Update app.py

app.py

@@ -257,9 +257,11 @@ def process_pdf(uploaded_files, llm_model, n_criteria = num_criteria):
             'Title': title,
             'Author': author_result
         }
-        
         new_row.update({f'score_cr_{i}': score for i, score in enumerate(score_list, 1)})
-        new_row.update({f'reasoning_cr_{i}': re for i, re in enumerate(reasoning, 1)})
+        new_row.update({f'reasoning_cr_{i}': reasoning for i, reasoning in enumerate(reasoning, 1)})
+
+        # Convert new_row dictionary to a DataFrame for easy appending
+        new_row_df = pd.DataFrame([new_row])
 
         # Check if the CSV file exists
         if os.path.exists(csv_file_path):
@@ -267,11 +269,12 @@ def process_pdf(uploaded_files, llm_model, n_criteria = num_criteria):
             df = pd.read_csv(csv_file_path)
         else:
             # Or create a new DataFrame if the file does not exist
-            df = pd.DataFrame(columns=['Id'] + [f'score_cr_{i}' for i in range(1, 10)] + [f'reasoning_cr_{i}' for i in range(1, 10)])
-
-        # Append the new data
-        df = df.append(new_row, ignore_index=True)
+            columns = ['Id', 'Title', 'Author'] + [f'score_cr_{i}' for i in range(1, 10)] + [f'reasoning_cr_{i}' for i in range(1, 10)]
+            df = pd.DataFrame(columns=columns)
 
+        # Append the new data using pd.concat
+        df = pd.concat([df, new_row_df], ignore_index=True)
+        
         # Save the updated DataFrame back to CSV
         df.to_csv(csv_file_path, index=False)