🚨 auto fix by pre-commit hooks

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.8.2 → v0.16.6](https://github.com/astral-sh/ruff-pre-commit/compare/v0.8.2...v0.16.6)

.pre-commit-config.yaml

@@ -7,7 +7,7 @@ ci:
   autoupdate_commit_msg: ":arrow_up: auto update by pre-commit hooks"
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.2
+    rev: v0.16.6
     hooks:
       - id: ruff
         args: [--fix]

__version__

@@ -1 +1 @@
-__version__: v0.2.4-33d6ea1
+__version__: v0.2.4-203754e

zhenxun/builtin_plugins/hooks/auth/auth_admin.py

@@ -76,8 +76,7 @@ async def auth_admin(
                 raise SkipPluginException(
                     f"{plugin.name}({plugin.module}) 管理员权限不足...",
                     tip_message=(
-                        f"你的权限不足喔，该功能需要的权限等级: "
-                        f"{plugin.admin_level}"
+                        f"你的权限不足喔，该功能需要的权限等级: {plugin.admin_level}"
                     ),
                     tip_background=True,
                 )

zhenxun/builtin_plugins/hooks/auth/context.py

@@ -181,8 +181,7 @@ def event_cache_key(
     channel_id = entity.channel_id or ""
     scope = platform_scope or platform
     return (
-        f"{scope}:{platform}:{bot_id}:{entity.user_id}:"
-        f"{group_id}:{channel_id}:{msg_id}"
+        f"{scope}:{platform}:{bot_id}:{entity.user_id}:{group_id}:{channel_id}:{msg_id}"
     )
 
 

zhenxun/builtin_plugins/info/my_info.py

@@ -121,14 +121,16 @@ async def get_chat_history(
     now = datetime.now()
     filter_date = now - timedelta(days=7)
     date_list = await _read_db(
-        lambda: ChatHistory.filter(
-            user_id=user_id,
-            group_id=group_id,
-            create_time__gte=filter_date,
-        )
-        .annotate(date=RawSQL("DATE(create_time)"), count=Count("id"))
-        .group_by("date")
-        .values("date", "count"),
+        lambda: (
+            ChatHistory.filter(
+                user_id=user_id,
+                group_id=group_id,
+                create_time__gte=filter_date,
+            )
+            .annotate(date=RawSQL("DATE(create_time)"), count=Count("id"))
+            .group_by("date")
+            .values("date", "count")
+        ),
         "MyInfo.chat_history_chart",
         [],
     )

zhenxun/builtin_plugins/llm_manager/__init__.py

@@ -44,11 +44,6 @@ __plugin_meta__ = PluginMetadata(
     llm keys <ProviderName>
       - 查看指定提供商的所有API Key状态。
 
-    llm reset [ProviderName]
-      - 重置 API Key 的熔断与冷却状态。
-      - 带参数: 仅重置指定提供商的所有 Key。
-      - 不带参数: 全局重置所有提供商的所有 Key。
-
     llm mcp [action] [targets...]
       - 管理 MCP (Model Context Protocol) 服务。
       - 不带参数: 查看当前配置的 MCP 服务列表及序号。
@@ -79,9 +74,6 @@ llm_cmd = on_alconna(
             "test", Args["model_name", str], alias=["ping"], help_text="测试模型连通性"
         ),
         Subcommand("keys", Args["provider_name", str], help_text="查看API密钥状态"),
-        Subcommand(
-            "reset", Args["provider_name", str, ""], help_text="重置API密钥状态"
-        ),
         Subcommand(
             "mcp",
             Option("添加", Args["json_strs", MultiVar(str)], alias=["add"]),
@@ -181,22 +173,6 @@ async def handle_keys(arp: Arparma, provider_name: Match[str]):
     await llm_cmd.finish(MessageUtils.build_message(image))
 
