video1.0<iframe src="https://www.loom.com/embed/f7bc05facf894e20a204d56be3381571" frameborder="0" width="1728" height="1296" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12961728Loomhttps://www.loom.com12961728https://cdn.loom.com/sessions/thumbnails/f7bc05facf894e20a204d56be3381571-00001.gif157.59999999999997In this video, I introduce our project, which aims to help students learn faster and better using ragged LLM models. We explain how we take input like notion notes and pdfs, extract the semantics, and generate embeddings to create questions for student training. Although we initially planned to create a PWA with NAKJS and implement additional features like setting up meetings and sending reminders, we focused on the PDF part extraction using lemma index and MongoDB Atlas. Join me as I demonstrate how to input a file and showcase the output, including questions for different levels of learning pace.