Quizzer Transforms PDFs Into Interactive Study Courses
Quizzer transforms static PDF documents into interactive, terminal-based study courses. Users drop a textbook, manual, or lecture notes into the tool, and it automatically generates practice questions for active recall.
Created by suncloudsmoon, this project addresses the limitations of standard text extraction by treating each page as a visual context window. Professionals and learners who prefer local control over their study materials can run the entire workflow without sending data to external servers.
Interactive terminal study engine
- Converts PDFs into structured courses with seven distinct question formats.
- Applies the SM-2 spaced repetition algorithm to schedule timely reviews.
- Adjusts question difficulty automatically based on recent performance.
- Provides an integrated terminal chat for immediate tutor feedback.
- Tracks progress through experience points, streaks, and linear lesson unlocks.
- Accepts any OpenAI-compatible local or remote model for inference.
Students mastering dense technical manuals and independent professionals retaining certification material will benefit most from this workflow. The combination of progressive recall exercises and targeted feedback replaces passive reading with measurable skill building.
Creator notes on performance and design
The system processes each document page by converting it to an image before passing it to the vision model, a deliberate choice to bypass optical character recognition errors. This approach preserves diagrams, charts, and layout cues that standard text extractors frequently miss.
Generating complete courses does demand patience, with longer textbooks requiring up to twelve hours to process depending on available computing resources.
"The issue is that this misses many details that can only be found if I actually look at the PDF page itself,"
said the developer in a post.
You can download quizzer directly from GitHub to start building your own study modules today.