 
-@llm_cmd.assign("reset")
-async def handle_reset(arp: Arparma):
-    """处理 'llm reset' 命令"""
-    provider_name = arp.query("reset.provider_name", "").strip()
-    target_log = provider_name if provider_name else "ALL"
-    logger.info(
-        f"执行 API Key 重置操作: {target_log}",
-        command="LLM Manage",
-        session=arp.header_result,
-    )
-    _success, msg = await DataSource.reset_keys(
-        provider_name if provider_name else None
-    )
-    await llm_cmd.finish(msg)
-
-
 @llm_cmd.assign("mcp")
 async def handle_mcp(arp: Arparma, event: Event):
     """处理 'llm mcp' 命令"""

zhenxun/builtin_plugins/llm_manager/data_source.py

@@ -6,10 +6,8 @@ from zhenxun.configs.path_config import DATA_PATH
 from zhenxun.services.ai.core.exceptions import LLMException
 from zhenxun.services.ai.llm.api import chat
 from zhenxun.services.ai.llm.manager import (
-    get_configured_providers,
     get_model_instance,
     list_available_models,
-    reset_key_status,
 )
 from zhenxun.services.ai.tools.providers.mcp.provider import mcp_provider
 
@@ -107,34 +105,6 @@ class DataSource:
 
         return sorted_stats_list
 
-    @staticmethod
-    async def reset_keys(provider_name: str | None = None) -> tuple[bool, str]:
-        """重置指定或所有提供商的 API Key 状态"""
-        providers = get_configured_providers()
-
-        if provider_name:
-            target = next(
-                (p for p in providers if p.name.lower() == provider_name.lower()), None
-            )
-            if not target:
-                return False, f"❌ 未找到提供商 '{provider_name}'，请检查名称是否正确。"
-            await reset_key_status(target.name)
-            return (
-                True,
-                f"✅ 已成功重置提供商 '{target.name}'"
-                "的所有 API Key 状态为健康 (HEALTHY)。",
-            )
-        else:
-            count = 0
-            for p in providers:
-                await reset_key_status(p.name)
-                count += 1
-            return (
-                True,
-                f"✅ 已成功重置所有提供商 (共 {count} 个) "
-                "的 API Key 状态为健康 (HEALTHY)。",
-            )
-
     @staticmethod
     async def get_mcp_list() -> list[dict[str, Any]]:
         """获取排序后的 MCP 列表"""

zhenxun/builtin_plugins/scheduler/auto_update_group.py

@@ -59,7 +59,7 @@ async def _prune_stale_tags():
     deleted_count = await tag_manager.prune_stale_group_links()
     if deleted_count > 0:
         logger.info(
-            f"定时任务：成功清理了 {deleted_count} 个无效的群组标签" f"关联。",
+            f"定时任务：成功清理了 {deleted_count} 个无效的群组标签关联。",
             "群组标签管理",
         )
     else:

zhenxun/builtin_plugins/sign_in/utils.py

@@ -23,9 +23,9 @@ from .config import (
     lik2relation,
 )
 
-assert (
-    len(level2attitude) == len(lik2level) == len(lik2relation)
-), "好感度态度、等级、关系长度不匹配！"
+assert len(level2attitude) == len(lik2level) == len(lik2relation), (
+    "好感度态度、等级、关系长度不匹配！"
+)
 
 AVA_URL = "http://q1.qlogo.cn/g?b=qq&nk={}&s=160"
 

zhenxun/builtin_plugins/superuser/tag_manage.py

@@ -426,8 +426,9 @@ async def handle_delete(names: Match[list[str]]):
 async def handle_clear():
     confirm = await prompt_until(
         "【警告】此操作将删除所有群组标签，是否继续？\n请输入 `是` 或 `确定` 确认操作",
-        lambda msg: msg.extract_plain_text().lower()
-        in ["是", "确定", "yes", "confirm"],
+        lambda msg: (
+            msg.extract_plain_text().lower() in ["是", "确定", "yes", "confirm"]
+        ),
         timeout=30,
         retry=1,
     )

zhenxun/services/ai/llm/adapters/deepseek.py

@@ -1,27 +1,24 @@
 from typing import Any
 
-from zhenxun.services.ai.core.messages import ImagePart, LLMMessage
 from zhenxun.services.ai.core.models import (
     ModelCapabilities,
     ModelDetail,
+    ModelIdentity,
 )
-from zhenxun.services.ai.core.options import GenerationConfig, ResponseFormat
+from zhenxun.services.ai.core.options import GenerationConfig
 
