🌿 NatureQuest AI: Turn Screen Time into Outdoor Adventures

#devchallenge #hf26challenge #opensource #python

Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Submission 🌿

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

What I Built

🌿 NatureQuest AI — Turn Screen Time into Outdoor Adventures

NatureQuest AI is an open-source web app designed to encourage people to step away from their screens and explore the outdoors.

Users select how much free time they have and an activity they enjoy. The app provides outdoor activity inspiration and practical steps for:

🚶 Nature walks
🐦 Birdwatching
🪴 Gardening
📸 Nature photography

The idea is simple: instead of spending every spare moment scrolling, use a little of that time to notice nature, learn about local biodiversity, or care for plants.

I built this project as a beginner developer to explore how open-source AI can support a simple, real-world idea.

Demo

🌐 Try NatureQuest AI:

https://naturequest-ai-drvqjysdphckzxeauycuub.streamlit.app/

Choose your interests, select your available time, and discover an outdoor activity.

Code

💻 GitHub repository:

https://github.com/Neeraja-Pyla/naturequest-ai

The repository includes the Python application, dependency list, setup instructions, and MIT license.

How I Built It

I built NatureQuest AI using:

Python for application logic
Streamlit for the interactive web interface
Hugging Face Transformers to integrate an open-source AI model
Google FLAN-T5 Small to generate activity inspiration
PyTorch to run the model
Git and GitHub for version control and source-code publishing

The app sends a prompt to FLAN-T5 Small based on the user's selected interests and available time. Since small language models can produce repetitive or imperfect responses, I also created predefined activity plans with practical steps and nature-related benefits.

I deployed the app using Streamlit Community Cloud so people can try it without installing Python locally.

One lesson I learned is that integrating AI is only part of the work. A useful application also needs thoughtful prompts, sensible fallback behaviour, and an interface that helps people achieve something in the real world.

Why Does Open Innovation Matter?

Open innovation made it possible for me to experiment with a language model and build a working application without relying entirely on a closed, paid AI API.

Using an open-source model gave me the opportunity to learn how model integration works, experiment with prompts, and understand some of the limitations of AI-generated text.

It also makes the project easier for other developers to inspect, learn from, adapt, and improve. Someone could contribute new outdoor activities, improve the prompts, or add features for local nature exploration.

For a beginner, access to open tools and models lowers the barrier to experimenting with AI and turning an idea into a working project.

My Agent Session

I built and tested this project with AI-assisted development. I have not published a DevRelay agent session for this submission.

Prize Categories

This project focuses on open-source AI and the Touch Grass theme. I am not claiming entry into any partner prize category unless it meets that category's specific requirements.

🌱 Let's turn a little screen time into time outdoors!

What outdoor activity would you add to NatureQuest AI?