TIGER-AI-Lab/LongRAG
Official repo for "LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs".
This project helps researchers and developers improve how large language models (LLMs) answer complex questions using external information. It takes a collection of documents (like Wikipedia articles) and user questions, then produces more accurate and comprehensive answers by finding and using longer, more relevant document sections. This is ideal for anyone building advanced question-answering systems.
245 stars. No commits in the last 6 months.
Use this if you are developing AI applications that need to answer detailed questions accurately by drawing information from a large pool of documents, especially when short snippets of text aren't sufficient.
Not ideal if you are looking for a pre-built, production-ready question-answering application rather than a research framework for enhancing RAG systems.
Stars
245
Forks
19
Language
Python
License
MIT
Category
Last pushed
Aug 25, 2024
Commits (30d)
0
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