 from .handlers.openai_handlers import (
-    OpenAIResponsesTextHandler,
-    ResponsesConfigMapper,
-    ResponsesMessageConverter,
-    ResponsesResponseParser,
-    ResponsesToolSerializer,
+    OpenAIConfigMapper,
+    OpenAITextHandler,
+    OpenAIToolSerializer,
 )
-from .openai import OpenAIResponsesAdapter
+from .openai import OpenAICompatAdapter
 
 
-class DeepSeekToolSerializer(ResponsesToolSerializer):
+class DeepSeekToolSerializer(OpenAIToolSerializer):
     """
     专门针对 DeepSeek 的工具序列化器。
     负责抹平 Pydantic Schema 与 DeepSeek Strict Mode 之间的差异。
-    由于继承了 ResponsesToolSerializer，已自动获得 web_search 工具的原生格式支持。
     """
 
     def __init__(self, api_type: str = "deepseek"):
@@ -71,35 +68,7 @@ class DeepSeekToolSerializer(ResponsesToolSerializer):
         return pipeline.run(schema)
 
 
-class DeepSeekMessageConverter(ResponsesMessageConverter):
-    """DeepSeek 专属 Responses 消息转换器"""
-
-    def __init__(self, api_type: str = "deepseek"):
-        super().__init__(api_type=api_type)
-
-    async def convert_messages_async(
-        self, messages: list[LLMMessage]
-    ) -> list[dict[str, Any]]:
-        input_items = await super().convert_messages_async(messages)
-
-        image_parts = [
-            p for msg in messages for p in msg.content if isinstance(p, ImagePart)
-        ]
-        img_idx = 0
-
-        for item in input_items:
-            if item.get("role") in ("user", "developer") and "content" in item:
-                for c in item["content"]:
-                    if c.get("type") == "input_image":
-                        if img_idx < len(image_parts):
-                            part = image_parts[img_idx]
-                            img_idx += 1
-                            if getattr(part, "media_resolution", None):
-                                c["detail"] = str(part.media_resolution).lower()
-        return input_items
-
-
-class DeepSeekConfigMapper(ResponsesConfigMapper):
+class DeepSeekConfigMapper(OpenAIConfigMapper):
     """DeepSeek 的专属配置映射器"""
 
     def map_config(
@@ -108,38 +77,39 @@ class DeepSeekConfigMapper(ResponsesConfigMapper):
         model_detail: ModelDetail | None = None,
         capabilities: ModelCapabilities | None = None,
     ) -> dict[str, Any]:
-        """拦截并处理 DeepSeek 目前无法严格遵循复杂 json_schema 的问题"""
-        if (
-            config.output.response_format == ResponseFormat.JSON
-            and config.output.response_schema
-        ):
-            config.output.response_schema = None
+        """映射生成参数并处理 DeepSeek 专有 `thinking` 与响应格式差异。"""
+        params = super().map_config(config, model_detail, capabilities)
 
-        return super().map_config(config, model_detail, capabilities)
+        if "response_format" in params:
+            rf = params["response_format"]
+            if isinstance(rf, dict) and rf.get("type") == "json_schema":
+                params["response_format"] = {"type": "json_object"}
+
+        return params
 
 
-class DeepSeekTextHandler(OpenAIResponsesTextHandler):
-    """DeepSeek 专有 Responses 文本对话处理器，组装所有定制化子件"""
+class DeepSeekTextHandler(OpenAITextHandler):
+    """DeepSeek 专有文本处理器，替换了特定序列化组件"""
 
     def __init__(self, api_type: str = "deepseek"):
+        """替换 OpenAI 默认组件为 DeepSeek 专用实现。"""
         super().__init__(api_type=api_type)
-        self.converter = DeepSeekMessageConverter(api_type=api_type)
         self.serializer = DeepSeekToolSerializer(api_type=api_type)
         self.mapper = DeepSeekConfigMapper(api_type=api_type)
-        self.parser = ResponsesResponseParser()
 
