Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (محدث بإضافة Timeout لجلب الحيتان وإصلاح IndentationError)
+# app.py (محدث بالكامل لربط الخدمات)
 import os
 import traceback
 import signal
@@ -20,7 +20,7 @@ try:
     from learning_engine import LearningEngine
     from sentiment_news import SentimentAnalyzer
     from trade_manager import TradeManager
-    import state
+    import state # 🔴 مهم: هذا هو ملف state.py
     from helpers import safe_float_conversion, validate_candidate_data_enhanced
 except ImportError as e:
     print(f"❌ خطأ في استيراد الوحدات: {e}")
@@ -36,9 +36,11 @@ sentiment_analyzer_global = None
 symbol_whale_monitor_global = None
 
 class StateManager:
+    # 🔴 هذا هو مدير الحالة "المحلي" للتطبيق
+    # الذي يدير الأقفال الداخلية لـ FastAPI
     def __init__(self):
         self.market_analysis_lock = asyncio.Lock()
-        self.trade_analysis_lock = asyncio.Lock()
+        self.trade_analysis_lock = asyncio.Lock() # 🔴 هذا هو القفل الذي سيتم تمريره
         self.initialization_complete = False
         self.initialization_error = None
         self.services_initialized = {
@@ -65,6 +67,7 @@ class StateManager:
         self.initialization_error = error
         print(f"❌ خطأ في التهيئة: {error}")
 
+# 🔴 إنشاء نسخة مدير الحالة المحلي
 state_manager = StateManager()
 
 async def initialize_services():
@@ -82,11 +85,44 @@ async def initialize_services():
             symbol_whale_monitor_global = EnhancedWhaleMonitor(contracts_database, r2_service_global)
             state_manager.set_service_initialized('symbol_whale_monitor'); print("   ✅ مراقب الحيتان مهيأ")
         except Exception as e: print(f"   ⚠️ فشل تهيئة مراقب الحيتان: {e}"); symbol_whale_monitor_global = None
-        print("   🔄 تهيئة DataManager..."); data_manager_global = DataManager(contracts_database, symbol_whale_monitor_global); await data_manager_global.initialize(); state_manager.set_service_initialized('data_manager'); print("   ✅ DataManager مهيأ")
-        print("   🔄 تهيئة LLMService..."); llm_service_global = LLMService(); llm_service_global.r2_service = r2_service_global; state_manager.set_service_initialized('llm_service'); print("   ✅ LLMService مهيأة")
-        print("   🔄 تهيئة محلل المشاعر..."); sentiment_analyzer_global = SentimentAnalyzer(data_manager_global); state_manager.set_service_initialized('sentiment_analyzer'); print("   ✅ محلل المشاعر مهيأ")
-        print("   🔄 تهيئة محرك التعلم..."); learning_engine_global = LearningEngine(r2_service_global, data_manager_global); await learning_engine_global.initialize_enhanced(); state_manager.set_service_initialized('learning_engine'); print("   ✅ محرك التعلم مهيأ")
-        print("   🔄 تهيئة مدير الصفقات..."); trade_manager_global = TradeManager(r2_service_global, learning_engine_global, data_manager_global); state_manager.set_service_initialized('trade_manager'); print("   ✅ مدير الصفقات مهيأ")
+        print("   🔄 تهيئة DataManager..."); data_manager_global = DataManager(contracts_database, symbol_whale_monitor_global); await data_manager_global.initialize(); state_manager.set_service_initialized('data_manager'); print("   ✅ DataManager مهيأة")
+        
+        # --- 🔴 بدء التعديل (الربط) ---
+        
+        print("   🔄 تهيئة LLMService..."); 
+        llm_service_global = LLMService(); 
+        llm_service_global.r2_service = r2_service_global; 
+        # (لا نضع علامة مهيأ هنا بعد)
+
+        print("   🔄 تهيئة محلل المشاعر..."); 
+        sentiment_analyzer_global = SentimentAnalyzer(data_manager_global); 
+        state_manager.set_service_initialized('sentiment_analyzer'); 
+        print("   ✅ محلل المشاعر مهيأ")
+        
+        print("   🔄 تهيئة محرك التعلم..."); 
+        learning_engine_global = LearningEngine(r2_service_global, data_manager_global); 
+        await learning_engine_global.initialize_enhanced(); 
+        state_manager.set_service_initialized('learning_engine'); 
+        print("   ✅ محرك التعلم مهيأ")
+
+        # 🔴 ربط محرك التعلم بـ LLM (للتغذية الراجعة)
+        llm_service_global.learning_engine = learning_engine_global
+        state_manager.set_service_initialized('llm_service'); # 🔴 الآن نضع علامة مهيأ لـ LLM
+        print("   ✅ LLMService مهيأة (ومربوطة بمحرك التعلم)")
+
+        print("   🔄 تهيئة مدير الصفقات..."); 
+        # 🔴 تمرير state_manager إلى TradeManager (لإدارة التعارض)
+        trade_manager_global = TradeManager(
+            r2_service_global, 
+            learning_engine_global, 
+            data_manager_global,
+            state_manager  # 🔴 تمرير مدير الحالة المحلي هنا
+        )
+        state_manager.set_service_initialized('trade_manager'); 
+        print("   ✅ مدير الصفقات مهيأ (ومدرك لحالة النظام)")
+        
+        # --- 🔴 نهاية التعديل ---
+
         print("🎯 اكتملت تهيئة جميع الخدمات بنجاح"); return True
     except Exception as e: error_msg = f"فشل تهيئة الخدمات: {str(e)}"; print(f"❌ {error_msg}"); state_manager.set_initialization_error(error_msg); return False
 
