This project is an advanced YouTube + RAG-based academic assistant that transforms educational videos into structured, research-grade knowledge. It automatically extracts YouTube transcripts, generates detailed academic summaries using Gemini, and connects them with relevant concepts from textbooks or academic PDFs using Retrieval-Augmented Generation (RAG).
By leveraging Sentence Transformers, FAISS vector search, and CrossEncoder re-ranking, the system ensures high-quality context matching and produces citation-aware summaries that bridge practical video content with theoretical depth.
Designed for students, educators, and researchers, this tool turns passive watching into active learning—helping users understand, revise, and even generate quizzes from the merged knowledge.
Built With
- python
- streamlit
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