I Built an AI Study Assistant for My Friend Using Gemma, React and Render...

I Built an AI Notes Simplifier for My Friend Using Gemma, React and Render

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

What I Built

A friend of mine often struggles with exam preparation because lecture notes can be long and difficult to revise quickly. Reading pages of notes before an exam takes time, and finding the most important concepts is not always easy.

To solve this problem, I built Noteform, an AI-powered study companion that helps students turn lengthy notes into useful study material within seconds.

The application can:

• Generate concise summaries from long notes
• Create important exam-focused questions
• Generate viva questions for oral exam preparation
• Help students revise faster and more effectively

The goal was to make studying less overwhelming and more productive.

Demo

Live Application

https://ai-notes-simplifier.vercel.app/

Backend API

https://ai-notes-simplifier.onrender.com/

GitHub Repository

https://github.com/Banshraj1/ai-notes-simplifier

Screenshots

Home Page

AI Summarization

Important Question Generation

Viva Question Generation

How I Built It

Frontend

• React
• Vite
• Tailwind CSS
• Axios

Backend

• Node.js
• Express.js

AI Stack

• Google Gemma
• Hugging Face Inference API

Deployment

• Vercel (Frontend)
• Render (Backend)

Features

Smart Summaries

Transforms lengthy notes into concise, revision-ready summaries.

Important Questions

Generates exam-focused questions from notes to help students prioritize their revision.

Viva Preparation

Creates viva-style questions that help students practice before oral examinations.

Clean Interface

A simple and distraction-free interface designed around the study workflow.

Why Does Open Innovation Matter?

This project is powered by Gemma, an open AI model, through Hugging Face.

Using an open model gave me more flexibility in how AI is integrated into the application and avoids tying the project entirely to a single proprietary AI provider.

The open approach also makes it easier to experiment with different models and gives the project a path toward self-hosted inference in the future.

For a student-built project, this is especially useful because it lowers the barrier to experimenting with modern AI while keeping the architecture flexible.

Feedback

I shared the application with my friend, who found the Important Questions feature especially useful for quickly identifying what to revise before exams.

Prize Categories

• Build for a Friend
• Best Use of Open Source AI
• Best Use of Render