TrailQuest AI 🌿 — Less scrolling. More exploring.
I’m working on TrailQuest AI, an outdoor quest companion for the Touch Grass open-source AI challenge.
Choose a Nature Walk, Birdwatching session, Photography Hunt, or Gardening activity. Set your available time and energy level, add an optional interest, and get a short mission with practical tasks and safety reminders. Complete the tasks to earn Trail Points, then put your phone away and enjoy the outdoors.
Why this idea?
Technology can help us start an activity without becoming the activity itself. TrailQuest is designed to make the phone a starting point for curiosity—not something to keep staring at.
Built with
- Python and Flask
- HTML, CSS, and JavaScript
- Browser local storage for Trail Points
- Optional Ollama integration for local open-weight model inference
- Built-in mission library as a fallback when local AI is unavailable
AI status: The current demo uses the built-in mission library unless Ollama is installed, running, and confirmed by the app. Live local AI generation has not been verified.
Links
- Live Demo: https://trailquest-ai.onrender.com
- Source Code: https://github.com/Tasadduque2004/TrailQuest-AI
Outdoor test
I plan to test TrailQuest outdoors and share what I observe after trying it.
This project is released under the MIT License. Contributions and suggestions are welcome.
Top comments (1)
🌿 Excited to share TrailQuest AI!
I built this project to encourage people to spend less time scrolling and more time exploring the outdoors. It combines outdoor quests, practical tasks, safety reminders, and Trail Points to make activities like nature walks and birdwatching more engaging.
The current demo uses a built-in mission library, with optional local AI integration planned for use when Ollama is available and configured.
I’d love to hear your feedback and suggestions! 🌱
🔗 Live Demo: trailquest-ai.onrender.com
💻 GitHub: github.com/Tasadduque2004/TrailQue...
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