update

pages/1_Injection.py

@@ -73,15 +73,14 @@ else:
         file_options = st.radio("Choose file source:", ["Upload", "Example"])
         if file_options == "Example":
             #df = pd.read_csv("prompt_test.csv")
-            df = pd.read_csv("resume.csv")
-            df = df[df['Occupation'] == st.session_state.occupation]
+            df_raw = pd.read_csv("resume.csv")
+            df = df_raw[df_raw['Occupation'] == st.session_state.occupation]
         else:
             st.session_state.uploaded_file = st.file_uploader("Choose a file")
             if st.session_state.uploaded_file is not None:
                 data = StringIO(st.session_state.uploaded_file.getvalue().decode("utf-8"))
                 df= pd.read_csv(data)
         if df is not None:
-
             st.write('Data:', df)
 
             # Button to add a new row
@@ -108,15 +107,15 @@ else:
                 # Process data and display results
                 with st.spinner('Processing data...'):
                     parameters = {"temperature": st.session_state.temperature, "max_tokens": st.session_state.max_tokens}
-                    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.additional_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.additional_charateristics)
                     st.session_state.data_processed = True  # Mark as processed
 
-                st.write('Processed Data:', df)
+                st.write('Processed Data:', preprocessed_df)
 
                 # Allow downloading of the evaluation results
                 st.download_button(
                     label="Download Generation Results",
-                    data=df.to_csv().encode('utf-8'),
+                    data=preprocessed_df.to_csv().encode('utf-8'),
                     file_name='generation_results.csv',
                     mime='text/csv',
                 )