Inspiration

We were inspired by how often students struggle with transforming messy lecture notes into something actually useful — flashcards, quizzes, and short study plans. We wanted to build a small but powerful assistant that saves time, reduces stress, and helps people study smarter, not harder.

What it does

StudyBuddy takes any block of text and automatically generates: 🎴 Five clean flashcards ❓ A short multiple-choice quiz 📝 A quick study plan summarizing the most important points

How we built it

We built a lightweight pipeline consisting of:

  1. A minimal backend that receives user input
  2. A prompt-engineered LLM that produces structured study materials
  3. A simple UI that displays flashcards, quizzes, and the study plan clearly Tech stack includes a small API server (FastAPI/Node), an LLM endpoint, and SQLite for minimal state storage. ## Challenges we ran into
  4. Keeping LLM outputs consistent (fixed number of items, correct structure)
  5. Handling extremely long or extremely short notes
  6. Avoiding hallucinated answers in quizzes
  7. Making the UI intuitive under tight time constraints
  8. Balancing simplicity and functionality in a hackathon setting ## Accomplishments that we're proud of
  9. Delivering a fully working MVP in a short time
  10. Creating clean, structured study materials from unstructured text
  11. Building a tool that our teammates already started using during the hackathon
  12. Designing a minimal UI that feels fast and friendly ## What we learned
  13. Better prompt engineering and output validation
  14. How to design an AI tool with real users in mind
  15. Working effectively in a fast, iterative workflow
  16. Using Markdown and LaTeX formatting consistently
  17. Communicating clearly inside a small team ## What's next for InvalidError-01
  18. Adding OCR for handwritten notes
  19. Exporting to PDF and Anki
  20. Personalized analytics and spaced repetition
  21. Gamification (streaks, progress levels)
  22. A mobile-friendly interface

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