A recent open-source project on GitHub, Get It, offers a new solution for learning from PDF documents. It’s not just a simple text summarizer; instead, it aims to transform static PDFs (like textbooks and research papers) into an interactive, quantifiable learning map, helping users make the deep leap from reading to understanding.
Core Feature: From PDF to Interactive Knowledge Map
Get It’s core feature is the deep analysis of text-based PDF documents. After a user imports a file, the application automatically identifies key concepts in the text and highlights them in the original content. Unlike traditional reading software, clicking on these concepts prompts the system to call an AI model to generate various forms of visual aids, such as 3D scenes, 2D animations, mathematical formula derivations, or function graphs, making abstract knowledge concrete.
At the same time, Get It builds a complete knowledge graph based on the document’s content. This graph visually displays the internal logic and hierarchical relationships between concepts, helping learners build a structured understanding of the knowledge system and quickly identify their weak areas.
Multi-dimensional Interactive Exercises: Beyond Traditional Q&A
To promote active learning and knowledge internalization, Get It integrates four different interactive exercise modes. In addition to the standard ‘Chat’ Q&A function, it provides ‘Flashcards’ for memory consolidation and ‘Quizzes’ (multiple-choice questions) for self-assessment.
A major highlight of the tool is the introduction of ‘Feynman Mode.’ This mode applies the principles of the ‘Feynman Technique,’ requiring the user to explain a concept to the AI in their own words, while the AI acts as a novice who keeps asking follow-up questions. This ‘learn by teaching’ design effectively tests whether the user truly understands the material, guiding them toward deeper thinking and expression.
Gamified Assessment and Quantified Learning Progress
Get It introduces a quantitative assessment system to track user learning progress. After each exercise, the system evaluates the user’s performance on related concepts across four dimensions—memory, comprehension, structure, and application—on a scale of 0 to 100.
This scoring system is designed to only increase, never decrease. This positive feedback gamification strategy aims to encourage continuous learning. Compared to vague progress trackers like ‘read 30 pages today,’ this multi-dimensional, quantifiable feedback provides a more precise and motivating progress indicator for scenarios like exam preparation and research.
Technical Architecture and Data Privacy Considerations
Technically, Get It is a cross-platform desktop application supporting macOS, Windows, and Linux, giving it broad accessibility. Its AI functions rely on the user’s own OpenAI account (via ChatGPT or API Key) and can be integrated using the Codex CLI tool. This design makes it clear that costs and rate limits are determined by the user’s personal account.
The project team emphasizes the importance of data privacy. All processed documents, learning records, and user data are stored locally on the user’s computer, without passing through any of Get It’s proprietary servers, ensuring user data privacy and security. Users should also note that the current version does not yet support scanned or image-only PDFs, and processing very long documents may consume significant time and API credits.
