from __future__ import annotations

from functools import lru_cache
from pathlib import Path
from typing import Literal

from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    model_config = SettingsConfigDict(
        env_file=".env",
        env_file_encoding="utf-8",
        extra="ignore",
    )

    ai_host: str = "0.0.0.0"
    ai_port: int = 8001

    demo_mode: Literal["demo", "real", "auto"] = "auto"
    yolo_weights: str = ""

    llm_base_url: str = "https://api.deepseek.com"
    llm_api_key: str = ""
    llm_model: str = "deepseek-chat"
    llm_temperature: float = 0.3

    knowledge_dir: str = "./app/knowledge"
    vector_dir: str = "./data/vectorstore"

    @property
    def root_dir(self) -> Path:
        return Path(__file__).resolve().parent.parent

    def resolve_path(self, value: str) -> Path:
        p = Path(value)
        if p.is_absolute():
            return p
        return (self.root_dir / p).resolve()

    @property
    def knowledge_path(self) -> Path:
        return self.resolve_path(self.knowledge_dir)

    @property
    def vector_path(self) -> Path:
        return self.resolve_path(self.vector_dir)

    @property
    def yolo_weights_path(self) -> Path | None:
        if not self.yolo_weights or not self.yolo_weights.strip():
            return None
        path = self.resolve_path(self.yolo_weights.strip())
        return path if path.is_file() else None

    @property
    def llm_enabled(self) -> bool:
        return bool(self.llm_api_key and self.llm_api_key.strip())


@lru_cache
def get_settings() -> Settings:
    return Settings()