Added code

app.py

@@ -22,7 +22,8 @@ model = joblib.load(model_dir + "/stckhlm_inc_model.pkl")
 print("Model downloaded")
 
 
-def predict(magnitudeOfDelay, hour, iconCategory, latitude, longitude, month):
+def predict(code, magnitudeOfDelay, hour, iconCategory, latitude, longitude, month):
+    
     # Change the magnitude delay to an integer based on the index
     if magnitudeOfDelay == 'Unknown':
         magnitudeOfDelay = 0
@@ -65,20 +66,18 @@ def predict(magnitudeOfDelay, hour, iconCategory, latitude, longitude, month):
 
     # Create a row from the input
     row = {
+        'code': int(code),
         'magnitudeOfDelay': int(magnitudeOfDelay),
         'hour': int(hour),
         'iconCategory': int(iconCategory),
         'latitude': latitude,
         'longitude': longitude,
-        'month': month
+        'month': int(month)
     }
 
     # Create a df from the row
     df_row = pd.DataFrame(row, index=[0])
 
-    # change the order to code	hour	iconCategory	latitude	longitude	magnitudeOfDelay	month	duration
-    df_row = df_row[['magnitudeOfDelay', 'hour', 'iconCategory', 'latitude', 'longitude', 'month']]
-
     # make the features lower case
     df_row.columns = df_row.columns.str.lower()
     df_row.columns = df_row.columns.str.replace(' ', '_')
@@ -97,6 +96,7 @@ demo = gr.Interface(
     description="Predicts the duration of a traffic incident in Stockholm",
     allow_flagging="never",
     inputs=[
+        gr.inputs.radio(["101", "108", "115", "122", "201", "500", "701", "1101"]),
         gr.inputs.Radio(["Unknown", "Minor", "Moderate", "Major", "Undefined"]),
         gr.inputs.Slider(0, 23, label="Hour"),
         gr.inputs.Radio(["Unknown", "Accident", "Fog", "Dangerous Conditions", "Rain", "Ice", "Jam", "Lane Closed", "Road Closed", "Road Works", "Wind", "Flooding", "Broken Down Vehicle"], label="Icon Category"),