Update ml_engine/processor.py

ml_engine/processor.py

@@ -1,6 +1,5 @@
-# ============================================================
-# 🧠 ml_engine/processor.py (V35.1 - GEM-Architect: Adaptive Affinity)
-# ============================================================
+# ml_engine/processor.py
+# (V35.2 - GEM-Architect: Volume Flow Aware)
 
 import asyncio
 import traceback
@@ -10,39 +9,21 @@ import sys
 import numpy as np
 from typing import Dict, Any, List, Optional
 
-# --- استيراد المحركات (كما هي) ---
-try:
-    from .titan_engine import TitanEngine
+try: from .titan_engine import TitanEngine
 except ImportError: TitanEngine = None
-
-try:
-    from .patterns import ChartPatternAnalyzer
+try: from .patterns import ChartPatternAnalyzer
 except ImportError: ChartPatternAnalyzer = None
-
-try:
-    from .monte_carlo import MonteCarloEngine
+try: from .monte_carlo import MonteCarloEngine
 except ImportError: MonteCarloEngine = None
-
-try:
-    from .oracle_engine import OracleEngine
+try: from .oracle_engine import OracleEngine
 except ImportError: OracleEngine = None
-
-try:
-    from .sniper_engine import SniperEngine
+try: from .sniper_engine import SniperEngine
 except ImportError: SniperEngine = None
-
-# ✅ استيراد الحارسين
-try:
-    from .hybrid_guardian import HybridDeepSteward
+try: from .hybrid_guardian import HybridDeepSteward
 except ImportError: HybridDeepSteward = None
-
-try:
-    from .guardian_hydra import GuardianHydra
+try: from .guardian_hydra import GuardianHydra
 except ImportError: GuardianHydra = None
 
-# ============================================================
-# 📂 مسارات النماذج (كما هي)
-# ============================================================
 BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 MODELS_L2_DIR = os.path.join(BASE_DIR, "ml_models", "layer2")
 MODELS_PATTERN_DIR = os.path.join(BASE_DIR, "ml_models", "xgboost_pattern2")
@@ -53,39 +34,22 @@ MODEL_V2_PATH = os.path.join(BASE_DIR, "ml_models", "DeepSteward_V2_Production.j
 MODEL_V3_PATH = os.path.join(BASE_DIR, "ml_models", "DeepSteward_V3_Production.json")
 MODEL_V3_FEAT = os.path.join(BASE_DIR, "ml_models", "DeepSteward_V3_Features.json")
 
-# ============================================================
-# 🎛️ SYSTEM LIMITS & THRESHOLDS (UPDATED)
-# ============================================================
 class SystemLimits:
-    """GEM-Architect: The Central Constitution (Updated for Affinity Logic)."""
-    
-    # --- Layer 1 (Data Manager Control) ---
-    # هذا هو المتغير الجديد الذي سيتحكم به النظام التكيفي
-    # كلما زاد الرقم، زادت صرامة الفلتر (يتطلب توافقاً أعلى مع النماذج)
     L1_MIN_AFFINITY_SCORE = 10
-    
-    # --- Layer 2 Weights ---
     L2_WEIGHT_TITAN    = 0.50
     L2_WEIGHT_PATTERNS = 0.40
     L2_WEIGHT_MC       = 0.10
-
     PATTERN_TF_WEIGHTS = {'15m': 0.40, '1h': 0.30, '5m': 0.20, '4h': 0.10, '1d': 0.00}
     PATTERN_THRESH_BULLISH = 0.60
     PATTERN_THRESH_BEARISH = 0.40
-
-    # --- Layer 3 ---
     L3_CONFIDENCE_THRESHOLD = 0.65
     L3_WHALE_IMPACT_MAX = 0.10
     L3_NEWS_IMPACT_MAX  = 0.05
     L3_MC_ADVANCED_MAX  = 0.10
-
-    # --- Layer 4 ---
     L4_ENTRY_THRESHOLD  = 0.30
     L4_WEIGHT_ML        = 0.60
     L4_WEIGHT_OB        = 0.40
     L4_OB_WALL_RATIO    = 0.40
-
-    # --- Layer 0: Hydra Thresholds ---
     HYDRA_CRASH_THRESH      = 0.60
     HYDRA_GIVEBACK_THRESH   = 0.70
     HYDRA_STAGNATION_THRESH = 0.50
@@ -93,7 +57,6 @@ class SystemLimits:
     @classmethod
     def to_dict(cls) -> Dict[str, Any]:
         return {k: v for k, v in cls.__dict__.items() if not k.startswith('__') and not callable(v)}
-
     @classmethod
     def update_from_dict(cls, config: Dict[str, Any]):
         if not config: return
@@ -101,14 +64,10 @@ class SystemLimits:
             if hasattr(cls, k): setattr(cls, k, v)
         print("🔄 [SystemLimits] Config Updated.")
 
