# TouchGrass AI — An Open-Weight AI That Gets You Off the Screen and Into the Real World

> Source: <https://dev.to/ayush_kasaudhan_01/touchgrass-ai-an-open-weight-ai-that-gets-you-off-the-screen-and-into-the-real-world-3c0d>
> Published: 2026-10-09 11:11:45+00:00

*This is a submission for the [Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass](https://dev.to/challenges/hacktoberfest-week1-2026-10-05)*

I built **TouchGrass AI**, an AI-powered outdoor adventure companion designed to turn screen time into real-world activity.

The idea is simple: instead of keeping users inside an AI chat, the AI gives them a reason to **put the phone down and go outside**.

Users choose how much time they have, their environment, their mood, and what kind of experience they want. TouchGrass AI then generates a personalized outdoor mission, such as exploring nature, taking a short walk, observing plants or birds, or completing a small outdoor challenge.

The website also includes:

The target audience is anyone who spends too much time on screens and needs a simple push to get outside.

The core philosophy is:

**The best AI interaction is the one that gets you to stop using the AI.**

**Live Website:**

[https://ayushkasaudhan957-eng.github.io/TouchGrass-AI/](https://ayushkasaudhan957-eng.github.io/TouchGrass-AI/)

The website is deployed and can be used directly in the browser.

**GitHub Repository:**

[https://github.com/ayushkasaudhan957-eng/TouchGrass-AI](https://github.com/ayushkasaudhan957-eng/TouchGrass-AI)

The complete source code is open and available in the repository.

TouchGrass AI is built around **open-weight AI models** accessed through Hugging Face Inference Providers.

For text generation, I used:

`openai/gpt-oss-120b`)` Qwen/Qwen2.5-VL-3B-Instruct`) for vision-based image analysis
Hugging Face Inference Providers provides access to open models through an OpenAI-compatible chat-completion endpoint, allowing the application to use hosted inference without requiring users to download a local model.

```
User
  ↓
TouchGrass AI Website
  ↓
HTML + CSS + JavaScript
  ↓
Node.js / Express Backend
  ↓
Hugging Face Inference Providers
  ↓
Open-Weight AI Models
  ↓
Personalized Outdoor Mission / Nature Analysis
```

The frontend handles the user experience, mission builder, timer, XP, journal and image upload.

The backend acts as a secure AI proxy so that the Hugging Face API token is not exposed in the browser.

For mission generation, the user's preferences are converted into a structured prompt and sent to the open-weight language model.

For the nature discovery feature, an uploaded image is sent to a vision-language model which analyzes what is visible and provides an AI-generated observation.

I intentionally chose hosted inference instead of requiring users to install Ollama, LM Studio, or download large models. This makes the project much easier to try while still keeping open-weight models at the core of the AI functionality.

Open innovation makes this project possible because the AI layer is not loc