WILDQUEST-Touch the grass

#devchallenge #hf26challenge

WildQuest: An AI That Gets You Outside Instead of Keeping You Scrolling

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

What I Built

We spend a lot of time staring at screens, even when we want to take a break and go outside. But sometimes, the hardest part of going outdoors is figuring out what to do.

That's why I built WildQuest — an AI-powered outdoor adventure generator that turns a simple walk outside into a fun, interactive quest.

Instead of endlessly scrolling for things to do, you can generate your own outdoor adventure based on your interests, surroundings, and available time.

What can you do with WildQuest?

Generate personalized outdoor quests with exactly 3 quests and 3 tasks per quest.
Explore nature, discover your surroundings, and try activities tailored to your interests.
Customize your adventure based on how much time you have.
Complete tasks interactively and track your progress.
Record your experiences in a Field Journal.
Explore responsibly with safety-focused nature activities.

WildQuest is designed for anyone who wants to take a break from their screen, get moving, and make their time outdoors a little more interesting.

The idea is simple: use AI to help people spend less time on screens and more time experiencing the real world.

Demo

Try WildQuest live:

https://wild-quest-4auzlw2dk-devansh-55f9.vercel.app/

Generate a quest, head outside, complete the challenges, and track your progress!

Code

GitHub repository:

https://github.com/Devansh270/WildQuest

The project is open source, and you can explore the implementation, run it locally, or contribute improvements.

How I Built It

I built WildQuest with a React frontend and a Python FastAPI backend, with Google's Gemini model powering the quest-generation experience.

Here's the tech stack:

Frontend: React, Vite, JavaScript, and CSS.
Backend: Python and FastAPI.
AI: Google Gemini through the google-genai SDK.
Deployment: Vercel for the frontend and Render for the backend.

The frontend lets users customize their adventures, interact with generated tasks, and track their progress. The FastAPI backend handles quest-generation requests and communicates with Gemini to generate structured outdoor activities.

I also implemented API health checks, configured cross-origin requests between the deployed frontend and backend, and kept the AI API key in environment variables rather than exposing it in the frontend.

One of the important design decisions was to make the output actionable rather than simply generating a paragraph of suggestions. WildQuest returns structured quests with individual tasks that users can complete and track.

Why Does Open Innovation Matter?

I wanted to build something that wasn't just another AI chatbot wrapped in a website.

Open innovation makes it possible for developers to experiment, learn from existing tools, share their work, and build applications that others can inspect and improve.

For WildQuest, open-source development means that anyone can explore how the application works, suggest new quest types, improve the user experience, or contribute features of their own.

Using an accessible AI development stack also made it practical for me to connect a modern generative model to a small, independently built application without needing to train a model from scratch.

A closed API can provide powerful AI capabilities, but the openness of the surrounding project matters too: people should be able to understand the application, inspect its implementation, and help shape what it becomes.

I'd love to see WildQuest grow through contributions from people who care about outdoor exploration, gamification, and building useful AI-powered tools.