Update app.py

app.py

@@ -156,7 +156,7 @@ def remove_file(n_clicks, existing_files):
 def generate_matrix_with_gpt(matrix_type, file_contents):
     prompt = f"Generate a {matrix_type} based on the following project artifacts:\n\n"
     prompt += "\n\n".join(file_contents)
-    prompt += f"\n\nCreate a {matrix_type} in a format that can be represented as a pandas DataFrame."
+    prompt += f"\n\nCreate a {matrix_type} in a format that can be represented as a pandas DataFrame. Use '|' to separate columns and ensure each row has the same number of columns."
 
     response = openai.ChatCompletion.create(
         model="gpt-3.5-turbo",
@@ -167,11 +167,19 @@ def generate_matrix_with_gpt(matrix_type, file_contents):
     )
 
     matrix_text = response.choices[0].message.content
-    # Parse the matrix_text into a pandas DataFrame
-    # This is a simplified parsing, you might need to adjust based on the actual output format
-    lines = matrix_text.strip().split('\n')
-    headers = lines[0].split('|')
-    data = [line.split('|') for line in lines[2:]]
+    
+    # More robust parsing of the matrix text
+    lines = [line.strip() for line in matrix_text.strip().split('\n') if line.strip()]
+    data = [line.split('|') for line in lines]
+    
+    # Ensure all rows have the same number of columns
+    max_columns = max(len(row) for row in data)
+    data = [row + [''] * (max_columns - len(row)) for row in data]
+    
+    # Use the first row as headers, and the rest as data
+    headers = data[0]
+    data = data[1:]
+    
     return pd.DataFrame(data, columns=headers)
 
 @app.callback(