{"repo": "aidocplus/dragonstock", "files": {"backend/app/services/llm/llm_service.py": {"33297c5dc6145856df0f0852bcc704f784cf14c2": {"t": 1785746497.640697, "n": 20797, "h": "ada5b13d85d122da", "c": "\"\"\"\n统一LLM服务 - 单例模式，管理所有提供商切换与配置持久化\n\"\"\"\nimport json\nimport logging\nimport sqlite3\nfrom typing import Any, AsyncIterator, Dict, List, Optional\n\nfrom app.services.llm.base import (\n    LLMProvider, LLMMessage, LLMToolDef, LLMResponse,\n    ModelInfo, ProviderConfig,\n)\nfrom app.services.llm.openai_provider import OpenAICompatibleProvider\nfrom app.services.database_service import database_service\n\nlogger = logging.getLogger(__name__)\n\n# ============================================================\n# 内置提供商预设（截至2026.03调研）\n# ============================================================\nBUILTIN_PROVIDERS: Dict[str, Dict[str, Any]] = {\n    \"openai\": {\n        \"display_name\": \"OpenAI\",\n        \"base_url\": \"https://api.openai.com/v1\",\n        \"needs_proxy\": True,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.openai.com/api-keys\",\n        \"models\": [\n            {\"id\": \"gpt-4o\", \"name\": \"GPT-4o\", \"type\": \"chat\"},\n            {\"id\": \"gpt-4o-mini\", \"name\": \"GPT-4o Mini\", \"type\": \"lightweight\"},\n            {\"id\": \"gpt-4.1\", \"name\": \"GPT-4.1（代码优化）\", \"type\": \"chat\"},\n            {\"id\": \"gpt-4.1-mini\", \"name\": \"GPT-4.1 Mini\", \"type\": \"lightweight\"},\n            {\"id\": \"gpt-4.1-nano\", \"name\": \"GPT-4.1 Nano\", \"type\": \"lightweight\"},\n            {\"id\": \"o3\", \"name\": \"o3（深度推理）\", \"type\": \"reasoning\"},\n            {\"id\": \"o4-mini\", \"name\": \"o4-mini（快速推理）\", \"type\": \"reasoning\"},\n            {\"id\": \"gpt-5\", \"name\": \"GPT-5\", \"type\": \"chat\"},\n            {\"id\": \"gpt-5-mini\", \"name\": \"GPT-5 Mini\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"gemini\": {\n        \"display_name\": \"Google Gemini\",\n        \"base_url\": \"https://generativelanguage.googleapis.com/v1beta/openai\",\n        \"needs_proxy\": True,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://aistudio.google.com/apikey\",\n        \"models\": [\n            {\"id\": \"gemini-3-pro-preview\", \"name\": \"Gemini 3 Pro（预览）\", \"type\": \"chat\"},\n            {\"id\": \"gemini-3-flash-preview\", \"name\": \"Gemini 3 Flash（预览）\", \"type\": \"chat\"},\n            {\"id\": \"gemini-2.5-pro\", \"name\": \"Gemini 2.5 Pro\", \"type\": \"chat\"},\n            {\"id\": \"gemini-2.5-flash\", \"name\": \"Gemini 2.5 Flash（稳定推荐）\", \"type\": \"chat\"},\n            {\"id\": \"gemini-2.5-flash-lite\", \"name\": \"Gemini 2.5 Flash Lite\", \"type\": \"lightweight\"},\n            {\"id\": \"gemini-2.0-flash\", \"name\": \"Gemini 2.0 Flash\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"xai\": {\n        \"display_name\": \"xAI (Grok)\",\n        \"base_url\": \"https://api.x.ai/v1\",\n        \"needs_proxy\": True,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://console.x.ai/\",\n        \"models\": [\n            {\"id\": \"grok-4-0709\", \"name\": \"Grok 4\", \"type\": \"chat\"},\n            {\"id\": \"grok-3\", \"name\": \"Grok 3\", \"type\": \"chat\"},\n            {\"id\": \"grok-3-mini\", \"name\": \"Grok 3 Mini\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"deepseek\": {\n        \"display_name\": \"DeepSeek\",\n        \"base_url\": \"https://api.deepseek.com\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.deepseek.com/api_keys\",\n        \"models\": [\n            {\"id\": \"deepseek-chat\", \"name\": \"DeepSeek-V3.2（通用）\", \"type\": \"chat\"},\n            {\"id\": \"deepseek-reasoner\", \"name\": \"DeepSeek-R1（推理）\", \"type\": \"reasoning\"},\n        ],\n    },\n    \"qwen\": {\n        \"display_name\": \"通义千问 (Qwen)\",\n        \"base_url\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://bailian.console.aliyun.com/#/api-key\",\n        \"models\": [\n            {\"id\": \"qwen3-max\", \"name\": \"Qwen3 Max（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"qwen-max\", \"name\": \"Qwen Max\", \"type\": \"chat\"},\n            {\"id\": \"qwen-plus\", \"name\": \"Qwen Plus（推荐）\", \"type\": \"chat\"},\n            {\"id\": \"qwen-turbo\", \"name\": \"Qwen Turbo\", \"type\": \"lightweight\"},\n            {\"id\": \"qwen-long\", \"name\": \"Qwen Long\", \"type\": \"chat\"},\n            {\"id\": \"qwen3-coder-plus\", \"name\": \"Qwen3 Coder Plus（编码）\", \"type\": \"coding\"},\n            {\"id\": \"qwen-coder-plus\", \"name\": \"Qwen Coder Plus\", \"type\": \"coding\"},\n            {\"id\": \"qwq-plus\", \"name\": \"QwQ Plus（推理）\", \"type\": \"reasoning\"},\n            {\"id\": \"qwen-flash\", \"name\": \"Qwen Flash\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"glm\": {\n        \"display_name\": \"智谱 AI（通用）\",\n        \"base_url\": \"https://open.bigmodel.cn/api/paas/v4\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://open.bigmodel.cn/usercenter/apikeys\",\n        \"models\": [\n            {\"id\": \"glm-5\", \"name\": \"GLM-5（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.7\", \"name\": \"GLM-4.7\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.7-flash\", \"name\": \"GLM-4.7 Flash（免费）\", \"type\": \"lightweight\"},\n            {\"id\": \"glm-4.6\", \"name\": \"GLM-4.6\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.5-air\", \"name\": \"GLM-4.5 Air\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.5-airx\", \"name\": \"GLM-4.5 