 
-class DeepSeekAdapter(OpenAIResponsesAdapter):
-    """DeepSeek Responses API 适配器"""
+class DeepSeekAdapter(OpenAICompatAdapter):
+    """DeepSeek 官方 API 适配器"""
 
     def __init__(self):
+        """初始化 DeepSeek 适配器并挂载文本处理器。"""
         super().__init__()
         self.text_handler = DeepSeekTextHandler(api_type=self.api_type)
 
     @property
     def log_sanitization_context(self) -> str:
-        """复用 Responses API 的日志清洗上下文。"""
-        return "openai_responses_request"
+        """返回 DeepSeek 请求日志清洗上下文。"""
+        return "openai_request"
 
     @property
     def api_type(self) -> str:
@@ -150,3 +120,7 @@ class DeepSeekAdapter(OpenAIResponsesAdapter):
     def supported_api_types(self) -> list[str]:
         """当前适配器支持的 API 类型列表。"""
         return ["deepseek"]
+
+    def get_chat_endpoint(self, identity: ModelIdentity) -> str:
+        """返回对话端点，优先使用模型级自定义端点。"""
+        return "/v1/chat/completions"

zhenxun/services/ai/llm/adapters/factory.py

@@ -31,7 +31,6 @@ class LLMAdapterFactory:
         from .doubao import DoubaoAdapter
         from .gemini import GeminiAdapter
         from .glm import GLMAdapter
-        from .grok import GrokAdapter
         from .jina import JinaAdapter
         from .mimo import MiMoAdapter
         from .minimax import MiniMaxAdapter
@@ -49,7 +48,6 @@ class LLMAdapterFactory:
         cls.register_adapter(MiMoAdapter())
         cls.register_adapter(MiniMaxAdapter())
         cls.register_adapter(DoubaoAdapter())
-        cls.register_adapter(GrokAdapter())
 
     @classmethod
     def register_adapter(cls, adapter: BaseAdapter) -> None:
@@ -116,7 +114,6 @@ class SmartAdapter(BaseAdapter):
         ("*gemini*", "gemini"),
         ("*deepseek*", "deepseek"),
         ("*minimax*", "minimax"),
-        ("*grok*", "grok"),
         ("*gpt*", "openai_responses"),
     ]
     _DEFAULT_API_TYPE: ClassVar[str] = "openai"

zhenxun/services/ai/llm/adapters/grok.py

@@ -1,60 +0,0 @@
-from typing import Any
-
-from zhenxun.services.ai.core.models import ModelCapabilities
-from zhenxun.services.ai.llm.adapters.handlers.openai_handlers import (
-    OpenAIResponsesTextHandler,
-    ResponsesToolSerializer,
-)
-from zhenxun.services.ai.llm.adapters.openai import OpenAIResponsesAdapter
-
-
-class GrokToolSerializer(ResponsesToolSerializer):
-    """Grok 专属工具序列化器"""
-
-    def serialize_server_tools(
-        self, tools: list[Any], capabilities: ModelCapabilities
-    ) -> list[dict[str, Any]]:
-        res = []
-        for t in tools:
-            type_id = getattr(t, "type_id", "unknown")
-            if type_id not in capabilities.supported_native_tools:
-                continue
-
-            if type_id == "web_search":
-                res.append({"type": "web_search"})
-            elif type_id == "x_search":
-                payload = {"type": "x_search"}
-                if getattr(t, "allowed_x_handles", None):
-                    payload["allowed_x_handles"] = t.allowed_x_handles
-                if getattr(t, "excluded_x_handles", None):
-                    payload["excluded_x_handles"] = t.excluded_x_handles
-                res.append(payload)
-            elif type_id == "code_execution":
-                res.append({"type": "code_interpreter"})
-            elif type_id == "file_search":
-                res.append({"type": "file_search"})
-        return res
-
-
-class GrokTextHandler(OpenAIResponsesTextHandler):
-    """Grok 文本处理器"""
-
-    def __init__(self, api_type: str = "grok"):
-        super().__init__(api_type=api_type)
-        self.serializer = GrokToolSerializer(api_type=api_type)
-
-
-class GrokAdapter(OpenAIResponsesAdapter):
-    """xAI Grok API 适配器"""
-
-    def __init__(self):
-        super().__init__()
-        self.text_handler = GrokTextHandler(api_type=self.api_type)
-
-    @property
-    def api_type(self) -> str:
-        return "grok"
-
-    @property
-    def supported_api_types(self) -> list[str]:
-        return ["grok"]

