Create adaptive_hub.py

learning_hub/adaptive_hub.py

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+# learning_hub/adaptive_hub.py
+# (V33.0 - R2 Persistence Enabled)
+
+import json
+import asyncio
+import traceback
+from datetime import datetime
+from collections import deque
+from typing import Dict, Any, List
+
+from ml_engine.processor import SystemLimits
+
+class AdaptiveHub:
+    def __init__(self, r2_service=None):
+        self.r2 = r2_service
+        # اسم الملف الذي سنحفظ فيه الأوزان والعتبات في R2
+        self.config_key = "learning/adaptive_system_config.json"
+        
+        self.recent_results = deque(maxlen=20)
+        self.current_regime = "NEUTRAL"
+        self.wins = 0
+        self.losses = 0
+        self.consecutive_losses = 0
+        
+        print("🧠 [AdaptiveHub] Meta-Learner Online (R2 Persistence).")
+
+    async def initialize(self):
+        """تحميل الإعدادات المحفوظة من R2 عند بدء التشغيل"""
+        if not self.r2: return
+
+        print(f"📥 [AdaptiveHub] Loading config from R2: {self.config_key}...")
+        try:
+            # 1. جلب الملف من R2
+            # ملاحظة: تأكد أن r2_service لديه دالة get_file_async وتعمل بشكل صحيح
+            data_bytes = await self.r2.get_file_async(self.config_key)
+            
+            if data_bytes:
+                saved_state = json.loads(data_bytes)
+                
+                # A. استعادة حالة التعلم (الذاكرة)
+                self.current_regime = saved_state.get("regime", "NEUTRAL")
+                self.wins = saved_state.get("stats", {}).get("wins", 0)
+                self.losses = saved_state.get("stats", {}).get("losses", 0)
+                self.recent_results = deque(saved_state.get("history", []), maxlen=20)
+                
+                # B. استعادة عتبات النظام (تطبيقها على SystemLimits)
+                thresholds = saved_state.get("thresholds", {})
+                SystemLimits.update_from_dict(thresholds)
+                
+                print(f"✅ [AdaptiveHub] Restored Regime: {self.current_regime}")
+            else:
+                print("⚠️ [AdaptiveHub] No saved config found. Using defaults.")
+                self._apply_neutral_settings() # البدء بوضع محايد
+
+        except Exception as e:
+            print(f"❌ [AdaptiveHub] Load failed: {e}")
+            # في حال الفشل، نعود للافتراضي للأمان
+            self._apply_neutral_settings()
+
+    async def register_trade_outcome(self, trade_data: Dict[str, Any]):
+        try:
+            pnl = trade_data.get('profit_pct', 0.0)
+            is_win = pnl > 0
+            
+            self.recent_results.append(1 if is_win else 0)
+            if is_win:
+                self.wins += 1
+                self.consecutive_losses = 0
+            else:
+                self.losses += 1
+                self.consecutive_losses += 1
+
+            # تقييم وتعديل (في الذاكرة)
+            await self._evaluate_and_adapt()
+            
+            # حفظ الحالة الجديدة (في R2)
+            await self._save_state_to_r2()
+            
+        except Exception as e:
+            print(f"❌ [AdaptiveHub] Error analyzing trade: {e}")
+
+    async def _evaluate_and_adapt(self):
+        # ... (نفس منطق التقييم السابق: DEFENSIVE / AGGRESSIVE / NEUTRAL) ...
+        # (الكود هنا مطابق للرد السابق، لا تغيير في المنطق، فقط نستدعي Apply settings)
+        
+        win_rate_window = sum(self.recent_results) / len(self.recent_results) if self.recent_results else 0.5
+        
+        if self.consecutive_losses >= 3 or (len(self.recent_results) >= 10 and win_rate_window < 0.3):
+            if self.current_regime != "DEFENSIVE":
+                print("🛡️ [AdaptiveHub] -> DEFENSIVE Mode.")
+                self.current_regime = "DEFENSIVE"
+                self._apply_defensive_settings()
+                
+        elif len(self.recent_results) >= 10 and win_rate_window > 0.7:
+            if self.current_regime != "AGGRESSIVE":
+                print("🚀 [AdaptiveHub] -> AGGRESSIVE Mode.")
+                self.current_regime = "AGGRESSIVE"
+                self._apply_aggressive_settings()
+        else:
+            if self.current_regime != "NEUTRAL":
+                print("⚖️ [AdaptiveHub] -> NEUTRAL Mode.")
+                self.current_regime = "NEUTRAL"
+                self._apply_neutral_settings()
+
+    def _apply_defensive_settings(self):
+        # تطبيق القيم في الذاكرة (RAM)
+        SystemLimits.L1_MIN_QUOTE_VOLUME = 5_000_000
+        SystemLimits.L1_MAX_PUMP_4H = 5.0
+        SystemLimits.L1_MAX_RSI = 60.0
+        SystemLimits.L3_CONFIDENCE_THRESHOLD = 0.75
+        SystemLimits.L4_ENTRY_THRESHOLD = 0.55
+        SystemLimits.HYDRA_CRASH_THRESH = 0.50
+
+    def _apply_aggressive_settings(self):
+        SystemLimits.L1_MIN_QUOTE_VOLUME = 500_000
+        SystemLimits.L1_MAX_PUMP_4H = 15.0
+        SystemLimits.L1_MAX_RSI = 75.0
+        SystemLimits.L3_CONFIDENCE_THRESHOLD = 0.55
+        SystemLimits.L4_ENTRY_THRESHOLD = 0.40
+        SystemLimits.HYDRA_CRASH_THRESH = 0.75
+
+    def _apply_neutral_settings(self):
+        SystemLimits.L1_MIN_QUOTE_VOLUME = 1_000_000
+        SystemLimits.L1_MAX_PUMP_4H = 8.0
+        SystemLimits.L1_MAX_RSI = 70.0
+        SystemLimits.L3_CONFIDENCE_THRESHOLD = 0.65
+        SystemLimits.L4_ENTRY_THRESHOLD = 0.45
+        SystemLimits.HYDRA_CRASH_THRESH = 0.60
+
+    async def _save_state_to_r2(self):
+        """حفظ الحالة الحالية + قيم العتبات في ملف JSON"""
+        if not self.r2: return
+        
+        try:
+            # تجميع البيانات
+            state_packet = {
+                "last_updated": datetime.now().isoformat(),
+                "regime": self.current_regime,
+                "history": list(self.recent_results),
+                "stats": {"wins": self.wins, "losses": self.losses},
+                
+                # ✅ الأهم: حفظ القيم الحالية للعتبات
+                "thresholds": SystemLimits.to_dict()
+            }
+            
+            # رفع الملف
+            await self.r2.upload_json_async(state_packet, self.config_key)
+            # print("💾 [AdaptiveHub] System State & Thresholds Saved to R2.")
+            
+        except Exception as e:
+            print(f"❌ [AdaptiveHub] Save to R2 failed: {e}")
+
+    def get_status(self):
+        win_rate = (self.wins / (self.wins + self.losses)) * 100 if (self.wins + self.losses) > 0 else 0
+        return f"Regime: {self.current_regime} | WR: {win_rate:.1f}% | Trend: {sum(self.recent_results)}/{len(self.recent_results)}"