AutoStudy AI — Interactive Flashcards & UI/UX Polish

Today I expanded AutoStudy AI’s study pipeline by introducing AI-generated flashcards with an interactive flip-card interface, alongside a cleaner and more polished user experience.

What works

AI Flashcard Generation: Integrated structured JSON generation via local Qwen2.5:3b (Ollama) to automatically parse PDF text into 5–8 study flashcards (Questions & Answers).
Interactive Flashcard Viewer: Built a smooth, 3D CSS-flipped card component allowing users to click to reveal answers and navigate seamlessly through their study deck.
Safe State & JSON Parsing: Implemented robust backend cleaning and frontend IIFE scoping to securely pass and render dynamic JSON datasets without client-side conflicts.
UI/UX Overhaul: Upgraded the visual hierarchy with modern card containers, responsive controls, clear progress counters (Card X of Y), and sleek loading animations during document processing.

Why this matters

AutoStudy AI is evolving from a basic text extractor into a true, active-recall study tool. By combining local AI intelligence with interactive flashcards, users can now test their knowledge directly from their study materials while maintaining 100% data privacy and offline capability.

Tech stack

Flask (Python backend)
Ollama (Qwen2.5:3b for local structured JSON extraction)
PyMuPDF (PDF text processing)
Vanilla HTML5, CSS3 (3D transforms & transitions), & JavaScript (IIFE modules)

Next step

Implement custom study tool selection on the homepage (allowing users to choose between summaries, flashcards, or AI assistants per upload) and build a history sidebar for quick access to past documents.

Second milestone achieved: active recall study workflows are now fully operational offline. 🚀