pivots

core/orchestrator.py

@@ -136,6 +136,11 @@ class TradingOrchestrator:
         self.recent_decisions: Dict[str, List[TradingDecision]] = {}    # {symbol: List[TradingDecision]}
         self.model_performance: Dict[str, Dict[str, Any]] = {}   # {model_name: {'correct': int, 'total': int, 'accuracy': float}}
         
+        # Signal rate limiting to prevent spam
+        self.last_signal_time: Dict[str, Dict[str, datetime]] = {}  # {symbol: {action: datetime}}
+        self.min_signal_interval = timedelta(seconds=30)  # Minimum 30 seconds between same signals
+        self.last_confirmed_signal: Dict[str, Dict[str, Any]] = {}  # {symbol: {action, timestamp, confidence}}
+        
         # Signal accumulation for trend confirmation
         self.signal_accumulator: Dict[str, List[Dict]] = {}  # {symbol: List[signal_data]}
         self.required_confirmations = 3  # Number of consistent signals needed
@@ -871,6 +876,22 @@ class TradingOrchestrator:
             'CNN': self.config.orchestrator.get('cnn_weight', 0.7),
             'RL': self.config.orchestrator.get('rl_weight', 0.3)
         }
+        
+        # Add weights for specific models if they exist
+        if hasattr(self, 'cnn_model') and self.cnn_model:
+            self.model_weights["enhanced_cnn"] = 0.4
+            
+        # Only add DQN agent weight if it exists
+        if hasattr(self, 'rl_agent') and self.rl_agent:
+            self.model_weights["dqn_agent"] = 0.3
+            
+        # Add COB RL model weight if it exists
+        if hasattr(self, 'cob_rl_agent') and self.cob_rl_agent:
+            self.model_weights["cob_rl_model"] = 0.2
+            
+        # Add extrema trainer weight if it exists
+        if hasattr(self, 'extrema_trainer') and self.extrema_trainer:
+            self.model_weights["extrema_trainer"] = 0.15
     
     def register_model(self, model: ModelInterface, weight: Optional[float] = None) -> bool:
         """Register a new model with the orchestrator"""
@@ -1960,10 +1981,27 @@ class TradingOrchestrator:
         logger.info("Trading executor set for position tracking and P&L feedback")
     
     def _check_signal_confirmation(self, symbol: str, signal_data: Dict) -> Optional[str]:
-        """Check if we have enough signal confirmations for trend confirmation"""
+        """Check if we have enough signal confirmations for trend confirmation with rate limiting"""
         try:
-            # Clean up expired signals
             current_time = signal_data['timestamp']
+            action = signal_data['action']
+            
+            # Initialize signal tracking for this symbol if needed
+            if symbol not in self.last_signal_time:
+                self.last_signal_time[symbol] = {}
+            if symbol not in self.last_confirmed_signal:
+                self.last_confirmed_signal[symbol] = {}
+            
+            # RATE LIMITING: Check if we recently confirmed the same signal
+            if action in self.last_confirmed_signal[symbol]:
+                last_confirmed = self.last_confirmed_signal[symbol][action]
+                time_since_last = current_time - last_confirmed['timestamp']
+                if time_since_last < self.min_signal_interval:
+                    logger.debug(f"Rate limiting: {action} signal for {symbol} too recent "
+                               f"({time_since_last.total_seconds():.1f}s < {self.min_signal_interval.total_seconds()}s)")
+                    return None
+            
+            # Clean up expired signals
             self.signal_accumulator[symbol] = [
                 s for s in self.signal_accumulator[symbol] 
                 if (current_time - s['timestamp']).total_seconds() < self.signal_timeout_seconds
@@ -1982,8 +2020,8 @@ class TradingOrchestrator:
             
             # Count action consensus
             action_counts = {}
-            for action in actions:
-                action_counts[action] = action_counts.get(action, 0) + 1
+            for action_item in actions:
+                action_counts[action_item] = action_counts.get(action_item, 0) + 1
             
             # Find dominant action
             dominant_action = max(action_counts, key=action_counts.get)
@@ -1991,8 +2029,24 @@ class TradingOrchestrator:
             
             # Require at least 2/3 consensus
             if consensus_count >= max(2, self.required_confirmations * 0.67):
+                # ADDITIONAL RATE LIMITING: Don't confirm if we just confirmed the same action
+                if dominant_action in self.last_confirmed_signal[symbol]:
+                    last_confirmed = self.last_confirmed_signal[symbol][dominant_action]
+                    time_since_last = current_time - last_confirmed['timestamp']
+                    if time_since_last < self.min_signal_interval:
+                        logger.debug(f"Rate limiting: Preventing duplicate {dominant_action} confirmation for {symbol}")
+                        return None
+                
+                # Record this confirmation
+                self.last_confirmed_signal[symbol][dominant_action] = {
+                    'timestamp': current_time,
+                    'confidence': signal_data['confidence']
+                }
+                
                 # Clear accumulator after confirmation
                 self.signal_accumulator[symbol] = []
+                
+                logger.info(f"Signal confirmed after rate limiting: {dominant_action} for {symbol}")
                 return dominant_action
             
             return None