zhenxun/services/ai/llm/adapters/handlers/openai_handlers.py

@@ -521,9 +521,6 @@ class ResponsesConfigMapper(OpenAIConfigMapper):
 class ResponsesMessageConverter(MessageConverter):
     """针对 OpenAI Responses API 的消息转换器"""
 
-    def __init__(self, api_type: str = "openai_responses"):
-        self.api_type = api_type
-
     async def convert_messages_async(
         self, messages: list[LLMMessage]
     ) -> list[dict[str, Any]]:
@@ -546,14 +543,11 @@ class ResponsesMessageConverter(MessageConverter):
                     continue
 
             content_list: list[dict[str, Any]] = []
-            thought_text = ""
             for part in msg.content:
                 if part is None:
                     continue
 
-                if isinstance(part, ThoughtPart):
-                    thought_text += part.thought_text
-                elif isinstance(part, TextPart):
+                if isinstance(part, TextPart):
                     c_type = "output_text" if role == "assistant" else "input_text"
                     content_list.append({"type": c_type, "text": part.text})
                 elif isinstance(part, ImagePart):
@@ -579,26 +573,6 @@ class ResponsesMessageConverter(MessageConverter):
                             {"type": "input_image", "image_url": image_src}
                         )
 
-            if role == "assistant" and thought_text:
-                if self.api_type == "deepseek":
-                    input_items.append(
-                        {
-                            "type": "reasoning",
-                            "content": [
-                                {"type": "reasoning_text", "text": thought_text}
-                            ],
-                            "summary": [],
-                        }
-                    )
-                else:
-                    input_items.append(
-                        {
-                            "type": "reasoning",
-                            "content": [],
-                            "summary": [{"type": "summary_text", "text": thought_text}],
-                        }
-                    )
-
             if content_list:
                 input_items.append({"role": role, "content": content_list})
 
@@ -687,10 +661,6 @@ class ResponsesResponseParser(OpenAIResponseParser):
                     )
                 )
             elif item.get("type") == "reasoning":
-                for r_content in item.get("content", []):
-                    if r_content.get("type") == "reasoning_text":
-                        thought_content += r_content.get("text", "")
-
                 for summary_item in item.get("summary", []):
                     if summary_item.get("type") == "summary_text":
                         thought_content += summary_item.get("text", "")
@@ -898,7 +868,7 @@ class OpenAIResponsesTextHandler(OpenAITextHandler):
 
     def __init__(self, api_type: str = "openai_responses"):
         super().__init__(api_type=api_type)
-        self.converter = ResponsesMessageConverter(api_type=api_type)
+        self.converter = ResponsesMessageConverter()
         self.serializer = ResponsesToolSerializer(api_type=api_type)
         self.mapper = ResponsesConfigMapper(api_type=api_type)
         self.parser = ResponsesResponseParser()

zhenxun/services/ai/llm/engine/middlewares.py

@@ -301,7 +301,7 @@ class LoggingMiddleware:
 
             smart_adapter = cast(SmartAdapter, self.adapter)
             delegate_adapter = smart_adapter._get_delegate_adapter(self.identity)
-            sanitizer_req_context = delegate_adapter.log_sanitization_context
+            sanitizer_req_context = f"{delegate_adapter.api_type}_request"
         else:
             sanitizer_req_context = self.adapter.log_sanitization_context
 

