Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (V15.11 - Fix LLM Reason Key + Deep MC Debugging)
+# app.py (V15.12 - Fix MC Logic & Restore Full Logging)
 import os
 import sys
 import traceback
@@ -174,7 +174,7 @@ async def _analyze_symbol_task(symbol: str) -> Dict[str, Any]:
         return None
 
 # ==============================================================================
-# [ 🚀 🚀 🚀 ] الدورة الموحدة (النسخة النهائية V15.11)
+# [ 🚀 🚀 🚀 ] الدورة الموحدة (النسخة النهائية V15.12 - MC Fixed)
 # ==============================================================================
 async def run_unified_cycle():
     """
@@ -273,7 +273,7 @@ async def run_unified_cycle():
 
             candidate['news_text'] = news_text
 
-            # ج. مونت كارلو المتقدمة [ 🚀 تصحيح ومراقبة ]
+            # ج. مونت كارلو المتقدمة [ 🚀 تصحيح المنطق V15.12 ]
             adv_mc_score = 0.0
             try:
                 full_ohlcv_1h = await data_manager.get_latest_ohlcv(symbol, '1h', limit=100)
@@ -283,17 +283,30 @@ async def run_unified_cycle():
                 else:
                     mc_data = {'1h': full_ohlcv_1h}
                     mc_res = await ml_processor.mc_analyzer.generate_1h_distribution_advanced(mc_data)
-                    if mc_res:
+                    
+                    if mc_res and not mc_res.get('error', False):
                         prob_gain = mc_res.get('probability_of_gain', 0.5)
+                        model_name = mc_res.get('simulation_model', 'Unknown')
                         
-                        # [ 🚀 ] طباعة لفهم سبب الدرجات الصفرية
-                        print(f"       ℹ️ [MC Debug] {symbol}: Prob={prob_gain:.4f}")
+                        # طباعة للتتبع
+                        print(f"       ℹ️ [MC Info] {symbol} | Prob: {prob_gain:.2f} | Model: {model_name}")
                         
+                        # منطق الحساب الجديد:
+                        # إذا كان الاحتمال أعلى من 50%، امنح نقاطاً.
+                        # (prob - 0.5) * 0.20 يعني:
+                        # 0.51 -> +0.002
+                        # 0.60 -> +0.02
+                        # 1.00 -> +0.10 (Max)
                         if prob_gain > 0.5:
-                            adv_mc_score = (prob_gain - 0.5) * 2 * 0.10
-                            if adv_mc_score > 0.10: adv_mc_score = 0.10
+                            adv_mc_score = min(0.10, (prob_gain - 0.5) * 0.20)
+                        else:
+                            adv_mc_score = 0.0
+                    else:
+                        reason = mc_res.get('reason', 'Unknown Error') if mc_res else "Null Result"
+                        print(f"       ⚠️ [MC Warning] {symbol} skipped: {reason}")
+
             except Exception as e:
-                print(f"       ⚠️ [MC Error] {symbol}: {e}")
+                print(f"       ⚠️ [MC Exception] {symbol}: {e}")
                 
             # --- د. حساب الدرجة النهائية ---
             final_score = l1_score + whale_score + news_score + adv_mc_score
@@ -385,7 +398,7 @@ async def run_unified_cycle():
 # ==============================================================================
 app = FastAPI(
     lifespan=lifespan, 
-    title="Titan V15.11 (Verbose Reason & MC Debug)", 
+    title="Titan V15.12 (Verbose Reason & MC Fixed)", 
     description="نظام تداول آلي هجين مع تعزيز رقمي L2"
 )