RAGHub and HiRAG
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 HiRAG
hhy-huang/HiRAG
[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.
This project helps you get more accurate and comprehensive answers from large language models (LLMs) when querying your specific documents or knowledge base. You provide your textual content, and it processes it to enable a system that understands the hierarchical relationships within your information. The result is a more insightful and detailed response to your questions. This is for data scientists, researchers, or anyone building advanced question-answering systems over their proprietary data.
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