This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
IRL Quest is a gamified real-life mission app built around a simple idea: make getting away from screens feel like a real-life adventure!
The app encourages users to step outside, try small activities, explore their surroundings, and complete real-world challenges. Instead of just scrolling through a screen, users can choose a mission, complete it in real life, earn XP, and unlock achievements.
✨ Key Features
- 🎯 Real-Life Missions: Discover small challenges designed to encourage offline activities.
- 🤖 AI-Generated Missions: Generate new missions using a locally running AI model.
- ⭐ XP & Leveling: Earn experience points by completing missions.
- 🏆 Achievements & Ranks: Track progress and celebrate milestones.
- ⏱️ Mission Timer: Keep track of time spent on a quest.
- 💾 Local Progress: Save progress in the browser using Local Storage.
IRL Quest is for anyone who wants to make everyday activities more engaging, build healthier screen habits, and add a little fun to real life.
The goal is simple: use technology to motivate people to spend more time experiencing the world beyond their screens. 🌱
Code
💻 GitHub Repository:
https://github.com/rudra5002-code/IRL-Quest
The project source code is available on GitHub. Feel free to explore the implementation, share feedback, and suggest improvements!
How I Built It
I built IRL Quest using:
- HTML — app structure
- CSS — styling and layout
- JavaScript — mission logic, XP, achievements, timers, and UI interactions
- Ollama — local inference for AI-generated missions
- Qwen3 4B — the open-weight language model used to generate missions
- Browser Local Storage — saving progress locally
For AI mission generation, the app sends a request to the locally running Ollama API. The model generates a mission in JSON format, which the application validates before displaying it to the user.
Note: AI-generated missions require Ollama and the Qwen3 4B model to be installed locally. Generation speed depends on your computer's hardware. The AI feature may not work until the local setup is complete.
Why Does Open Innovation Matter?
Open innovation matters because it makes AI experimentation more accessible to developers and creators.
By using an open-weight model through Ollama, I could experiment with AI-powered features locally instead of depending entirely on a hosted, closed AI API.
For a project like IRL Quest, the idea is especially meaningful: AI helps create the missions, but the real experience happens away from the screen.
Open tools make it easier to experiment, share what we learn, and build on each other's work. 🌍
🌿 Touch grass. Complete quests. Earn XP. Level up IRL.
Built for the Hacktoberfest Open-Source AI Challenge — Week 1: Touch Grass.
Top comments (0)