update

pages/1_Injection.py

@@ -107,7 +107,7 @@ else:
                 # Process data and display results
                 with st.spinner('Processing data...'):
                     parameters = {"temperature": st.session_state.temperature, "max_tokens": st.session_state.max_tokens}
-                    preprocessed_df = process_scores_multiple(df[["Resume"]], st.session_state.num_run, parameters, st.session_state.privilege_label,st.session_state.protect_label, agent, st.session_state.group_name,st.session_state.occupation)#,st.session_state.charateristics)
+                    preprocessed_df = process_scores_multiple(df, st.session_state.num_run, parameters, st.session_state.privilege_label,st.session_state.protect_label, agent, st.session_state.group_name,st.session_state.occupation)#,st.session_state.charateristics)
                     st.session_state.data_processed = True  # Mark as processed
 
                 st.write('Processed Data:', preprocessed_df)

util/injection.py

@@ -83,9 +83,10 @@ def process_scores_multiple(df, num_run, parameters, privilege_label, protect_la
         for index, (idx, row) in tqdm(enumerate(df.iterrows()), total=len(df), desc="Processing entries", unit="entry"):
             summary = []
             for column, value in row.items():
-                if group_name.lower() not in column.lower():
-                    readable_name = ' '.join(word.capitalize() for word in column.split('_'))
-                    summary.append(f"{readable_name}: {value};")
+                if column == 'Resume':
+                    if group_name.lower() not in column.lower():
+                        readable_name = ' '.join(word.capitalize() for word in column.split('_'))
+                        summary.append(f"{readable_name}: {value};")
 
             for key, label in zip(['Privilege', 'Protect', 'Neutral'], [privilege_label, protect_label, False]):
                 #prompt_charateristics = create_summary(group_name, label, occupation,'\n'.join(summary) + '\n' + charateristics)