AirX\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.5-flash\", \"name\": \"GLM-4.5 Flash（免费）\", \"type\": \"lightweight\"},\n            {\"id\": \"glm-4-flash\", \"name\": \"GLM-4 Flash（免费）\", \"type\": \"lightweight\"},\n            {\"id\": \"glm-4-long\", \"name\": \"GLM-4 Long\", \"type\": \"chat\"},\n        ],\n    },\n    \"glm-code\": {\n        \"display_name\": \"智谱 AI（Coding Plan）\",\n        \"base_url\": \"https://open.bigmodel.cn/api/coding/paas/v4\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://open.bigmodel.cn/usercenter/apikeys\",\n        \"share_api_key_with\": \"glm\",\n        \"models\": [\n            {\"id\": \"GLM-5\", \"name\": \"GLM-5（旗舰）\", \"type\": \"coding\"},\n            {\"id\": \"GLM-4.7\", \"name\": \"GLM-4.7\", \"type\": \"coding\"},\n            {\"id\": \"GLM-4.6\", \"name\": \"GLM-4.6\", \"type\": \"coding\"},\n            {\"id\": \"GLM-4.5-air\", \"name\": \"GLM-4.5 Air\", \"type\": \"coding\"},\n        ],\n    },\n    \"minimax\": {\n        \"display_name\": \"MiniMax（通用）\",\n        \"base_url\": \"https://api.minimaxi.com/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.minimaxi.com/dashboard\",\n        \"models\": [\n            {\"id\": \"MiniMax-M2.5\", \"name\": \"MiniMax M2.5（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"MiniMax-M2.5-highspeed\", \"name\": \"MiniMax M2.5 高速版\", \"type\": \"lightweight\"},\n            {\"id\": \"MiniMax-M2.1\", \"name\": \"MiniMax M2.1\", \"type\": \"chat\"},\n            {\"id\": \"MiniMax-M2.1-highspeed\", \"name\": \"MiniMax M2.1 高速版\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"minimax-code\": {\n        \"display_name\": \"MiniMax（Coding Plan）\",\n        \"base_url\": \"https://api.minimaxi.com/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.minimaxi.com/dashboard\",\n        \"share_api_key_with\": \"minimax\",\n        \"models\": [\n            {\"id\": \"MiniMax-M2.5\", \"name\": \"MiniMax M2.5\", \"type\": \"coding\"},\n            {\"id\": \"MiniMax-M2.5-highspeed\", \"name\": \"MiniMax M2.5 高速版\", \"type\": \"coding\"},\n        ],\n    },\n    \"kimi\": {\n        \"display_name\": \"Kimi / Moonshot 开放平台\",\n        \"base_url\": \"https://api.moonshot.cn/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.moonshot.cn/console/api-keys\",\n        \"models\": [\n            {\"id\": \"kimi-k2.5\", \"name\": \"Kimi K2.5（旗舰多模态）\", \"type\": \"chat\"},\n            {\"id\": \"kimi-k2\", \"name\": \"Kimi K2\", \"type\": \"chat\"},\n            {\"id\": \"kimi-latest\", \"name\": \"Kimi Latest\", \"type\": \"chat\"},\n            {\"id\": \"moonshot-v1-auto\", \"name\": \"Moonshot v1 Auto\", \"type\": \"chat\"},\n            {\"id\": \"moonshot-v1-128k\", \"name\": \"Moonshot v1 128K\", \"type\": \"chat\"},\n        ],\n    },\n    \"kimi-code\": {\n        \"display_name\": \"Kimi Code（会员编程）\",\n        \"base_url\": \"https://api.kimi.com/coding/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.moonshot.cn/console/api-keys\",\n        \"share_api_key_with\": \"kimi\",\n        \"models\": [\n            {\"id\": \"kimi-for-coding\", \"name\": \"Kimi for Coding（默认）\", \"type\": \"coding\"},\n        ],\n    },\n    \"doubao\": {\n        \"display_name\": \"豆包 (Doubao)\",\n        \"base_url\": \"https://ark.cn-beijing.volces.com/api/v3\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://console.volcengine.com/ark/region:ark+cn-beijing/apiKey\",\n        \"models\": [\n            {\"id\": \"doubao-seed-2-0-pro\", \"name\": \"Doubao Seed 2.0 Pro（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"doubao-seed-2-0-code\", \"name\": \"Doubao Seed 2.0 Code（编码）\", \"type\": \"coding\"},\n            {\"id\": \"doubao-seed-2-0-lite\", \"name\": \"Doubao Seed 2.0 Lite（轻量）\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"ollama\": {\n        \"display_name\": \"Ollama（本地）\",\n        \"base_url\": \"http://localhost:11434/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": False,\n        \"api_key_url\": \"https://ollama.com/download\",\n        \"models\": [],  # 动态检测\n    },\n    \"custom\": {\n        \"display_name\": \"自定义（OpenAI兼容）\",\n        \"base_url\": \"\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"\",\n        \"models\": [],\n    },\n}\n\n\nclass LLMService:\n    \"\"\"统一LLM服务单例\"\"\"\n\n    _instance: Optional[\"LLMService\"] = None\n\n    def __new__(cls) -> \"LLMService\":\n        if cls._instance is None:\n            cls._instance = super().__new__(cls)\n            cls._instance._initialized = False\n        return cls._instance\n\n    def __init__(self):\n        if self._initialized:\n            return\n        self._initialized = True\n        self._provider: Optional[LLMProvider] = None\n        self._active_provider_name: str = \"\"\n        self._db_path: str = \"\"\n        logger.info(\"LLMService 初始化完成\")\n\n    def set_db_path(self, db_path: str):\n        \"\"\"设置数据库路径并初始化llm_settings表\"\"\"\n        self._db_path = db_path\n        self._init_db()\n        self._load_provider_from_db()\n\n    # ============================================================\n    # 数据库操作\n    # ============================================================\n    def _init_db(self):\n        if not self._db_path:\n            return\n        try:\n            with database_service.get_connection() as conn:\n                conn.execute(\"\"\"\n                    CREATE TABLE IF NOT EXISTS llm_settings (\n                        key TEXT PRIMARY KEY,\n                        value TEXT NOT NULL,\n                        updated_at TEXT DEFAULT (datetime('now', 'localtime'))\n                    )\n                \"\"\")\n                conn.commit()\n        except Exception as e:\n            logger.error(\"初始化llm_settings表失败: %s\", e)\n\n    def _get_setting(self, key: str, default: str = \"\") -> str:\n        if not self._db_path:\n            return default\n        try:\n            with database_service.get_connection() as conn:\n                row = conn.execute(\n                    \"SELECT value FROM llm_settings WHERE key = ?