Soru.ai

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Inspiration

In college, we constantly faced the challenge of retaining course material effectively. We discovered that flashcards were an ideal solution, but the majority of our notes were handwritten, making the process of creating these flashcards extremely time-consuming. This inspired us to develop a solution that transforms handwritten notes into personalized, digital flashcards effortlessly, optimizing study time and enhancing memory retention.

What it does

Our platform performs two key functions: it reads your notes, regardless of their format, and transforms them into personalized quizzes.

How we built it

We developed our web application with the Reflex Python library for rapid development. We integrated 'trocr' for advanced handwritten recognition and used the Google Gemini API to create dynamic, personalized quizzes.

Challenges we ran into

1. We faced significant Wi-Fi issues due to high attendance
2. Send API requests through Reflex.

Accomplishments that we're proud of

Combining text-recognition model and LLM to bring simple solution for a complex problem.

What we learned

Working with ML Models on Huggingface, sending serverless requests Developing a full-stack application only using Python start your project earlier you should come earlier to the Dinner

What's next for Soru.ai

We aim to enhance Soru.ai by adding features like a customized study roadmap and gamification elements to track progress. We also plan to incorporate multi-sensory learning aids, including audio, to maximize study efficiency.

Built With

• gemini
• huggingface
• python
• reflex
• trocr