main cleanup

main_dashboard.py

@@ -0,0 +1,157 @@
+#!/usr/bin/env python3
+"""
+Real-time Trading Dashboard & Live Training
+
+Main entry point for:
+- Live market data streaming
+- Real-time model training
+- Web dashboard visualization  
+- Live trading execution
+
+Usage:
+    python main_dashboard.py [--port 8051] [--no-training]
+    
+Examples:
+    # Full system with training
+    python main_dashboard.py --port 8051
+    
+    # Dashboard only (no training)
+    python main_dashboard.py --port 8051 --no-training
+"""
+
+import os
+import sys
+import logging
+import argparse
+from typing import Optional
+
+# Add project root to path
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+# Import core components
+try:
+    from core.config import setup_logging
+    from core.data_provider import DataProvider
+    from core.orchestrator import TradingOrchestrator
+    from core.trading_executor import TradingExecutor
+    from web.clean_dashboard import create_clean_dashboard
+except ImportError as e:
+    print(f"Error importing core modules: {e}")
+    sys.exit(1)
+
+logger = logging.getLogger(__name__)
+
+def create_safe_orchestrator() -> Optional[TradingOrchestrator]:
+    """Create orchestrator with safe CNN model handling"""
+    try:
+        # Create orchestrator with basic configuration (uses correct constructor parameters)
+        orchestrator = TradingOrchestrator(
+            enhanced_rl_training=True  # Enable RL training for model improvement
+        )
+        
+        logger.info("Trading orchestrator created successfully")
+        return orchestrator
+        
+    except Exception as e:
+        logger.error(f"Error creating orchestrator: {e}")
+        logger.info("Continuing without orchestrator - dashboard will run in view-only mode")
+        return None
+
+def create_safe_trading_executor() -> Optional[TradingExecutor]:
+    """Create trading executor with safe configuration"""
+    try:
+        # TradingExecutor only accepts config_path parameter
+        trading_executor = TradingExecutor(config_path="config.yaml")
+        
+        logger.info("Trading executor created successfully")
+        return trading_executor
+        
+    except Exception as e:
+        logger.error(f"Error creating trading executor: {e}")
+        logger.info("Continuing without trading executor - dashboard will be view-only")
+        return None
+
+def main():
+    """Main entry point for realtime dashboard"""
+    parser = argparse.ArgumentParser(description='Real-time Trading Dashboard')
+    parser.add_argument('--port', type=int, default=8051, help='Dashboard port (default: 8051)')
+    parser.add_argument('--host', type=str, default='127.0.0.1', help='Dashboard host (default: 127.0.0.1)')
+    parser.add_argument('--debug', action='store_true', help='Enable debug mode')
+    parser.add_argument('--no-training', action='store_true', help='Disable ML training for stability')
+    
+    args = parser.parse_args()
+    
+    # Setup logging
+    try:
+        setup_logging()
+        logger.info("=" * 80)
+        logger.info("REAL-TIME TRADING DASHBOARD & LIVE TRAINING")
+        logger.info("=" * 80)
+        logger.info(f"Dashboard: http://{args.host}:{args.port}")
+        logger.info(f"Training: {'DISABLED' if args.no_training else 'ENABLED'}")
+        logger.info("Features: Real-time Charts, Trading Interface, Model Monitoring")
+        logger.info("=" * 80)
+    except Exception as e:
+        print(f"Error setting up logging: {e}")
+        # Continue without logging setup
+    
+    # Set environment variables for optimization
+    os.environ['ENABLE_REALTIME_CHARTS'] = '1'
+    if not args.no_training:
+        os.environ['ENABLE_NN_MODELS'] = '1'
+    
+    try:
+        # Model Selection at Startup
+        logger.info("Performing intelligent model selection...")
+        try:
+            from utils.model_selector import select_and_load_best_models
+            selected_models, loaded_models = select_and_load_best_models()
+            logger.info(f"Selected {len(selected_models)} model types, loaded {len(loaded_models)} models")
+        except Exception as e:
+            logger.warning(f"Model selection failed, using defaults: {e}")
+            selected_models, loaded_models = {}, {}
+
+        # Create data provider
+        logger.info("Initializing data provider...")
+        data_provider = DataProvider(symbols=['ETH/USDT', 'BTC/USDT'])
+
+        # Create orchestrator (with safe CNN handling)
+        logger.info("Initializing trading orchestrator...")
+        orchestrator = create_safe_orchestrator()
+        
+        # Create trading executor
+        logger.info("Initializing trading executor...")
+        trading_executor = create_safe_trading_executor()
+        
+        # Create and run dashboard
+        logger.info("Creating dashboard...")
+        dashboard = create_clean_dashboard(
+            data_provider=data_provider,
+            orchestrator=orchestrator,
+            trading_executor=trading_executor
+        )
+        
+        # Start the dashboard server
+        logger.info(f"Starting dashboard server on http://{args.host}:{args.port}")
+        dashboard.run_server(
+            host=args.host,
+            port=args.port,
+            debug=args.debug
+        )
+        
+    except KeyboardInterrupt:
+        logger.info("Dashboard stopped by user")
+    except Exception as e:
+        logger.error(f"Error running dashboard: {e}")
+        
+        # Try to provide helpful error message
+        if "model.fit" in str(e) or "CNN" in str(e):
+            logger.error("CNN model training error detected. Try running with --no-training flag")
+            logger.error("Command: python main_dashboard.py --no-training")
+        
+        sys.exit(1)
+    finally:
+        logger.info("Dashboard shutdown complete")
+
+if __name__ == '__main__':
+    main()