAG concepts. The project covers essential components such as embeddings, local vector database construction, retrieval strategies, and context-augmented generation. It offers step-by-step code walkthroughs, explaining every function and concept, making advanced AI approachable. Key learning areas include how embeddings work, building in-memory and LanceDB/Qdrant vector stores, basic and hybrid retrieval, query preprocessing, multi-query retrieval, and query rewriting. The project aims to provide a clear, practical, and comprehensive learning path for developers interested in RAG.
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