Update app.py

app.py

@@ -222,33 +222,55 @@ def generate_matrix_with_gpt(matrix_type, file_contents):
     data = data[1:]
     
     return pd.DataFrame(data, columns=headers)
+
+@app.callback(
+    Output('chat-output', 'children'),
+    Output('matrix-preview', 'children', allow_duplicate=True),
+    Input('btn-send-chat', 'n_clicks'),
+    State('chat-input', 'value'),
+    prevent_initial_call=True
 )
 def update_matrix_via_chat(n_clicks, chat_input):
-    global current_matrix
+    global current_matrix, matrix_type
     if not chat_input or current_matrix is None:
         raise PreventUpdate
     
     prompt = f"Update the following {matrix_type} based on this instruction: {chat_input}\n\n"
-    prompt += current_matrix.to_string()
+    prompt += current_matrix.to_string(index=False)
+    prompt += "\n\nProvide the updated matrix using '|' to separate columns. Do not include any separator lines, headers, or formatting characters. Start directly with the column names separated by '|'."
     
     response = openai.ChatCompletion.create(
         model="gpt-3.5-turbo",
         messages=[
-            {"role": "system", "content": "You are a helpful assistant that updates project management matrices."},
+            {"role": "system", "content": "You are a helpful assistant that updates project management matrices without any formatting or separator lines."},
             {"role": "user", "content": prompt}
         ]
     )
 
     updated_matrix_text = response.choices[0].message.content
-    # Parse the updated_matrix_text into a pandas DataFrame
-    # This is a simplified parsing, you might need to adjust based on the actual output format
-    lines = updated_matrix_text.strip().split('\n')
-    headers = lines[0].split('|')
-    data = [line.split('|') for line in lines[2:]]
+    print("Raw updated matrix text from GPT:", updated_matrix_text)  # For debugging
+
+    # Filter out any lines that don't contain the '|' character
+    lines = [line.strip() for line in updated_matrix_text.strip().split('\n') if '|' in line]
+    
+    # Parse the matrix text
+    data = [line.split('|') for line in lines]
+    
+    # Strip whitespace from each cell
+    data = [[cell.strip() for cell in row] for row in data]
+    
+    # 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:]
+    
     current_matrix = pd.DataFrame(data, columns=headers)
     
     return f"Matrix updated based on: {chat_input}", dbc.Table.from_dataframe(current_matrix, striped=True, bordered=True, hover=True)
-
+    
 @app.callback(
     Output("download-matrix", "data"),
     Input("btn-download", "n_clicks"),