cloud_run_server.py

"""
Cloud Run server - Handles HTTP requests for trading predictions

Routes:
- /weekday - Runs LSTM make_predictions_on_next_data() every 15 minutes on weekdays (Mon-Fri)
- /mlp_minute - Runs MLP make_predictions_on_next_data() every 1 minute

Schedules:
- Weekday: Every 15 minutes from 8:01 AM to 4:46 PM CST (Monday-Friday) - triggered by Cloud Scheduler
- MLP Minute: Every 1 minute - triggered by Cloud Scheduler
"""

import functions_framework
from datetime import datetime
import logging
import json
import os

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


@functions_framework.http
def run_server(request):
    """
    Main Cloud Run server endpoint
    Handles prediction requests for both LSTM and MLP strategies
    
    Routes:
    - /weekday: LSTM strategy - Every 15 minutes from 8:01 AM to 4:46 PM CST, Monday-Friday
    - /mlp_minute: MLP strategy - Every 1 minute
    """
    try:
        # Get the route from the request path
        path = request.path.strip('/')
        
        logger.info("=" * 80)
        logger.info(f"🚀 Request received: {path}")
        logger.info(f"   Method: {request.method}")
        logger.info(f"   Execution time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
        logger.info("=" * 80)
        
        if path == 'weekday' or path == 'weekday_predict_stocks':
            # Weekday prediction: LSTM make_predictions_on_next_data()
            # Schedule: Every 15 minutes from 8:01 AM to 4:46 PM CST (Monday-Friday)
            # Triggered by: Cloud Scheduler with schedule "1,16,31,46 8-16 * * 1-5"
            
            logger.info("📅 Running weekday LSTM prediction (make_predictions_on_next_data)...")
            import importlib
            main_module = importlib.import_module('lstm_strategy_main')
            main_module.make_predictions_on_next_data()
            
            logger.info("=" * 80)
            logger.info("✅ Weekday LSTM prediction completed successfully")
            logger.info("=" * 80)
            
            response_data = {
                'status': 'success',
                'message': 'Weekday LSTM predictions completed and saved to Firebase',
                'timestamp': datetime.now().isoformat()
            }
            return json.dumps(response_data), 200, {'Content-Type': 'application/json'}
            
        elif path == 'mlp_minute' or path == 'mlp_predict':
            # MLP prediction: make_predictions_on_next_data()
            # Schedule: Every 1 minute
            # Triggered by: Cloud Scheduler with schedule "* * * * *" (every minute)
            
            logger.info("⏱️ Running MLP prediction (make_predictions_on_next_data)...")
            import importlib
            mlp_module = importlib.import_module('mlp_strategy_main')
            mlp_module.make_predictions_on_next_data()
            
            logger.info("=" * 80)
            logger.info("✅ MLP prediction completed successfully")
            logger.info("=" * 80)
            
            response_data = {
                'status': 'success',
                'message': 'MLP predictions completed and saved to Firebase',
                'timestamp': datetime.now().isoformat()
            }
            return json.dumps(response_data), 200, {'Content-Type': 'application/json'}
            
        elif path == '' or path == 'health':
            # Health check endpoint
            return json.dumps({'status': 'healthy', 'timestamp': datetime.now().isoformat()}), 200, {'Content-Type': 'application/json'}
            
        else:
            # Unknown route
            response_data = {
                'status': 'error',
                'message': f'Unknown route: {path}. Use /weekday or /mlp_minute',
                'timestamp': datetime.now().isoformat()
            }
            return json.dumps(response_data), 404, {'Content-Type': 'application/json'}
        
    except Exception as e:
        logger.error("=" * 80)
        logger.error(f"❌ Error in Cloud Run server: {str(e)}", exc_info=True)
        logger.error("=" * 80)
        response_data = {
            'status': 'error',
            'message': str(e),
            'timestamp': datetime.now().isoformat()
        }
        return json.dumps(response_data), 500, {'Content-Type': 'application/json'}