Updated the chart title

app.py

@@ -6,7 +6,9 @@ from datetime import date
 import plotly.graph_objects as go
 import itertools
 import json
-from ta import add_all_ta_features
+# --- MODIFIED IMPORTS: Changed to import specific indicator classes from 'ta' ---
+from ta.volatility import BollingerBands
+from ta.momentum import RSIIndicator
 from multiprocessing import Pool, cpu_count
 from functools import partial
 
@@ -161,10 +163,16 @@ def run_backtest(data, params, use_rsi, use_volatility, use_trend, use_volume, r
     if len(df) < params.get('large_ma_period', 200) or len(df) < params.get('bband_period', 20):
         return 0, 0, 0, 0, None, ([], [], [], []), []
     df['large_ma'] = df['Close'].rolling(window=params['large_ma_period']).mean()
-    bband = df.ta.bbands(length=params['bband_period'], std=params['bband_std_dev'], append=True)
-    df['bband_lower'] = bband[f'BBL_{params["bband_period"]}_{params["bband_std_dev"]}']
-    df['bband_upper'] = bband[f'BBU_{params["bband_period"]}_{params["bband_std_dev"]}']
-    df.ta.rsi(length=14, append=True, col_names=('RSI',))
+    
+    # --- MODIFIED: Calculate Bollinger Bands using the 'ta' library ---
+    indicator_bb = BollingerBands(close=df['Close'], window=params['bband_period'], window_dev=params['bband_std_dev'])
+    df['bband_lower'] = indicator_bb.bollinger_lband()
+    df['bband_upper'] = indicator_bb.bollinger_hband()
+    
+    # --- MODIFIED: Calculate RSI using the 'ta' library ---
+    indicator_rsi = RSIIndicator(close=df['Close'], window=14)
+    df['RSI'] = indicator_rsi.rsi()
+    
     df['Volatility_p'] = df['Close'].pct_change().rolling(window=14).std()
     df['SMA_200'] = df['Close'].rolling(window=200, min_periods=1).mean()
     if 'Volume' in df.columns:
@@ -540,9 +548,9 @@ def generate_advisor_report(main_df, main_content_placeholder):
                 data_for_backtest = main_df[cols_to_use].rename(columns={ticker_symbol: 'Close', f'{ticker_symbol}_Volume': 'Volume'})
                 
                 _, _, _, _, _, _, open_trades = run_backtest(data_for_backtest, params_for_run, 
-                                                            use_rsi, use_vol, use_trend, use_volume, 
-                                                            factor_weights['rsi'], factor_weights['vol'], 
-                                                            factor_weights['trend'], factor_weights['volume'])
+                                                             use_rsi, use_vol, use_trend, use_volume, 
+                                                             factor_weights['rsi'], factor_weights['vol'], 
+                                                             factor_weights['trend'], factor_weights['volume'])
 
                 if open_trades:
                     for trade in open_trades: