RAGHub and Master-Retrieval-Augmented-Generation-RAG-Systems
About RAGHub
Andrew-Jang/RAGHub
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
This is a living directory of tools, frameworks, and resources for Retrieval-Augmented Generation (RAG). It helps you navigate the rapidly changing landscape of RAG by providing a curated list of new and emerging solutions. You'll find frameworks for building RAG applications, evaluation tools, and data preparation frameworks. Developers and AI engineers who are building or evaluating RAG systems would use this to stay informed and choose appropriate tools.
About Master-Retrieval-Augmented-Generation-RAG-Systems
PacktPublishing/Master-Retrieval-Augmented-Generation-RAG-Systems
This is the code repository for Master Retrieval-Augmented Generation (RAG) Systems, published by Packt Publishing
This course helps AI practitioners, data scientists, and machine learning engineers build and refine AI systems that can provide highly accurate and relevant answers by accessing external knowledge. You'll learn to take a collection of documents and a user's question, then develop a system to find the best information and generate a precise, informed response. It's designed for anyone looking to enhance their AI applications' ability to answer complex queries reliably.
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