This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
Touchgrass.local is a small AI-powered browser app that encourages people to step away from their screens and spend some time outdoors.
Users describe how their day has gone, and an open-weight language model running directly in the browser gives them one small outdoor mission along with a friendly nudge.
Once the mission is completed, the user can mark it as done and watch a field of CSS grass grow. The app also tracks completed missions and streaks using localStorage.
The project is designed to be simple, private, lightweight, and useful for students and anyone who spends too much time in front of a screen.
Demo
🚀 Live Demo:
[Add your deployed GitHub Pages link here]
🤖 Claude Artifact:
https://claude.ai/artifact/RaTCVWFjQi3FrfYGTA213Z
Code
💻 GitHub Repository:
https://github.com/aniruddhapandey01/Touchgrass.local
The repository contains the complete source code and is built using plain HTML, CSS, and JavaScript.
How I Built It
Touchgrass.local uses WebLLM by MLC AI to run an open-weight language model directly inside the browser using WebGPU.
The project supports models including:
Gemma 2 2B
Qwen 2.5 1.5B
Llama 3.2 1B
The application is built with:
HTML — page structure
CSS — UI, themes, animations, and growing grass
JavaScript — model loading, prompting, mission generation, streaks, and local storage
WebLLM — in-browser AI inference
There is no backend and no API key. After the model is downloaded, it is cached by the browser and can work offline. User input stays on the device instead of being sent to a server.
Why Does Open Innovation Matter?
Open innovation makes it possible to build AI applications without depending entirely on closed APIs.
For Touchgrass.local, using open-weight models and WebLLM makes the project more private, accessible, customizable, and transparent. The model runs locally in the browser, so there is no API bill or backend required.
It also makes experimentation easier. Users can switch between different supported models and compare their behaviour.
Most importantly, the project can be shared openly so other developers can learn from it, modify it, add new missions, improve the UI, or contribute new ideas.
My Agent Session
🤖 Claude Artifact / Agent Session:
https://claude.ai/artifact/RaTCVWFjQi3FrfYGTA213Z
Prize Categories
Hacktoberfest Open-Source AI Challenge — Week 1: Touch Grass
Open-Source AI
Local / In-Browser AI
Open-Weight Models
Final Thoughts
Touchgrass.local started with a simple idea:
What if AI could encourage us to spend less time using technology?
Instead of making another app that keeps users on their screens, I wanted to build something that uses AI to give people a reason to step away from the screen and do something in the real world.
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