StudyBuddy — Your Personal AI Study Partner

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend.

What I Built

I built StudyBuddy, an AI-powered study companion for a friend who spends a lot of time studying from lengthy notes and PDFs and often needs a faster way to understand, revise, and practice the material.

Instead of switching between a PDF reader, a summarizer, a quiz website, and a chatbot, StudyBuddy brings the complete study workflow into one place:

Learn → Summarize → Practice → Ask → Revisit

A student can paste their notes or upload a PDF, and StudyBuddy can:

• Generate a simple and structured summary.
• Create fresh multiple-choice quizzes from the study material.
• Show correct answers and explanations after attempting a quiz.
• Keep quiz history so previous quizzes can be revisited.
• Answer questions using the student's own study notes as context.
• Save study sessions so notes, summaries, quizzes, and history can be revisited later.

The goal was not to build another generic chatbot. I wanted to build something focused on a real study workflow that my friend could actually use when preparing from large amounts of study material.

Demo

Live Demo: [https://hactober-dev-challenge1-1.onrender.com/]

The demo shows the complete flow:

1. Add study notes or upload a PDF.
2. Generate an AI-powered summary.
3. Generate a quiz from the same material.
4. Attempt the quiz and see the score.
5. Review previous quizzes and their correct answers.
6. Ask questions directly from the study notes.
7. Save and revisit the study session.

Code

GitHub Repository: [https://github.com/jeeya8127/Hactober_Dev_challenge1]

The project is organized into a React frontend and an Express/Node.js backend.

The backend handles the API layer, AI integration, PDF text extraction, and MongoDB persistence, while the frontend provides the study workspace and session-based interface.

How I Built It

StudyBuddy is built with:

• React + Vite — frontend
• Node.js + Express — backend
• MongoDB Atlas — persistent storage
• Hugging Face Router — access to open-weight AI models
• OpenAI-compatible SDK — AI integration
• pdf-parse — PDF text extraction

The core AI functionality uses an open-weight model through the Hugging Face OpenAI-compatible router.

The AI is at the core of the application and powers:

• Study note summarization
• Quiz generation
• Question answering

AI Workflow

text
Notes / PDF
     ↓
PDF text extraction
     ↓
StudyBuddy AI
     ↓
 ┌───────────────┐
 │   Summary     │
 ├───────────────┤
 │     Quiz      │
 ├───────────────┤
 │   Q&A Chat    │
 └───────────────┘
     ↓
 MongoDB Atlas
     ↓
Saved Study Session