NatureMate AI: Touch Grass, Explore More — Bringing Open-Source AI into the Real World

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

What I Built

🌿 NatureMate AI — Touch Grass, Explore More

I built NatureMate AI, an AI-powered outdoor companion that encourages people to spend less time in front of screens and more time exploring the real world.

The idea behind this project is simple: technology should help us experience nature, not keep us glued to our devices.

NatureMate AI helps users discover outdoor activities, generate personalized nature challenges, plan beginner-friendly gardening activities, and maintain a digital journal of their outdoor observations.

Key Features

• 🌱 AI Adventure Generator: Creates personalized outdoor missions based on users' interests, such as bird watching, nature exploration, gardening, and photography.
• 🪴 Smart Garden Planner: Provides gardening suggestions based on the user's region, available space, and experience.
• 🍃 Outdoor Challenges: Encourages users to observe leaves, watch birds, explore clouds, and discover their surroundings.
• 📔 Nature Journal: Allows users to save observations and memories from their outdoor experiences.
• ✅ Challenge Tracker: Tracks completed outdoor activities.
• 🔒 Privacy-Focused AI: Uses a locally running AI model so prompts can be processed on the user's own computer.

NatureMate AI is designed for students, beginners, nature lovers, and anyone looking for simple ways to reconnect with the outdoors.

Demo

🌐 Live Website: https://rishiyadavcreator.github.io/NATURE-MATE/

The website demonstrates the NatureMate interface and its outdoor exploration features.

Note: The GitHub Pages version is a static frontend. Features that require the locally running AI backend need the project to be set up on a computer with Ollama and the selected model installed.

Code

💻 GitHub Repository: https://github.com/rishiyadavcreator/NATURE-MATE

The project is built using HTML, CSS, and JavaScript, with a Node.js backend for connecting to local AI.

The repository contains the website code and project documentation.

How I Built It

I built NatureMate AI using familiar web technologies and an open-weight language model.

Technology stack:

• HTML5: Structures the website and its sections.
• CSS3: Creates the responsive, nature-inspired user interface.
• JavaScript: Handles user interactions, outdoor challenge tracking, journal entries, and AI requests.
• Node.js: Provides the backend for serving the application and forwarding AI requests.
• Ollama: Runs the language model locally.
• Qwen2.5 1.5B: Generates outdoor mission ideas and gardening suggestions.
• Browser LocalStorage: Saves journal entries and challenge progress on the user's device.

How the AI works

1. The user selects an outdoor activity or enters gardening details.
2. JavaScript prepares a prompt based on the user's input.
3. The Node.js backend sends the prompt to Ollama's local API.
4. The locally running Qwen2.5 model generates a response.
5. The response is displayed in the website.

The project is designed so that AI requests can run locally without an external AI API, once the model and required software have been installed.