RAG-ception is designed to help researchers stay current with the fast-moving field of Retrieval-Augmented Generation (RAG). Since dozens of new RAG papers appear on arXiv every week, manually tracking them is inefficient and time consuming. Our system automates the entire workflow. From discovering new papers, extracting and organizing their content, generating structured summaries, enabling semantic search through an intuitive web interface. The tool primarily targets researchers, graduate students, and practitioners who need a reliable way to keep up with emerging RAG literature.
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Install the requirements
$ pip install -r requirements.txt -
Run the app
$ streamlit run app.py