@@ -97,6 +133,7 @@ async def monitor_market_async():
         if not await state_manager.wait_for_initialization(): print("❌ فشل تهيئة الخدمات - إيقاف مراقبة السوق"); return
         while True:
             try:
+                # 🔴 استخدام قفل مدير الحالة المحلي
                 async with state_manager.market_analysis_lock:
                     market_context = await sentiment_analyzer_global.get_market_sentiment()
                     if not market_context: state.MARKET_STATE_OK = True; await asyncio.sleep(60); continue
@@ -346,13 +383,18 @@ async def run_3_layer_analysis():
                 timeframes_count = candidate.get('successful_timeframes', 0); total_candles = sum(len(data) for data in ohlcv_data.values()) if ohlcv_data else 0
                 if total_candles < 30: print(f"      ⚠️ بيانات شموع غير كافية لـ {symbol}: {total_candles} شمعة فقط"); continue
                 print(f"      📊 إرسال {symbol} للنموذج: {total_candles} شمعة في {timeframes_count} إطار زمني")
+                
+                # 🔴 تمرير بيانات إضافية (مثل sentiment) إلى النموذج
+                candidate['sentiment_data'] = await data_manager_global.get_market_context_async() # ضمان أحدث سياق
+                
                 llm_analysis = await llm_service_global.get_trading_decision(candidate) 
+                
                 if llm_analysis and llm_analysis.get('action') in ['BUY']: 
                     opportunity={'symbol': symbol, 'current_price': candidate.get('current_price', 0), 'decision': llm_analysis, 'enhanced_score': candidate.get('enhanced_final_score', 0), 'llm_confidence': llm_analysis.get('confidence_level', 0), 'strategy': llm_analysis.get('strategy', 'GENERIC'), 'analysis_timestamp': datetime.now().isoformat(), 'timeframes_count': timeframes_count, 'total_candles': total_candles}
                     final_opportunities.append(opportunity)
-                    print(f"   ✅ {symbol}: {llm_analysis.get('action')} - ثقة: {llm_analysis.get('confidence_level', 0):.2f}")
+                    print(f"   ✅ {symbol}: {llm_analysis.get('action')} - ثقة: {llm_analysis.get('confidence_level', 0):.2f} (ملف خروج: {llm_analysis.get('exit_profile')})") # 🔴
                 else: action = llm_analysis.get('action', 'NO_DECISION') if llm_analysis else 'NO_RESPONSE'; print(f"   ⚠️ {symbol}: لا يوجد قرار تداول من النموذج الضخم ({action})")
-            except Exception as e: print(f"❌ خطأ في تحليل النموذج الضخم لـ {candidate.get('symbol')}: {e}"); continue
+            except Exception as e: print(f"❌ خطأ في تحليل النموذج الضخم لـ {candidate.get('symbol')}: {e}"); traceback.print_exc(); continue
 
         if final_opportunities:
             final_opportunities.sort(key=lambda x: (x['llm_confidence'] + x['enhanced_score']) / 2, reverse=True)
@@ -367,7 +409,6 @@ async def run_3_layer_analysis():
                 if whale_data and whale_data.get('data_available'): signal = whale_data.get('trading_signal', {}); action = signal.get('action', 'HOLD'); confidence = signal.get('confidence', 0); reason_preview = signal.get('reason', 'N/A')[:75] + "..." if signal.get('reason') else 'N/A'; whale_summary = f"Action: {action}, Conf: {confidence:.2f}, Alert: {signal.get('critical_alert', False)}, Reason: {reason_preview}"
                 elif whale_data and whale_data.get('error'): whale_summary = f"Error: {whale_data['error'][:50]}..."
                 
