Refactor all main.py
This commit is contained in:
Urtzi Alfaro
@@ -6,144 +6,141 @@ Forecasting Service Main Application
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Demand prediction and forecasting service for bakery operations
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"""
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import structlog
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from contextlib import asynccontextmanager
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from fastapi import FastAPI, Request
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import JSONResponse
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from fastapi import FastAPI
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from app.core.config import settings
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from app.core.database import database_manager, get_db_health
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from app.core.database import database_manager
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from app.api import forecasts, predictions
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from app.services.messaging import setup_messaging, cleanup_messaging
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from app.services.forecasting_alert_service import ForecastingAlertService
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from shared.monitoring.logging import setup_logging
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from shared.monitoring.metrics import MetricsCollector
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from shared.service_base import StandardFastAPIService
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# Setup structured logging
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setup_logging("forecasting-service", settings.LOG_LEVEL)
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logger = structlog.get_logger()
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# Initialize metrics collector
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metrics_collector = MetricsCollector("forecasting-service")
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class ForecastingService(StandardFastAPIService):
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"""Forecasting Service with standardized setup"""
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# Initialize alert service
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alert_service = None
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def __init__(self):
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# Define expected database tables for health checks
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forecasting_expected_tables = [
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'forecasts', 'prediction_batches', 'model_performance_metrics', 'prediction_cache'
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]
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Application lifespan manager for startup and shutdown events"""
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# Startup
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logger.info("Starting Forecasting Service", version="1.0.0")
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try:
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# Initialize database
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logger.info("Initializing database connection")
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await database_manager.create_tables()
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logger.info("Database initialized successfully")
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# Initialize messaging
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logger.info("Setting up messaging")
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self.alert_service = None
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# Create custom checks for alert service
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async def alert_service_check():
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"""Custom health check for forecasting alert service"""
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return await self.alert_service.health_check() if self.alert_service else False
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# Define custom metrics for forecasting service
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forecasting_custom_metrics = {
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"forecasts_generated_total": {
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"type": "counter",
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"description": "Total forecasts generated"
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},
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"predictions_served_total": {
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"type": "counter",
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"description": "Total predictions served"
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},
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"prediction_errors_total": {
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"type": "counter",
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"description": "Total prediction errors"
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},
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"forecast_processing_time_seconds": {
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"type": "histogram",
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"description": "Time to process forecast request"
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},
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"prediction_processing_time_seconds": {
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"type": "histogram",
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"description": "Time to process prediction request"
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},
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"model_cache_hits_total": {
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"type": "counter",
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"description": "Total model cache hits"
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},
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"model_cache_misses_total": {
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"type": "counter",
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"description": "Total model cache misses"
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}
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}
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super().__init__(
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service_name="forecasting-service",
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app_name="Bakery Forecasting Service",
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description="AI-powered demand prediction and forecasting service for bakery operations",
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version="1.0.0",
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log_level=settings.LOG_LEVEL,
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cors_origins=settings.CORS_ORIGINS_LIST,
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api_prefix="/api/v1",
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database_manager=database_manager,
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expected_tables=forecasting_expected_tables,
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custom_health_checks={"alert_service": alert_service_check},
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enable_messaging=True,
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custom_metrics=forecasting_custom_metrics
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)
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async def _setup_messaging(self):
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"""Setup messaging for forecasting service"""
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await setup_messaging()
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logger.info("Messaging initialized")
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self.logger.info("Messaging initialized")
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async def _cleanup_messaging(self):
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"""Cleanup messaging for forecasting service"""
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await cleanup_messaging()
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async def on_startup(self, app: FastAPI):
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"""Custom startup logic for forecasting service"""
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# Initialize forecasting alert service
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logger.info("Setting up forecasting alert service")
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global alert_service
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alert_service = ForecastingAlertService(settings)
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await alert_service.start()
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logger.info("Forecasting alert service initialized")
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# Register custom metrics
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metrics_collector.register_counter("forecasts_generated_total", "Total forecasts generated")
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metrics_collector.register_counter("predictions_served_total", "Total predictions served")
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metrics_collector.register_counter("prediction_errors_total", "Total prediction errors") # ← MISSING REGISTRATION!
