Update learning_hub/adaptive_hub.py

learning_hub/adaptive_hub.py

@@ -1,26 +1,22 @@
 # ==============================================================================
 # 🧠 learning_hub/adaptive_hub.py 
-# (V53.0 - GEM-Architect: Structure-Aware Core)
+# (V54.0 - GEM-Architect: Time Lord Support)
 # ==============================================================================
 
 import json
 import asyncio
 import traceback
-from datetime import datetime
-from collections import deque
-from typing import Dict, Any, List, Optional
+from typing import Dict, Any, List
 
-# استيراد الحدود المركزية
 from ml_engine.processor import SystemLimits
 
 class StrategyDNA:
     def __init__(self, name, model_weights, ob_settings, filters, guard_settings=None):
         self.name = name
-        self.model_weights = model_weights  # أوزان النماذج (Titan, Sniper, Structure)
-        self.ob_settings = ob_settings      # إعدادات دفتر الطلبات
-        self.filters = filters              # فلاتر L1 (Thresholds)
-        self.guard_settings = guard_settings if guard_settings else {} 
-        
+        self.model_weights = model_weights
+        self.ob_settings = ob_settings
+        self.filters = filters
+        self.guard_settings = guard_settings if guard_settings else {}
         self.stats = {"wins": 0, "losses": 0, "win_rate": 0.0}
 
     def to_dict(self):
@@ -36,168 +32,54 @@ class StrategyDNA:
 class AdaptiveHub:
     def __init__(self, r2_service=None):
         self.r2 = r2_service
-        # قمنا بتحديث مفتاح الملف لضمان عدم تحميل إعدادات قديمة متعارضة
         self.dna_file_key = "learning/strategic_dna_v5_struct.json" 
         self.current_market_regime = "RANGE"
         self.strategies: Dict[str, StrategyDNA] = {}
-        
-        self.TACTICAL_LEARNING_RATE = 0.05 
-        print("🧠 [AdaptiveHub V53.0] Structure-Aware Core Initialized.")
+        print("🧠 [AdaptiveHub V54.0] Time Lord Core Initialized.")
 
     async def initialize(self):
-        print(f"📥 [AdaptiveHub] Loading Strategy DNA from R2...")
         try:
             if self.r2:
                 data_bytes = await self.r2.get_file_async(self.dna_file_key)
                 if data_bytes:
                     saved_data = json.loads(data_bytes)
                     self._load_from_dict(saved_data)
-                    print("✅ [AdaptiveHub] DNA Loaded Successfully.")
                 else:
-                    print("⚠️ [AdaptiveHub] No DNA found. Creating Default Genomes.")
                     self._create_default_dna()
             else:
                 self._create_default_dna()
-                
             self._inject_current_parameters()
-            
-        except Exception as e:
-            print(f"❌ [AdaptiveHub] Init Failed: {e}")
-            traceback.print_exc()
+        except Exception:
             self._create_default_dna()
 
