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Offline AI Study Assistant

Project Overview

Offline AI Study Assistant is a web application that helps students study in a smarter and more efficient way. The main idea of this project is to provide AI-powered features like note summarization, keyword extraction, flashcard generation, and quiz creation without depending on cloud-based AI services.

Instead of sending user data to online servers, the AI will run directly on the user's device. This makes the application faster, more private, and usable even with limited or no internet connection.

I am building this project for OSDHack 2026 under the On-Device AI theme.

Problem Statement

Many students use online AI tools for studying, but these tools require an internet connection and send personal notes or documents to cloud servers. This can create privacy issues and also makes learning difficult in areas with poor internet access.

Proposed Solution

The goal of this project is to develop a simple web application where students can upload their notes or PDF files and get AI-generated summaries, important keywords, flashcards, and quizzes. All the AI processing will happen locally on the user's device instead of using cloud APIs.

Planned Features

  • Upload PDF or text notes
  • AI-generated summary
  • Keyword extraction
  • Flashcard generation
  • Quiz and MCQ generation
  • Simple and user-friendly interface
  • Offline support
  • Privacy-focused On-Device AI

Tech Stack

  • React.js
  • Vite
  • JavaScript
  • Node.js
  • Express.js
  • Transformers.js
  • ONNX Runtime Web

Current Status

This project is currently in the initial development phase.

Completed:

  • Repository created
  • Project structure designed
  • React application setup
  • Basic folder organization

Work in Progress:

  • User Interface
  • AI integration
  • PDF processing
  • Testing

License

This project is licensed under the MIT License.

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An open-source On-Device AI powered study assistant that summarizes notes, generates flashcards, extracts keywords, and creates quizzes locally in the browser for complete privacy.

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