-# ============================================================
-# 🧠 MLProcessor Class (باقي الكود كما هو تماماً)
-# ============================================================
 class MLProcessor:
     def __init__(self, data_manager=None):
         self.data_manager = data_manager
         self.initialized = False
-        
         self.titan = TitanEngine(model_dir=MODELS_L2_DIR) if TitanEngine else None
         self.pattern_engine = ChartPatternAnalyzer(models_dir=MODELS_PATTERN_DIR) if ChartPatternAnalyzer else None
         self.mc_analyzer = MonteCarloEngine() if MonteCarloEngine else None
@@ -126,12 +85,10 @@ class MLProcessor:
                 v3_model_path=MODEL_V3_PATH,
                 v3_features_map_path=MODEL_V3_FEAT
             )
-
-        print(f"🧠 [MLProcessor V35.1] Affinity-Ready Limits Online.")
+        print(f"🧠 [MLProcessor V35.2] 30m-Depth Logic Ready.")
 
     async def initialize(self):
         if self.initialized: return
-        print("⚙️ [Processor] Initializing Neural Grid...")
         try:
             tasks = []
             if self.titan: tasks.append(self.titan.initialize())
@@ -143,7 +100,6 @@ class MLProcessor:
                 tasks.append(self.oracle.initialize())
             if self.sniper: 
                 if hasattr(self.sniper, 'configure_settings'): 
-                    # ✅ GEM-Architect Update: Pass Weights explicitly
                     self.sniper.configure_settings(
                         threshold=SystemLimits.L4_ENTRY_THRESHOLD, 
                         wall_ratio=SystemLimits.L4_OB_WALL_RATIO,
@@ -151,33 +107,23 @@ class MLProcessor:
                         w_ob=SystemLimits.L4_WEIGHT_OB
                     )
                 tasks.append(self.sniper.initialize())
-            
             if tasks: await asyncio.gather(*tasks)
 
             if self.guardian_hydra: 
                 self.guardian_hydra.initialize()
-                print("   🛡️ [Guard 1] Hydra X-Ray: Active")
-            
             if self.guardian_legacy:
-                if asyncio.iscoroutinefunction(self.guardian_legacy.initialize):
-                    await self.guardian_legacy.initialize()
-                else:
-                    self.guardian_legacy.initialize()
-                print("   🛡️ [Guard 2] Legacy Steward: Active")
+                if asyncio.iscoroutinefunction(self.guardian_legacy.initialize): await self.guardian_legacy.initialize()
+                else: self.guardian_legacy.initialize()
 
             self.initialized = True
-            print("✅ [Processor] All Systems Operational.")
             
         except Exception as e:
             print(f"❌ [Processor FATAL] Init failed: {e}")
             traceback.print_exc()
 
     async def process_compound_signal(self, raw_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
-        # (نفس المنطق السابق تماماً - لم يتغير)
         if not self.initialized: await self.initialize()
-        symbol = raw_data.get('symbol')
-        ohlcv_data = raw_data.get('ohlcv')
-        current_price = raw_data.get('current_price', 0.0)
+        symbol = raw_data.get('symbol'); ohlcv_data = raw_data.get('ohlcv'); current_price = raw_data.get('current_price', 0.0)
         if not symbol or not ohlcv_data: return None
         try:
             score_titan = 0.5; titan_res = {}
@@ -198,7 +144,6 @@ class MLProcessor:
             return {'symbol': symbol, 'current_price': current_price, 'enhanced_final_score': hybrid_score, 'titan_score': score_titan, 'patterns_score': score_patterns, 'mc_score': mc_score, 'components': {'titan_score': score_titan, 'patterns_score': score_patterns, 'mc_score': mc_score}, 'pattern_name': pattern_name, 'ohlcv': ohlcv_data, 'titan_details': titan_res, 'pattern_details': pattern_res.get('details', {})}
         except Exception: return None
 
-    # (باقي الدوال: consult_oracle, check_sniper_entry, consult_dual_guardians, run_advanced_monte_carlo كما هي)
     async def consult_oracle(self, symbol_data: Dict[str, Any]) -> Dict[str, Any]:
         if not self.initialized: await self.initialize()
         if self.oracle:
@@ -215,36 +160,47 @@ class MLProcessor:
         if self.sniper: return await self.sniper.check_entry_signal_async(ohlcv_1m_data, order_book_data)
         return {'signal': 'WAIT', 'reason': 'Sniper Engine Missing'}
 
-    def consult_dual_guardians(self, symbol, ohlcv_1m, ohlcv_5m, ohlcv_15m, trade_context):
-        # (نفس كود الدالة السابقة دون تغيير)
+    # ✅ GEM-Architect Update: Now accepts volume_30m from context
+    def consult_dual_guardians(self, symbol, ohlcv_1m, ohlcv_5m, ohlcv_15m, trade_context, order_book_snapshot=None):
         response = {'action': 'HOLD', 'detailed_log': '', 'probs': {}}
+        
+        # 1. Hydra (Unchanged)
         hydra_result = {'action': 'HOLD', 'reason': 'Disabled', 'probs': {}}
         if self.guardian_hydra and self.guardian_hydra.initialized:
             hydra_result = self.guardian_hydra.analyze_position(symbol, ohlcv_1m, ohlcv_5m, ohlcv_15m, trade_context)
             h_probs = hydra_result.get('probs', {})
-            p_crash = h_probs.get('crash', 0.0)
-            p_giveback = h_probs.get('giveback', 0.0)
+            p_crash = h_probs.get('crash', 0.0); p_giveback = h_probs.get('giveback', 0.0)
             if hydra_result['action'] == 'HOLD':
                 if p_crash >= SystemLimits.HYDRA_CRASH_THRESH:
                     hydra_result['action'] = 'EXIT_HARD'; hydra_result['reason'] = f"Hydra Crash Risk {p_crash:.2f}"
                 elif p_giveback >= SystemLimits.HYDRA_GIVEBACK_THRESH:
                     hydra_result['action'] = 'EXIT_SOFT'; hydra_result['reason'] = f"Hydra Giveback Risk {p_giveback:.2f}"
         