-                # 🔴 --- بدء التعديل: إضافة تفاصيل مونت كارلو للسجل --- 🔴
                 mc_summary = "N/A"
                 mc_dist = c.get('monte_carlo_distribution')
                 if mc_dist:
@@ -379,7 +420,6 @@ async def run_3_layer_analysis():
                     else: # Phase1 or Error
                         var_val = mc_dist.get('risk_metrics', {}).get('VaR_95_value', 0)
                         mc_summary = f"{mc_model}_VaR({var_val:.4f})"
-                # 🔴 --- نهاية التعديل --- 🔴
                         
                 top_10_detailed_summary.append({ 
                     "symbol": c.get('symbol'), 
@@ -388,7 +428,7 @@ async def run_3_layer_analysis():
                     "whale_data_summary": whale_summary, 
                     "strategy": c.get('target_strategy', 'N/A'), 
                     "pattern": c.get('pattern_analysis', {}).get('pattern_detected', 'N/A'),
-                    "mc_analysis_level": mc_summary # 🔴 إضافة الحقل الجديد
+                    "mc_analysis_level": mc_summary 
                 })
                 
             other_successful_candidates = layer2_candidates[target_count:]
@@ -415,7 +455,9 @@ async def re_analyze_open_trade_async(trade_data):
     """إعادة تحليل الصفقة المفتوحة"""
     symbol = trade_data.get('symbol')
     try:
+        # 🔴 استخدام قفل مدير الحالة المحلي
         async with state_manager.trade_analysis_lock:
+            print(f"🔄 [Re-Analyze] بدء التحليل الاستراتيجي لـ {symbol}...")
             market_context = await data_manager_global.get_market_context_async()
             ohlcv_data_list = []
             temp_queue = asyncio.Queue()
@@ -440,18 +482,15 @@ async def re_analyze_open_trade_async(trade_data):
 
             ml_processor = MLProcessor(market_context, data_manager_global, learning_engine_global)
             
-            # 🔴 عند إعادة التحليل، نستخدم دائماً النموذج المتقدم (GARCH+LGBM)
             print(f"🔄 [Re-Analyze] استخدام مونت كارلو (Phase 2+3) لـ {symbol}...")
             advanced_mc_results = await ml_processor.monte_carlo_analyzer.generate_1h_distribution_advanced(
                 ohlcv_data.get('ohlcv')
             )
             
-            # معالجة أساسية للحصول على المؤشرات
             processed_data = await ml_processor.process_and_score_symbol_enhanced(ohlcv_data, {symbol: re_analysis_whale_data} if re_analysis_whale_data else {})
             
             if not processed_data: return None
             
-            # استبدال نتائج MC (إن وجدت) بالنتائج المتقدمة الدقيقة
             if advanced_mc_results:
                 processed_data['monte_carlo_distribution'] = advanced_mc_results
                 processed_data['monte_carlo_probability'] = advanced_mc_results.get('probability_of_gain', 0)
@@ -459,10 +498,14 @@ async def re_analyze_open_trade_async(trade_data):
             processed_data['raw_ohlcv'] = ohlcv_data.get('raw_ohlcv') or ohlcv_data.get('ohlcv')
             processed_data['ohlcv'] = processed_data['raw_ohlcv']
             
+            # 🔴 إضافة سياق السوق إلى البيانات المرسلة لإعادة التحليل
+            processed_data['sentiment_data'] = market_context
+            
             re_analysis_decision = await llm_service_global.re_analyze_trade_async(trade_data, processed_data)
             
