Update app.py

app.py

@@ -513,6 +513,8 @@ def get_bot_skills():
 
 
 
+
+
 def detect_chart_scenario(df, df_1m=None, df_5m=None, df_15m=None, df_1h=None):
     try:
         # 🛠️ Fix colonnes KuCoin
@@ -531,6 +533,7 @@ def detect_chart_scenario(df, df_1m=None, df_5m=None, df_15m=None, df_1h=None):
         vwap = (typical_price * df['volume']).cumsum() / (df['volume'].cumsum() + 1e-9)
         price_above_vwap = df['close'].iloc[-1] > vwap.iloc[-1]
         price_below_vwap = df['close'].iloc[-1] < vwap.iloc[-1]
+        
         # ========================
         # 🔥 VWAP BANDS (Institutional zones)
         # ========================
@@ -540,7 +543,6 @@ def detect_chart_scenario(df, df_1m=None, df_5m=None, df_15m=None, df_1h=None):
 
         price_extended_high = df['close'].iloc[-1] > vwap_upper.iloc[-1]
         price_extended_low = df['close'].iloc[-1] < vwap_lower.iloc[-1]
-  
 
         # --- 2. MULTI TIMEFRAME (1m, 5m, 15m, 1h) ---
         mtf_bull = mtf_bear = 0
@@ -593,12 +595,6 @@ def detect_chart_scenario(df, df_1m=None, df_5m=None, df_15m=None, df_1h=None):
         near_liquidity_high = abs(c[-1] - liquidity_high_zone) / c[-1] < 0.002
         near_liquidity_low = abs(c[-1] - liquidity_low_zone) / c[-1] < 0.002
 
-        # ========================
-        # 🔥 FAKE BREAKOUT FILTER
-        # ========================
-        fake_breakout_up = bos_up and c[-1] < recent_high
-        fake_breakout_down = bos_down and c[-1] > recent_low
-
         # --- 5. STRUCTURE ET RSI ---
         range_start, range_end = np.mean(h[:20] - l[:20]), np.mean(h[-20:] - l[-20:])
         squeeze = range_end < range_start * 0.65
@@ -611,6 +607,12 @@ def detect_chart_scenario(df, df_1m=None, df_5m=None, df_15m=None, df_1h=None):
         bos_up = np.max(h[-20:]) > np.max(h[-40:-20])
         bos_down = np.min(l[-20:]) < np.min(l[-40:-20])
 
+        # ========================
+        # 🔥 FAKE BREAKOUT FILTER (Déplacé ici pour corriger le bug !)
+        # ========================
+        fake_breakout_up = bos_up and c[-1] < recent_high
+        fake_breakout_down = bos_down and c[-1] > recent_low
+
         bullish_div = bearish_div = False
         if 'RSI' in df.columns:
             rsi = df['RSI'].values