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lightweight, multilingual AI system to generate educational content

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MasterG 🧑‍🏫

Welcome to MasterG 📚

Project Overview

MasterG is a lightweight, multilingual AI-powered educational platform that generates curriculum-aligned content in 22+ Indian languages. Designed for 100% offline operation with zero reliance on cloud services, MasterG runs efficiently on low-resource devices (4-8GB RAM) without requiring internet connectivity.

🏆 MasterG Won First Place at Eduthon Techfest IIT B 29th Edition 🎉

Tech Stack

Frontend

  • React 19 with TypeScript
  • Vite
  • Tailwind CSS
  • React Router DOM
  • Recharts (Data Visualization)
  • KaTeX (Math Rendering)
  • HTML5 Canvas API

Backend

  • Node.js + Express with TypeScript
  • MongoDB (Local session management)
  • ChromaDB (Local vector embeddings)
  • Tesseract.js (OCR)
  • Ollama (Local AI inference)

Mobile

  • Expo + React Native
  • Expo Router
  • Expo Camera
  • Expo SQLite (Local storage)
  • llama.rn (On-device AI processing)

AI & Machine Learning

  • DeepSeek-R1 1.5B (Local reasoning model)
  • NLLB-200 600M (Local multilingual translation)
  • ChromaDB (Local vector database)
  • Tesseract.js (Local OCR)

Features

  • AI Whiteboard (AI-Board) 📝 - Canvas-based drawing with AI-powered card operations
  • AI Chat Interface 💬 - Document upload with RAG-powered multilingual chat
  • Learning Material Resource (LMR) 📚 - Generate summaries, quizzes, and revision notes
  • Educational Poster Generation 🖼️ - Culturally relevant educational posters
  • Offline Content Generator (Stitch) 🌎 - Real-time multilingual content generation
  • Mobile Application 📱 - Cross-platform offline-capable mobile app

Setup and Installation

  1. Clone this repository:
    git clone https://github.com/ayuxy027/MasterG.git
  2. Install frontend dependencies:
    cd frontend
    npm install
  3. Install backend dependencies:
    cd ../backend
    npm install
  4. Setup Ollama (Required for AI features):
    # Install Ollama from https://ollama.ai
    # Pull required models
    ollama pull deepseek-r1:1.5b
  5. Setup ChromaDB (Required for vector storage):
    # ChromaDB runs locally, no cloud setup needed
    # Follow ChromaDB installation guide
  6. Start backend server:
    cd backend
    npm run dev
  7. Start frontend development server:
    cd frontend
    npm run dev

Note: MasterG is 100% offline and requires no external API keys or cloud services. All AI processing happens locally using Ollama and local models.

Contributing

Contributions are welcomed! 😁
Let's keep the spirit of open source alive!

Important

  • Please follow the project's license terms before redistributing or modifying.
  • Creating something from scratch takes a lot of hard work, and I hope you respect that. 😄
  • If you have any questions or need permission for something specific, feel free to reach out.

Contact

If you have any inquiries or suggestions, please reach out:


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