Abeshith/RAG-FundaMentals
🔰 A Comprehensive RAG repository covering basic vanilla RAG techniques, advanced retrieval methods, hybrid search fusion approaches, hands-on reranking techniques with code + explanation 📚✨
This project helps developers and data scientists who are building applications that use large language models (LLMs) to answer questions from custom data. It provides practical examples and code for integrating various information retrieval and generation techniques. You'll put in your own documents (like PDFs or web content) and user questions, and the project shows you how to get back accurate, context-aware answers from an LLM.
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Use this if you are a developer or data scientist looking for hands-on guidance to implement or optimize Retrieval-Augmented Generation (RAG) systems for LLMs using your specific data.
Not ideal if you are looking for a ready-to-use, off-the-shelf RAG application rather than a toolkit for building one.
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Last pushed
Sep 20, 2025
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