zhenxun/services/ai/llm/engine/router.py

@@ -88,8 +88,7 @@ class FallbackRouter(BaseModelRouter):
                     )
                     raise e
                 logger.warning(
-                    f"⚠️ 节点 '{m_name}' "
-                    f"错误 ({e.__class__.__name__})，触发故障转移..."
+                    f"⚠️ 节点 '{m_name}' 错误 ({e.__class__.__name__})，触发故障转移..."
                 )
                 errors.append(f"{m_name}({e.__class__.__name__})")
             except Exception as e:
@@ -99,7 +98,7 @@ class FallbackRouter(BaseModelRouter):
         if all_nodes_bypassed and len(model_names) > 1:
             fallback_model = health_manager.get_best_fallback_route(model_names)
             logger.warning(
-                f"⚠️ 路由组所有节点均已宕机！" f"强制放行 '{fallback_model}' 探活..."
+                f"⚠️ 路由组所有节点均已宕机！强制放行 '{fallback_model}' 探活..."
             )
             try:
                 async with await get_model_instance(

zhenxun/services/ai/llm/manager.py

@@ -58,7 +58,6 @@ def get_default_api_base_for_type(api_type: str) -> str | None:
         "glm": "https://open.bigmodel.cn",
         "gemini": "https://generativelanguage.googleapis.com",
         "openrouter": "https://openrouter.ai/api",
-        "grok": "https://api.x.ai/v1",
         "smart": None,
         "openai_responses": None,
     }

zhenxun/services/ai/llm/system/capabilities.py

@@ -9,7 +9,6 @@ from zhenxun.utils.pydantic_compat import model_copy
 
 CTX_1_05M = 1_050_000
 CTX_1M = 1_000_000
-CTX_500K = 500_000
 CTX_400K = 400_000
 CTX_256K = 256_000
 CTX_200K = 204_800
@@ -123,16 +122,7 @@ CAP_OPENAI_MULTIMODAL = ModelCapabilities(
     },
     reasoning_effort_map={"max": "xhigh", "minimal": "none"},
 )
-CAP_GROK = ModelCapabilities(
-    input_modalities={ModelModality.TEXT, ModelModality.IMAGE},
-    output_modalities={ModelModality.TEXT},
-    supports_tool_calling=True,
-    reasoning_mode=ReasoningMode.EFFORT,
-    reasoning_visibility="visible",
-    supported_native_tools={"web_search", "x_search", "code_execution", "file_search"},
-)
-
-CAP_DEEPSEEK_PRO = ModelCapabilities(
+CAP_DEEPSEEK_V4 = ModelCapabilities(
     input_modalities={ModelModality.TEXT},
     output_modalities={ModelModality.TEXT},
     supports_tool_calling=True,
@@ -140,14 +130,6 @@ CAP_DEEPSEEK_PRO = ModelCapabilities(
     reasoning_mode=ReasoningMode.EFFORT,
     reasoning_visibility="visible",
     reasoning_effort_map={"minimal": "low"},
-    supported_native_tools={"web_search"},
-)
-
-CAP_DEEPSEEK_FLASH = model_copy(
-    CAP_DEEPSEEK_PRO,
-    update={
-        "input_modalities": {ModelModality.TEXT, ModelModality.IMAGE},
-    },
 )
 CAP_MINIMAX_REASONING = ModelCapabilities(
     input_modalities={ModelModality.TEXT},
@@ -297,10 +279,7 @@ _ROUTING_TABLE: list[tuple[list[str], ModelCapabilities, int]] = [
     (["*gemini*image*", "*nano-banana*"], CAP_GEMINI_IMAGE, CTX_128K),
     (["glm-4.6v*"], CAP_GLM_MULTIMODAL, CTX_128K),
     (["glm-4.7-flash*"], STANDARD_TEXT_TOOL_CAPABILITIES, CTX_128K),
-    (["*grok-4.3*", "*grok-4.20*"], CAP_GROK, CTX_1M),
-    (["*grok*"], CAP_GROK, CTX_500K),
-    (["*deepseek*pro*"], CAP_DEEPSEEK_PRO, CTX_1M),
-    (["*deepseek*flash*"], CAP_DEEPSEEK_FLASH, CTX_1M),
+    (["deepseek-v4-pro*", "deepseek-v4-flash*"], CAP_DEEPSEEK_V4, CTX_1M),
     (["glm-4-long*"], STANDARD_TEXT_TOOL_CAPABILITIES, CTX_1M),
     (["*MiniMax-M3*"], CAP_MINIMAX_MULTIMODAL, CTX_1M),
     (["mimo-v2.5-pro*", "mimo-v2-pro*", "mimo-v2-flash*"], CAP_MIMO_TEXT, CTX_1M),

