{"repo": "3rqreqr/opsmate", "files": {"app/agent/llm_factory.py": {"4758de4e2e1a7b0f7c07c01e33ab03b347cc9f0a": {"t": 1785747511.7023058, "n": 3084, "h": "f36857cb9fb47300", "c": "\"\"\"\nLLM 工厂\n统一管理通义千问 / DeepSeek / OpenAI 等多 LLM 提供商\n\"\"\"\nfrom typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom langchain_core.language_models import BaseChatModel\n\n# 验证 ChatOpenAI 是 BaseChatModel 的子类\nprint(issubclass(ChatOpenAI, BaseChatModel))  # 输出: True\n\n# 创建实例示例\nllm = ChatOpenAI(\n    model=\"gpt-3.5-turbo\",\n    temperature=0.7,\n    api_key=\"your-api-key-here\"\n)\n\n# 检查类型\nprint(isinstance(llm, BaseChatModel))  # 输出: True\n\nfrom app.core.config import settings\nfrom loguru import logger\n\n\nclass LLMFactory:\n    \"\"\"LLM 实例工厂\"\"\"\n\n    # 各提供商的默认 Base URL\n    PROVIDER_CONFIGS = {\n        \"dashscope\": {\n            \"base_url\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\",\n            \"api_key_env\": \"DASHSCOPE_API_KEY\",\n            \"default_model\": \"qwen-plus\",\n        },\n        \"deepseek\": {\n            \"base_url\": \"https://api.deepseek.com\",\n            \"api_key_env\": \"DEEPSEEK_API_KEY\",\n            \"default_model\": \"deepseek-chat\",\n        },\n        \"openai\": {\n            \"base_url\": \"https://api.openai.com/v1\",\n            \"api_key_env\": \"OPENAI_API_KEY\",\n            \"default_model\": \"gpt-4o-mini\",\n        },\n    }\n\n    _instances: dict = {}\n\n    @classmethod\n    def get_chat_model(\n        cls,\n        model: Optional[str] = None,\n        temperature: Optional[float] = None,\n        max_tokens: Optional[int] = None,\n        provider: Optional[str] = None,\n    ) -> BaseChatModel:\n        \"\"\"获取 Chat Model 实例（带缓存）\"\"\"\n        provider = provider or settings.LLM_PROVIDER\n        model = model or settings.LLM_MODEL\n        temperature = temperature if temperature is not None else settings.LLM_TEMPERATURE\n        max_tokens = max_tokens or settings.LLM_MAX_TOKENS\n\n        cache_key = f\"{provider}:{model}:{temperature}\"\n        if cache_key in cls._instances:\n            return cls._instances[cache_key]\n\n        config = cls.PROVIDER_CONFIGS.get(provider)\n        if config is None:\n            logger.warning(f\"未知的 LLM 提供商: {provider}，使用 dashscope 兜底\")\n            config = cls.PROVIDER_CONFIGS[\"dashscope\"]\n            provider = \"dashscope\"\n\n        # 获取 API Key\n        api_key = getattr(settings, config[\"api_key_env\"], None)\n        if not api_key:\n            logger.warning(\n                f\"未设置 {config['api_key_env']}，\"\n                f\"请在 .env 中配置或设置环境变量\"\n            )\n\n        base_url = settings.LLM_BASE_URL or config[\"base_url\"]\n\n        llm = ChatOpenAI(\n            model=model,\n            api_key=api_key or \"sk-placeholder\",  # LangChain 要求非空\n            base_url=base_url,\n            temperature=temperature,\n            max_tokens=max_tokens,\n            streaming=False,\n        )\n\n        cls._instances[cache_key] = llm\n        logger.info(f\"LLM 实例创建: provider={provider}, model={model}\")\n        return llm\n\n    @classmethod\n    def clear_cache(cls):\n        \"\"\"清空实例缓存\"\"\"\n        cls._instances.clear()\n\n\ndef get_llm(\n    model: Optional[str] = None,\n    temperature: Optional[float] = None,\n) -> BaseChatModel:\n    \"\"\"快捷获取 LLM 实例\"\"\"\n    return LLMFactory.get_chat_model(model=model, temperature=temperature)\n"}}}}