BrainUp

Inspiration

Each of us have experience with brainrot from insta reels and TikTok

What it does

takes in user instagram data and uses AI to process the data and creates a recommended activity that is given to user so that they can be productive

How we built it

Used ReactJS to build the frontend, AI models: clustering, HDB scan, embedding(MPnet-base v2), frame capturing (blip2-opt-2.7b), key-frame (katna), text gen (mistral), gliner to optimize name entity recomendation, whisper-small. Selenium to scrape web for recommended courses, and flask to build the backend server api.

Challenges we ran into

• rate limit when gathering data from instagram
• overcoming learning curve, using new technologies and frameworks
• Physical challenges, coding for long periods, staying awake and healthy. ## Accomplishments that we're proud of overcoming challenges as a team: I felt that we all worked together really well and when we faced challenges, we worked through them together. having an idea we all liked: We all contributed to brainstorming ideas and found a really unique idea with exciting technologies we wanted to use.

What we learned

For many of us, this is the first hackathon we've ever attended. So being able to manage working in a team. , with various differnt levels of comfort with the tech we were working with and pushing through hurdles was a great learning exerperiance for us

What's next for BrainUp

We've got a ton of tweaks for the proejcts, performace optimzations and such. Supporting more classified websites, and refining the UI

Built With

• flask
• javascript
• llm
• machine-learning
• python
• react