\", (key,)\n                ).fetchone()\n                return row[0] if row else default\n        except Exception:\n            return default\n\n    def _set_setting(self, key: str, value: str):\n        if not self._db_path:\n            return\n        try:\n            with database_service.get_connection() as conn:\n                conn.execute(\"\"\"\n                    INSERT INTO llm_settings (key, value, updated_at)\n                    VALUES (?, ?, datetime('now', 'localtime'))\n                    ON CONFLICT(key) DO UPDATE SET\n                        value = excluded.value,\n                        updated_at = excluded.updated_at\n                \"\"\", (key, value))\n                conn.commit()\n        except Exception as e:\n            logger.error(\"保存LLM设置失败 [%s]: %s\", key, e)\n\n    # ============================================================\n    # Provider管理\n    # ============================================================\n    def _load_provider_from_db(self):\n        \"\"\"从数据库加载已保存的provider配置\"\"\"\n        provider_name = self._get_setting(\"active_provider\", \"\")\n        if not provider_name:\n            return\n        try:\n            self._build_provider(provider_name)\n        except Exception as e:\n            logger.warning(\"加载已保存的LLM provider失败: %s\", e)\n\n    def _build_provider(self, provider_name: str):\n        \"\"\"根据provider名称构建Provider实例\"\"\"\n        if provider_name not in BUILTIN_PROVIDERS:\n            raise ValueError(f\"未知的LLM提供商: {provider_name}\")\n\n        preset = BUILTIN_PROVIDERS[provider_name]\n\n        api_key = self._get_setting(f\"{provider_name}_api_key\", \"\")\n        # 支持 share_api_key_with：Coding Plan 提供商可共享主提供商的 API Key\n        if not api_key and preset.get(\"share_api_key_with\"):\n            api_key = self._get_setting(f\"{preset['share_api_key_with']}_api_key\", \"\")\n        model = self._get_setting(f\"{provider_name}_model\", \"\")\n        custom_base_url = self._get_setting(f\"{provider_name}_base_url\", \"\")\n        proxy_url = self._get_setting(\"proxy_url\", \"\")\n        proxy_enabled = self._get_setting(\"proxy_enabled\", \"false\") == \"true\"\n        temperature = float(self._get_setting(\"temperature\", \"0.7\"))\n        max_tokens = int(self._get_setting(\"max_tokens\", \"0\"))\n\n        base_url = custom_base_url or preset[\"base_url\"]\n\n        # 对非Ollama提供商，没有API Key则不创建\n        if provider_name not in (\"ollama\", \"custom\") and not api_key:\n            logger.info(\"提供商 %s 未配置API Key，跳过\", provider_name)\n            return\n\n        # 默认选第一个模型\n        if not model and preset[\"models\"]:\n            model = preset[\"models\"][0][\"id\"]\n\n        models = [\n            ModelInfo(id=m[\"id\"], name=m[\"name\"], model_type=m.get(\"type\", \"chat\"))\n            for m in preset[\"models\"]\n        ]\n\n        # 代理由用户全局开关控制\n        effective_proxy = proxy_url if (proxy_enabled and proxy_url) else None\n\n        config = ProviderConfig(\n            provider_name=provider_name,\n            display_name=preset[\"display_name\"],\n            base_url=base_url,\n            api_key=api_key,\n            model=model,\n            proxy=effective_proxy,\n            temperature=temperature,\n            max_tokens=max_tokens,\n            models=models,\n            supports_tools=preset.get(\"supports_tools\", True),\n            needs_proxy=preset.get(\"needs_proxy\", False),\n            api_key_url=preset.get(\"api_key_url\", \"\"),\n        )\n\n        self._provider = OpenAICompatibleProvider(config)\n        self._active_provider_name = provider_name\n        logger.info(\"LLM Provider已切换: %s / %s\", provider_name, model)\n\n    def switch_provider(self, provider_name: str, config: Dict[str, Any]):\n        \"\"\"切换提供商并保存配置\"\"\"\n        if config.get(\"api_key\"):\n            self._set_setting(f\"{provider_name}_api_key\", config[\"api_key\"])\n        if config.get(\"model\"):\n            self._set_setting(f\"{provider_name}_model\", config[\"model\"])\n        if config.get(\"base_url\"):\n            self._set_setting(f\"{provider_name}_base_url\", config[\"base_url\"])\n        if config.get(\"proxy_url\") is not None:\n            self._set_setting(\"proxy_url\", config[\"proxy_url\"])\n        if config.get(\"proxy_enabled\") is not None:\n            self._set_setting(\"proxy_enabled\", \"true\" if config[\"proxy_enabled\"] else \"false\")\n        if config.get(\"temperature\") is not None:\n            self._set_setting(\"temperature\", str(config[\"temperature\"]))\n        if config.get(\"max_tokens\") is not None:\n            self._set_setting(\"max_tokens\", str(config[\"max_tokens\"]))\n\n        self._set_setting(\"active_provider\", provider_name)\n        self._build_provider(provider_name)\n\n    # ============================================================\n    # 对外接口\n    # ============================================================\n    @property\n    def is_configured(self) -> bool:\n        return self._provider is not None\n\n    @property\n    def active_provider_name(self) -> str:\n        return self._active_provider_name\n\n    def get_provider(self) -> Optional[LLMProvider]:\n        return self._provider\n\n    async def chat(\n        self,\n        messages: List[LLMMessage],\n        tools: Optional[List[LLMToolDef]] = None,\n        stream: bool = False,\n        temperature: Optional[float] = None,\n        max_tokens: Optional[int] = None,\n    ) -> LLMResponse:\n        if not self._provider:\n            raise RuntimeError(\"LLM服务未配置，请先在设置中选择并配置AI模型提供商\")\n        return await self._provider.chat(messages, tools, stream, temperature, max_tokens)\n\n    async def chat_stream(\n        self,\n        messages: List[LLMMessage],\n        tools: Optional[List[LLMToolDef]] = None,\n        temperature: Optional[float] = None,\n        max_tokens: Optional[int] = None,\n    ) -> AsyncIterator[str]:\n        if not self._provider:\n            raise RuntimeError(\"LLM服务未配置，请先在设置中选择并配置AI模型提供商\")\n        async for chunk in self._provider.chat_stream(messages, tools, temperature, max_tokens):\n            yield chunk\n\n    async def test_connection(self) -> Dict[str, Any]:\n        if not self._provider:\n            return {\"success\": False, \"message\": \"LLM服务未配置\"}\n        return await self._provider.test_connection()\n\n    async def list_models(self, provider_name: Optional[str] = None) -> List[ModelInfo]:\n        \"\"\"获取指定提供商或当前提供商的模型列表\"\"\"\n        if provider_name and provider_name == \"ollama\":\n            # Ollama需要动态检测\n            temp_config = ProviderConfig(\n                provider_name=\"ollama\",\n                display_name=\"Ollama\",\n                base_url=self._get_setting(\"ollama_base_url\", \"http://localhost:11434/v1\"),\n                api_key=\"ollama\",\n                model=\"\",\n            )\n            temp_provider = OpenAICompatibleProvider(temp_config)\n            models = await temp_provider.list_models()\n            await temp_provider.close()\n            return models\n\n        if provider_name and provider_name in BUILTIN_PROVIDERS:\n            preset = BUILTIN_PROVIDERS[provider_name]\n            return [\n                ModelInfo(id=m[\"id\"], name=m[\"name\"], model_type=m.get(\"type\", \"chat\"))\n                for m in preset[\"models\"]\n            ]\n\n        if self._provider:\n            return await self._provider.list_models()\n        return []\n\n    def get_settings(self) -> Dict[str, Any]:\n        \"\"\"获取当前所有LLM设置\"\"\"\n        settings: Dict[str, Any] = {\n            \"active_provider\": self._get_setting(\"active_provider\", \"\"),\n            \"proxy_url\": self._get_setting(\"proxy_url\", \"\"),\n            \"proxy_enabled\": self._get_setting(\"proxy_enabled\", \"false\") == \"true\",\n            \"temperature\": float(self._get_setting(\"temperature\", \"0.7\")),\n            \"max_tokens\": int(self._get_setting(\"max_tokens\", \"0\")),\n        }\n\n        # 各提供商独立配置\n        for name in BUILTIN_PROVIDERS:\n            settings[f\"{name}_api_key\"] = \"***\" if self._get_setting(f\"{name}_api_key\") else \"\"\n            settings[f\"{name}_model\"] = self._get_setting(f\"{name}_model\", \"\")\n            settings[f\"{name}_base_url\"] = self._get_setting(f\"{name}_base_url\", \"\")\n\n        return settings\n\n    def get_providers_info(self) -> List[Dict[str, Any]]:\n        \"\"\"获取全部可用提供商信息\"\"\"\n        providers = []\n        for name, preset in BUILTIN_PROVIDERS.items():\n            has_key = bool(self._get_setting(f\"{name}_api_key\"))\n            # Coding Plan 提供商可共享主提供商的 API Key\n            share_with = preset.get(\"share_api_key_with\", \"\")\n            if not has_key and share_with:\n                has_key = bool(self._get_setting(f\"{share_with}_api_key\"))\n            selected_model = self._get_setting(f\"{name}_model\", \"\")\n            custom_base_url = self._get_setting(f\"{name}_base_url\", \"\")\n            providers.append({\n                \"name\": name,\n                \"display_name\": preset[\"display_name\"],\n                \"base_url\": preset[\"base_url\"],\n                \"custom_base_url\": custom_base_url,\n                \"needs_proxy\": preset.get(\"needs_proxy\", False),\n                \"supports_tools\": preset.get(\"supports_tools\", True),\n                \"api_key_url\": preset.get(\"api_key_url\", \"\"),\n                \"has_api_key\": has_key,\n                \"selected_model\": selected_model,\n                \"is_active\": name == self._active_provider_name,\n                \"models\": preset[\"models\"],\n                \"share_api_key_with\": share_with,\n            })\n        return providers\n\n    def save_settings(self, settings: Dict[str, Any]):\n        \"\"\"批量保存设置\"\"\"\n        for key, value in settings.items():\n            if key.endswith(\"_api_key\") and value == \"***\":\n                continue  # 跳过未修改的密钥\n            self._set_setting(key, str(value))\n\n        # 如果active_provider变了，重建provider\n        new_provider = settings.get(\"active_provider\", \"\")\n        if new_provider and new_provider != self._active_provider_name:\n            try:\n                self._build_provider(new_provider)\n            except Exception as e:\n                logger.error(\"切换provider失败: %s\", e)\n\n\n# 