zhenxun/services/ai/sandbox/addons/mcp_proxy.py

@@ -3,7 +3,6 @@ from contextlib import asynccontextmanager
 import json
 from typing import Any
 
-import anyio
 from anyio import create_memory_object_stream, create_task_group
 from mcp.shared.message import SessionMessage
 from mcp.types import JSONRPCMessage
@@ -62,25 +61,16 @@ class UniversalMcpExtension(BaseMcpProxyExtension):
                                 if not line.strip():
                                     continue
                                 try:
-                                    msg_obj = model_validate(
+                                    msg = model_validate(
                                         JSONRPCMessage, json.loads(line)
                                     )
-                                    await read_prod.send(
-                                        SessionMessage(message=msg_obj)
-                                    )
+                                    await read_prod.send(SessionMessage(message=msg))
                                 except Exception as exc:
                                     await read_prod.send(exc)
-                except anyio.ClosedResourceError:
+                except Exception:
                     pass
-                except BaseException as e:
-                    logger.debug(
-                        f"🔇 [MCP Universal] 读流异常: {type(e).__name__}: {e}"
-                    )
                 finally:
-                    try:
-                        await read_prod.aclose()
-                    except Exception:
-                        pass
+                    await read_prod.aclose()
 
             async def stream_writer():
                 try:
@@ -92,12 +82,8 @@ class UniversalMcpExtension(BaseMcpProxyExtension):
                             + b"\n"
                         )
                         await process_stream.write(data)
-                except anyio.ClosedResourceError:
+                except Exception:
                     pass
-                except BaseException as e:
-                    logger.debug(
-                        f"🔇 [MCP Universal] 写流异常: {type(e).__name__}: {e}"
-                    )
 
             async with create_task_group() as tg:
                 tg.start_soon(stream_reader)

zhenxun/services/ai/tools/providers/builtin/native.py

@@ -30,23 +30,6 @@ class CodeExecutionTool(ServerSideTool):
         self.timeout = timeout
 
 
-class XSearchTool(ServerSideTool):
-    """原生 X (推特) 搜索工具 (Grok独占)"""
-
-    type_id = "x_search"
-
-    def __init__(
-        self,
-        allowed_x_handles: list[str] | None = None,
-        excluded_x_handles: list[str] | None = None,
-    ):
-        super().__init__(
-            name="x_search", description="在 X (Twitter) 上搜索推文、用户资料和时间线。"
-        )
-        self.allowed_x_handles = allowed_x_handles
-        self.excluded_x_handles = excluded_x_handles
-
-
 class ComputerUseTool(ServerSideTool):
     """原生的桌面环境控制工具"""
 
@@ -87,7 +70,10 @@ class UrlContextTool(ServerSideTool):
 
 class Native:
     """
-    云端原生工具命名空间工厂
+    云端原生工具命名空间工厂 (Namespace Factory)。
+
+    为开发者提供统一的云端内置工具调用入口，享受顶级 IDE 补全体验。
+    此类工具仅会向大模型提供描述，物理执行发生在各大模型厂商的服务端。
     """
 
     @classmethod
@@ -103,17 +89,6 @@ class Native:
         """
         return WebSearchTool(name, description, dynamic_threshold, domain_filters)
 
