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import os
from typing import Optional
from pathlib import Path
from dotenv import load_dotenv
# Load .env file từ project root
project_root = Path(__file__).resolve().parents[2]
env_path = project_root / ".env"
load_dotenv(env_path)
class Settings:
# API Settings (đơn giản)
API_BASE_URL: str = os.getenv("API_BASE_URL", "http://localhost:3454/api")
# Gemini AI Settings
GEMINI_API_KEY: Optional[str] = os.getenv("GEMINI_API_KEY")
# Model URLs (Hugging Face)
HF_MODEL_BASE_URL: str = "https://huggingface.co/NGOC1712/transportation-models/resolve/main/"
HF_MODEL_FILES: dict = {
"xgboost_model": "xgboost_model.pkl",
"label_encoders": "all_label_encoders.joblib",
"shipment_encoders": "shipment_label_encoders.pkl",
"scaler": "scaler_weight_freight.pkl"
}
HF_TOKEN: Optional[str] = os.getenv("ACCESS")
FUNCTIONS_DIR: Path = Path(__file__).resolve().parents[1] / "domain" / "functions"
# Logging Configuration
LOG_LEVEL: str = "INFO"
LOG_FILE_ENABLED: bool = True
LOG_CONSOLE_ENABLED: bool = True
LOG_ROTATION_SIZE: int = 10 * 1024 * 1024 # 10MB
LOG_BACKUP_COUNT: int = 5
LOG_RETENTION_DAYS: int = 30
@classmethod
def get_predict_url(cls) -> str:
"""Lấy URL đầy đủ cho predict endpoint"""
return f"{cls.API_BASE_URL}/predict-transportation"
@classmethod
def get_chat_url(cls) -> str:
"""Lấy URL đầy đủ cho chat endpoint"""
return f"{cls.API_BASE_URL}/chat"
@classmethod
def validate_gemini_key(cls) -> bool:
"""Kiểm tra xem Gemini API key có được thiết lập không"""
return cls.GEMINI_API_KEY is not None and len(cls.GEMINI_API_KEY.strip()) > 0
@classmethod
def get_gemini_config(cls) -> dict:
return {
"api_key": cls.GEMINI_API_KEY
}
# Global settings instance
settings = Settings()
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