merge and kill task fixes

web/clean_dashboard.py

@@ -279,9 +279,12 @@ class CleanTradingDashboard:
             logger.warning(f"Error loading config settings, using defaults: {e}")
             # Keep default values
         
+        # Initialize starting balance for metrics tracking
+        self.starting_balance = self._get_initial_balance()
+        
         # Initialize layout and component managers
         self.layout_manager = DashboardLayoutManager(
-            starting_balance=self._get_initial_balance(),
+            starting_balance=self.starting_balance,
             trading_executor=self.trading_executor,
             dashboard=self
         )
@@ -323,7 +326,6 @@ class CleanTradingDashboard:
         self._sync_ui_state_from_orchestrator()
         
         # Trading mode and cold start settings from config
-        from core.config import get_config
         config = get_config()
         
         # Initialize trading mode from config (default to simulation)
@@ -2916,6 +2918,80 @@ class CleanTradingDashboard:
         # Return None if absolutely nothing available
         return None
     
+    def _check_exchange_connection(self) -> bool:
+        """Check if exchange connection is available"""
+        try:
+            # Check if data provider is connected
+            if hasattr(self.data_provider, 'is_connected'):
+                return self.data_provider.is_connected()
+            
+            # Check if trading executor has active exchange connection
+            if hasattr(self.trading_executor, 'is_connected'):
+                return self.trading_executor.is_connected()
+            
+            # Check if we can get current price (indicates connection)
+            if hasattr(self.data_provider, 'get_current_price'):
+                try:
+                    price = self.data_provider.get_current_price('ETH/USDT')
+                    return price is not None and price > 0
+                except Exception:
+                    return False
+            
+            # Default to True if we can't determine (avoid false negatives)
+            return True
+            
+        except Exception as e:
+            logger.debug(f"Error checking exchange connection: {e}")
+            return False
+    
+    def _train_all_models_on_prediction(self, signal: Dict):
+        """Train all models on prediction result"""
+        try:
+            # Get prediction outcome for training
+            prediction_outcome = self._get_prediction_outcome_for_training(signal)
+            if not prediction_outcome:
+                return
+            
+            # Delegate to orchestrator's training system if available
+            if hasattr(self.orchestrator, 'train_on_signal'):
+                try:
+                    self.orchestrator.train_on_signal(signal, prediction_outcome)
+                    return
+                except Exception as e:
+                    logger.debug(f"Orchestrator training failed: {e}")
+            
+            # Fallback: Train individual models
+            try:
+                # Train DQN on prediction
+                if hasattr(self, '_train_dqn_on_prediction'):
+                    self._train_dqn_on_prediction(signal, prediction_outcome)
+            except Exception as e:
+                logger.debug(f"DQN training failed: {e}")
+            
+            try:
+                # Train CNN on prediction
+                if hasattr(self, '_train_cnn_on_prediction'):
+                    self._train_cnn_on_prediction(signal, prediction_outcome)
+            except Exception as e:
+                logger.debug(f"CNN training failed: {e}")
+            
+            try:
+                # Train Transformer on prediction
+                if hasattr(self, '_train_transformer_on_prediction'):
+                    self._train_transformer_on_prediction(signal, prediction_outcome)
+            except Exception as e:
+                logger.debug(f"Transformer training failed: {e}")
+            
+            try:
+                # Train COB RL on prediction
+                if hasattr(self, '_train_cob_rl_on_prediction'):
+                    self._train_cob_rl_on_prediction(signal, prediction_outcome)
+            except Exception as e:
+                logger.debug(f"COB RL training failed: {e}")
+                
+        except Exception as e:
+            logger.debug(f"Error training models on prediction: {e}")
+    
     def _create_price_chart(self, symbol: str, show_pivots: bool = True, return_legend: bool = False):
         """Create 1-minute main chart with 1-second mini chart - Updated every second
         If return_legend is True, returns (figure, legend_children) and keeps legend out of chart to avoid scale issues.