This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
Touch Grass Quest is an AI adventure planner that gets you off the screen and into the world. I'm a student and I spend most of my day on a laptop and phone, so I wanted something that makes going outside feel like a small game.
You tell it where you are, the landmarks you know nearby, how much time you have, your energy, the weather and what you enjoy. Then it:
- suggests outdoor activities
- makes a short walking route (using only the landmarks you named)
- lists things to look for while you are outside
- creates an offline adventure checklist
- lets you record notes and photos
- writes a small Adventure Journal after your walk, using only your own notes
It is for students and anyone who wants a small reason to step outside.
My first real walk: I used Touch Grass Quest to plan a walk, then went to the ground near my home and spent time outside enjoying nature. It was a very beautiful experience, and a nice break from my laptop and phone. Afterwards I wrote my notes in the app for my Adventure Journal.
Demo
Video: https://youtu.be/AEHpszJ6AUc
Try it on a laptop with Chrome or Edge: https://saurabhh-cloud.github.io/touch-grass-quest/
The first load downloads the AI model once (about 1.5 GB). If you only want to see how it looks, click "Try a sample plan (no AI)". That sample is ready-made and not written by the AI.
![Touch Grass Quest plan and checklist]
Code
https://github.com/saurabhh-cloud/touch-grass-quest
How I Built It
It is one HTML file with no backend. It uses WebLLM to run Google's open-weight Gemma 2 2B model directly in the browser on the user's GPU. You can also switch to Qwen 2.5 or Llama 3.2 in a dropdown.
A few choices came from the "touch grass" idea:
- The AI model cannot run on a phone, but people carry phones outside. So you plan on a laptop, then download an offline card (a small HTML file with your plan, checklist and notes box) and open it on your phone with no internet.
- A small AI model can invent places. The prompt tells it to use only the landmarks you list and not to make up streets or shops.
- A small AI model can also invent details in the journal. After it writes the journal, a simple word check highlights any word that is not in your own notes, so you can edit or delete it. It is a simple check, not a guarantee, so I still recommend reading the journal once.
- There is also a basic journal option that works without the AI, and a safety reminder under the plan.
I'm a first-year Maths student learning HTML, CSS, JavaScript and Python. I built this with the help of an AI coding assistant (Claude) and tested the app myself.
Why Does Open Innovation Matter?
- Privacy: A planner like this needs to know where you walk. Because the model runs on your own device, your location, notes and photos never go to a server I don't control.
- Works offline: After the one-time download the model is cached, and the offline card works with no signal, which suits parks and trails.
- Free: There is no API key or subscription, so anyone can use it.
- Swappable: With open weights I can switch between Gemma, Qwen and Llama and change how the guide behaves by editing the prompt. A closed API would not let me do that.
My Agent Session
I built the first version with Claude, an AI coding assistant. I did not record the session with DevRelay.
Prize Categories
Best Use of Gemma: the app runs Google's Gemma 2 2B locally in the browser.
Top comments (1)
Thanks for reading! 🌿 A few quick notes:
I would love feedback on the plan and journal quality, or ideas for making the app better.