MohammedAly22/GenQuest-RAG
A Question Generation Application leveraging RAG and Weaviate vector store to be able to retrieve relative contexts and generate a more useful answer-aware questions
This system helps educators, content creators, and researchers automatically generate insightful questions from any given text, pulling in extra context from Wikipedia as needed. You provide a text passage and specify the answer within it, and the system produces multiple relevant questions for that answer. It's designed for anyone looking to quickly create high-quality, contextually rich questions for learning, content development, or research.
No commits in the last 6 months.
Use this if you need to quickly generate accurate and contextually relevant questions from a specific text and its related Wikipedia information, enhancing learning or content creation workflows.
Not ideal if you need questions generated from highly specialized, non-public data that is not available on Wikipedia.
Stars
17
Forks
3
Language
Jupyter Notebook
License
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Last pushed
Feb 03, 2025
Commits (30d)
0
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