# backend/src/api/config.py
"""
Configuration for Road Damage Detection Backend Orchestrator

Architecture:
- Local YOLO11 model (active, weight=1.0)
- Future HuggingFace Spaces for YOLO12 and SAHI (pending, weight=0.0)

When additional models are trained and deployed:
1. Update MODEL_WEIGHTS to enable them
2. Add HF_SPACES URLs
3. Set MIN_ENSEMBLE_VOTES to require agreement
"""

import os
from pydantic_settings import BaseSettings
from typing import Dict, List

class Settings(BaseSettings):
    """Global configuration for the backend orchestrator"""
    
    # API Settings
    API_TITLE: str = "Road Damage Detection - Backend Orchestrator"
    API_VERSION: str = "2.0.0"
    API_HOST: str = "0.0.0.0"
    API_PORT: int = 8001
    
    # ===========================================
    # MODEL CONFIGURATION
    # ===========================================
    
    # Model weights for ensemble voting
    # Currently: only yolo11 is active (local model)
    # Future: yolo12 and sahi on HuggingFace Spaces
    MODEL_WEIGHTS: Dict[str, float] = {
        "yolo11": 1.0,   # Active - local model (models/yolo11base.pt)
        "yolo12": 0.0,   # Pending - training in progress
        "sahi": 0.0      # Pending - training in progress
    }
    
    # Local model path (relative to backend directory)
    YOLO11_MODEL_PATH: str = "../models/yolo11base.pt"
    
    # HuggingFace Spaces URLs (for future use)
    HF_SPACES: Dict[str, str] = {
        "yolo12": "https://YOUR_USERNAME-road-damage-yolo12.hf.space",
        "sahi": "https://YOUR_USERNAME-road-damage-sahi.hf.space"
    }
    
    # ===========================================
    # INFERENCE SETTINGS
    # ===========================================
    
    # Confidence threshold for detections
    CONFIDENCE_THRESHOLD: float = 0.25
    
    # NMS IoU threshold for merging overlapping boxes
    NMS_IOU_THRESHOLD: float = 0.45
    
    # Minimum models that must agree (for future ensemble)
    # Currently set to 1 since only yolo11 is active
    MIN_ENSEMBLE_VOTES: int = 1
    
    # Image size for inference
    INFERENCE_IMG_SIZE: int = 640
    
    # ===========================================
    # GPS FALLBACK - NEAR DJI SAMPLE LOCATION
    # ===========================================
    # Based on DJI_202511261727_006 sample data GPS
    # Original: 16.009719, 108.258302 (Da Nang area)
    # Fallback: 50 meters to the right (East)
    DEFAULT_LATITUDE: float = 16.009719
    DEFAULT_LONGITUDE: float = 108.258852
    DEFAULT_ALTITUDE: float = 68.5
    
    # ===========================================
    # DAMAGE CLASS MAPPING
    # ===========================================
    # Standard RDD2022 classes
    CLASS_NAMES: Dict[int, str] = {
        0: "D00",  # Longitudinal Crack
        1: "D10",  # Transverse Crack  
        2: "D20",  # Alligator Crack
        3: "D40",  # Pothole
    }
    
    CLASS_DISPLAY_NAMES: Dict[str, str] = {
        "D00": "Longitudinal Crack",
        "D10": "Transverse Crack",
        "D20": "Alligator Crack", 
        "D40": "Pothole",
    }
    
    # ===========================================
    # SEVERITY THRESHOLDS
    # ===========================================
    # Based on damage area relative to image
    SEVERITY_THRESHOLDS: Dict[str, float] = {
        "light": 0.05,    # < 5% of image
        "medium": 0.15,   # 5-15% of image
        # > 15% = heavy
    }
    
    # ===========================================
    # FILE SETTINGS
    # ===========================================
    MAX_IMAGE_SIZE_MB: int = 50
    SUPPORTED_FORMATS: List[str] = ["jpg", "jpeg", "png", "bmp", "tiff"]
    UPLOAD_DIR: str = "data/uploads"
    
    # ===========================================
    # CORS
    # ===========================================
    ALLOWED_ORIGINS: List[str] = [
        "http://localhost:3000",
        "http://localhost:3001", 
        "http://localhost:8001",
        "http://127.0.0.1:3000",
        "http://127.0.0.1:3001",
    ]
    
    class Config:
        env_file = ".env"
        case_sensitive = True


# Global settings instance
settings = Settings()

# Update model path based on environment
if os.getenv("YOLO11_MODEL_PATH"):
    settings.YOLO11_MODEL_PATH = os.getenv("YOLO11_MODEL_PATH")

# Update HF username if provided
if os.getenv("HF_USERNAME"):
    username = os.getenv("HF_USERNAME")
    settings.HF_SPACES = {
        "yolo12": f"https://{username}-road-damage-yolo12.hf.space",
        "sahi": f"https://{username}-road-damage-sahi.hf.space"
    }