     def _create_default_dna(self):
-        """
-        إنشاء الإعدادات الافتراضية مع دعم وزن الهيكل (Structure Weight)
-        """
-        default_guards = {
-            "hydra_crash": 0.85, "hydra_giveback": 0.70,
-            "legacy_v2": 0.95, "legacy_v3": 0.95
-        }
-
-        # ملاحظة: تم استبدال 'patterns' بـ 'structure' في model_weights
-
-        # 1. BULL: تركيز متوازن بين Titan والهيكل
-        self.strategies["BULL"] = StrategyDNA(
-            name="BULL",
-            # Titan: الذكاء الاصطناعي | Structure: الفلتر الهندسي الجديد
-            model_weights={"titan": 0.50, "structure": 0.30, "sniper": 0.20},
-            ob_settings={"wall_ratio_limit": 0.60, "imbalance_thresh": 0.5},
-            filters={"l1_min_score": 0.55, "l3_conf_thresh": 0.60},
-            guard_settings=default_guards
-        )
-
-        # 2. BEAR: اعتماد أكبر على الهيكل (Structure) لتجنب الإشارات الكاذبة
-        self.strategies["BEAR"] = StrategyDNA(
-            name="BEAR",
-            model_weights={"titan": 0.30, "structure": 0.40, "sniper": 0.30},
-            ob_settings={"wall_ratio_limit": 0.30, "imbalance_thresh": 0.7},
-            filters={"l1_min_score": 0.75, "l3_conf_thresh": 0.75}, 
-            guard_settings=default_guards
-        )
-
-        # 3. RANGE: التوازن المثالي
-        self.strategies["RANGE"] = StrategyDNA(
-            name="RANGE",
-            model_weights={"titan": 0.40, "structure": 0.40, "sniper": 0.20},
-            ob_settings={"wall_ratio_limit": 0.40, "imbalance_thresh": 0.6},
-            filters={"l1_min_score": 0.65, "l3_conf_thresh": 0.65},
-            guard_settings=default_guards
-        )
+        default_guards = {"hydra_crash": 0.85, "hydra_giveback": 0.70, "legacy_v2": 0.95, "legacy_v3": 0.95}
         
-        # DEAD Mode
-        self.strategies["DEAD"] = StrategyDNA(
-            name="DEAD",
-            model_weights={"titan": 0.25, "structure": 0.25, "sniper": 0.25},
-            ob_settings={"wall_ratio_limit": 0.20, "imbalance_thresh": 0.8},
-            filters={"l1_min_score": 0.85, "l3_conf_thresh": 0.80},
-            guard_settings=default_guards
-        )
+        self.strategies["BULL"] = StrategyDNA("BULL", {"titan": 0.50, "structure": 0.30, "sniper": 0.20}, {"wall_ratio_limit": 0.60, "imbalance_thresh": 0.5}, {"l1_min_score": 0.55, "l3_conf_thresh": 0.60}, default_guards)
+        self.strategies["BEAR"] = StrategyDNA("BEAR", {"titan": 0.30, "structure": 0.40, "sniper": 0.30}, {"wall_ratio_limit": 0.30, "imbalance_thresh": 0.7}, {"l1_min_score": 0.75, "l3_conf_thresh": 0.75}, default_guards)
+        self.strategies["RANGE"] = StrategyDNA("RANGE", {"titan": 0.40, "structure": 0.40, "sniper": 0.20}, {"wall_ratio_limit": 0.40, "imbalance_thresh": 0.6}, {"l1_min_score": 0.65, "l3_conf_thresh": 0.65}, default_guards)
+        self.strategies["DEAD"] = StrategyDNA("DEAD", {"titan": 0.25, "structure": 0.25, "sniper": 0.25}, {"wall_ratio_limit": 0.20, "imbalance_thresh": 0.8}, {"l1_min_score": 0.85, "l3_conf_thresh": 0.80}, default_guards)
 
     def _load_from_dict(self, data):
         for key, val in data.get("strategies", {}).items():
-            self.strategies[key] = StrategyDNA(
-                name=val["name"],
-                model_weights=val["model_weights"],
-                ob_settings=val["ob_settings"],
-                filters=val["filters"],
-                guard_settings=val.get("guard_settings", {})
-            )
-            self.strategies[key].stats = val.get("stats", {"wins":0, "losses":0})
-        
+            self.strategies[key] = StrategyDNA(val["name"], val["model_weights"], val["ob_settings"], val["filters"], val.get("guard_settings", {}))
         self.current_market_regime = data.get("current_regime", "RANGE")
 
