Update app.py

app.py

@@ -7,12 +7,12 @@ with open('./rf_cv_waze.pickle' , 'rb') as file:
 
 # Define the function for making predictions
 def salifort(sessions, drives, total_sessions, n_days_after_onboarding, total_navigations_fav1, total_navigations_fav2, driven_km_drives, duration_minutes_drives, activity_days, driving_days, km_per_driving_day, percent_sessions_in_last_month, professional_driver, total_sessions_per_day, km_per_hour, km_per_drive, percent_of_drives_to_favorite, device2):
-    inputs = [[ float('sessions'), float('drives'), float('total_sessions'), float('n_days_after_onboarding'),
-                float('total_navigations_fav1'), float('total_navigations_fav2'), float('driven_km_drives'),
-                float('duration_minutes_drives'), float('activity_days'), float('driving_days'),
-                float('km_per_driving_day'), float('percent_sessions_in_last_month'),
-                float('professional_driver'), float('total_sessions_per_day'), float('km_per_hour'),
-                float('km_per_drive'), float('percent_of_drives_to_favorite'), float('device2')
+    inputs = [[ float(sessions), float(drives), float(total_sessions), float(n_days_after_onboarding),
+                float(total_navigations_fav1), float(total_navigations_fav2), float(driven_km_drives),
+                float(duration_minutes_drives), float(activity_days), float(driving_days),
+                float(km_per_driving_day), float(percent_sessions_in_last_month),
+                float(professional_driver), float(total_sessions_per_day), float(km_per_hour),
+                float(km_per_drive), float(percent_of_drives_to_favorite), float(device2)
                 ]]
     prediction = model.predict(inputs)
     prediction_value = prediction[0]