import os
from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    DB_USER: str = os.getenv("DB_USER", "postgres")
    DB_PASS: str = os.getenv("DB_PASS", "postgres")
    DB_NAME: str = os.getenv("DB_NAME", "test_db")
    DB_HOST: str = os.getenv("DB_HOST", "db")
    DB_PORT: str = os.getenv("DB_PORT", "5432")

    DEFAULT_VOSK_MODEL: str = os.getenv(
        "DEFAULT_VOSK_MODEL", "models/vosk-model-small-ru-0.22"
    )
    SUBTITLE_LANGS: str = os.getenv("SUBTITLE_LANGS", "ru,en")

    # External LLM (OpenAI-compatible). The LLM itself is NOT hosted in this container —
    # point at any provider/proxy/local server that speaks /v1/chat/completions.
    LLM_BASE_URL: str = os.getenv("LLM_BASE_URL", "")
    LLM_API_KEY: str = os.getenv("LLM_API_KEY", "")
    LLM_MODEL: str = os.getenv("LLM_MODEL", "")
    LLM_TIMEOUT: int = int(os.getenv("LLM_TIMEOUT", "120"))
    # reasoning-модели тратят max_tokens и на размышления — 1000 им мало
    LLM_MAX_TOKENS: int = int(os.getenv("LLM_MAX_TOKENS", "8000"))
    LLM_TEMPERATURE: float = float(os.getenv("LLM_TEMPERATURE", "0.3"))

    @property
    def database_url(self) -> str:
        return (
            f"postgresql+asyncpg://{self.DB_USER}:{self.DB_PASS}"
            f"@{self.DB_HOST}:{self.DB_PORT}/{self.DB_NAME}"
        )

    @property
    def subtitle_langs_list(self) -> list[str]:
        return [x.strip() for x in self.SUBTITLE_LANGS.split(",") if x.strip()]


settings = Settings()