GreenBuddy

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

What I Built

GreenBuddy is an AI-powered gardening assistant designed to help beginners turn gardening questions into real-world action.

Users can enter their city, available growing space, sunlight conditions, and the plants they want to grow. GreenBuddy generates a personalized gardening plan with practical care tips and an outdoor mission to complete.

The idea is simple: spend less time looking at a screen and more time growing something in the real world

Code

ANILION-CODE / GreenBuddy

GreenBuddy is an AI-powered gardening assistant designed to help beginners turn gardening questions into real-world action. Users can enter their city, available growing space, sunlight conditions, and the plants they want to grow. GreenBuddy generates a personalized gardening plan with practical care tips and an outdoor mission to complete.

How I Built It

GreenBuddy is built with Python and Streamlit, with Hugging Face Inference powering its AI gardening assistant.

The prototype collects basic information about a user's growing environment and sends it to an open-weight language model to generate personalized gardening guidance.

The application is designed to be beginner-friendly, with a simple interface and practical recommendations instead of an unnecessarily complicated setup.

Why Does Open Innovation Matter?

Open innovation makes it possible to experiment with AI without depending entirely on proprietary models or building expensive infrastructure.

By using an open-weight model through hosted inference, GreenBuddy can explore model choice and customization while keeping the application code accessible to other developers.

The project also leaves room for future improvements, including alternative models, local inference, and a gardening journal that users control.

My goal is to make AI useful beyond the screen: helping people learn about plants, spend time outdoors, and build a gardening habit.