1. Trained on scientific documents for a comprehensive understanding of technical language and context. 2. Utilizes the RAG model for effective retrieval and generation on top of pre-trained Large Language Models, ensuring accurate and contextually relevant outputs. 3. Employs NextJS and ShadCN Library for seamless processing of scientific documents, enhancing user experience. 4. Versatile compatibility with various file formats (pptx, docx, pdf, latex, csv, epub, ipynb, json) and the ability to handle multiple files. 5. Technology Used: Python, Large Language Models, llama-index, open-ai, NextJs, Flask, and Firebase