116 lines
3.9 KiB
Python
116 lines
3.9 KiB
Python
import logging
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import os
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import threading
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import time
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from dataclasses import dataclass
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import httpx
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logger = logging.getLogger(__name__)
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@dataclass(frozen=True)
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class ChatModelConfig:
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api_base_url: str
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api_key: str
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model: str
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max_tokens: int
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timeout_seconds: float
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vision_model: str
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ocr_model: str
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vision_max_tokens: int
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vision_timeout_seconds: float
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source: str
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_cache_lock = threading.Lock()
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_cached_config: ChatModelConfig | None = None
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_cache_expires_at = 0.0
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def _environment_config() -> ChatModelConfig:
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return ChatModelConfig(
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api_base_url=os.getenv(
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"CHAT_API_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1"
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).rstrip("/"),
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api_key=os.getenv("CHAT_API_KEY", ""),
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model=os.getenv("CHAT_MODEL", "qwen-plus"),
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max_tokens=max(128, int(os.getenv("CHAT_MAX_OUTPUT_TOKENS", "1024"))),
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timeout_seconds=max(5.0, float(os.getenv("CHAT_TIMEOUT_SECONDS", "30"))),
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vision_model=os.getenv("VISION_MODEL", "qwen3.6-flash"),
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ocr_model=os.getenv("VISION_OCR_MODEL", "qwen-vl-ocr"),
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vision_max_tokens=max(256, int(os.getenv("VISION_MAX_OUTPUT_TOKENS", "2048"))),
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vision_timeout_seconds=max(10.0, float(os.getenv("VISION_TIMEOUT_SECONDS", "90"))),
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source="environment",
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)
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def _fetch_runtime_config() -> ChatModelConfig | None:
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url = os.getenv("CHAT_MODEL_CONFIG_URL", "").strip()
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token = os.getenv("AVATAR_MODEL_CONFIG_TOKEN", "").strip()
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if not url or not token:
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return None
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response = httpx.get(
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url,
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headers={"X-Avatar-Config-Token": token},
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timeout=max(2.0, float(os.getenv("CHAT_MODEL_CONFIG_TIMEOUT_SECONDS", "5"))),
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)
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response.raise_for_status()
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payload = response.json().get("data") or {}
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api_base_url = str(payload.get("api_base_url") or "").rstrip("/")
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api_key = str(payload.get("api_key") or "")
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model = str(payload.get("model") or "")
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if not api_base_url or not api_key or not model:
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raise ValueError("数字分身专用模型配置不完整")
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return ChatModelConfig(
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api_base_url=api_base_url,
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api_key=api_key,
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model=model,
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max_tokens=max(128, int(payload.get("max_tokens") or 1024)),
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timeout_seconds=max(5.0, float(payload.get("timeout_seconds") or 30)),
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vision_model=str(
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payload.get("vision_model")
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or os.getenv("VISION_MODEL", "qwen3.6-flash")
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),
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ocr_model=str(
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payload.get("ocr_model")
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or os.getenv("VISION_OCR_MODEL", "qwen-vl-ocr")
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),
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vision_max_tokens=max(
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256, int(os.getenv("VISION_MAX_OUTPUT_TOKENS", "2048"))
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),
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vision_timeout_seconds=max(
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10.0, float(os.getenv("VISION_TIMEOUT_SECONDS", "90"))
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),
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source="admin",
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)
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def get_chat_model_config(*, force_refresh: bool = False) -> ChatModelConfig:
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global _cached_config, _cache_expires_at
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now = time.monotonic()
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if not force_refresh and _cached_config is not None and now < _cache_expires_at:
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return _cached_config
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with _cache_lock:
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now = time.monotonic()
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if not force_refresh and _cached_config is not None and now < _cache_expires_at:
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return _cached_config
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try:
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config = _fetch_runtime_config() or _environment_config()
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except (httpx.HTTPError, ValueError, TypeError) as exc:
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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)
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config = _environment_config()
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_cached_config = config
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ttl = max(5, int(os.getenv("CHAT_MODEL_CONFIG_CACHE_SECONDS", "60")))
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_cache_expires_at = now + ttl
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return config
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def clear_chat_model_config_cache() -> None:
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global _cached_config, _cache_expires_at
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with _cache_lock:
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_cached_config = None
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_cache_expires_at = 0.0
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