Josephine Bouwens (21) uit Knokke-Heist studeerde toegepaste informatica aan Hogeschool PXL en ontwikkelde een StudyBuddy voor kinderen met dyslexie en dysfasie. Het gaat om een chatbot die niet voorzegt, maar vragen stelt, luistert en feedback geeft op je eigen cursus. The...

Studente toegepaste informatica Josephine Bouwens uit Knokke ontwikkelde voor haar bachelorproef aan Hogeschool PXL in Hasselt een chatbot waarmee leerlingen met een taalstoornis hun leerstof kunnen i...

StudyBuddy is an AI-powered learning assistant designed to help students learn smarter through personalized academic support. Built with React, AWS Lambda, Amazon Bedrock, and DynamoDB, it demonstrates how generative AI and cloud technologies can create an interactive, scalable learning experience.

# I Built StudyBuddy AI: An Open-Source Study Assistant for Students Using Ollama and Llama 3 _This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend._ ## What I Built I built **StudyBuddy AI** , an AI-powered study assistant designed for students like me and my classmates. A friend mentioned that preparing for exams often takes longer than studying itself. Students spend hours creating summaries, flashcards, and quizzes from lecture notes. To solve that problem, I created StudyBuddy AI. The application transforms notes into: * Summaries * Quizzes * Flashcards * Personalized study plans using open-source AI running locally. ## Demo ### Live Application https://symmetrical-waddle-7j79j569w74364g-8501.app.github.dev/ ### GitHub Repository https://github.com/psanogo/studybuddy-ai ## Features ✅ Note Summarization ✅ Quiz Generation ✅ Flashcard Creation ✅ Personalized Study Plans ✅ Local AI Processing with Ollama ✅ Student-Friendly Interface ## Code Repository: https://github.com/psanogo/studybuddy-ai ## How I Built It ### Tech Stack * Python * Streamlit * Ollama * Llama 3 * SQLite * GitHub ### Architecture Student Notes ↓ Streamlit UI ↓ Ollama ↓ Llama 3 ↓ Summaries | Quizzes | Flashcards | Study Plans The application uses Ollama to run open-source AI models locally while Streamlit provides an easy-to-use interface for students. ## Why Does Open Innovation Matter? Open innovation made this project possible. Using open-source AI allows: * Student data to remain private * Local model execution * Lower development costs * Full transparency and customization * Learning without relying on expensive proprietary APIs Because the models are open, anyone can improve, customize, and learn from the technology. For students, that means accessible AI-powered learning tools. ## What I Learned Building StudyBuddy AI helped me learn: * AI application development * Prompt engineering * Local LLM deployment * Streamlit development * GitHub project management Most importantly, I learned that a small project can create meaningful impact when it solves a real problem. ## Future Roadmap * [ ] PDF Upload Support * [ ] Voice Notes * [ ] Multi-Language Support * [ ] Exam Readiness Scoring * [ ] Syllabus-to-Semester Planner * [ ] Mobile Optimization ## Feedback After seeing the project, one classmate said: > "I wish I had this before my last exam." That feedback confirmed that this project addresses a real student need. ## Why This Fits the Challenge StudyBuddy AI was built to help fellow students spend less time preparing study materials and more time learning. It uses open-source AI at its core, runs locally with Ollama, protects user privacy, and solves a real educational challenge. Thank you for reading!