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Aditya Pathak
Aditya Pathak

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TrailLens

#devchallenge #hf26challenge #touchgrass

🌿 TrailLens — Offline AI Nature Explorer

TrailLens is an outdoor-first AI nature companion built for the Hacktoberfest Open-Source AI Challenge, Week 1 — Touch Grass.

Take a photo of something you find outside. TrailLens identifies it with Ollama + Qwen3-VL 2B, explains it in simple language, gives you three facts, and gives you an outdoor challenge.

The screen is not the destination. The screen gives you your next reason to go outside.

Why open innovation matters

The core image understanding runs locally through Ollama and the open-weight Qwen3-VL 2B vision model. The local experience can analyze photos without sending them to a closed AI provider, and the model can be swapped or changed by the developer.

Features

  • 📷 Camera-friendly photo upload
  • 🧠 Local image understanding with Ollama + Qwen3-VL 2B
  • 🌿 Beginner-friendly identification and facts
  • 🎯 Outdoor challenges designed to get people exploring
  • ⚡ XP and levels
  • 📓 SQLite discovery journal
  • 🌐 Explicit Demo Mode for hosted deployments

Architecture 

Photo
  ↓
FastAPI
  ↓
Ollama
  ↓
Qwen3-VL 2B
  ↓
Identification + Facts + Outdoor Challenge
  ↓
SQLite Journal + XP
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Local setup

Requirements:

  • Python 3.10+
  • Ollama

Pull the model:

ollama pull qwen3-vl:2b
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Install dependencies:

python -m pip install -r requirements.txt
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Run:

python -m uvicorn main:app --host 127.0.0.1 --port 8000
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Open https://traillens-26.onrender.com.

Local AI vs online demo

Local Mode is the core experience:

![ ](https://dev-to-uploads.s3.us-east-2.amazonaws.com/uploads/articles/wk60gegrwa58fbllakhs.png)
![ ](https://dev-to-uploads.s3.us-east-2.amazonaws.com/uploads/articles/6d7m5elf1w64fmn7wk03.png)
Your Mac
  ↓
FastAPI
  ↓
Ollama
  ↓
Qwen3-VL 2B
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No cloud AI is required for image analysis.

A hosted Render service cannot access the Ollama process running on your Mac. For that reason, the included Render configuration enables an explicitly labelled Demo Mode instead of pretending that local Ollama is running remotely.

Render deployment

The repository includes render.yaml.

Build command:

pip install -r requirements.txt
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Start command:

uvicorn main:app --host 0.0.0.0 --port $PORT
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The hosted service uses Demo Mode. The real local open-weight AI remains available when TrailLens is run locally with Ollama.

Repository structure 

trail-lens/
├── main.py
├── backend/
│   ├── __init__.py
│   ├── config.py
│   ├── database.py
│   ├── demo.py
│   ├── ollama.py
│   └── xp.py
├── frontend/
│   ├── index.html
│   ├── journal.html
│   ├── app.js
│   ├── journal.js
│   └── styles.css
├── data/
├── uploads/
├── .env.example
├── .gitignore
├── .python-version
├── render.yaml
├── requirements.txt
└── README.md
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License

MIT.

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