✨ feat(llm): 优化 DeepSeek 适配器 (#2160)

* ✨ feat(llm): 新增 Grok 适配器及 API 密钥重置指令

- 新增 Grok 适配器并支持原生推特检索工具 `x_search`
- 优化 DeepSeek 适配器以迁移至 Responses 协议，增强多模态支持
- 在 LLM 管理插件中新增 `llm reset` 子命令以重置 Key 状态
- 增强 MCP 连接异常处理及流关闭容错能力

* 🚨 auto fix by pre-commit hooks

---------

Co-authored-by: webjoin111 <455457521@qq.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

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

@@ -1,24 +1,27 @@
 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
+from zhenxun.services.ai.core.options import GenerationConfig, ResponseFormat
 
 from .handlers.openai_handlers import (
-    OpenAIConfigMapper,
-    OpenAITextHandler,
-    OpenAIToolSerializer,
+    OpenAIResponsesTextHandler,
+    ResponsesConfigMapper,
+    ResponsesMessageConverter,
+    ResponsesResponseParser,
+    ResponsesToolSerializer,
 )
-from .openai import OpenAICompatAdapter
+from .openai import OpenAIResponsesAdapter
 
 
-class DeepSeekToolSerializer(OpenAIToolSerializer):
+class DeepSeekToolSerializer(ResponsesToolSerializer):
     """
     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"):
@@ -68,7 +71,35 @@ class DeepSeekToolSerializer(OpenAIToolSerializer):
         return pipeline.run(schema)
 
 
-class DeepSeekConfigMapper(OpenAIConfigMapper):
+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):
     """DeepSeek 的专属配置映射器"""
 
     def map_config(
@@ -77,39 +108,38 @@ class DeepSeekConfigMapper(OpenAIConfigMapper):
         model_detail: ModelDetail | None = None,
         capabilities: ModelCapabilities | None = None,
     ) -> dict[str, Any]:
-        """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)
+        """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
 
-        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
+        return super().map_config(config, model_detail, capabilities)
 
 
-class DeepSeekTextHandler(OpenAITextHandler):
-    """DeepSeek 专有文本处理器，替换了特定序列化组件"""
+class DeepSeekTextHandler(OpenAIResponsesTextHandler):
+    """DeepSeek 专有 Responses 文本对话处理器，组装所有定制化子件"""
 
     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(OpenAICompatAdapter):
-    """DeepSeek 官方 API 适配器"""
+class DeepSeekAdapter(OpenAIResponsesAdapter):
+    """DeepSeek Responses 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:
-        """返回 DeepSeek 请求日志清洗上下文。"""
-        return "openai_request"
+        """复用 Responses API 的日志清洗上下文。"""
+        return "openai_responses_request"
 
     @property
     def api_type(self) -> str:
@@ -120,7 +150,3 @@ class DeepSeekAdapter(OpenAICompatAdapter):
     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"