fix model mappings,dash updates, trading

run_clean_dashboard.py

@@ -125,11 +125,14 @@ def start_clean_dashboard_with_training():
         logger.info("Neural Decision Fusion: ENABLED")
         logger.info("COB Integration: ENABLED")
         logger.info("GPU Training: ENABLED")
+        logger.info("TensorBoard Integration: ENABLED")
         logger.info("Multi-symbol: ETH/USDT, BTC/USDT")
         
         # Get port from environment or use default
         dashboard_port = int(os.environ.get('DASHBOARD_PORT', '8051'))
+        tensorboard_port = int(os.environ.get('TENSORBOARD_PORT', '6006'))
         logger.info(f"Dashboard: http://127.0.0.1:{dashboard_port}")
+        logger.info(f"TensorBoard: http://127.0.0.1:{tensorboard_port}")
         logger.info("=" * 80)
         
         # Check environment variables
@@ -159,6 +162,10 @@ def start_clean_dashboard_with_training():
         # Create trading executor
         trading_executor = TradingExecutor()
         
+        # Connect trading executor to orchestrator
+        orchestrator.trading_executor = trading_executor
+        logger.info("Trading Executor connected to Orchestrator")
+        
         # Import clean dashboard
         from web.clean_dashboard import create_clean_dashboard
         
@@ -185,12 +192,30 @@ def start_clean_dashboard_with_training():
         # Wait a moment for training to initialize
         time.sleep(3)
         
+        # Start TensorBoard in background
+        from web.tensorboard_integration import get_tensorboard_integration
+        tensorboard_port = int(os.environ.get('TENSORBOARD_PORT', '6006'))
+        tensorboard_integration = get_tensorboard_integration(log_dir="runs", port=tensorboard_port)
+        
+        # Start TensorBoard server
+        tensorboard_started = tensorboard_integration.start_tensorboard(open_browser=False)
+        if tensorboard_started:
+            logger.info(f"TensorBoard started at {tensorboard_integration.get_tensorboard_url()}")
+        else:
+            logger.warning("Failed to start TensorBoard - training metrics will not be visualized")
+        
         # Start dashboard server (this blocks)
         logger.info(" Starting Clean Dashboard Server...")
         dashboard.run_server(host='127.0.0.1', port=dashboard_port, debug=False)
         
     except KeyboardInterrupt:
         logger.info("System stopped by user")
+        # Stop TensorBoard
+        try:
+            tensorboard_integration = get_tensorboard_integration()
+            tensorboard_integration.stop_tensorboard()
+        except:
+            pass
     except Exception as e:
         logger.error(f"Error running clean dashboard with training: {e}")
         import traceback