This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady
What I Built
I built StudyEase AI, an AI-powered study assistant that helps students revise their notes more easily.
Students can use it to turn study notes into:
- 📚 Easy-to-understand summaries
- ✨ Key revision points
- ❓ Practice questions for self-testing
The goal is to make studying and revision simpler, faster, and less overwhelming.
Demo
🎥 Watch the demo: https://youtu.be/iBl5yhgl6xI
Code
💻 GitHub Repository: https://github.com/Rehu33/studyease-ai
How I Built It
I built StudyEase AI using Python, Streamlit, Ollama, and Gemma 3 1B.
The app uses Gemma 3 1B through Ollama to process study notes and generate summaries, revision points, and practice questions. Streamlit provides the user interface, making the tool easy to use.
By running the model locally with Ollama, the project explores how open-weight AI can power a useful study tool without depending entirely on a hosted AI API.
Why Does Open Innovation Matter?
Open innovation makes AI more accessible to students and developers who want to experiment, learn, and build useful tools.
Using an open-weight model like Gemma 3 1B with Ollama gave me the opportunity to explore local AI inference and build a practical application around it. This approach can reduce reliance on paid, closed AI APIs and offers more control over how the model is used.
StudyEase AI is my small contribution toward making AI-powered learning tools more accessible and customizable.
The Lazy Payoff
Instead of manually creating summaries, revision points, and practice questions separately, students can generate these study materials from their notes with the help of AI.
This can reduce repetitive preparation work and leave more time for reviewing concepts and practicing questions.
Prize Categories
My project focuses on open-source AI and productivity.
Thanks for checking out StudyEase AI! Feedback and contributions are welcome. 🚀
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