Awesome-RAG and Awesome-GraphRAG
These are complementary resources, as the second tool specifically curates resources for graph-based RAG, which is a specialized subfield of the broader RAG applications covered by the first tool, allowing a user to first explore general RAG applications and then deep-dive into graph-based approaches if relevant.
About Awesome-RAG
Danielskry/Awesome-RAG
😎 Awesome list of Retrieval-Augmented Generation (RAG) applications in Generative AI.
This resource map helps AI developers and researchers discover and understand Retrieval-Augmented Generation (RAG) applications. It takes in various tools, frameworks, and techniques for RAG, and provides structured links and explanations to guide the building of sophisticated AI systems. Anyone looking to enhance Large Language Models with external, up-to-date knowledge will find this useful.
About Awesome-GraphRAG
DEEP-PolyU/Awesome-GraphRAG
Awesome-GraphRAG: A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation.
This project compiles a comprehensive list of research and open-source tools related to Graph-based Retrieval-Augmented Generation (GraphRAG). It helps researchers, PhD students, and AI practitioners explore advanced methods for building more accurate and context-aware customized Large Language Models (LLMs). The project categorizes and explains various techniques for organizing knowledge, retrieving information, and integrating it with LLMs, moving beyond traditional text-chunking approaches.
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