Grassroots

Inspiration

Local politics, neighborhood happenings, and small businesses. These things all directly closely impact our lives, and they're right in our backyard — and yet, most people don't bat an eye. We wanted to help make these things more accessible and digestible for everyone.

What it does

Using large-language models, Grassroots synthesizes a variety of sources and viewpoints to show the bigger picture, reducing bias and converging towards the truth.

How we built it

We utilized OpenAI's API for our LLM and AI needs, React for our frontend, Python for our backend, and node.js and Flask to tie it all together.

Challenges we ran into

Scraping large amounts of data (text, images, and links) from the Web was a daunting task, but we managed to utilize the resources given to us well and put together a good solution.

Accomplishments that we're proud of

We're proud of coming this far and learning so much about AI. This was (for some of us) our first hackathon, and we're very proud of having a finished product that met our standards.

What we learned

We learned a lot about the fundamentals of web scraping and LLMs, which will certainly be useful for our future endeavours in research and career work.