An extensive set of RAG implementations+many different strategies

What it does

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial. - NirDiamant/RAG_Techniques

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  Turn any website into a knowledge base for LLMs2024 · embedding.io · ▲305

  I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...

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  I started a repo for sharing algorithm implementations2013 · github.com · ▲52

  Everything that would be here is in the README. I hope this gets big, it has tons of potential.

• IB
  I built a browser-based tutorial for learning RAG for LLMs2024 · takehomes.com · ▲25

  Hey all! I wanted to share this project I've been working on that can maybe help you or your developer friends out. I built a RAG system for our product a while back and didn't realize how easy they were to get started. So I put together my learnings into this online course. It's not quite ready but if you sign up and mention HackerNews, I can get you early access. I'm looking to get feedback on the following: (1) materials — is it engaging & did you learn something? (2) UI/UX of the platform — did you have any issues that prevented you from starting or finishing the tutorial? (3)…

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  Ragas – Open-source library for evaluating RAG pipelines2024 · github.com · ▲121

  Ragas is an open-source library for evaluating and testing RAG and other LLM applications. Github: https://docs.ragas.io/en/stable/, docs: https://docs.ragas.io/. Ragas provides you with different sets of metrics and methods like synthetic test data generation to help you evaluate your RAG applications. Ragas started off by scratching our own itch for evaluating our RAG chatbots last year. Problems Ragas can solve - How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? - How do you formulate a test dataset…

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  Cognita – open-source RAG framework for modular applications2024 · github.com · ▲142

  Hey HN, exciting news! Our RAG framework, Cognita (https://github.com/truefoundry/cognita), born from collaborations with diverse enterprises, is now open-source. Currently, it offers seamless integrations with Qdrant and SingleStore. In recent weeks, numerous engineers have explored Cognita, providing invaluable insights and feedback. We deeply appreciate your input and encourage ongoing dialogue (share your thoughts in the comments – let's keep this ‘open source’). While RAG is undoubtedly powerful, the process of building a functional application with it can feel…

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  Demystifying Advanced RAG Pipelines2023 · github.com · ▲131

  I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…

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  Dev tools · 2024 · github.com