---
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

```bash
# 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

```bash
# 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