This repository is a curated collection of resources for building applications leveraging the Retrieval-Augmented Generation (RAG) pattern with Large Language Models (LLMs). It targets engineers, researchers, and practitioners seeking comprehensive information on RAG techniques, tools, and applications, aiming to accelerate development and understanding in this rapidly evolving field.

How It Works

The project acts as a knowledge hub, categorizing and linking to a vast array of academic papers, open-source tools, frameworks, and practical guides related to RAG. It covers the entire RAG lifecycle, from data preprocessing and query optimization to retrieval strategies, re-ranking, evaluation, and deployment. The organization by topic and the inclusion of recent research papers provide a structured approach to understanding and implementing advanced RAG solutions.

Quick Start & Requirements

This repository is a curated list of resources, not a runnable application. It requires no installation but relies on external links to various tools and papers.

Highlighted Details

• Extensive categorization of RAG components: preprocessing, retrieval strategies, re-ranking, evaluation, security, prompting, and more.
• Regularly updated with recent research papers (as of January 2025), providing insights into the latest advancements.
• Includes links to numerous open-source tools and frameworks for building RAG applications (e.g., LangChain, LlamaIndex, QAnything, RAGFlow).
• Features practical application examples, enterprise practices, and case studies from companies like Bilibili, Hello Chuxing, and JD.

Maintenance & Community

The repository was last updated on January 2, 2025, indicating active curation. It links to various community resources and projects, suggesting a broad ecosystem of contributors and users.

Licensing & Compatibility

The licensing of individual linked resources varies. This repository itself does not impose specific licensing restrictions beyond those of the linked content.

Limitations & Caveats

As a curated list, the repository does not provide direct functionality. Users must navigate external links to access tools and papers, and the quality and maintenance of those external resources are beyond the scope of this repository.