Update scripts/app.py

scripts/app.py

@@ -17,10 +17,10 @@ from environment import PortfolioEnv
 from scripts.evaluate_baselines import buy_and_hold, equally_weighted_rebalanced
 
 # --- Configuration ---
-MODEL_PATH = os.path.join(project_root, "checkpoints", "sac_portfolio_model.zip")
+MODEL_PATH = os.path.join("checkpoints", "sac_portfolio_model.zip")
 WINDOW_SIZE = 30
 MACRO_COLS = list(FRED_IDS.values())
-DASHBOARD_DATA_PATH = os.path.join(project_root, "data", "historical_dashboard_data.csv")
+DASHBOARD_DATA_PATH = os.path.join("data", "historical_dashboard_data.csv")
 
 # *** UPDATE THESE DATES TO MATCH YOUR ACTUAL TRAINING PERIOD ***
 TRAIN_START_DATE = "2015-01-01"
@@ -393,7 +393,7 @@ def get_latest_data_window(window_size=30):
     lookback_days = window_size + 150
     end_date = datetime.now().strftime('%Y-%m-%d')
     start_date = (datetime.now() - timedelta(days=lookback_days)).strftime('%Y-%m-%d')
-    temp_filename = os.path.join(project_root, "data", "temp_gradio_prediction_data.csv")
+    temp_filename = os.path.join("data", "temp_gradio_prediction_data.csv")
     fetch_market_data(start_date, end_date, temp_filename)
     if not os.path.exists(temp_filename): raise Exception("Failed to fetch market data file.")
     df = pd.read_csv(temp_filename, index_col=0, parse_dates=True)