✨ 添加额外请求体字段和推理内容请求选项到预设配置以支持deepseek-v4

README.md

@@ -157,6 +157,8 @@ _✨ 支持多API预设、MCP协议、内置工具、联网搜索、视觉模型
 | proxy | 否 | 无 | 请求API时使用的HTTP代理 |
 | support_mcp | 否 | False | 是否支持MCP协议 |
 | support_image | 否 | False | 是否支持图片输入 |
+| extra_body | 否 | {} | 额外的请求体字段，用于兼容不同API的特殊参数 |
+| request_with_reasoning_content | 否 | false | 请求中是否包含推理过程内容（部分模型要求进行了工具调用后，必须完整回传推理过程给API） |
 
 
 LLMCHAT__MCP_SERVERS同样为一个dict，key为服务器名称，value配置的格式基本兼容 Claude.app 的配置格式，具体支持如下
@@ -184,6 +186,18 @@ LLMCHAT__MCP_SERVERS同样为一个dict，key为服务器名称，value配置的
     LLMCHAT__PRIVATE_CHAT_PRESET="deepseek-v1"
     LLMCHAT__API_PRESETS='
     [
+        {
+            "name": "deepseek-v4-pro",
+            "api_key": "sk-your-api-key",
+            "model_name": "deepseek-v4-pro",
+            "api_base": "https://api.deepseek.com",
+            "support_mcp": true,
+            "support_image": false,
+            "extra_body": {
+                "thinking": {"type": "enabled"}
+            },
+            "request_with_reasoning_content": true
+        }，
         {
             "name": "aliyun-deepseek-v3",
             "api_key": "sk-your-api-key",

nonebot_plugin_llmchat/__init__.py

@@ -443,6 +443,7 @@ async def process_messages(context_id: int, is_group: bool = True):
                 "max_tokens": preset.max_tokens,
                 "temperature": preset.temperature,
                 "timeout": 60,
+                "extra_body": preset.extra_body,
             }
 
             if preset.support_mcp:
@@ -461,10 +462,14 @@ async def process_messages(context_id: int, is_group: bool = True):
 
             # 处理响应并处理工具调用
             while preset.support_mcp and message and message.tool_calls:
-                new_messages.append({
+                llm_reply: ChatCompletionMessageParam = {
                     "role": "assistant",
+                    "content": message.content,
                     "tool_calls": [tool_call.model_dump() for tool_call in message.tool_calls]
-                })
+                }
+
+                if preset.request_with_reasoning_content:
+                    llm_reply["reasoning_content"] = message.reasoning_content# pyright: ignore[reportGeneralTypeIssues]
 
                 # 发送LLM调用工具时的回复，一般没有
                 if message.content:
@@ -531,6 +536,9 @@ async def process_messages(context_id: int, is_group: bool = True):
                 # openai的sdk里的assistant消息暂时没有images字段，需要单独处理
                 llm_reply["images"] = reply_images # pyright: ignore[reportGeneralTypeIssues]
 
+            if preset.request_with_reasoning_content:
+                llm_reply["reasoning_content"] = reasoning_content# pyright: ignore[reportGeneralTypeIssues]
+
             new_messages.append(llm_reply)
 
             # 请求成功后再保存历史记录，保证user和assistant穿插，防止R1模型报错
@@ -540,12 +548,20 @@ async def process_messages(context_id: int, is_group: bool = True):
             if state.output_reasoning_content and reasoning_content:
                 try:
                     bot = get_bot(str(event.self_id))
+                    if is_group:
                         await bot.send_group_forward_msg(
                             group_id=group_id,
                             messages=build_reasoning_forward_nodes(
                                 bot.self_id, reasoning_content
                             ),
                         )
+                    else:
+                        await bot.send_private_forward_msg(
+                            user_id=context_id,
+                            messages=build_reasoning_forward_nodes(
+                                bot.self_id, reasoning_content
+                            ),
+                        )
                 except Exception as e:
                     logger.error(f"合并转发消息发送失败：\n{e!s}\n")
 

nonebot_plugin_llmchat/config.py

@@ -13,6 +13,11 @@ class PresetConfig(BaseModel):
     proxy: str = Field("", description="HTTP代理服务器")
     support_mcp: bool = Field(False, description="是否支持MCP")
     support_image: bool = Field(False, description="是否支持图片输入")
+    extra_body: dict = Field({}, description="额外的请求体字段，用于兼容不同API的特殊参数")
+    request_with_reasoning_content: bool = Field(
+        False,
+        description="请求中是否包含推理过程内容（部分模型要求进行了工具调用后，必须完整回传推理过程给API）"
+    )
 
 class MCPServerConfig(BaseModel):
     """MCP服务器配置"""