from functools import lru_cache

from pydantic import field_validator
from pydantic_settings import BaseSettings, SettingsConfigDict


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

    app_env: str = "development"
    database_url: str = "sqlite:///data/app.db"
    tikhub_api_key: str = ""
    tikhub_base_url: str = "https://api.tikhub.io"
    ai_provider: str = "openai-compatible"
    ai_base_url: str = ""
    ai_api_key: str = ""
    ai_model: str = ""
    ai_batch_size: int = 20
    ai_concurrency: int = 2
    ai_max_retries: int = 3
    ai_timeout_seconds: int = 30
    http_timeout_seconds: int = 20
    http_max_retries: int = 3
    crawl_page_interval_seconds: float = 1.5

    hot_limit_min: int = 1
    hot_limit_max: int = 10
    item_limit_per_hot_min: int = 1
    item_limit_per_hot_max: int = 10
    comment_limit_per_item_min: int = 10
    comment_limit_per_item_max: int = 100

    @field_validator("ai_concurrency", mode="after")
    @classmethod
    def cap_ai_concurrency(cls, value: int) -> int:
        return min(value, 3)


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