wgcyeo/UniversalRAG
UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities
This framework helps AI developers build advanced Retrieval-Augmented Generation (RAG) systems capable of searching across various data types like text, images, and videos. It takes diverse data corpora and user queries, then intelligently directs each query to the most relevant data source, providing a more accurate and nuanced context for generative AI models. AI researchers and machine learning engineers who are building next-generation AI applications will find this valuable.
161 stars. No commits in the last 6 months.
Use this if you are building an RAG system and need to accurately retrieve information from a complex mix of text, images, and videos to provide context for a large language model.
Not ideal if you are a business user looking for a no-code solution or only dealing with simple text-based data for your RAG applications.
Stars
161
Forks
10
Language
Python
License
Apache-2.0
Category
Last pushed
May 21, 2025
Commits (30d)
0
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