from openai import AsyncOpenAI from tenacity import before_sleep_log, retry, retry_if_exception_type, stop_after_attempt, wait_exponential from yuxi.models.providers.cache import model_cache from yuxi.utils import logger class OpenAIBase: def __init__(self, api_key, base_url, model_name, **kwargs): self.model_params = kwargs.pop("model_params", {}) or {} self.api_key = api_key self.base_url = base_url self.client = AsyncOpenAI(api_key=api_key, base_url=base_url, **kwargs) self.model_name = model_name self.info = kwargs @retry( stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=1, max=10), retry=retry_if_exception_type((Exception,)), before_sleep=before_sleep_log(logger, log_level="WARNING"), reraise=True, ) async def call(self, message, stream=False): if isinstance(message, str): messages = [{"role": "user", "content": message}] else: messages = message try: if stream: response = self._stream_response(messages) else: response = await self._get_response(messages) except Exception as e: err = ( f"Error streaming response: {e}, URL: {self.base_url}, " f"API Key: {self.api_key[:5]}***, Model: {self.model_name}" ) logger.error(err) raise Exception(err) return response async def _stream_response(self, messages): response = await self.client.chat.completions.create( model=self.model_name, messages=messages, stream=True, **self.model_params, ) async for chunk in response: if len(chunk.choices) > 0: yield chunk.choices[0].delta async def _get_response(self, messages): response = await self.client.chat.completions.create( model=self.model_name, messages=messages, stream=False, **self.model_params, ) return response.choices[0].message async def get_models(self): try: return await self.client.models.list(extra_query={"type": "text"}) except Exception as e: logger.error(f"Error getting models: {e}") return [] class GeneralResponse: def __init__(self, content): self.content = content self.is_full = False def select_model(model_spec: str, **kwargs) -> OpenAIBase: if not model_spec: raise ValueError("model_spec 不能为空") info = model_cache.get_model_info(model_spec) if not info: available = model_cache.get_all_specs("chat") available_ids = [item.spec for item in available[:10]] raise ValueError(f"未找到模型: '{model_spec}'。可用聊天模型 ({len(available)}): {available_ids}") if info.model_type != "chat": raise ValueError(f"Model {model_spec} is not a chat model (type={info.model_type})") logger.info(f"Selecting model: {model_spec} (provider_type={info.provider_type})") return OpenAIBase( api_key=info.api_key, base_url=info.base_url, model_name=info.model_id, **kwargs, ) async def test_chat_model_status_by_spec(spec: str) -> dict: try: logger.debug(f"Testing model status by spec: {spec}") model = select_model(model_spec=spec) test_messages = [{"role": "user", "content": "Say 1"}] response = await model.call(test_messages, stream=False) if response and response.content: return {"spec": spec, "status": "available", "message": "连接正常"} return {"spec": spec, "status": "unavailable", "message": "响应无效"} except Exception as e: logger.error(f"测试模型状态失败 {spec}: {e}") return {"spec": spec, "status": "error", "message": str(e)} if __name__ == "__main__": pass