#!/usr/bin/env python3
"""
Test script to verify model stats functionality
"""

import sys
import os
sys.path.append(os.path.dirname(os.path.abspath(__file__)))

import logging
from core.orchestrator import TradingOrchestrator

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def test_model_stats():
    """Test the model stats functionality"""
    try:
        logger.info("Testing model stats functionality...")
        
        # Create orchestrator instance (this will initialize model states)
        orchestrator = TradingOrchestrator()
        
        # Sync with dashboard values
        orchestrator.sync_model_states_with_dashboard()
        
        # Get current model stats
        stats = orchestrator.get_model_training_stats()
        
        logger.info("Current model training stats:")
        for model_name, model_stats in stats.items():
            if model_stats['current_loss'] is not None:
                logger.info(f"  {model_name.upper()}: {model_stats['current_loss']:.4f} loss, {model_stats['improvement_pct']:.1f}% improvement")
            else:
                logger.info(f"  {model_name.upper()}: No training data yet")
        
        # Test updating a model loss
        orchestrator.update_model_loss('cnn', 0.0001)
        logger.info("Updated CNN loss to 0.0001")
        
        # Get updated stats
        updated_stats = orchestrator.get_model_training_stats()
        cnn_stats = updated_stats['cnn']
        logger.info(f"CNN updated: {cnn_stats['current_loss']:.4f} loss, {cnn_stats['improvement_pct']:.1f}% improvement")
        
        return True
        
    except Exception as e:
        logger.error(f"❌ Model stats test failed: {e}")
        return False

if __name__ == "__main__":
    success = test_model_stats()
    sys.exit(0 if success else 1)