import logging
import os
import threading
import time
from dataclasses import dataclass

import httpx

logger = logging.getLogger(__name__)


@dataclass(frozen=True)
class ChatModelConfig:
    api_base_url: str
    api_key: str
    model: str
    max_tokens: int
    timeout_seconds: float
    vision_model: str
    ocr_model: str
    vision_max_tokens: int
    vision_timeout_seconds: float
    source: str


_cache_lock = threading.Lock()
_cached_config: ChatModelConfig | None = None
_cache_expires_at = 0.0


def _environment_config() -> ChatModelConfig:
    return ChatModelConfig(
        api_base_url=os.getenv(
            "CHAT_API_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1"
        ).rstrip("/"),
        api_key=os.getenv("CHAT_API_KEY", ""),
        model=os.getenv("CHAT_MODEL", "qwen-plus"),
        max_tokens=max(128, int(os.getenv("CHAT_MAX_OUTPUT_TOKENS", "1024"))),
        timeout_seconds=max(5.0, float(os.getenv("CHAT_TIMEOUT_SECONDS", "30"))),
        vision_model=os.getenv("VISION_MODEL", "qwen3.6-flash"),
        ocr_model=os.getenv("VISION_OCR_MODEL", "qwen-vl-ocr"),
        vision_max_tokens=max(256, int(os.getenv("VISION_MAX_OUTPUT_TOKENS", "2048"))),
        vision_timeout_seconds=max(10.0, float(os.getenv("VISION_TIMEOUT_SECONDS", "90"))),
        source="environment",
    )


def _fetch_runtime_config() -> ChatModelConfig | None:
    url = os.getenv("CHAT_MODEL_CONFIG_URL", "").strip()
    token = os.getenv("AVATAR_MODEL_CONFIG_TOKEN", "").strip()
    if not url or not token:
        return None
    response = httpx.get(
        url,
        headers={"X-Avatar-Config-Token": token},
        timeout=max(2.0, float(os.getenv("CHAT_MODEL_CONFIG_TIMEOUT_SECONDS", "5"))),
    )
    response.raise_for_status()
    payload = response.json().get("data") or {}
    api_base_url = str(payload.get("api_base_url") or "").rstrip("/")
    api_key = str(payload.get("api_key") or "")
    model = str(payload.get("model") or "")
    if not api_base_url or not api_key or not model:
        raise ValueError("数字分身专用模型配置不完整")
    return ChatModelConfig(
        api_base_url=api_base_url,
        api_key=api_key,
        model=model,
        max_tokens=max(128, int(payload.get("max_tokens") or 1024)),
        timeout_seconds=max(5.0, float(payload.get("timeout_seconds") or 30)),
        vision_model=str(
            payload.get("vision_model")
            or os.getenv("VISION_MODEL", "qwen3.6-flash")
        ),
        ocr_model=str(
            payload.get("ocr_model")
            or os.getenv("VISION_OCR_MODEL", "qwen-vl-ocr")
        ),
        vision_max_tokens=max(
            256, int(os.getenv("VISION_MAX_OUTPUT_TOKENS", "2048"))
        ),
        vision_timeout_seconds=max(
            10.0, float(os.getenv("VISION_TIMEOUT_SECONDS", "90"))
        ),
        source="admin",
    )


def get_chat_model_config(*, force_refresh: bool = False) -> ChatModelConfig:
    global _cached_config, _cache_expires_at

    now = time.monotonic()
    if not force_refresh and _cached_config is not None and now < _cache_expires_at:
        return _cached_config

    with _cache_lock:
        now = time.monotonic()
        if not force_refresh and _cached_config is not None and now < _cache_expires_at:
            return _cached_config
        try:
            config = _fetch_runtime_config() or _environment_config()
        except (httpx.HTTPError, ValueError, TypeError) as exc:
            logger.warning("读取数字分身专用模型配置失败，暂时使用环境变量配置: %s", exc)
            config = _environment_config()
        _cached_config = config
        ttl = max(5, int(os.getenv("CHAT_MODEL_CONFIG_CACHE_SECONDS", "60")))
        _cache_expires_at = now + ttl
        return config


def clear_chat_model_config_cache() -> None:
    global _cached_config, _cache_expires_at
    with _cache_lock:
        _cached_config = None
        _cache_expires_at = 0.0