This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle
What I Built
OpenStudy AI — Your AI-Powered Study Companion 📚
OpenStudy AI is a web-based study assistant designed to help students understand difficult concepts, prepare for exams, and revise topics.
Students can choose how they want a topic explained instead of receiving only one style of answer.
Current features:
- Simple Explanation: Understand concepts in beginner-friendly language.
- Exam Answer: Generate structured, exam-oriented responses.
- Step-by-Step: Break a problem into manageable steps.
- Quick Summary: Create concise revision notes.
- AI Question Answering: Ask study questions and receive AI-generated responses.
Who could pay for it?
School students, college students, and independent learners who need affordable academic support could benefit from OpenStudy AI. In the future, it could offer personalized revision plans, quizzes, and other premium learning tools.
This is currently a student-built prototype. I am looking for feedback from real users to improve it.
Demo
🎥 Demo Video: [Watch OpenStudy AI in action]https://youtu.be/CcKaaNCAkCg
💻 GitHub Repository: https://github.com/dhinesh-babu-7/OpenStudy-AI
Live demo: The application currently runs locally and is not yet publicly deployed.
Code
The source code for OpenStudy AI is available on GitHub:
https://github.com/dhinesh-babu-7/OpenStudy-AI
The project uses a React and Vite frontend with a Node.js and Express backend.
How I Built It
I built OpenStudy AI using:
- React + Vite for the frontend.
- Node.js + Express for the backend.
- OpenRouter to access a hosted AI model.
- Git and GitHub for version control and source-code hosting.
When a student submits a question and selects a study mode, the frontend sends the request to the backend. The backend communicates with the configured AI model and returns the generated answer.
I built this project to learn how to integrate AI into a practical web application while keeping API credentials on the server rather than exposing them in the frontend.
AI model: NVIDIA Nemotron 3 Super, accessed through OpenRouter using nvidia/nemotron-3-super-120b-a12b:free.
The model is open-weight and is released under the NVIDIA Nemotron Open Model License. I chose it to make the AI component of OpenStudy AI more transparent and to explore the use of open models in affordable educational tools.
The application currently uses hosted inference through OpenRouter; it does not run the model locally. The free endpoint may have usage limits, and I will need to review the model license and provider terms as the project develops.
Model information: https://openrouter.ai/nvidia/nemotron-3-super-120b-a12b:free
Why Does Open Innovation Matter?
Open innovation gives student developers opportunities to experiment, learn, and build useful tools without needing to train a large AI model from scratch.
For OpenStudy AI, accessible development tools and AI infrastructure helped me turn an idea into a working prototype. Open-source frameworks also made it possible to build and connect the frontend, backend, and AI integration.
My next goal is to explore model customization, compare open models, and investigate the possibility of local inference.
I believe useful learning tools should become more accessible to students. By building and improving projects in public, developers can share what they learn and benefit from feedback from the wider community.
My next goals are to explore:
- AI-generated quizzes and revision flashcards.
- Personalized study plans.
- Asking questions about uploaded study notes.
- Feedback from students who try the application.
- An open-weight AI model that fits the project's needs.
OpenStudy AI is my first step toward building a practical study companion that students can use in their everyday learning.
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