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metrics_collector.register_histogram("forecast_processing_time_seconds", "Time to process forecast request")
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metrics_collector.register_histogram("prediction_processing_time_seconds", "Time to process prediction request") # ← ADD MISSING METRIC!
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metrics_collector.register_gauge("active_models_count", "Number of active models")
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metrics_collector.register_counter("model_cache_hits_total", "Total model cache hits") # ← ADD USEFUL METRIC!
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metrics_collector.register_counter("model_cache_misses_total", "Total model cache misses") # ← ADD USEFUL METRIC!
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# Start metrics server
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metrics_collector.start_metrics_server(8080)
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logger.info("Forecasting Service started successfully")
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yield
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except Exception as e:
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logger.error("Failed to start Forecasting Service", error=str(e))
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raise
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finally:
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# Shutdown
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logger.info("Shutting down Forecasting Service")
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try:
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# Cleanup alert service
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if alert_service:
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await alert_service.stop()
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logger.info("Alert service cleanup completed")
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await cleanup_messaging()
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logger.info("Messaging cleanup completed")
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except Exception as e:
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logger.error("Error during messaging cleanup", error=str(e))
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self.alert_service = ForecastingAlertService(settings)
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await self.alert_service.start()
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self.logger.info("Forecasting alert service initialized")
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# Create FastAPI app with lifespan
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app = FastAPI(
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title="Bakery Forecasting Service",
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description="AI-powered demand prediction and forecasting service for bakery operations",
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version="1.0.0",
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async def on_shutdown(self, app: FastAPI):
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"""Custom shutdown logic for forecasting service"""
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# Cleanup alert service
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if self.alert_service:
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await self.alert_service.stop()
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self.logger.info("Alert service cleanup completed")
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def get_service_features(self):
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"""Return forecasting-specific features"""
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return [
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"demand_prediction",
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"ai_forecasting",
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"model_performance_tracking",
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"prediction_caching",
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"alert_notifications",
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"messaging_integration"
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]
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def setup_custom_endpoints(self):
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"""Setup custom endpoints for forecasting service"""
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@self.app.get("/alert-metrics")
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async def get_alert_metrics():
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"""Alert service metrics endpoint"""
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if self.alert_service:
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return self.alert_service.get_metrics()
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return {"error": "Alert service not initialized"}
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# Create service instance
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service = ForecastingService()
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# Create FastAPI app with standardized setup
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app = service.create_app(
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docs_url="/docs",
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redoc_url="/redoc",
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lifespan=lifespan
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redoc_url="/redoc"
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)
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# CORS middleware
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app.add_middleware(
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CORSMiddleware,
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allow_origins=settings.CORS_ORIGINS_LIST,
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Setup standard endpoints
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service.setup_standard_endpoints()
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# Setup custom endpoints
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service.setup_custom_endpoints()
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# Include API routers
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app.include_router(forecasts.router, prefix="/api/v1", tags=["forecasts"])
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app.include_router(predictions.router, prefix="/api/v1", tags=["predictions"])
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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db_health = await get_db_health()
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alert_health = await alert_service.health_check() if alert_service else {"status": "not_initialized"}
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overall_health = db_health and alert_health.get("status") == "healthy"
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return {
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"status": "healthy" if overall_health else "unhealthy",
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"service": "forecasting-service",
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"version": "1.0.0",
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"database": "connected" if db_health else "disconnected",
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"alert_service": alert_health,
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"timestamp": structlog.get_logger().info("Health check requested")
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}
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@app.get("/metrics")
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async def get_metrics():
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"""Metrics endpoint for Prometheus"""
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return metrics_collector.get_metrics()
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@app.get("/alert-metrics")
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async def get_alert_metrics():
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"""Alert service metrics endpoint"""
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if alert_service:
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return alert_service.get_metrics()
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return {"error": "Alert service not initialized"}
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service.add_router(forecasts.router, tags=["forecasts"])
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service.add_router(predictions.router, tags=["predictions"])
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if __name__ == "__main__":
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import uvicorn
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