import os
from dataclasses import dataclass, field
from pathlib import Path

from dotenv import load_dotenv


BASE_DIR = Path(__file__).resolve().parent.parent
load_dotenv(BASE_DIR / ".env")


def _resolve_path(env_name: str, default_relative_path: str) -> str:
    raw_value = os.getenv(env_name)
    path = Path(raw_value) if raw_value else BASE_DIR / default_relative_path
    return str(path if path.is_absolute() else (BASE_DIR / path).resolve())


def _resolve_optional_path(
    env_name: str,
    default_relative_path: str | None = None,
) -> str | None:
    raw_value = os.getenv(env_name)

    if raw_value:
        path = Path(raw_value)
        return str(path if path.is_absolute() else (BASE_DIR / path).resolve())

    if not default_relative_path:
        return None

    default_path = (BASE_DIR / default_relative_path).resolve()
    if default_path.exists():
        return str(default_path)

    return None


def _parse_origins() -> tuple[str, ...]:
    raw_origins = os.getenv(
        "CORS_ORIGINS",
        "http://127.0.0.1:5173,http://localhost:5173",
    )
    return tuple(
        origin.strip()
        for origin in raw_origins.split(",")
        if origin.strip()
    )


def _parse_bool(name: str, default: bool) -> bool:
    raw_value = os.getenv(name)
    if raw_value is None:
        return default
    return raw_value.strip().lower() in {"1", "true", "yes", "on"}


@dataclass(frozen=True)
class Settings:
    """
    Central configuration for the inspection system.
    """

    # -----------------------------
    # PATHS
    # -----------------------------
    BASE_DIR: str = str(BASE_DIR)
    MODEL_PATH: str = field(
        default_factory=lambda: _resolve_path("MODEL_PATH", "models/steel_inspection.pt")
    )
    IMAGE_FOLDER: str = field(
        default_factory=lambda: _resolve_path("IMAGE_FOLDER", "test_images")
    )
    REPORT_FOLDER: str = field(
        default_factory=lambda: _resolve_path("REPORT_FOLDER", "reports")
    )
    FRONTEND_DIST: str = field(
        default_factory=lambda: _resolve_path("FRONTEND_DIST", "dashboard/dist")
    )

    # -----------------------------
    # DEMO / SIMULATION SETTINGS
    # -----------------------------
    IMAGE_REPEAT: int = field(default_factory=lambda: int(os.getenv("IMAGE_REPEAT", "5")))
    BLANK_FRAMES: int = field(default_factory=lambda: int(os.getenv("BLANK_FRAMES", "3")))

    # -----------------------------
    # TRACKING / LIFECYCLE
    # -----------------------------
    MAX_MISSING_FRAMES: int = field(
        default_factory=lambda: int(os.getenv("MAX_MISSING_FRAMES", "5"))
    )

