rl cob agent
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Dobromir Popov
321
run_realtime_rl_cob_trader.py
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321
run_realtime_rl_cob_trader.py
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#!/usr/bin/env python3
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"""
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Real-time RL COB Trader Launcher
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Launch script for the real-time reinforcement learning trader that:
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1. Uses COB data for training a 1B parameter model
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2. Performs inference every 200ms
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3. Accumulates confident signals for trade execution
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4. Trains continuously in real-time based on outcomes
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This script provides a complete trading system integration.
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"""
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import asyncio
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import logging
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import signal
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import sys
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import json
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import os
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from datetime import datetime
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from typing import Dict, Any
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# Local imports
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from core.realtime_rl_cob_trader import RealtimeRLCOBTrader
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from core.trading_executor import TradingExecutor
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from core.config import load_config
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler('logs/realtime_rl_cob_trader.log'),
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logging.StreamHandler(sys.stdout)
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]
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)
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logger = logging.getLogger(__name__)
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class RealtimeRLCOBTraderLauncher:
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"""
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Launcher for Real-time RL COB Trader system
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"""
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def __init__(self, config_path: str = "config.yaml"):
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"""Initialize launcher with configuration"""
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self.config = load_config(config_path)
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self.trader = None
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self.trading_executor = None
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self.running = False
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# Setup signal handlers for graceful shutdown
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signal.signal(signal.SIGINT, self._signal_handler)
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signal.signal(signal.SIGTERM, self._signal_handler)
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logger.info("RealtimeRLCOBTraderLauncher initialized")
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def _signal_handler(self, signum, frame):
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"""Handle shutdown signals"""
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logger.info(f"Received signal {signum}, initiating graceful shutdown...")
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self.running = False
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async def start(self):
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"""Start the real-time RL COB trading system"""
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try:
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logger.info("=" * 60)
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logger.info("REAL-TIME RL COB TRADER SYSTEM STARTING")
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logger.info("=" * 60)
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# Initialize trading executor
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await self._initialize_trading_executor()
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# Initialize RL trader
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await self._initialize_rl_trader()
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# Start the trading system
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await self._start_trading_system()
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# Run main loop
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await self._run_main_loop()
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except Exception as e:
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logger.error(f"Critical error in trader launcher: {e}")
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raise
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finally:
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await self.stop()
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async def _initialize_trading_executor(self):
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"""Initialize the trading executor"""
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logger.info("Initializing Trading Executor...")
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# Get trading configuration
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trading_config = self.config.get('trading', {})
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mexc_config = self.config.get('mexc', {})
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# Determine if we should run in simulation mode
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simulation_mode = mexc_config.get('simulation_mode', True)
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if simulation_mode:
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logger.info("Running in SIMULATION mode - no real trades will be executed")
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else:
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logger.warning("Running in LIVE TRADING mode - real money at risk!")
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# Add safety confirmation for live trading
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confirmation = input("Type 'CONFIRM_LIVE_TRADING' to proceed with live trading: ")
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if confirmation != 'CONFIRM_LIVE_TRADING':
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logger.info("Live trading not confirmed, switching to simulation mode")
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simulation_mode = True
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# Initialize trading executor
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self.trading_executor = TradingExecutor(
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simulation_mode=simulation_mode,
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mexc_config=mexc_config
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)
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logger.info(f"Trading Executor initialized in {'SIMULATION' if simulation_mode else 'LIVE'} mode")
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async def _initialize_rl_trader(self):
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"""Initialize the RL trader"""
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logger.info("Initializing Real-time RL COB Trader...")
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# Get RL configuration
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rl_config = self.config.get('realtime_rl', {})
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# Trading symbols
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symbols = rl_config.get('symbols', ['BTC/USDT', 'ETH/USDT'])
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# RL parameters
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inference_interval_ms = rl_config.get('inference_interval_ms', 200)
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min_confidence_threshold = rl_config.get('min_confidence_threshold', 0.7)
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required_confident_predictions = rl_config.get('required_confident_predictions', 3)
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model_checkpoint_dir = rl_config.get('model_checkpoint_dir', 'models/realtime_rl_cob')
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# Initialize RL trader
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self.trader = RealtimeRLCOBTrader(
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symbols=symbols,
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trading_executor=self.trading_executor,
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model_checkpoint_dir=model_checkpoint_dir,
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inference_interval_ms=inference_interval_ms,
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min_confidence_threshold=min_confidence_threshold,
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required_confident_predictions=required_confident_predictions
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)
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logger.info(f"RL Trader initialized for symbols: {symbols}")
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logger.info(f"Inference interval: {inference_interval_ms}ms")
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logger.info(f"Confidence threshold: {min_confidence_threshold}")
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logger.info(f"Required predictions: {required_confident_predictions}")
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async def _start_trading_system(self):
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"""Start the complete trading system"""
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logger.info("Starting Real-time RL COB Trading System...")
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# Start RL trader (this will start COB integration internally)
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await self.trader.start()
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self.running = True
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logger.info("✅ Real-time RL COB Trading System started successfully!")
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logger.info("🔥 1B parameter model training and inference active")
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logger.info("📊 COB data streaming and processing")
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logger.info("🎯 Signal accumulation and trade execution ready")
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logger.info("⚡ Real-time training on prediction outcomes")
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async def _run_main_loop(self):
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"""Main monitoring and statistics loop"""
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logger.info("Starting main monitoring loop...")
