# 🌱 TouchGrass AI: Stop Scrolling, Start Exploring > Source: > Published: 2026-10-08 16:10:11+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**, a local AI-powered outdoor activity companion designed to help people spend less time on screens and more time in the real world. The idea is simple: **Use AI for a few seconds → get an outdoor mission → put the phone away → go outside. 🌱** The user chooses: TouchGrass AI then uses a locally running AI model to generate a short, practical outdoor mission. For example, a user with 30 minutes who chooses Nature can receive a simple nature exploration challenge with 3–5 steps. The project is designed for anyone who wants a quick reason to walk, explore, observe nature, or spend time outdoors with friends and family. The goal isn't to create another app that keeps users chatting with AI. **The goal is to make the screen the shortest part of the experience.** The project currently runs locally using Streamlit and Ollama. I will include a short screen recording showing: The complete source code is available on GitHub: [https://github.com/Samruddhipathrikar/TouchGrassAI](https://github.com/Samruddhipathrikar/TouchGrassAI) The repository contains the Streamlit application and its dependencies. I built TouchGrass AI using Python, Streamlit, Ollama, and the open-weight **Llama 3.2 3B** model. The user interacts with a simple Streamlit interface. The application collects the user's: These inputs are converted into a prompt for the local Llama 3.2 model. The application sends the prompt to Ollama through its local API: `http://localhost:11434/api/chat` The generated response is then displayed as the user's outdoor mission. ``` text User ↓ Streamlit UI ↓ Time + Activity + Company ↓ Prompt ↓ Ollama Local API ↓ Llama 3.2 3B ↓ Outdoor Mission ↓ 🌱 Go Outside ```