Update app.py

app.py

@@ -188,40 +188,25 @@ def generate_matrix_with_gpt(matrix_type, file_contents):
     [Input(f'btn-{matrix_type.lower().replace(" ", "-")}', 'n_clicks') for matrix_type in matrix_types.keys()],
     prevent_initial_call=True
 )
-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. Use '|' 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 generates project management matrices without any formatting or separator lines."},
-            {"role": "user", "content": prompt}
-        ]
-    )
-
-    matrix_text = response.choices[0].message.content
-    print("Raw matrix text from GPT:", matrix_text)  # For debugging
-
-    # Filter out any lines that don't contain the '|' character
-    lines = [line.strip() for line in matrix_text.strip().split('\n') if '|' in line]
-    
-    # More robust parsing of 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]
+def generate_matrix(*args):
+    global current_matrix, matrix_type
+    ctx = dash.callback_context
+    if not ctx.triggered:
+        raise PreventUpdate
+    button_id = ctx.triggered[0]['prop_id'].split('.')[0]
+    matrix_type = button_id.replace('btn-', '').replace('-', ' ').title()
     
-    # Use the first row as headers, and the rest as data
-    headers = data[0]
-    data = data[1:]
+    if not uploaded_files:
+        return html.Div("Please upload project artifacts before generating a matrix."), ""
+
+    file_contents = list(uploaded_files.values())
     
-    return pd.DataFrame(data, columns=headers)
+    try:
+        current_matrix = generate_matrix_with_gpt(matrix_type, file_contents)
+        return dbc.Table.from_dataframe(current_matrix, striped=True, bordered=True, hover=True), f"{matrix_type} generated"
+    except Exception as e:
+        print(f"Error generating matrix: {str(e)}")
+        return html.Div(f"Error generating matrix: {str(e)}"), "Error"
 
 @app.callback(
     Output('chat-output', 'children'),