This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
🌿 WildWalk AI — Your AI Guide to the World Outside
I built WildWalk AI, an open-source AI-powered outdoor companion designed to help people spend less time on screens and more time in the real world.
Instead of using AI to keep people chatting with a screen, WildWalk uses AI to create personalized outdoor adventures and encourage users to actually go outside.
A user can tell WildWalk:
"I have 60 minutes free and want to go for a peaceful walk."
WildWalk then creates a personalized outdoor mission based on their available time, interests, and activity level.
For example:
🌳 60-Minute Nature Quest
Distance: 3 km
Difficulty: Easy
Duration: 60 minutes
Your missions:
- Find 3 different types of leaves
- Listen for 2 different bird calls
- Take one interesting photograph
- Find something you've never noticed before
- Spend the final 10 minutes without looking at your phone
WildWalk can also help users explore nature by identifying plants, flowers, birds, and other things they discover outdoors.
After completing an adventure, users can create an AI-generated Adventure Journal containing their experience, discoveries, and observations.
The goal is simple:
Generate the adventure. Put the phone away. Go outside. Touch grass. 🌿
The project is designed for people who want to walk, hike, run, explore nature, practice photography, go birdwatching, garden, or simply spend more intentional time outdoors.
Demo
The demo will show the complete WildWalk experience:
- User enters their available time and preferred outdoor activity.
- WildWalk generates a personalized outdoor adventure.
- The user receives nature challenges and missions.
- The user goes outside and completes the adventure.
- The user can document their discoveries.
- WildWalk generates an Adventure Journal from the experience.
How I Built It
WildWalk is built around open-weight AI, with Gemma serving as the core AI model.
The project is designed so that the AI can run locally using Ollama, allowing the adventure-generation experience to work without depending entirely on a closed cloud AI API.
The planned architecture uses:
- React for the frontend
- Python + FastAPI for the backend
- Gemma as the open-weight AI model
- Ollama for local inference
- MongoDB Atlas for storing adventures and journals
- Render for deployment
- Sentry for monitoring and debugging
- ElevenLabs for optional voice guidance
The AI is responsible for generating personalized outdoor adventures, missions, nature challenges, explanations, and post-adventure journals.
The important part is that the open-weight model isn't just an add-on. It is part of what makes the experience work.
Why Does Open Innovation Matter?
Most AI applications are designed to keep people interacting with technology.
WildWalk takes the opposite approach.
The question behind the project is:
What if AI could help us spend less time with technology?
Using an open-weight model makes this idea more practical because the AI can potentially run locally rather than requiring every interaction to be sent to a closed AI provider.
That provides several advantages:
- 🔒 More control over user data
- 📴 Potential offline functionality
- 💰 Lower running costs
- 🔧 Ability to experiment with different models
- 🧠 Ability to customize the AI experience
- 🌐 Less dependence on a single closed AI provider
For an outdoor application, local AI is especially interesting because users may be hiking, walking, camping, or exploring places with limited connectivity.
The user can prepare their adventure before leaving and take the experience outside with them.
This project demonstrates a different philosophy for AI:
AI shouldn't always make us spend more time online. Sometimes, its job should be to help us log off.
My Agent Session
Prize Categories
Potential categories for WildWalk AI include:
- Gemma — Best Use of Gemma
- Render — Best Use of Render
- MongoDB — Best Use of MongoDB Atlas
- Sentry — Best Use of Sentry Agent Tracing
- ElevenLabs — Best Use of ElevenLabs
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