+        # 2. Legacy (Volume-Aware Veto)
         legacy_result = {'action': 'HOLD', 'reason': 'Disabled', 'scores': {}}
         if self.guardian_legacy and self.guardian_legacy.initialized:
             entry_price = float(trade_context.get('entry_price', 0.0))
-            legacy_result = self.guardian_legacy.analyze_position(ohlcv_1m, ohlcv_5m, ohlcv_15m, entry_price)
+            # Extract 30m Volume from Context
+            vol_30m = trade_context.get('volume_30m_usd', 0.0)
+            
+            legacy_result = self.guardian_legacy.analyze_position(
+                ohlcv_1m, ohlcv_5m, ohlcv_15m, entry_price, 
+                order_book=order_book_snapshot,
+                volume_30m_usd=vol_30m
+            )
 
-        h_probs = hydra_result.get('probs', {}); h_c = h_probs.get('crash', 0.0); h_g = h_probs.get('giveback', 0.0); h_s = h_probs.get('stagnation', 0.0)
-        l_scores = legacy_result.get('scores', {}); l_v2 = l_scores.get('v2', 0.0); l_v3 = l_scores.get('v3', 0.0)
-        stamp_str = f"🐲[C:{h_c:.0%}|G:{h_g:.0%}|S:{h_s:.0%}] 🕸️[V2:{l_v2:.0%}|V3:{l_v3:.0%}]"
+        # 3. Final Arbitration
+        h_probs = hydra_result.get('probs', {}); l_scores = legacy_result.get('scores', {})
+        h_c = h_probs.get('crash', 0.0); h_g = h_probs.get('giveback', 0.0)
+        l_v2 = l_scores.get('v2', 0.0); l_v3 = l_scores.get('v3', 0.0)
+        stamp_str = f"🐲[C:{h_c:.0%}|G:{h_g:.0%}] 🕸️[V2:{l_v2:.0%}|V3:{l_v3:.0%}]"
 
         final_action = 'HOLD'; final_reason = f"Safe. {stamp_str}"
-        if hydra_result['action'] == 'EXIT_HARD': final_action = 'EXIT_HARD'; final_reason = f"🚨 HYDRA KILL: {hydra_result['reason']} | {stamp_str}"
-        elif legacy_result['action'] == 'EXIT_HARD': final_action = 'EXIT_HARD'; final_reason = f"🚨 LEGACY KILL: {legacy_result['reason']} | {stamp_str}"
-        elif hydra_result['action'] == 'EXIT_SOFT': final_action = 'EXIT_SOFT'; final_reason = f"⚠️ HYDRA WARN: {hydra_result['reason']} | {stamp_str}"
-        elif legacy_result['action'] == 'EXIT_SOFT': final_action = 'EXIT_SOFT'; final_reason = f"⚠️ LEGACY WARN: {legacy_result['reason']} | {stamp_str}"
-        elif hydra_result['action'] in ['TIGHTEN_SL', 'TRAIL_SL']: final_action = hydra_result['action']; final_reason = f"🛡️ {hydra_result['action']} | {stamp_str}"
+        
+        if hydra_result['action'] in ['EXIT_HARD', 'EXIT_SOFT', 'TIGHTEN_SL', 'TRAIL_SL']:
+             final_action = hydra_result['action']; final_reason = f"🐲 HYDRA: {hydra_result['reason']} | {stamp_str}"
+        elif legacy_result['action'] in ['EXIT_HARD', 'EXIT_SOFT']:
+             final_action = legacy_result['action']; final_reason = f"🕸️ LEGACY: {legacy_result['reason']} | {stamp_str}"
 
         return {'action': final_action, 'reason': final_reason, 'detailed_log': f"{final_action} | {stamp_str}", 'probs': h_probs, 'scores': l_scores}
 
@@ -252,8 +208,6 @@ class MLProcessor:
         if self.mc_analyzer and self.data_manager:
             try:
                 ohlcv = await self.data_manager.get_latest_ohlcv(symbol, timeframe, limit=300)
-                if ohlcv:
-                    closes = [c[4] for c in ohlcv]
-                    return self.mc_analyzer.run_advanced_simulation(closes)
+                if ohlcv: return self.mc_analyzer.run_advanced_simulation([c[4] for c in ohlcv])
             except Exception: pass
         return 0.0