AI generated

Making a study app that runs on a local model, Aula: https://github.com/luumlabs/aula You feed it your slides, notes and old exams (or just type a topic) and it builds a course: short lessons, exercises it grades as you go, flashcards, a mock exam in the shape of the real one, and a spaced schedule until the exam date. It also pulls the material from Canvas / Moodle / Classroom / Blackboard and keeps a calendar with your deadlines. Why local matters here: your slides are often someone else's copyrighted material, and it's your whole semester. Handing that to a cloud API is the annoying part. It points at llama.cpp, Ollama or LM Studio over an OpenAI-compatible endpoint, so with a local model nothing leaves the machine. Against other study apps: the ones I know either start and end at flashcards or have no LMS import at all. Where they're still better: Anki's scheduler and deck ecosystem are far more mature than mine, and Quizlet has a library you can't compete with. My SRS is basic next to Anki. How it was tested: it started as a tool for my wife's degree and most of the fixes come from her using it daily on real coursework. Electron, GH releases, AGPL-3.0. Still early, so I'd rather hear where a small local model falls apart at the tutoring than pretend it's finished.