update

app.py

@@ -79,9 +79,9 @@ def show_demo(placeholder):
                 if submitted:
 
                     try:
-                        yaml_dict = yaml.safe_load(input_yaml)
+                        yaml_dict = yaml.safe_load(input_yaml)                        
                     except yaml.YAMLError as e:
-                        st.error(f"Yikes, you better get your YAML straight! Check https://yaml.org/ for help!")
+                        st.error(f"Yikes, you better get your YAML straight! Check https://yaml.org/ for help!")                       
                         return(None)
 
                     try:
@@ -94,14 +94,18 @@ def show_demo(placeholder):
                     try:
                         st.session_state.input_data = modeling.process_yaml_input(yaml_dict)
                     except Exception as error:
-                        st.error(error)
+                        error_msg = f"Error while processing YAML-input: {error}"
+                        st.error(error_msg)
+                        
                         st.json(yaml_dict)
                         return(None)                   
 
                     try:
                         st.session_state.input_data = modeling.encode_input_data()
                     except Exception as error:
-                        st.error(error)
+                        error_msg = f"Error while encoding data: {error}"
+                        st.error(error_msg)
+                        print(error)
                         st.json(yaml_dict)
                         return(None)
 

modeling.py

@@ -29,8 +29,9 @@ def load_model():
             logging.info('Loaded SurveyBot3000!')
 
 def process_yaml_input(yaml_dict):
-
+    
     input_data = pd.DataFrame({k: pd.Series(v) for k, v in yaml_dict.items()})
+        
     df = (
         input_data
         .stack()
@@ -38,8 +39,9 @@ def process_yaml_input(yaml_dict):
         .drop('level_0', axis=1)
         .rename(columns={'level_1': 'scale', 0: "item"})
     )
+    
     df['item'] = df['item'].apply(lambda item: utils.clean_text(item))
-
+    
     return(df)
 
 def get_items_per_scale():

utils.py

@@ -4,7 +4,7 @@ import json
 import hashlib
 from io import StringIO
 from datetime import datetime
-
+    
 def clean_text(input):
 
     text = ftfy.fix_text(input)