What I built
I built AI Study Buddy, a web app that helps students summarize long texts into clear, short versions. It’s designed for anyone who needs quick understanding of study material without wasting time.
The app supports multiple summarization algorithms (LexRank, LSA, Luhn, Edmundson), giving flexibility to students and educators who want different styles of summaries.
It’s deployed on Heroku, making it free and accessible anywhere.
Demo
👉 Live App: https://ai-study-buddy-challenge-10c223d9b0e6.herokuapp.com/
Screenshots:
Category Submission:
Student Success (helps students save time, learn faster, and study smarter).
How I built it
Backend: Flask(Python)
Summarization: sumy library with multiple algorithms
Frontend: HTML, CSS, animations
Deployment: Heroku (using gunicorn, requirements.txt, Procfile)
I used Flask to connect the summarization logic with a clean web interface. Students paste their text, choose summarizer type, and get results instantly.
Challenges I ran into
- Setting up Heroku deployment (requirements.txt, Procfile, dynos).
- Debugging package versions and making sure the app runs the same on Heroku as on my PC.
- Styling the app to make it both useful and enjoyable with animations.
Accomplishments that I’m proud of
- Got the app running live on Heroku 🚀
- Combined multiple summarization algorithms in one place.
- Built a clean, animated UI that feels smooth and modern.
What I learned
- How to deploy Python/Flask apps on Heroku.
- The importance of package management (requirements.txt).
- How different summarization algorithms work.
- What’s next for AI Study Buddy
- Adding support for uploading PDFs and summarizing automatically.
- Integrating AI-powered summaries (transformer-based like BERT or GPT).
- Expanding to multiple languages for international students.
Built with
- Python
- Flask
- Sumy
- HTML
- CSS
- Heroku
🚀 Submission for: Heroku Back to School AI Challenge
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