"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"\n",
"import joblib\n",
"\n",
"with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:\n",
" gr.Markdown(feature_info)\n",
" gr.Markdown(\n",
" \"\"\"\n",
" # 🌫️ Air Quality Index (AQI) Predictor\n",
" Enter pollutant values to predict the AQI using a trained CatBoost model.\n",
" \"\"\")\n",
"# Add an info box above the input fields to explain the features in simple terms\n",
"feature_info = \"\"\"\n",
"\n",
"
What do these features mean?\n",
"
\n",
" - PM2.5 (μg/m³): Fine particulate matter. Low: 0-50 (Good), High: 250+ (Hazardous)
\n",
" - NO2 (μg/m³): Nitrogen dioxide. Low: 0-40 (Good), High: 200+ (Very unhealthy)
\n",
" - CO (mg/m³): Carbon monoxide. Low: 0-2 (Good), High: 10+ (Dangerous)
\n",
" - SO2 (μg/m³): Sulfur dioxide. Low: 0-20 (Good), High: 100+ (Very unhealthy)
\n",
" - O3 (μg/m³): Ozone. Low: 0-60 (Good), High: 180+ (Unhealthy)
\n",
"
\n",
"
Higher values mean more pollution and worse air quality.\n",
"
\n",
" Model: CatBoostRegressor | Features: PM2.5, NO2, CO, SO2, O3\n",
"
\n",
" \"\"\"\n",
" )\n",
"\n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8fa9ed64",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "air",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}