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
Implements answer-aware question generation by fine-tuning T5 models on SQuAD with answer-highlighting tokens, then augmenting generation through semantic retrieval from Wikipedia via Weaviate's vector search. The system uses LangChain to orchestrate the RAG pipeline, combining retrieved contextual passages with an instruction-based prompt format to generate topic-specific, answer-grounded questions evaluated against BLEU, ROUGE, METEOR, and BERTScore metrics.
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Feb 03, 2025
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