🚀 OpenPrep AI

OpenPrep AI is an advanced AI-powered exam preparation platform designed to help students optimize their study habits, analyze previous exam papers, identify knowledge gaps, and study smarter.

Explore Architecture • Getting Started • Contribution Guidelines • API Documentation

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🎯 Problem Statement

Most students waste critical preparation hours trying to figure out:

• What chapters hold the highest exam weightage?
• Which questions are repeatedly asked?
• How to schedule daily study topics effectively?
• Where their weak points lie?

OpenPrep AI resolves these frustrations by utilizing advanced LLMs (Gemini API) and data-driven learning strategies (spaced repetition, adaptive planning) to structure their preparation path automatically.

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✨ Features

• 📄 PDF & Notes Analysis: Extract core themes, chapter summaries, and revision points from academic uploads.
• 📊 PYQ Intelligence: Parse Previous Year Question Papers (PYQs) to map chapter weightage, extract repeated questions, and detect trends.
• 🧠 AI Quiz Generator: Dynamically generate MCQ assessments based on custom uploaded notes or specific syllabus topics.
• 📅 Smart Study Planner: Input your exam date, syllabus scope, and study hours to generate a customized, calendarized study schedule.
• 🎯 Weakness Detection: Tracks performance across quiz attempts to dynamically highlight weak subjects and adapt study goals.
• 📚 Spaced Repetition Flashcards: Memorize complex concepts using flashcards backed by the SuperMemo SM-2 adaptation algorithm.

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🛠️ Tech Stack

Component	Technologies Used
Frontend	React, Vite, Tailwind CSS, Redux Toolkit, React Router
Backend	Node.js, Express.js, JWT Authentication
Database	PostgreSQL, Sequelize ORM
AI Integration	Gemini API (gemini-1.5-flash)
DevOps & CI	Docker, Docker Compose, GitHub Actions

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📂 Project Structure

OpenPrep-AI/
├── .github/             # GitHub actions, templates & labelers
├── backend/             # Node.js + Express backend
│   ├── config/          # Database configuration
│   ├── controllers/     # MVC controller logic
│   ├── middleware/      # Auth, upload, and validation middleware
│   ├── models/          # Sequelize database schemas
│   ├── routes/          # Express API route declarations
│   └── services/        # Gemini API integration service
├── docs/                # Comprehensive system documentation
└── frontend/            # React + Vite + Tailwind CSS frontend
    ├── public/          # Static files and assets
    └── src/
        ├── components/  # Reusable UI components
        ├── context/     # Global contexts (Theme, etc.)
        ├── services/    # Axios API client integrations
        └── store/       # Redux Toolkit global state store

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🚦 Getting Started

For a step-by-step setup guide with environment variable details, review the Setup Guide.

Quick Launch with Docker

If you have Docker installed, you can spin up the frontend, backend, and PostgreSQL instances with a single command:

docker-compose up --build

The React frontend will be available at http://localhost:5173 and the Express API at http://localhost:5000.

Manual Local Launch

1. Clone the Repository:

   git clone https://github.com/yourusername/OpenPrep-AI.git
   cd OpenPrep-AI

2. Setup Backend:

   cd backend
   npm install
   # Copy the environment template to create your own configuration
   cp .env.example .env  # Or "copy .env.example .env" on Windows CMD
   # Open the new .env file and set your own DB_URI, JWT_SECRET, etc.
   npm run dev

3. Setup Frontend:

   cd ../frontend
   npm install
   npm run dev

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🗺️ Roadmap

• v1.0: Core authentication, AI study planners, quiz generators, and analytics dashboards.
• v1.5: Spaced repetition engine, PYQ PDF parser, and attempt history trends.
• v2.0: Weakness-adapted scheduling, community note pools, and OCR processing.
• v3.0: Live study battles, AI chat mentors, and React Native mobile client.

For the comprehensive technical roadmap, review docs/project-roadmap.md.

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🤝 Contributing

We welcome contributions of all levels! Please check the Contributing Guide to understand how to fork the project, set up formatting rules, and make your first Pull Request.

Please also adhere to the community standards in our Code of Conduct.

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📜 License

This project is licensed under the MIT License. See LICENSE for more details.

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❤️ Support

If you love this project, show your support:

• ⭐ Star our repository on GitHub.
• 🍴 Fork it to start contributing.
• 📢 Share it with your classmates and peers!

Built with ❤️ for students worldwide.