全局单例\nllm_service = LLMService()\n"}, "53ac1ac7eb7feb5c2e626742969c856f9a1dc66b": {"t": 1785764975.4044533, "n": 20735, "h": "ec603eda193f7042", "c": "\"\"\"\n统一LLM服务 - 单例模式，管理所有提供商切换与配置持久化\n\"\"\"\nimport json\nimport logging\nimport sqlite3\nfrom typing import Any, AsyncIterator, Dict, List, Optional\n\nfrom app.services.llm.base import (\n    LLMProvider, LLMMessage, LLMToolDef, LLMResponse,\n    ModelInfo, ProviderConfig,\n)\nfrom app.services.llm.openai_provider import OpenAICompatibleProvider\n\nlogger = logging.getLogger(__name__)\n\n# ============================================================\n# 内置提供商预设（截至2026.03调研）\n# ============================================================\nBUILTIN_PROVIDERS: Dict[str, Dict[str, Any]] = {\n    \"openai\": {\n        \"display_name\": \"OpenAI\",\n        \"base_url\": \"https://api.openai.com/v1\",\n        \"needs_proxy\": True,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.openai.com/api-keys\",\n        \"models\": [\n            {\"id\": \"gpt-4o\", \"name\": \"GPT-4o\", \"type\": \"chat\"},\n            {\"id\": \"gpt-4o-mini\", \"name\": \"GPT-4o Mini\", \"type\": \"lightweight\"},\n            {\"id\": \"gpt-4.1\", \"name\": \"GPT-4.1（代码优化）\", \"type\": \"chat\"},\n            {\"id\": \"gpt-4.1-mini\", \"name\": \"GPT-4.1 Mini\", \"type\": \"lightweight\"},\n            {\"id\": \"gpt-4.1-nano\", \"name\": \"GPT-4.1 Nano\", \"type\": \"lightweight\"},\n            {\"id\": \"o3\", \"name\": \"o3（深度推理）\", \"type\": \"reasoning\"},\n            {\"id\": \"o4-mini\", \"name\": \"o4-mini（快速推理）\", \"type\": \"reasoning\"},\n            {\"id\": \"gpt-5\", \"name\": \"GPT-5\", \"type\": \"chat\"},\n            {\"id\": \"gpt-5-mini\", \"name\": \"GPT-5 Mini\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"gemini\": {\n        \"display_name\": \"Google Gemini\",\n        \"base_url\": \"https://generativelanguage.googleapis.com/v1beta/openai\",\n        \"needs_proxy\": True,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://aistudio.google.com/apikey\",\n        \"models\": [\n            {\"id\": \"gemini-3-pro-preview\", \"name\": \"Gemini 3 Pro（预览）\", \"type\": \"chat\"},\n            {\"id\": \"gemini-3-flash-preview\", \"name\": \"Gemini 3 Flash（预览）\", \"type\": \"chat\"},\n            {\"id\": \"gemini-2.5-pro\", \"name\": \"Gemini 2.5 Pro\", \"type\": \"chat\"},\n            {\"id\": \"gemini-2.5-flash\", \"name\": \"Gemini 2.5 Flash（稳定推荐）\", \"type\": \"chat\"},\n            {\"id\": \"gemini-2.5-flash-lite\", \"name\": \"Gemini 2.5 Flash Lite\", \"type\": \"lightweight\"},\n            {\"id\": \"gemini-2.0-flash\", \"name\": \"Gemini 2.0 Flash\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"xai\": {\n        \"display_name\": \"xAI (Grok)\",\n        \"base_url\": \"https://api.x.ai/v1\",\n        \"needs_proxy\": True,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://console.x.ai/\",\n        \"models\": [\n            {\"id\": \"grok-4-0709\", \"name\": \"Grok 4\", \"type\": \"chat\"},\n            {\"id\": \"grok-3\", \"name\": \"Grok 3\", \"type\": \"chat\"},\n            {\"id\": \"grok-3-mini\", \"name\": \"Grok 3 Mini\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"deepseek\": {\n        \"display_name\": \"DeepSeek\",\n        \"base_url\": \"https://api.deepseek.com\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.deepseek.com/api_keys\",\n        \"models\": [\n            {\"id\": \"deepseek-chat\", \"name\": \"DeepSeek-V3.2（通用）\", \"type\": \"chat\"},\n            {\"id\": \"deepseek-reasoner\", \"name\": \"DeepSeek-R1（推理）\", \"type\": \"reasoning\"},\n        ],\n    },\n    \"qwen\": {\n        \"display_name\": \"通义千问 (Qwen)\",\n        \"base_url\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://bailian.console.aliyun.com/#/api-key\",\n        \"models\": [\n            {\"id\": \"qwen3-max\", \"name\": \"Qwen3 Max（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"qwen-max\", \"name\": \"Qwen Max\", \"type\": \"chat\"},\n            {\"id\": \"qwen-plus\", \"name\": \"Qwen Plus（推荐）\", \"type\": \"chat\"},\n            {\"id\": \"qwen-turbo\", \"name\": \"Qwen Turbo\", \"type\": \"lightweight\"},\n            {\"id\": \"qwen-long\", \"name\": \"Qwen Long\", \"type\": \"chat\"},\n            {\"id\": \"qwen3-coder-plus\", \"name\": \"Qwen3 Coder Plus（编码）\", \"type\": \"coding\"},\n            {\"id\": \"qwen-coder-plus\", \"name\": \"Qwen Coder Plus\", \"type\": \"coding\"},\n            {\"id\": \"qwq-plus\", \"name\": \"QwQ Plus（推理）\", \"type\": \"reasoning\"},\n            {\"id\": \"qwen-flash\", \"name\": \"Qwen Flash\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"glm\": {\n        \"display_name\": \"智谱 AI（通用）\",\n        \"base_url\": \"https://open.bigmodel.cn/api/paas/v4\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://open.bigmodel.cn/usercenter/apikeys\",\n        \"models\": [\n            {\"id\": \"glm-5\", \"name\": \"GLM-5（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.7\", \"name\": \"GLM-4.7\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.7-flash\", \"name\": \"GLM-4.7 Flash（免费）\", \"type\": \"lightweight\"},\n            {\"id\": \"glm-4.6\", \"name\": \"GLM-4.6\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.5-air\", \"name\": \"GLM-4.5 Air\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.5-airx\", \"name\": \"GLM-4.5 AirX\", \"type\": \"chat\"},\n            {\"id\": \"glm-4.5-flash\", \"name\": \"GLM-4.5 Flash（免费）\", \"type\": \"lightweight\"},\n            {\"id\": \"glm-4-flash\", \"name\": \"GLM-4 Flash（免费）\", \"type\": \"lightweight\"},\n            {\"id\": \"glm-4-long\", \"name\": \"GLM-4 Long\", \"type\": \"chat\"},\n        ],\n    },\n    \"glm-code\": {\n        \"display_name\": \"智谱 AI（Coding Plan）\",\n        \"base_url\": \"https://open.bigmodel.cn/api/coding/paas/v4\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://open.bigmodel.cn/usercenter/apikeys\",\n        \"share_api_key_with\": \"glm\",\n        \"models\": [\n            {\"id\": \"GLM-5\", \"name\": \"GLM-5（旗舰）\", \"type\": \"coding\"},\n            {\"id\": \"GLM-4.7\", \"name\": \"GLM-4.7\", \"type\": \"coding\"},\n            {\"id\": \"GLM-4.6\", \"name\": \"GLM-4.6\", \"type\": \"coding\"},\n            {\"id\": \"GLM-4.5-air\", \"name\": \"GLM-4.5 Air\", \"type\": \"coding\"},\n        ],\n    },\n    \"minimax\": {\n        \"display_name\": \"MiniMax（通用）\",\n        \"base_url\": \"https://api.minimaxi.com/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.minimaxi.com/dashboard\",\n        \"models\": [\n            {\"id\": \"MiniMax-M2.5\", \"name\": \"MiniMax M2.5（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"MiniMax-M2.5-highspeed\", \"name\": \"MiniMax M2.5 高速版\", \"type\": \"lightweight\"},\n            {\"id\": \"MiniMax-M2.1\", \"name\": \"MiniMax M2.1\", \"type\": \"chat\"},\n            {\"id\": \"MiniMax-M2.1-highspeed\", \"name\": \"MiniMax M2.1 高速版\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"minimax-code\": {\n        \"display_name\": \"MiniMax（Coding Plan）\",\n        \"base_url\": \"https://api.minimaxi.com/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.minimaxi.com/dashboard\",\n        \"share_api_key_with\": \"minimax\",\n        \"models\": [\n            {\"id\": \"MiniMax-M2.5\", \"name\": \"MiniMax M2.5\", \"type\": \"coding\"},\n            {\"id\": \"MiniMax-M2.5-highspeed\", \"name\": \"MiniMax M2.5 高速版\", \"type\": \"coding\"},\n        ],\n    },\n    \"kimi\": {\n        \"display_name\": \"Kimi / Moonshot 开放平台\",\n        \"base_url\": \"https://api.moonshot.cn/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.moonshot.cn/console/api-keys\",\n        \"models\": [\n            {\"id\": \"kimi-k2.5\", \"name\": \"Kimi K2.5（旗舰多模态）\", \"type\": \"chat\"},\n            {\"id\": \"kimi-k2\", \"name\": \"Kimi K2\", \"type\": \"chat\"},\n            {\"id\": \"kimi-latest\", \"name\": \"Kimi Latest\", \"type\": \"chat\"},\n            {\"id\": \"moonshot-v1-auto\", \"name\": \"Moonshot v1 Auto\", \"type\": \"chat\"},\n            {\"id\": \"moonshot-v1-128k\", \"name\": \"Moonshot v1 128K\", \"type\": \"chat\"},\n        ],\n    },\n    \"kimi-code\": {\n        \"display_name\": \"Kimi Code（会员编程）\",\n        \"base_url\": \"https://api.kimi.com/coding/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://platform.moonshot.cn/console/api-keys\",\n        \"share_api_key_with\": \"kimi\",\n        \"models\": [\n            {\"id\": \"kimi-for-coding\", \"name\": \"Kimi for Coding（默认）\", \"type\": \"coding\"},\n        ],\n    },\n    \"doubao\": {\n        \"display_name\": \"豆包 (Doubao)\",\n        \"base_url\": \"https://ark.cn-beijing.volces.com/api/v3\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"https://console.volcengine.com/ark/region:ark+cn-beijing/apiKey\",\n        \"models\": [\n            {\"id\": \"doubao-seed-2-0-pro\", \"name\": \"Doubao Seed 2.0 Pro（旗舰）\", \"type\": \"chat\"},\n            {\"id\": \"doubao-seed-2-0-code\", \"name\": \"Doubao Seed 2.0 Code（编码）\", \"type\": \"coding\"},\n            {\"id\": \"doubao-seed-2-0-lite\", \"name\": \"Doubao Seed 2.0 Lite（轻量）\", \"type\": \"lightweight\"},\n        ],\n    },\n    \"ollama\": {\n        \"display_name\": \"Ollama（本地）\",\n        \"base_url\": \"http://localhost:11434/v1\",\n        \"needs_proxy\": False,\n        \"supports_tools\": False,\n        \"api_key_url\": \"https://ollama.com/download\",\n        \"models\": [],  # 动态检测\n    },\n    \"custom\": {\n        \"display_name\": \"自定义（OpenAI兼容）\",\n        \"base_url\": \"\",\n        \"needs_proxy\": False,\n        \"supports_tools\": True,\n        \"api_key_url\": \"\",\n        \"models\": [],\n    },\n}\n\n\nclass LLMService:\n    \"\"\"统一LLM服务单例\"\"\"\n\n    _instance: Optional[\"LLMService\"] = None\n\n    def __new__(cls) -> \"LLMService\":\n        if cls._instance is None:\n            cls._instance = super().__new__(cls)\n            cls._instance._initialized = False\n        return cls._instance\n\n    def __init__(self):\n        if self._initialized:\n            return\n        self._initialized = True\n        self._provider: Optional[LLMProvider] = None\n        self._active_provider_name: str = \"\"\n        self._db_path: str = \"\"\n        logger.info(\"LLMService 初始化完成\")\n\n    def set_db_path(self, db_path: str):\n        \"\"\"设置数据库路径并初始化llm_settings表\"\"\"\n        self._db_path = db_path\n        self._init_db()\n        self._load_provider_from_db()\n\n    # ============================================================\n    # 数据库操作\n    # ============================================================\n    def _init_db(self):\n        if not self._db_path:\n            return\n        try:\n            with sqlite3.connect(self._db_path) as conn:\n                conn.execute(\"\"\"\n                    CREATE TABLE IF NOT EXISTS llm_settings (\n                        key TEXT PRIMARY KEY,\n                        value TEXT NOT NULL,\n                        updated_at TEXT DEFAULT (datetime('now', 'localtime'))\n                    )\n                \"\"\")\n                conn.commit()\n        except Exception as e:\n            logger.error(\"初始化llm_settings表失败: %s\", e)\n\n    def _get_setting(self, key: str, default: str = \"\") -> str:\n        if not self._db_path:\n            return default\n        try:\n            with sqlite3.connect(self._db_path) as conn:\n                row = conn.execute(\n                    \"SELECT value FROM llm_settings WHERE key = ?