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Sujah Ameer
Sujah Ameer

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SunStride: The Screen-Free Outdoor AI Companion

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

What I Built

SunStride — A screen-free outdoor companion powered by local Gemma 3 1B AI that generates personalized audio briefings in 10 seconds, then encourages you to put your phone away and enjoy nature completely offline.

Problem: Outdoor apps keep you staring at screens checking weather, UV charts, and fitness widgets.

Solution: SunStride takes 10 seconds of input, generates AI-powered guidance, and literally tells you to close the app and go outside screen-free.

Who it's for: Nature lovers, runners, hikers, privacy advocates, and anyone fighting phone addiction.


Demo

🎥 Live App: https://sunstride.onrender.com/

Try it in 90 seconds:

  1. Set: Duration (5-60 mins), Activity (Walk/Run/Garden), UV Level
  2. Click: "🚀 Prepare My Session & Lock Screen"
  3. Listen: AI-generated audio briefing (~30 sec)
  4. Go: Put phone in pocket, enjoy nature screen-free

Example output:

"You're heading out for 20 minutes. The sun's moderate—grab water and reapply sunscreen in 15 minutes. Notice the tree canopies. Phone in your pocket now. Enjoy!"


Code

GitHub logo AslamSujah / sunstride

Screen-Free Outdoor Sunlight & UV Companion | Powered by Local Gemma & Ollama

☀️ SunStride: Screen-Free Outdoor Companion

Submitted for Hacktoberfest Open-Source AI Challenge - Week 1: Touch Grass

SunStride is an offline-first, screen-free outdoor session planner powered by open-weight local AI (Google Gemma via Ollama). Spend less time on screens and more time touching grass.

🌿 The Problem We Solve

Modern health tools keep us glued to vibrant screens:

  • Checking live weather dashboards before outdoor activities
  • Monitoring UV charts while walking
  • Staring at fitness widgets during park visits

SunStride flips the script: You spend 10 seconds preparing on your laptop, then step outside screen-free with audio guidance.

🎯 How It Works

  1. Open SunStride → Set your activity duration, type, and current UV level (10 seconds)
  2. Generate Briefing → Local Gemma model creates a personalized audio script
  3. Hit Play → Listen to the 30-second safety & mindfulness tip
  4. Put Phone Away → Entire outdoor session with zero screen time
  5. Enjoy → Audio reminders…

Repository: github.com/AslamSujah/sunstride

License: MIT | Status: Production-ready on Render

Tech Stack:

  • AI: Google Gemma 3 1B (256 MB, <2s inference)
  • Inference: Ollama (100% local)
  • UI: Streamlit (minimal, distraction-free)
  • Backend: Python 3 + SQLite
  • Audio: espeak-ng / say / pyttsx3 (cross-platform offline TTS)
  • Deploy: Docker + Render

4 dependencies only: streamlit, ollama, pyttsx3, python-dotenv


How I Built It

Architecture

User Input (10s) → Streamlit UI → Ollama Server (Local) → Gemma 3 1B → Text-to-Speech → Audio File → Browser Player → User Goes Outside (100% Offline) → SQLite Journal (Local Logging)

Code

Why Gemma 3 1B?

Aspect Gemma 3 1B Llama 7B Closed API
Size 256 MB ✅ 4 GB ❌ Cloud
Speed <2s ✅ 8-15s ❌ 1-2s
Privacy 100% Local ✅ 100% Local ✅ No ❌
Cost $0 ✅ $0 ✅ 💰💰💰
Safety ⭐⭐⭐⭐⭐ ⭐⭐⭐ ⭐⭐⭐

Gemma won because it's small, fast, safe, and runs locally.

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