from functools import lru_cache
from typing import ClassVar

from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    """Runtime configuration.

    Values come from `DASH_`-prefixed environment variables or a local
    `.env` file; unknown variables are ignored. See `.env.example` for the
    full list of knobs.
    """

    model_config: ClassVar[SettingsConfigDict] = SettingsConfigDict(env_prefix="DASH_", env_file=".env", extra="ignore")

    host: str = "127.0.0.1"
    port: int = 8501
    sample_interval: float = 2.0
    retention_minutes: int = 60
    chart_max_points: int = 200

    llama_base_url: str = "http://127.0.0.1:8080"
    llama_api_key: str = ""
    llama_timeout: float = 4.0

    @property
    def history_maxlen(self) -> int:
        """Ring buffer size for `retention_minutes` of samples (min 10).

        Returns:
            `retention_minutes * 60 / sample_interval`, at least 10.
        """
        return max(10, int(self.retention_minutes * 60 / self.sample_interval))


@lru_cache
def get_settings() -> Settings:
    """Return the process-wide cached Settings instance.

    Returns:
        A Settings instance, parsed once and reused for the process lifetime.
    """
    return Settings()