WildQuest AI (Touch Grass): On-Device AI Scavenger Hunts That Get You Outside

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

WildQuest AI turns a short walk into a nature-discovery game. Pick a session of 3, 5, or 7 missions (roughly 5-20 minutes), and each mission asks you to find something real outside — a leaf, a flower, bark, the sky. You open your camera, photograph what you found, and an on-device AI model checks whether it's a match. There are no feeds, no streaks, and no accounts — just a short list of reasons to look up from your screen. When the session ends, the app tells you to put the phone away.

It's for anyone who wants a tiny, concrete excuse to step outside: someone on a work break, a parent keeping a kid occupied on a walk, or a remote worker who needs ten real minutes of air between meetings.

Live app: https://touch-grass-sepia-theta.vercel.app/

It's installable as a PWA — add it to your home screen, and after the first visit (which downloads the ~90MB model) it keeps working offline.

GitHub: https://github.com/Gautam5514/Touch-Grass

WildQuest AI turns a short walk into a nature-discovery game. Get a handful of small missions — find a green leaf, a flower, a tree trunk, the sky — photograph what you find, and an open-weight vision model running entirely on your own device checks each photo. When you finish, the app tells you to put the phone away.

Built for the DEV Hacktoberfest Open-Source AI Challenge · Week 1: Touch Grass.

Screenshots use real photos with a stubbed score from the mock-AI test build, so they're deterministic. Real model behavior is covered by tests/e2e/real.spec.ts and docs/EVALUATION.md.