    # -----------------------------
    # MODEL / INFERENCE SETTINGS
    # -----------------------------
    CONF_THRESHOLD: float = field(default_factory=lambda: float(os.getenv("CONF_THRESHOLD", "0.20")))
    SECONDARY_CONF_THRESHOLD: float = field(
        default_factory=lambda: float(os.getenv("SECONDARY_CONF_THRESHOLD", "0.25"))
    )
    IMAGE_SIZE: int = field(default_factory=lambda: int(os.getenv("IMAGE_SIZE", "896")))
    MIN_DEFECT_AREA: int = field(default_factory=lambda: int(os.getenv("MIN_DEFECT_AREA", "120")))
    MAX_AREA_RATIO: float = field(default_factory=lambda: float(os.getenv("MAX_AREA_RATIO", "0.12")))
    SURFACE_GATE_ENABLED: bool = field(
        default_factory=lambda: _parse_bool("SURFACE_GATE_ENABLED", False)
    )
    SURFACE_DETECTOR_PATH: str | None = field(
        default_factory=lambda: _resolve_optional_path(
            "SURFACE_DETECTOR_PATH",
            "models/steel_surface_detector.pt",
        )
    )
    SURFACE_DETECTOR_CLASS_NAME: str = field(
        default_factory=lambda: os.getenv("SURFACE_DETECTOR_CLASS_NAME", "steel_surface")
    )
    SURFACE_DETECTOR_CONFIDENCE: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_DETECTOR_CONFIDENCE", "0.40"))
    )
    SURFACE_DETECTOR_MIN_AREA_RATIO: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_DETECTOR_MIN_AREA_RATIO", "0.12"))
    )
    SURFACE_DETECTOR_EXPAND_RATIO: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_DETECTOR_EXPAND_RATIO", "0.04"))
    )
    SURFACE_DETECTOR_IMAGE_SIZE: int = field(
        default_factory=lambda: int(os.getenv("SURFACE_DETECTOR_IMAGE_SIZE", "640"))
    )
    SURFACE_CLASSIFIER_PATH: str | None = field(
        default_factory=lambda: _resolve_optional_path(
            "SURFACE_CLASSIFIER_PATH",
            "models/steel_surface_classifier.pt",
        )
    )
    SURFACE_CLASSIFIER_STEEL_LABEL: str = field(
        default_factory=lambda: os.getenv("SURFACE_CLASSIFIER_STEEL_LABEL", "steel")
    )
    SURFACE_MIN_STEEL_CONFIDENCE: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MIN_STEEL_CONFIDENCE", "0.55"))
    )
    SURFACE_GRAY_DELTA: int = field(
        default_factory=lambda: int(os.getenv("SURFACE_GRAY_DELTA", "16"))
    )
    SURFACE_MIN_GRAY_RATIO: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MIN_GRAY_RATIO", "0.72"))
    )
    SURFACE_LOW_SAT_PIXEL_THRESHOLD: int = field(
        default_factory=lambda: int(os.getenv("SURFACE_LOW_SAT_PIXEL_THRESHOLD", "45"))
    )
    SURFACE_MIN_LOW_SAT_RATIO: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MIN_LOW_SAT_RATIO", "0.78"))
    )
    SURFACE_MAX_MEAN_SATURATION: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MAX_MEAN_SATURATION", "40"))
    )
    SURFACE_MAX_COLORFULNESS: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MAX_COLORFULNESS", "24"))
    )
    SURFACE_MAX_SKIN_RATIO: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MAX_SKIN_RATIO", "0.16"))
    )
    SURFACE_MIN_TEXTURE_VARIANCE: float = field(
        default_factory=lambda: float(os.getenv("SURFACE_MIN_TEXTURE_VARIANCE", "80"))
    )

    # -----------------------------
    # API / UI
    # -----------------------------
    CORS_ORIGINS: tuple[str, ...] = field(default_factory=_parse_origins)
    REPORT_FETCH_LIMIT: int = field(
        default_factory=lambda: int(os.getenv("REPORT_FETCH_LIMIT", "50"))
    )
    MAX_UPLOAD_SIZE_MB: int = field(
        default_factory=lambda: int(os.getenv("MAX_UPLOAD_SIZE_MB", "8"))
    )
    WEBSOCKET_HEARTBEAT_SECONDS: int = field(
        default_factory=lambda: int(os.getenv("WEBSOCKET_HEARTBEAT_SECONDS", "20"))
    )
    ENABLE_LLM_REPORTS: bool = field(
        default_factory=lambda: _parse_bool("ENABLE_LLM_REPORTS", True)
    )
    LLM_PROVIDER: str = field(
        default_factory=lambda: os.getenv("LLM_PROVIDER", "auto")
    )
    OLLAMA_BASE_URL: str = field(
        default_factory=lambda: os.getenv("OLLAMA_BASE_URL", "http://127.0.0.1:11434")
    )
    OLLAMA_MODEL: str = field(
        default_factory=lambda: os.getenv("OLLAMA_MODEL", "llama3")
    )
    OLLAMA_TIMEOUT_SECONDS: float = field(
        default_factory=lambda: float(os.getenv("OLLAMA_TIMEOUT_SECONDS", "6"))
    )
    HF_TOKEN: str | None = field(default_factory=lambda: os.getenv("HF_TOKEN"))
    HF_CHAT_MODEL: str = field(
        default_factory=lambda: os.getenv("HF_CHAT_MODEL", "meta-llama/Llama-3.1-8B-Instruct:cerebras")
    )
    HF_ROUTER_BASE_URL: str = field(
        default_factory=lambda: os.getenv("HF_ROUTER_BASE_URL", "https://router.huggingface.co/v1")
    )
    OPENROUTER_API_KEY: str | None = field(default_factory=lambda: os.getenv("OPENROUTER_API_KEY"))
    OPENROUTER_MODEL: str = field(
        default_factory=lambda: os.getenv("OPENROUTER_MODEL", "openrouter/free")
    )
    OPENROUTER_BASE_URL: str = field(
        default_factory=lambda: os.getenv("OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1")
    )

    # -----------------------------
    # DATABASE
    # -----------------------------
    DATABASE_URL: str | None = field(default_factory=lambda: os.getenv("DATABASE_URL"))

    @property
    def max_upload_bytes(self) -> int:
        return self.MAX_UPLOAD_SIZE_MB * 1024 * 1024


settings = Settings()