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last_stats_time = datetime.now()
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stats_interval = 60 # Print stats every 60 seconds
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while self.running:
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try:
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# Sleep for a bit
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await asyncio.sleep(10)
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# Print periodic statistics
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current_time = datetime.now()
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if (current_time - last_stats_time).total_seconds() >= stats_interval:
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await self._print_performance_stats()
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last_stats_time = current_time
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except asyncio.CancelledError:
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break
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except Exception as e:
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logger.error(f"Error in main loop: {e}")
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await asyncio.sleep(5)
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logger.info("Main monitoring loop stopped")
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async def _print_performance_stats(self):
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"""Print comprehensive performance statistics"""
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try:
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if not self.trader:
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return
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stats = self.trader.get_performance_stats()
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logger.info("=" * 80)
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logger.info("🔥 REAL-TIME RL COB TRADER PERFORMANCE STATISTICS")
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logger.info("=" * 80)
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# Model information
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logger.info("📊 Model Information:")
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for symbol, model_info in stats.get('model_info', {}).items():
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total_params = model_info.get('total_parameters', 0)
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logger.info(f" {symbol}: {total_params:,} parameters ({total_params/1e9:.2f}B)")
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# Training statistics
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logger.info("\n🧠 Training Statistics:")
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for symbol, training_stats in stats.get('training_stats', {}).items():
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total_preds = training_stats.get('total_predictions', 0)
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successful_preds = training_stats.get('successful_predictions', 0)
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success_rate = (successful_preds / max(1, total_preds)) * 100
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avg_loss = training_stats.get('average_loss', 0.0)
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training_steps = training_stats.get('total_training_steps', 0)
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last_training = training_stats.get('last_training_time')
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logger.info(f" {symbol}:")
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logger.info(f" Predictions: {total_preds} (Success: {success_rate:.1f}%)")
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logger.info(f" Training Steps: {training_steps}")
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logger.info(f" Average Loss: {avg_loss:.6f}")
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if last_training:
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logger.info(f" Last Training: {last_training}")
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# Inference statistics
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logger.info("\n⚡ Inference Statistics:")
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for symbol, inference_stats in stats.get('inference_stats', {}).items():
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total_inferences = inference_stats.get('total_inferences', 0)
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avg_time = inference_stats.get('average_inference_time_ms', 0.0)
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last_inference = inference_stats.get('last_inference_time')
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logger.info(f" {symbol}:")
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logger.info(f" Total Inferences: {total_inferences}")
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logger.info(f" Average Time: {avg_time:.1f}ms")
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if last_inference:
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logger.info(f" Last Inference: {last_inference}")
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# Signal statistics
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logger.info("\n🎯 Signal Accumulation:")
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for symbol, signal_stats in stats.get('signal_stats', {}).items():
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current_signals = signal_stats.get('current_signals', 0)
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confidence_sum = signal_stats.get('confidence_sum', 0.0)
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success_rate = signal_stats.get('success_rate', 0.0) * 100
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logger.info(f" {symbol}:")
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logger.info(f" Current Signals: {current_signals}")
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logger.info(f" Confidence Sum: {confidence_sum:.2f}")
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logger.info(f" Historical Success Rate: {success_rate:.1f}%")
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# Trading executor statistics
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if self.trading_executor:
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positions = self.trading_executor.get_positions()
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trade_history = self.trading_executor.get_trade_history()
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logger.info("\n💰 Trading Statistics:")
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logger.info(f" Active Positions: {len(positions)}")
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logger.info(f" Total Trades: {len(trade_history)}")
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if trade_history:
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# Calculate P&L statistics
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total_pnl = sum(trade.pnl for trade in trade_history)
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profitable_trades = sum(1 for trade in trade_history if trade.pnl > 0)
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win_rate = (profitable_trades / len(trade_history)) * 100
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logger.info(f" Total P&L: ${total_pnl:.2f}")
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logger.info(f" Win Rate: {win_rate:.1f}%")
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# Show active positions
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if positions:
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logger.info("\n📍 Active Positions:")
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for symbol, position in positions.items():
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logger.info(f" {symbol}: {position.side} {position.quantity:.6f} @ ${position.entry_price:.2f}")
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logger.info("=" * 80)
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except Exception as e:
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logger.error(f"Error printing performance stats: {e}")
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async def stop(self):
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"""Stop the trading system gracefully"""
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if not self.running:
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return
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logger.info("Stopping Real-time RL COB Trading System...")
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self.running = False
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# Stop RL trader
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if self.trader:
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await self.trader.stop()
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logger.info("✅ RL Trader stopped")
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# Print final statistics
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if self.trader:
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logger.info("\n📊 Final Performance Summary:")
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await self._print_performance_stats()
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logger.info("Real-time RL COB Trading System stopped successfully")
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async def main():
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"""Main entry point"""
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try:
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# Create logs directory if it doesn't exist
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os.makedirs('logs', exist_ok=True)
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# Initialize and start launcher
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launcher = RealtimeRLCOBTraderLauncher()
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await launcher.start()
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except KeyboardInterrupt:
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logger.info("Received keyboard interrupt, shutting down...")
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except Exception as e:
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logger.error(f"Critical error: {e}")
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raise
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if __name__ == "__main__":
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# Set event loop policy for Windows compatibility
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if hasattr(asyncio, 'WindowsProactorEventLoopPolicy'):
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asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
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asyncio.run(main())
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