This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass.
What I Built
GullyGames is an AI-powered app that creates short, collaborative outdoor games for friends, students, and community groups.
Users choose their environment, group size, available time, and preferred activity style. GullyGames generates a structured activity designed to encourage real-world interaction and reduce unnecessary screen time.
Demo
Code
GitHub repository — Gully-Games
How I Built It
I built GullyGames using Google AI Studio Build mode, React, TypeScript, and a Node.js/Express backend.
The application uses Google's open-weight Gemma 4 model through a server-side API integration to generate outdoor activities. It includes an activity setup flow, timed instructions, a distraction-free Pocket Mode, and local session history.
Why Does Open Innovation Matter?
Open-weight models give developers more flexibility to inspect, adapt, and experiment with AI models rather than depending entirely on a closed model ecosystem.
GullyGames keeps its model integration modular so that alternative inference setups can be explored as the project develops. The current version uses hosted inference, so it requires an internet connection for AI generation; it does not claim that model inference runs locally.
By keeping the experience lightweight and using browser-based storage for session history, the project can stay simple while leaving room for future improvements.
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