OutThere: An AI That Gets You Off Your Screen and Outside

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

What I Built

OutThere is a minimalist web application designed to be the "anti-app." Its primary goal is to give users a compelling, AI-powered reason to put their phones down and reconnect with the physical world.
It serves as a bridge between digital convenience and physical exploration. For anyone feeling "screen-locked," OutThere provides real-time, context-aware triggers to go outside—whether it's a personalized "OutThere Moment" based on the time of day, an AI-curated list of nearby parks and gardens tailored to the current weather, or a custom-generated "Outdoor Mission" that turns a simple walk into a small adventure.

Demo

Code

ariba-sayed / OutThere

🌿 OutThere

OutThere is a minimalist web application designed to encourage people to disconnect from their screens and reconnect with the physical world. It uses real-time weather data and AI-powered recommendations to give users a reason to "touch grass."

✨ Features

• Dynamic Home Experience: A personalized greeting and "OutThere Moment" card that changes based on the time of day (Sunrise, Morning, Afternoon, Sunset, Evening, Stargazing).
• Real-time Weather Integration: Fetches current temperature, wind speed, and celestial events (sunrise/sunset) via the Open-Meteo API.
• AI-Powered Explore: Uses Gemma AI to suggest the best nearby places to visit based on current weather conditions.
• Event Discovery: Integrates with Google Search (via SerpApi) to find real-world events happening today, tomorrow, and over the weekend.
• Outdoor Missions: A "Mission Builder" that generates a custom outdoor adventure based on the user's available time and desired mood.
• Direct Navigation: One-click "Get Directions" buttons…

View on GitHub

How I Built It

I built OutThere using a modern full-stack architecture focused on real-time data and open-weight AI:

• AI Core: I used Gemma (google/gemma-4-26B-A4B-it) via the Hugging Face Inference API. Gemma powers two critical features:
  • The Recommendation Engine: It analyzes a list of nearby outdoor locations (fetched via SerpApi) alongside real-time weather data to rank the top 3 best places to visit right now.
  • The Mission Builder: It generates structured, JSON-based "Outdoor Missions" based on the user's available time, budget, and desired mood, ensuring the activities are realistic and encourage physical movement.
• Backend: A Python/Flask server that orchestrates data between the frontend and multiple APIs.
• Frontend: A responsive React application using Lucide-React for a clean, nature-inspired aesthetic.
• External Data:
  • Open-Meteo API for hyper-local weather and celestial events (sunrise/sunset).
  • SerpApi (Google Maps) for discovering actual parks, gardens, and outdoor spaces in the user's vicinity.

Why Does Open Innovation Matter?

Open innovation was central to the "Touch Grass" philosophy of this project. By using an open-weight model like Gemma, I had the flexibility to implement strict JSON output constraints and specific persona-driven prompting (the "Mission Generator") without being locked into the rigid ecosystems or pricing tiers of closed APIs.
Open innovation allows developers to build specialized, lightweight agents that can be fine-tuned or swapped as better models emerge, ensuring that tools designed to "liberate" users from screens aren't themselves built on proprietary "black boxes." It makes the transition from a digital suggestion to a physical action seamless and customizable.

Prize Categories

• Google Gemma — Used Gemma 4 26B as the open-weight AI reasoning layer for recommendations and personalized outdoor missions.
• SerpApi — Used SerpApi to discover real nearby outdoor places and events instead of relying on static or manually entered data.