             if re_analysis_decision:
                 await r2_service_global.save_system_logs_async({ "trade_reanalyzed": True, "symbol": symbol, "action": re_analysis_decision.get('action'), 'strategy': re_analysis_decision.get('strategy', 'GENERIC') })
+                print(f"✅ [Re-Analyze] اكتمل التحليل الاستراتيجي لـ {symbol}. القرار: {re_analysis_decision.get('action')}")
                 return {"symbol": symbol, "decision": re_analysis_decision, "current_price": processed_data.get('current_price')}
             else: return None
     except Exception as error: await r2_service_global.save_system_logs_async({ "reanalysis_error": True, "symbol": symbol, "error": str(error) }); print(f"❌ Error in re_analyze_open_trade_async for {symbol}: {error}"); traceback.print_exc(); return None
@@ -484,6 +527,9 @@ async def run_bot_cycle_async():
                 trades_to_reanalyze = [t for t in open_trades if now >= datetime.fromisoformat(t.get('expected_target_time', now.isoformat()))]
                 if trades_to_reanalyze:
                     print(f"🔄 إعادة تحليل {len(trades_to_reanalyze)} صفقة (باستخدام MC المتقدم)")
+                    # 🔴 سيتم تشغيل هذه الدالة (re_analyze_open_trade_async)
+                    # وستقوم باستخدام قفل "state_manager.trade_analysis_lock"
+                    # مما يوقف المراقب التكتيكي مؤقتاً لتلك العملة
                     reanalysis_results = await asyncio.gather(*[re_analyze_open_trade_async(trade) for trade in trades_to_reanalyze], return_exceptions=True)
                     for i, result in enumerate(reanalysis_results):
                          trade = trades_to_reanalyze[i] 
@@ -501,7 +547,9 @@ async def run_bot_cycle_async():
                 if current_capital > 1:
                     print("🎯 البحث عن فرص تداول جديدة (نظام MC ثنائي المراحل)...")
                     best_opportunity = await run_3_layer_analysis()
-                    if best_opportunity: print(f"✅ فتح صفقة جديدة: {best_opportunity['symbol']}"); await trade_manager_global.open_trade( best_opportunity['symbol'], best_opportunity['decision'], best_opportunity['current_price'])
+                    if best_opportunity: 
+                        print(f"✅ فتح صفقة جديدة: {best_opportunity['symbol']}")
+                        await trade_manager_global.open_trade( best_opportunity['symbol'], best_opportunity['decision'], best_opportunity['current_price'])
                     else: print("❌ لم يتم العثور على فرص تداول مناسبة")
                 else: print("❌ رأس المال غير كافي لفتح صفقات جديدة")
             else: print("ℹ️ يوجد صفقة مفتوحة بالفعل، تخطي البحث عن صفقة جديدة.")
@@ -523,37 +571,38 @@ async def lifespan(application: FastAPI):
         success = await initialize_services()
         if not success: print("❌ فشل تهيئة التطبيق - إغلاق..."); yield; return
         asyncio.create_task(monitor_market_async())
+        # 🔴 بدء مراقبة الصفقات (المراقب التكتيكي)
         asyncio.create_task(trade_manager_global.start_trade_monitoring())
         await r2_service_global.save_system_logs_async({"application_started": True})
         print("🎯 التطبيق جاهز للعمل - نظام الطبقات 3 (MC ثنائي المراحل) فعال")
+        print("   -> 📈 المراقب التكتيكي (Dynamic Exit) نشط الآن")
         yield
     except Exception as error: 
         print(f"❌ Application startup failed: {error}"); 
         traceback.print_exc() 
         if r2_service_global: 
             await r2_service_global.save_system_logs_async({ "application_startup_failed": True, "error": str(error) })
-        # الإصلاح: فصل raise إلى سطر جديد 
-        raise # Correct indentation
+        raise 
     finally: 
         await cleanup_on_shutdown()
 
 
-application = FastAPI(lifespan=lifespan, title="AI Trading Bot", description="نظام تداول ذكي بتحليل مونت كارلو ثنائي المراحل (GARCH+LGBM)", version="3.3.0")
+application = FastAPI(lifespan=lifespan, title="AI Trading Bot", description="نظام تداول ذكي بتحليل مونت كارلو ثنائي المراحل (GARCH+LGBM) مع إدارة خروج ديناميكية", version="3.4.0") # 🔴
 