-    @classmethod
-    def x_search(
-        cls,
-        allowed_x_handles: list[str] | None = None,
-        excluded_x_handles: list[str] | None = None,
-    ) -> XSearchTool:
-        """
-        原生 X (Twitter) 检索工具 (Grok 独占)。
-        """
-        return XSearchTool(allowed_x_handles, excluded_x_handles)
-
     @classmethod
     def code_execution(
         cls, name: str = "code_execution", timeout: int | None = None

zhenxun/services/ai/tools/providers/mcp/provider.py

@@ -64,10 +64,8 @@ class MCPServerConfig(BaseModel):
             values["transport"] = values.pop("type")
 
         transport_val = values.get("transport")
-        if isinstance(transport_val, str):
-            t_lower = transport_val.lower()
-            if t_lower in ("streamablehttp", "http"):
-                values["transport"] = "streamable-http"
+        if isinstance(transport_val, str) and transport_val.lower() == "streamablehttp":
+            values["transport"] = "streamable-http"
 
         headers = values.get("headers")
         if isinstance(headers, dict):

zhenxun/services/ai/tools/providers/mcp/toolkit.py

@@ -98,15 +98,8 @@ async def filtered_stdio_client(
                         await filtered_send.send(item)
             except anyio.ClosedResourceError:
                 pass
-            except BaseException as e:
-                logger.debug(
-                    f"🔇 [MCP Stdout Filter] 捕获到底层流异常: {type(e).__name__}: {e}"
-                )
             finally:
-                try:
-                    await filtered_send.aclose()
-                except Exception:
-                    pass
+                await filtered_send.aclose()
 
         async with anyio.create_task_group() as tg:
             tg.start_soon(_forward_stdout)
@@ -547,12 +540,7 @@ class MCPToolkit(BaseToolkit):
                         await self._stop_event.wait()
                         return
 
-                except BaseException as e:
-                    if isinstance(
-                        e, asyncio.CancelledError | KeyboardInterrupt | SystemExit
-                    ):
-                        raise e
-
+                except Exception as e:
                     from zhenxun.services.ai.core.exceptions import SandboxFatalError
 
                     if isinstance(e, SandboxFatalError):
@@ -560,30 +548,23 @@ class MCPToolkit(BaseToolkit):
 
                     if attempt < max_attempts:
                         logger.warning(
-                            f"⚠️ [{self.server_name}] 进程启动或"
-                            f"底层流异常崩溃 ({type(e).__name__})，"
+                            f"⚠️ [{self.server_name}] 进程启动或运行异常崩溃，"
                             "疑似环境损坏。触发自愈机制 (准备重试)..."
                         )
-                        self._init_exception = (
-                            e if isinstance(e, Exception) else Exception(str(e))
-                        )
+                        self._init_exception = e
                         self._shared_session = None
                         if not self._is_initialized:
                             self._is_initialized = False
                         continue
 
-                    if not isinstance(e, Exception):
-                        raise Exception(f"底层致命异常: {e}") from e
                     raise e
 
-        except BaseException as e:
-            if isinstance(e, asyncio.CancelledError | KeyboardInterrupt | SystemExit):
-                raise e
-            self._init_exception = e if isinstance(e, Exception) else Exception(str(e))
+        except Exception as e:
+            self._init_exception = e
             logger.error(
                 f"MCP 服务器 '{self.server_name}' "
-                f"初始化连接或运行期间发生底层故障（模式: {self.transport}）。"
-                f"错误类型: {type(e).__name__}, 原因: {e}"
+                f"初始化连接失败（模式: {self.transport}）。"
+                f"错误原因: {e}"
             )
             if "Connection closed" in str(e):
                 logger.error(

zhenxun/services/db_context/schema_guard.py

@@ -339,9 +339,7 @@ def _index_sql(table: str, columns: tuple[str, ...], dialect: Dialect) -> str |
     index_sql = _quote_identifier(_index_name(table, columns), dialect)
     columns_sql = ", ".join(_quote_identifier(column, dialect) for column in columns)
     if dialect in {"sqlite", "postgres"}:
-        return (
-            f"CREATE INDEX IF NOT EXISTS {index_sql} " f"ON {table_sql}({columns_sql})"
-        )
+        return f"CREATE INDEX IF NOT EXISTS {index_sql} ON {table_sql}({columns_sql})"
     if dialect == "mysql":
         return f"CREATE INDEX {index_sql} ON {table_sql}({columns_sql})"
     return None