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TouchQuest: The Anti Doomscroll AI Companion

#devchallenge #hf26challenge

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

Modern apps and algorithmic feeds are engineered for infinite retention: notifications, autoplay loops, and endless dopamine scrolls keep us locked inside, staring at glass screens.

TouchQuest flips the paradigm. Instead of keeping you glued to a feed, TouchQuest gives you a structured reason to step outside, pocket your device, and engage your senses with the real living world.

Designed mobile-first with an earthy forest aesthetic (forest greens, warm cream, muted sage), TouchQuest serves outdoor enthusiasts, students, remote workers, and anyone looking to break screen fatigue through micro-adventures:

  1. AI Outdoor Mission Generator: Generates focused, sensory-grounded quests for 15, 30, or 60 minutes based on your local terrain (urban park, forest trail, backyard, or riverbank). Each mission guides your physical attention—listening for wind shear in tree canopies, feeling bark texture, or hunting sunlight patterns—with explicit reminders to keep your phone in your pocket between milestones.
  2. Nature Scanner: A multimodal open-weight vision scanner. Capture or upload a specimen photo to identify wild plants, trees, fungi, and natural organisms with scientific taxonomy and field observation tips.
  3. BirdCall AI: A dedicated bioacoustics classifier interface for recording avian songs and identifying species vocalizations in the field.
  4. Explore Nearby (Privacy-Preserving Cartography): An interactive map built with Leaflet + OpenStreetMap that queries real public green spaces, botanical sanctuaries, and wetlands via the Overpass API. It calculates real-time walking distances and features a 1-tap "Start Quest Here" launcher with zero surveillance advertising or location tracking sold.
  5. Field Nature Journal & Auth: A personal field notebook powered by Supabase Auth & PostgreSQL Row-Level Security (plus a resilient offline Guest mode). It tracks cumulative minutes spent offline, logs sensory reflections, and preserves biodiversity sightings.

Demo

  • Live Application: https://touchquest.vercel.app
  • Features to try live:
    • Launch a 15-minute sensory quest on the Missions tab.
    • Explore nearby parks and nature reserves on the Nearby Parks map using your GPS location.
    • Test the Nature Scanner by photographing leaves or trees.
    • Log your offline time and reflections in the Field Journal.

Code

The entire codebase is open-source under the MIT License:

GitHub logo parthbadgire-code / touchquest

A mobile-first, AI-powered nature exploration companion for outdoor micro-adventures, biodiversity discovery, and avian bioacoustics.

🌿 TouchQuest • Explore More. Scroll Less.

A mobile-first, AI-powered nature exploration companion designed to break algorithmic dopamine loops, inspire real-world outdoor micro-adventures, identify local biodiversity, and record avian bioacoustics.

Live Application: https://touchquest.vercel.app

🌲 Vision & Problem Statement

Modern feeds and short-form algorithms are tuned for continuous retention. TouchQuest flips the paradigm: instead of keeping you on the glass screen, it gives you a tactile outdoor quest (15, 30, or 60 minutes), guides your attention toward local flora and birdsong, and asks you to pocket the phone.

🛠️ Tech Stack

  • Framework: Next.js 14+ (App Router) with TypeScript & React 19
  • Design System: Vanilla Tailwind CSS with custom nature palette (Forest green #123324, Muted sage #88a38d, Warm cream #faf8f2, Earth ochre #c27d38), responsive mobile-first bottom navigation, glassmorphism tokens
  • Icons: lucide-react
  • Database & Auth: Supabase (PostgreSQL with Row-Level Security, Auth, Storage)
  • Maps: Leaflet & OpenStreetMap (Privacy-preserving local…
View on GitHub

Repository: https://github.com/parthbadgire-code/touchquest

How I Built It

TouchQuest is built around a resilient, dual-provider Adapter Pattern that strictly utilizes genuine hosted open-weight models:

  • Frontend & App Shell: Next.js 16 (App Router), React 19, TypeScript, Tailwind CSS v4, and Lucide icons.
  • Hosted Open-Weight AI Inference:
    • Missions & Vision Scanner: Powered by Groq Cloud running qwen/qwen3.8-27b—a state-of-the-art open-weight multimodal model. Missions use strict JSON schema mode for sub-second generation (~400ms latency), and the Nature Scanner processes base64 image data for botanical and fungal taxonomy.
    • Fallback Provider: An adapter fallback to Hugging Face Router v1 (Qwen/Qwen2.5-7B-Instruct and Qwen/Qwen2.5-VL-72B-Instruct).
    • Acoustic Serving: Dedicated Cornell BirdNET endpoint hook (HF_AUDIO_ENDPOINT) with 10MB upload guards and graceful standby reporting.
  • Cartography & Geodata: Leaflet loaded dynamically (ssr: false) with OpenStreetMap tiles. A custom Overpass API engine (src/lib/services/parks-service.ts) queries OSM nodes for leisure=park, nature_reserve, and garden, calculating Haversine distance from the user.
  • Database & Authentication: Supabase PostgreSQL with Row-Level Security policies safeguarding user profiles, saved quests, sightings, and journal entries, backed by a local storage synchronization layer for offline field resilience.

Why Does Open Innovation Matter?

  1. Nature Exploration Shouldn't Be Gated Behind Proprietary Walled Gardens: When nature apps rely on closed, black-box APIs, users are subjected to price hikes, telemetry lock-in, and sudden shutdowns. Open-weight models ensure that ecological tools remain transparent, accessible, and community-owned.
  2. Accessible Biodiversity Education: Open models like Qwen, BioCLIP, and BirdNET empower developers worldwide to build localized, multilingual taxonomy tools without requiring expensive enterprise credits or credit cards.
  3. Data Privacy in the Outdoors: Location data and personal journaling should remain private. By combining open-weight models with OpenStreetMap and client-side privacy boundaries, TouchQuest proves that AI can enhance our relationship with the natural world without turning nature into an ad-targeting engine.

My Agent Session

This application was engineered through an end-to-end pair-programming session with Antigravity (Google DeepMind), progressing through three structured milestones:

  1. Architectural scaffolding and mobile-first design tokens.
  2. AI adapter auditing, replacing deprecated serverless endpoints with hosted open-weight inference on Groq, and verifying live JSON schema generation.
  3. Leaflet OpenStreetMap integration, Supabase AuthContext implementation, and production deployment on Vercel.

Prize Categories

  • Touch Grass Challenge (Primary Track): Getting people away from algorithmic dopamine loops and into the physical outdoors through 15/30/60-minute sensory micro-adventures, biodiversity scanning, and outdoor journaling.
  • Open-Weight AI: Built exclusively with open-weight models (qwen/qwen3.8-27b, Qwen-2.5, BioCLIP, and BirdNET).

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