 @application.get("/")
-async def root(): return {"message": "مرحباً بك في نظام التداول الذكي", "system": "3-Layer Analysis System (Two-Stage MC: GARCH+LGBM)", "status": "running" if state_manager.initialization_complete else "initializing", "timestamp": datetime.now().isoformat()}
+async def root(): return {"message": "مرحباً بك في نظام التداول الذكي", "system": "3-Layer Analysis System (Dynamic Exit Management)", "status": "running" if state_manager.initialization_complete else "initializing", "timestamp": datetime.now().isoformat()}
 @application.get("/run-cycle")
 async def run_cycle_api():
     if not state_manager.initialization_complete: raise HTTPException(status_code=503, detail="الخدمات غير مهيأة بالكامل")
     asyncio.create_task(run_bot_cycle_async())
-    return {"message": "Bot cycle initiated (Two-Stage MC)", "system": "3-Layer Analysis"}
+    return {"message": "Bot cycle initiated (Dynamic Exit Management)", "system": "3-Layer Analysis"}
 @application.get("/health")
-async def health_check(): return {"status": "healthy" if state_manager.initialization_complete else "initializing", "initialization_complete": state_manager.initialization_complete, "services_initialized": state_manager.services_initialized, "initialization_error": state_manager.initialization_error, "timestamp": datetime.now().isoformat(), "system_architecture": "3-Layer Analysis System (Two-Stage MC: GARCH+LGBM)", "layers": {"layer1": "Data Manager - Rapid Screening", "layer1.5": "Whale Data Fetcher (Async)", "layer2": "ML Processor (MC-Phase1 Filter)", "layer2.5": "Advanced MC (GARCH+LGBM) for Top 10", "layer3": "LLM Service - Deep Analysis"}}
+async def health_check(): return {"status": "healthy" if state_manager.initialization_complete else "initializing", "initialization_complete": state_manager.initialization_complete, "services_initialized": state_manager.services_initialized, "initialization_error": state_manager.initialization_error, "timestamp": datetime.now().isoformat(), "system_architecture": "3-Layer Analysis System (Dynamic Exit Management)", "layers": {"layer1": "Data Manager - Rapid Screening", "layer1.5": "Whale Data Fetcher (Async)", "layer2": "ML Processor (MC-Phase1 Filter)", "layer2.5": "Advanced MC (GARCH+LGBM) for Top 10", "layer3": "LLM Service - Strategic Decision + Exit Profile", "TacticalLayer": "TradeManager - Dynamic Exit Monitor (1-min)"}}
 @application.get("/analyze-market")
 async def analyze_market_api():
     if not state_manager.initialization_complete: raise HTTPException(status_code=503, detail="الخدمات غير مهيأة بالكامل")
     result = await run_3_layer_analysis()
-    if result: return {"opportunity_found": True, "symbol": result['symbol'], "action": result['decision'].get('action'), "confidence": result['llm_confidence'], "strategy": result['strategy']}
+    if result: return {"opportunity_found": True, "symbol": result['symbol'], "action": result['decision'].get('action'), "confidence": result['llm_confidence'], "strategy": result['strategy'], "exit_profile": result['decision'].get('exit_profile')}
     else: return {"opportunity_found": False, "message": "No suitable opportunities found"}
 @application.get("/portfolio")
 async def get_portfolio_api():
@@ -568,7 +617,11 @@ async def cleanup_on_shutdown():
     print("🛑 Shutdown signal received. Cleaning up...")
     if trade_manager_global: trade_manager_global.stop_monitoring(); print("✅ Trade monitoring stopped")
     if learning_engine_global and learning_engine_global.initialized:
-        try: await learning_engine_global.save_weights_to_r2(); await learning_engine_global.save_performance_history(); print("✅ Learning engine data saved")
+        try: 
+            await learning_engine_global.save_weights_to_r2(); 
+            await learning_engine_global.save_performance_history(); 
+            await learning_engine_global.save_exit_profile_effectiveness(); # 🔴 حفظ بيانات الخروج
+            print("✅ Learning engine data saved")
         except Exception as e: print(f"❌ Failed to save learning engine data: {e}")
     if data_manager_global: await data_manager_global.close(); print("✅ Data manager closed")
     if r2_service_global:
@@ -580,5 +633,5 @@ def signal_handler(signum, frame): print(f"🛑 Received signal {signum}. Initia
 signal.signal(signal.SIGINT, signal_handler); signal.signal(signal.SIGTERM, signal_handler)
 
 if __name__ == "__main__": 
-    print("🚀 Starting AI Trading Bot with 3-Layer Analysis System (Two-Stage MC: GARCH+LGBM)...")
+    print("🚀 Starting AI Trading Bot with 3-Layer Analysis System (Dynamic Exit Management)...")
     uvicorn.run( application, host="0.0.0.0", port=7860, log_level="info", access_log=True )