\", (key,)\n                ).fetchone()\n                return row[0] if row else default\n        except Exception:\n            return default\n\n    def _set_setting(self, key: str, value: str):\n        if not self._db_path:\n            return\n        try:\n            with sqlite3.connect(self._db_path) as conn:\n                conn.execute(\"\"\"\n                    INSERT INTO llm_settings (key, value, updated_at)\n                    VALUES (?, ?, datetime('now', 'localtime'))\n                    ON CONFLICT(key) DO UPDATE SET\n                        value = excluded.value,\n                        updated_at = excluded.updated_at\n                \"\"\", (key, value))\n                conn.commit()\n        except Exception as e:\n            logger.error(\"保存LLM设置失败 [%s]: %s\", key, e)\n\n    # ============================================================\n    # Provider管理\n    # ============================================================\n    def _load_provider_from_db(self):\n        \"\"\"从数据库加载已保存的provider配置\"\"\"\n        provider_name = self._get_setting(\"active_provider\", \"\")\n        if not provider_name:\n            return\n        try:\n            self._build_provider(provider_name)\n        except Exception as e:\n            logger.warning(\"加载已保存的LLM provider失败: %s\", e)\n\n    def _build_provider(self, provider_name: str):\n        \"\"\"根据provider名称构建Provider实例\"\"\"\n        if provider_name not in BUILTIN_PROVIDERS:\n            raise ValueError(f\"未知的LLM提供商: {provider_name}\")\n\n        preset = BUILTIN_PROVIDERS[provider_name]\n\n        api_key = self._get_setting(f\"{provider_name}_api_key\", \"\")\n        # 支持 share_api_key_with：Coding Plan 提供商可共享主提供商的 API Key\n        if not api_key and preset.get(\"share_api_key_with\"):\n            api_key = self._get_setting(f\"{preset['share_api_key_with']}_api_key\", \"\")\n        model = self._get_setting(f\"{provider_name}_model\", \"\")\n        custom_base_url = self._get_setting(f\"{provider_name}_base_url\", \"\")\n        proxy_url = self._get_setting(\"proxy_url\", \"\")\n        proxy_enabled = self._get_setting(\"proxy_enabled\", \"false\") == \"true\"\n        temperature = float(self._get_setting(\"temperature\", \"0.7\"))\n        max_tokens = int(self._get_setting(\"max_tokens\", \"4096\"))\n\n        base_url = custom_base_url or preset[\"base_url\"]\n\n        # 对非Ollama提供商，没有API Key则不创建\n        if provider_name not in (\"ollama\", \"custom\") and not api_key:\n            logger.info(\"提供商 %s 未配置API Key，跳过\", provider_name)\n            return\n\n        # 默认选第一个模型\n        if not model and preset[\"models\"]:\n            model = preset[\"models\"][0][\"id\"]\n\n        models = [\n            ModelInfo(id=m[\"id\"], name=m[\"name\"], model_type=m.get(\"type\", \"chat\"))\n            for m in preset[\"models\"]\n        ]\n\n        # 代理由用户全局开关控制\n        effective_proxy = proxy_url if (proxy_enabled and proxy_url) else None\n\n        config = ProviderConfig(\n            provider_name=provider_name,\n            display_name=preset[\"display_name\"],\n            base_url=base_url,\n            api_key=api_key,\n            model=model,\n            proxy=effective_proxy,\n            temperature=temperature,\n            max_tokens=max_tokens,\n            models=models,\n            supports_tools=preset.get(\"supports_tools\", True),\n            needs_proxy=preset.get(\"needs_proxy\", False),\n            api_key_url=preset.get(\"api_key_url\", \"\"),\n        )\n\n        self._provider = OpenAICompatibleProvider(config)\n        self._active_provider_name = provider_name\n        logger.info(\"LLM Provider已切换: %s / %s\", provider_name, model)\n\n    def switch_provider(self, provider_name: str, config: Dict[str, Any]):\n        \"\"\"切换提供商并保存配置\"\"\"\n        if config.get(\"api_key\"):\n            self._set_setting(f\"{provider_name}_api_key\", config[\"api_key\"])\n        if config.get(\"model\"):\n            self._set_setting(f\"{provider_name}_model\", config[\"model\"])\n        if config.get(\"base_url\"):\n            self._set_setting(f\"{provider_name}_base_url\", config[\"base_url\"])\n        if config.get(\"proxy_url\") is not None:\n            self._set_setting(\"proxy_url\", config[\"proxy_url\"])\n        if config.get(\"proxy_enabled\") is not None:\n            self._set_setting(\"proxy_enabled\", \"true\" if config[\"proxy_enabled\"] else \"false\")\n        if config.get(\"temperature\") is not None:\n            self._set_setting(\"temperature\", str(config[\"temperature\"]))\n        if config.get(\"max_tokens\") is not None:\n            self._set_setting(\"max_tokens\", str(config[\"max_tokens\"]))\n\n        self._set_setting(\"active_provider\", provider_name)\n        self._build_provider(provider_name)\n\n    # ============================================================\n    # 对外接口\n    # ============================================================\n    @property\n    def is_configured(self) -> bool:\n        return self._provider is not None\n\n    @property\n    def active_provider_name(self) -> str:\n        return self._active_provider_name\n\n    def get_provider(self) -> Optional[LLMProvider]:\n        return self._provider\n\n    async def chat(\n        self,\n        messages: List[LLMMessage],\n        tools: Optional[List[LLMToolDef]] = None,\n        stream: bool = False,\n        temperature: Optional[float] = None,\n        max_tokens: Optional[int] = None,\n    ) -> LLMResponse:\n        if not self._provider:\n            raise RuntimeError(\"LLM服务未配置，请先在设置中选择并配置AI模型提供商\")\n        return await self._provider.chat(messages, tools, stream, temperature, max_tokens)\n\n    async def chat_stream(\n        self,\n        messages: List[LLMMessage],\n        tools: Optional[List[LLMToolDef]] = None,\n        temperature: Optional[float] = None,\n        max_tokens: Optional[int] = None,\n    ) -> AsyncIterator[str]:\n        if not self._provider:\n            raise RuntimeError(\"LLM服务未配置，请先在设置中选择并配置AI模型提供商\")\n        async for chunk in self._provider.chat_stream(messages, tools, temperature, max_tokens):\n            yield chunk\n\n    async def test_connection(self) -> Dict[str, Any]:\n        if not self._provider:\n            return {\"success\": False, \"message\": \"LLM服务未配置\"}\n        return await self._provider.test_connection()\n\n    async def list_models(self, provider_name: Optional[str] = None) -> List[ModelInfo]:\n        \"\"\"获取指定提供商或当前提供商的模型列表\"\"\"\n        if provider_name and provider_name == \"ollama\":\n            # Ollama需要动态检测\n            temp_config = ProviderConfig(\n                provider_name=\"ollama\",\n                display_name=\"Ollama\",\n                base_url=self._get_setting(\"ollama_base_url\", \"http://localhost:11434/v1\"),\n                api_key=\"ollama\",\n                model=\"\",\n            )\n            temp_provider = OpenAICompatibleProvider(temp_config)\n            models = await temp_provider.list_models()\n            await temp_provider.close()\n            return models\n\n        if provider_name and provider_name in BUILTIN_PROVIDERS:\n            preset = BUILTIN_PROVIDERS[provider_name]\n            return [\n                ModelInfo(id=m[\"id\"], name=m[\"name\"], model_type=m.get(\"type\", \"chat\"))\n                for m in preset[\"models\"]\n            ]\n\n        if self._provider:\n            return await self._provider.list_models()\n        return []\n\n    def get_settings(self) -> Dict[str, Any]:\n        \"\"\"获取当前所有LLM设置\"\"\"\n        settings: Dict[str, Any] = {\n            \"active_provider\": self._get_setting(\"active_provider\", \"\"),\n            \"proxy_url\": self._get_setting(\"proxy_url\", \"\"),\n            \"proxy_enabled\": self._get_setting(\"proxy_enabled\", \"false\") == \"true\",\n            \"temperature\": float(self._get_setting(\"temperature\", \"0.7\")),\n            \"max_tokens\": int(self._get_setting(\"max_tokens\", \"4096\")),\n        }\n\n        # 各提供商独立配置\n        for name in BUILTIN_PROVIDERS:\n            settings[f\"{name}_api_key\"] = \"***\" if self._get_setting(f\"{name}_api_key\") else \"\"\n            settings[f\"{name}_model\"] = self._get_setting(f\"{name}_model\", \"\")\n            settings[f\"{name}_base_url\"] = self._get_setting(f\"{name}_base_url\", \"\")\n\n        return settings\n\n    def get_providers_info(self) -> List[Dict[str, Any]]:\n        \"\"\"获取全部可用提供商信息\"\"\"\n        providers = []\n        for name, preset in BUILTIN_PROVIDERS.items():\n            has_key = bool(self._get_setting(f\"{name}_api_key\"))\n            # Coding Plan 提供商可共享主提供商的 API Key\n            share_with = preset.get(\"share_api_key_with\", \"\")\n            if not has_key and share_with:\n                has_key = bool(self._get_setting(f\"{share_with}_api_key\"))\n            selected_model = self._get_setting(f\"{name}_model\", \"\")\n            custom_base_url = self._get_setting(f\"{name}_base_url\", \"\")\n            providers.append({\n                \"name\": name,\n                \"display_name\": preset[\"display_name\"],\n                \"base_url\": preset[\"base_url\"],\n                \"custom_base_url\": custom_base_url,\n                \"needs_proxy\": preset.get(\"needs_proxy\", False),\n                \"supports_tools\": preset.get(\"supports_tools\", True),\n                \"api_key_url\": preset.get(\"api_key_url\", \"\"),\n                \"has_api_key\": has_key,\n                \"selected_model\": selected_model,\n                \"is_active\": name == self._active_provider_name,\n                \"models\": preset[\"models\"],\n                \"share_api_key_with\": share_with,\n            })\n        return providers\n\n    def save_settings(self, settings: Dict[str, Any]):\n        \"\"\"批量保存设置\"\"\"\n        for key, value in settings.items():\n            if key.endswith(\"_api_key\") and value == \"***\":\n                continue  # 跳过未修改的密钥\n            self._set_setting(key, str(value))\n\n        # 如果active_provider变了，重建provider\n        new_provider = settings.get(\"active_provider\", \"\")\n        if new_provider and new_provider != self._active_provider_name:\n            try:\n                self._build_provider(new_provider)\n            except Exception as e:\n                logger.error(\"切换provider失败: %s\", e)\n\n\n# 全局单例\nllm_service = LLMService()\n"}}}}