Update app.py

app.py

@@ -6,6 +6,16 @@ import gradio as gr
 # Load the trained model
 model = joblib.load('hackathonrf.joblib')
 
+# Define AQI category labels
+aqi_labels = {
+    0: 'good',
+    1: 'moderate',
+    2: 'unhealthy_sensitive',
+    3: 'unhealthy',
+    4: 'very_unhealthy',
+    5: 'hazardous'
+}
+
 # Function to get latitude and longitude from location name
 def get_coordinates(location):
     geolocator = geopy.geocoders.Nominatim(user_agent="air_quality_app")
@@ -26,7 +36,8 @@ def predict_air_quality(location):
     latitude, longitude = get_coordinates(location)
     aqi_value = get_aqi(latitude, longitude)
     prediction = model.predict([[aqi_value, aqi_value, aqi_value, aqi_value]])
-    return prediction[0]
+    label_string = aqi_labels[prediction[0]]
+    return f"{location} air quality is currently '{label_string}'"
 
 # Create Gradio interface
 iface = gr.Interface(fn=predict_air_quality,