Farmer Feast

Search for any meal, get the ingredients, and find local farmers and markets near you that have what you need. A fresher, more sustainable way to shop and cook whilst giving back to farmers.

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About Farmer Feast

GitHub Repo: https://github.com/aravadhikari05/farmer-feast

Inspiration

We wanted to build something that brought people closer to where their food comes from. With so many of us relying on big grocery chains, it’s easy to forget the fresh, local produce grown right around the corner. We aim to help bring people to farmer's markets, which will help support local farmers whilst providing themselves with fresher, more sustainable foods.

What it does

Farmer Feast connects people to local farmers by making it easier to source fresh ingredients for any meal. You type in a dish you want to cook, and the app returns a list of ingredients — then shows you which nearby farmer's markets and farms have those items. Users can check off ingredients they already have, view farmer bios and market hours, as well as find the closest market to them.

What we Learned

Each one of us decided to work with a tool we hadn't used before. Scraping with Pupeteer and figuring out how to send database requests proved to be a challenge but taught us valuable skills we hope to use in the future. We spent a lot of time perfecting our UI and learned about many useful tools such as Shadcn components and dynamic animations. None of us are UI designers but we tried our hardest creating something that people would want to use and it turned out great!

How we built it

  • Gemini API: Used to convert a meal name into a clean, structured list of ingredients.
  • Puppeteer: Scrapes farmers market websites for product lists, bios, locations, and availability.
  • Supabase: Stores scraped data and allows querying farms/products by ingredient.
  • Next.js + React: Frontend for input, UI rendering, and routing.
  • Vercel: Deployed our full-stack application with serverless API routes.

All of us worked in every part of the stack to gain some experience

A few challenges we ran into

  • Cleaning and matching AI-generated ingredients with scraped data.
  • Avoiding false positives when ingredient names didn’t exactly match product listings.
  • Scraping multiple market sites with different structures and limited data availability.
  • Building a smart UI that’s still easy to use in a short timeframe.

Thinking of a unique idea was the hardest part. We spent many hours brainstorming but finally settled on something we all wanted to work on.

We hope you enjoy this project!

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