Study Buddy: a retro AI study companion built for a friend

Study Buddy is a retro-style AI study companion designed to streamline the study process. Created for a friend who had to deal with long notes and exam preparation, Study Buddy consolidates various study tools into one convenient platform. Users can upload study materials, ask questions, generate practice quizzes, develop study plans, and monitor their progress through the application.

The user interface adopts a nostalgic retro aesthetic, aiming to make studying feel more enjoyable rather than overwhelming. One of the main goals is to reduce time spent organizing study materials, allowing users to focus more on actual learning.

Study Buddy was built with a Java backend and a React frontend. The frontend features a retro-inspired design that makes studying more approachable, while the backend, built using Spring Boot, offers REST APIs for the various study features. AI capabilities are powered by Hugging Face Inference Providers, which use open-weight language models to provide AI-assisted study support.

Document processing is handled through Apache PDFBox, enabling the extraction of text from PDF study materials. For storing user data and progress, Study Buddy utilizes browser local storage, eliminating the need for a traditional database.

The application is deployed using Docker and Render, allowing it to be accessed online. The frontend manages the user experience, while the backend takes care of document processing and AI requests. The Hugging Face API token is kept on the backend for security reasons, with the frontend communicating with Spring Boot to make authenticated requests to the model provider.

By integrating various study workflows into a single interface, Study Buddy aims to make AI-powered learning more accessible. Open innovation is crucial for developers to experiment with AI models and improve existing tools. Sharing the code allows others to learn, add features, and adapt the project to their own learning needs.

The author learned a lot while building Study Buddy, gaining insights into full-stack development and the challenges of incorporating AI into applications. Looking ahead, they aim to enhance Study Buddy with personalized revision recommendations, better tracking of weak topics, and additional practice tools to help students create a practical learning routine.