Initial commit - production deployment

services/training/app/core/config.py

@@ -0,0 +1,89 @@
+# ================================================================
+# TRAINING SERVICE CONFIGURATION
+# services/training/app/core/config.py
+# ================================================================
+
+"""
+Training service configuration
+ML model training and management
+"""
+
+from shared.config.base import BaseServiceSettings
+import os
+
+class TrainingSettings(BaseServiceSettings):
+    """Training service specific settings"""
+    
+    # Service Identity
+    APP_NAME: str = "Training Service"
+    SERVICE_NAME: str = "training-service"
+    DESCRIPTION: str = "Machine learning model training service"
+    
+    # Database configuration (secure approach - build from components)
+    @property
+    def DATABASE_URL(self) -> str:
+        """Build database URL from secure components"""
+        # Try complete URL first (for backward compatibility)
+        complete_url = os.getenv("TRAINING_DATABASE_URL")
+        if complete_url:
+            return complete_url
+
+        # Build from components (secure approach)
+        user = os.getenv("TRAINING_DB_USER", "training_user")
+        password = os.getenv("TRAINING_DB_PASSWORD", "training_pass123")
+        host = os.getenv("TRAINING_DB_HOST", "localhost")
+        port = os.getenv("TRAINING_DB_PORT", "5432")
+        name = os.getenv("TRAINING_DB_NAME", "training_db")
+
+        return f"postgresql+asyncpg://{user}:{password}@{host}:{port}/{name}"
+    
+    # Redis Database (dedicated for training cache)
+    REDIS_DB: int = 1
+    
+    # ML Model Storage
+    MODEL_BACKUP_ENABLED: bool = os.getenv("MODEL_BACKUP_ENABLED", "true").lower() == "true"
+    MODEL_VERSIONING_ENABLED: bool = os.getenv("MODEL_VERSIONING_ENABLED", "true").lower() == "true"
+    
+    # MinIO Configuration
+    MINIO_ENDPOINT: str = os.getenv("MINIO_ENDPOINT", "minio.bakery-ia.svc.cluster.local:9000")
+    MINIO_ACCESS_KEY: str = os.getenv("MINIO_ACCESS_KEY", "training-service")
+    MINIO_SECRET_KEY: str = os.getenv("MINIO_SECRET_KEY", "training-secret-key")
+    MINIO_USE_SSL: bool = os.getenv("MINIO_USE_SSL", "true").lower() == "true"
+    MINIO_MODEL_BUCKET: str = os.getenv("MINIO_MODEL_BUCKET", "training-models")
+    MINIO_CONSOLE_PORT: str = os.getenv("MINIO_CONSOLE_PORT", "9001")
+    MINIO_API_PORT: str = os.getenv("MINIO_API_PORT", "9000")
+    MINIO_REGION: str = os.getenv("MINIO_REGION", "us-east-1")
+    MINIO_MODEL_LIFECYCLE_DAYS: int = int(os.getenv("MINIO_MODEL_LIFECYCLE_DAYS", "90"))
+    MINIO_CACHE_TTL_SECONDS: int = int(os.getenv("MINIO_CACHE_TTL_SECONDS", "3600"))
+    
+    # Training Configuration
+    MAX_CONCURRENT_TRAINING_JOBS: int = int(os.getenv("MAX_CONCURRENT_TRAINING_JOBS", "3"))
+    
+    # Prophet Specific Configuration
+    PROPHET_HOLIDAYS_PRIOR_SCALE: float = float(os.getenv("PROPHET_HOLIDAYS_PRIOR_SCALE", "10.0"))
+    
+    # Spanish Holiday Integration
+    ENABLE_CUSTOM_HOLIDAYS: bool = os.getenv("ENABLE_CUSTOM_HOLIDAYS", "true").lower() == "true"
+    
+    # Data Processing
+    DATA_PREPROCESSING_ENABLED: bool = True
+    OUTLIER_DETECTION_ENABLED: bool = os.getenv("OUTLIER_DETECTION_ENABLED", "true").lower() == "true"
+    SEASONAL_DECOMPOSITION_ENABLED: bool = os.getenv("SEASONAL_DECOMPOSITION_ENABLED", "true").lower() == "true"
+    
+    # Model Validation
+    CROSS_VALIDATION_ENABLED: bool = os.getenv("CROSS_VALIDATION_ENABLED", "true").lower() == "true"
+    VALIDATION_SPLIT_RATIO: float = float(os.getenv("VALIDATION_SPLIT_RATIO", "0.2"))
+    MIN_MODEL_ACCURACY: float = float(os.getenv("MIN_MODEL_ACCURACY", "0.7"))
+    
+    # Distributed Training (for future scaling)
+    DISTRIBUTED_TRAINING_ENABLED: bool = os.getenv("DISTRIBUTED_TRAINING_ENABLED", "false").lower() == "true"
+    TRAINING_WORKER_COUNT: int = int(os.getenv("TRAINING_WORKER_COUNT", "1"))
+    
+    PROPHET_DAILY_SEASONALITY: bool = True
+    PROPHET_WEEKLY_SEASONALITY: bool = True
+    PROPHET_YEARLY_SEASONALITY: bool = True
+
+    # Throttling settings for parallel training to prevent heartbeat blocking
+    MAX_CONCURRENT_TRAININGS: int = int(os.getenv("MAX_CONCURRENT_TRAININGS", "3"))
+
+settings = TrainingSettings()