README.md

metadata

title: AIRA v2 — Arid-climate Intelligent Risk Assistant
emoji: 🌡️
colorFrom: yellow
colorTo: red
sdk: gradio
sdk_version: '4.44'
app_file: app.py
pinned: false
license: mit

🌡️ AIRA v2 — Arid-climate Intelligent Risk Assistant

AI-powered voice & vision safety copilot for heat-exposed workers in Qatar. Built for the QAI × Hugging Face Hackathon. Aligned with Qatar National Vision 2030 — Quality of Life.

🏗️ Architecture — Full Qwen Stack

Layer	Model	Role
👁️ Vision	Qwen/Qwen2-VL-2B-Instruct	Image analysis of job-site heat-stress indicators
🧠 Reasoning	Qwen/Qwen3-4B-Instruct	WBGT calculation, hydration & work-rest planning (Qatar MoPH aligned)
🎤 STT	openai/whisper-tiny	Speech-to-text in Arabic / Hindi / Urdu / English
🔊 TTS	gTTS	Spoken safety advice read back to worker
🌤️ Weather	Open-Meteo API	Live Qatar temperature & humidity

📁 Repository Structure

AIRA/
├── app.py              # Gradio Space: Vision + Qwen3 Reasoning + Voice + WBGT Safety
├── train_qwen_vision.py # LoRA fine-tuning script for Qwen2-VL on heat-stress imagery
├── requirements.txt    # Python dependencies
└── README.md           # This file (HF Space metadata + docs)

🚀 Deploy to Hugging Face Spaces

Prerequisites

⚠️ Gradio Spaces require a HF Pro subscription on cpu-basic hardware.
Subscribe at https://huggingface.co/pro (your $100 credits can cover this).

One-command deploy

# Install HF CLI
curl -LsSf https://hf.co/cli/install.sh | bash -s

# Login (you must do this yourself)
hf auth login

# Create + upload the Space (run once Pro is active)
hf repos create jonathan4e/aira-v2 --type space --sdk gradio --exist-ok
hf upload jonathan4e/aira-v2 --type space app.py requirements.txt README.md --commit-message "Deploy AIRA v2"
hf spaces settings jonathan4e/aira-v2 --hardware t4-small
hf spaces wait jonathan4e/aira-v2 --timeout 600

Your Space URL: https://huggingface.co/spaces/jonathan4e/aira-v2

🎯 Fine-tune Qwen2-VL on Your Own Dataset

# 1. Create/push a heat-stress image dataset to HF
python create_dataset.py --push jonathan4e/aira-heat-stress

# 2. Fine-tune Qwen2-VL-2B with LoRA (PEFT)
python train_qwen_vision.py \
  --dataset jonathan4e/aira-heat-stress \
  --output jonathan4e/aira-qwen2vl-heat \
  --epochs 1 --batch 2

# 3. Update app.py VISION_MODEL_ID to your fine-tuned model

🧠 WBGT Safety Logic (Qatar MoPH Aligned)

• WBGT estimate from temperature + humidity + solar load
• Risk bands: Low (<29°C), Moderate (29–31°C), High (31–33°C), Extreme (>33°C)
• Output: hydration (L/hr), work/rest cycle (min work / min rest shade), immediate actions
• Multilingual: English, Arabic, Hindi, Urdu

📱 Demo Features

• gr.Examples pre-loaded for instant hackathon judging
• Mobile-responsive Gradio UI with RTL support for Arabic/Urdu
• Voice input → transcription → Qwen3 reasoning → TTS audio output
• Image upload → Qwen2-VL heat-stress classification

🇶🇦 Alignment

Supports Qatar National Vision 2030 — Quality of Life by protecting outdoor, logistics, and construction workers from extreme summer heat with free, open-source, mobile-accessible AI.

📄 License

MIT