Update learning_hub/adaptive_hub.py

learning_hub/adaptive_hub.py

@@ -1,6 +1,6 @@
 # ==============================================================================
 # 🧠 learning_hub/adaptive_hub.py 
-# (V60.1 - GEM-Architect: Golden Values + Full Sync)
+# (V61.0 - GEM-Architect: Per-Asset Context Injection)
 # ==============================================================================
 
 import json
@@ -76,10 +76,10 @@ class StrategyDNA:
 class AdaptiveHub:
     def __init__(self, r2_service=None):
         self.r2 = r2_service
-        self.dna_file_key = "learning/strategic_dna_v60_layered.json" 
+        self.dna_file_key = "learning/strategic_dna_v61_context.json" 
         self.current_market_regime = "RANGE"
         self.strategies: Dict[str, StrategyDNA] = {}
-        print("🧠 [AdaptiveHub V60.1] Golden DNA Injection Active.")
+        print("🧠 [AdaptiveHub V61.0] Per-Asset Context Engine Ready.")
 
     def get_learning_progress(self) -> str:
         """يعيد نسبة التقدم في التعلم السريع"""
@@ -125,7 +125,7 @@ class AdaptiveHub:
 
         # 2. BEAR MARKET (Golden Config)
         d_guards_bear = {"hydra_crash": 0.60, "hydra_giveback": 0.60, "legacy_v2": 0.85}
-        d_filters_bear = {"l1_min_score": 0.60, "l3_oracle_thresh": 0.75, "l4_sniper_thresh": 0.30} # Sniper lower
+        d_filters_bear = {"l1_min_score": 0.60, "l3_oracle_thresh": 0.75, "l4_sniper_thresh": 0.30} 
         
         self.strategies["BEAR"] = StrategyDNA(
             "BEAR", 
@@ -172,6 +172,36 @@ class AdaptiveHub:
             self.strategies[key] = dna
         self.current_market_regime = data.get("current_regime", "RANGE")
 
+    # ============================================================
+    # 🧬 CONTEXT API (Per-Asset Injection)
+    # ============================================================
+    def get_regime_config(self, regime_name: str) -> Dict[str, Any]:
+        """
+        💎 Returns the specific configuration (DNA) for a given market regime.
+        Used to inject 'Per-Asset' limits dynamically.
+        """
+        target_regime = regime_name if regime_name in self.strategies else "RANGE"
+        dna = self.strategies[target_regime]
+        filters = dna.get_final_filters()
+        guards = dna.get_final_guards()
+        mw = dna.model_weights
+        
+        return {
+            "regime": target_regime,
+            # Layer 2 Weights
+            "w_titan": mw.get("titan", 0.4),
+            "w_patt": mw.get("structure", 0.3),
+            # Layer 3 & 4 Thresholds
+            "l1_min_score": filters.get("l1_min_score", 0.65),
+            "l3_oracle_thresh": filters.get("l3_oracle_thresh", 0.65),
+            "l4_sniper_thresh": filters.get("l4_sniper_thresh", 0.40),
+            "l4_ob_wall_ratio": dna.ob_settings.get("wall_ratio_limit", 0.4),
+            # Guard Thresholds
+            "hydra_crash": guards.get('hydra_crash', 0.85),
+            "hydra_giveback": guards.get('hydra_giveback', 0.70),
+            "legacy_v2": guards.get('legacy_v2', 0.95)
+        }
+
     # ============================================================
     # 🧪 STRATEGIC BACKTEST LINK (Base Updater)
     # ============================================================
@@ -275,6 +305,7 @@ class AdaptiveHub:
     # 💉 INJECTION
     # ============================================================
     def _inject_current_parameters(self):
+        """Injects Global Fallback Parameters"""
         if self.current_market_regime not in self.strategies or SystemLimits is None: return
         dna = self.strategies[self.current_market_regime]