-    async def register_trade_outcome(self, trade_data: Dict[str, Any]):
-        try:
-            pnl = trade_data.get('profit_pct', 0.0)
-            is_win = pnl > 0
-            
-            if self.current_market_regime in self.strategies:
-                active_dna = self.strategies[self.current_market_regime]
-                if is_win: active_dna.stats["wins"] += 1
-                else: active_dna.stats["losses"] += 1
-
-        except Exception as e:
-            print(f"❌ [AdaptiveHub] Trade Analysis Error: {e}")
-            traceback.print_exc()
-
     def _inject_current_parameters(self):
-        """
-        نقل الإعدادات إلى SystemLimits.
-        الخدعة هنا: نقوم بتعيين وزن الهيكل (structure) إلى L2_WEIGHT_PATTERNS
-        لأن المعالج (Processor) يستخدم هذا المتغير لحساب الدرجة الهجينة.
-        """
-        if self.current_market_regime not in self.strategies:
-            return
-
+        if self.current_market_regime not in self.strategies: return
         active_dna = self.strategies[self.current_market_regime]
         
-        print(f"💉 [AdaptiveHub] Injecting DNA for: {self.current_market_regime}")
-        
-        # 1. حقن أوزان L2
         mw = active_dna.model_weights
         total_w = sum(mw.values()) if sum(mw.values()) > 0 else 1.0
         
         SystemLimits.L2_WEIGHT_TITAN = mw.get("titan", 0.4) / total_w
-        
-        # 🔥 التعديل الجوهري: نستخدم وزن 'structure' بدلاً من 'patterns'
-        # ونضعه في المتغير الذي يقرأه المعالج (Processor)
         SystemLimits.L2_WEIGHT_PATTERNS = mw.get("structure", 0.3) / total_w
         
-        # 2. حقن عتبة الفلتر الهيكلي
-        thresh_ratio = active_dna.filters.get("l1_min_score", 0.65)
-        raw_score_limit = (thresh_ratio * 100.0) - 20.0
+        raw_score_limit = (active_dna.filters.get("l1_min_score", 0.65) * 100.0) - 20.0
         SystemLimits.L1_MIN_AFFINITY_SCORE = raw_score_limit
-        
-        # 3. باقي الإعدادات
         SystemLimits.CURRENT_REGIME = self.current_market_regime
         SystemLimits.L3_CONFIDENCE_THRESHOLD = active_dna.filters.get("l3_conf_thresh", 0.65)
         SystemLimits.L4_OB_WALL_RATIO = active_dna.ob_settings.get("wall_ratio_limit", 0.4)
-        
-        gs = active_dna.guard_settings
-        if gs:
-            SystemLimits.HYDRA_CRASH_THRESH = gs.get('hydra_crash', 0.60)
-            SystemLimits.HYDRA_GIVEBACK_THRESH = gs.get('hydra_giveback', 0.70)
-            SystemLimits.LEGACY_V2_PANIC_THRESH = gs.get('legacy_v2', 0.95)
-            SystemLimits.LEGACY_V3_HARD_THRESH = gs.get('legacy_v3', 0.95)
-
-    def update_market_regime(self, new_regime: str):
-        if new_regime in self.strategies:
-            self.current_market_regime = new_regime
-            print(f"🔄 [AdaptiveHub] Regime Switched to: {new_regime}")
-            self._inject_current_parameters()
-
-    def get_status(self):
-        dna = self.strategies.get(self.current_market_regime)
-        if not dna: return "System Initializing..."
-        
-        thresh_ratio = dna.filters.get('l1_min_score', 0)
-        
-        # عرض الحالة مع الأوزان الجديدة
-        return (f"Regime: {self.current_market_regime} | "
-                f"L1 Thresh: {thresh_ratio:.0%} | "
-                f"Titan: {dna.model_weights.get('titan'):.2f} | "
-                f"Struct: {dna.model_weights.get('structure'):.2f}")
 
     async def _save_state_to_r2(self):
         if not self.r2: return
@@ -207,5 +89,4 @@ class AdaptiveHub:
                 "strategies": {k: v.to_dict() for k, v in self.strategies.items()}
             }
             await self.r2.upload_json_async(data, self.dna_file_key)
-        except Exception as e:
-            print(f"❌ [AdaptiveHub] Save Failed: {e}")
+        except Exception: pass