修复 title 总结失败bug,新增enable_thinking参数

src/routers/deep_agent_chat.py

@@ -39,6 +39,7 @@ async def chat_stream(request: DeepAgentChatRequest):
 
     #### 2. 请求参数
     * `message`: 用户的设计意图（如：'我想设计一个极简风格的橡木办公桌'）。
+    * `enable_thinking`: 是否开启思考模式。
     * `quote_image_path`: 用户引用图片地址 如："fida-test/furniture/sketches/8a1804d1-5ac9-4d02-bf17-e65fa7272f65.png"。
     * `input_image_paths`: 用户上传图片地址集合如：["fida-test/furniture/sketches/8a1804d1-5ac9-4d02-bf17-e65fa7272f65.png"]。
     * `thread_id`: (可选) 现有项目的唯一标识。若不传，系统将自动分配并返回。
@@ -106,7 +107,7 @@ async def chat_stream(request: DeepAgentChatRequest):
     # 构建主agent
     workspace_dir = os.path.join(PROJECT_ROOT, f"agent_workspace/{target_thread_id}")
     logger.info(f"chat request data: {request} | target_thread_id : workspace_dir: {workspace_dir}")
-    main_agent = build_main_agent(request.use_report, workspace_dir)
+    main_agent = build_main_agent(request.use_report, workspace_dir, request.enable_thinking)
     # 2. 配置參數
     temp = request.config_params.temperature if request.config_params else 0.7
 
@@ -318,7 +319,7 @@ async def chat_stream(request: DeepAgentChatRequest):
         # 获取标题
         if need_title:
             title = await conversation_title(agent=main_agent, config=current_config)
-            logger.info(f"[need_title] {title}")
+            logger.info(f"[title] {title}")
             yield f"data: {json.dumps({'title': title}, ensure_ascii=False)}\n\n"
 
         yield f"data: {json.dumps({'status': 'end'}, ensure_ascii=False)}\n\n"

src/schemas/deep_agent_chat.py

@@ -11,6 +11,7 @@ class AgentConfig(BaseModel):
 
 class DeepAgentChatRequest(BaseModel):
     message: str = Field(..., description="用户的输入指令")
+    enable_thinking: Optional[bool] = Field(default=False, description="是否开启思考模式")
     quote_image_path: Optional[str] = Field(None, description="引用图片地址")  # ✅ 新增
     input_image_paths: Optional[list[str]] = Field(None, description="上传图片地址集合")  # ✅ 新增
     thread_id: Optional[str] = Field(None, description="会话线程ID，不传则开启新会话")

src/server/deep_agent/agents/main_agent.py

@@ -9,7 +9,7 @@ from src.core.config import MONGO_URI
 from src.server.deep_agent.agents.painter import build_painter_subagent
 from src.server.deep_agent.agents.researcher import build_researcher_subagent
 from src.server.deep_agent.agents.user_profile import user_profile_subagent
-from src.server.deep_agent.init_llm import main_llm
+from src.server.deep_agent.init_llm import build_main_llm
 from src.server.deep_agent.init_prompt import build_system_prompt
 
 client = MongoClient(MONGO_URI)
@@ -39,7 +39,7 @@ class CanvasMiddleware:
         return state, agent_input
 
 
-def build_main_agent(use_report, workspace_dir):
+def build_main_agent(use_report, workspace_dir, enable_thinking):
     research_subagent = build_researcher_subagent(workspace_dir)
     painter_subagent = build_painter_subagent(workspace_dir)
     subagents = [
@@ -48,7 +48,7 @@ def build_main_agent(use_report, workspace_dir):
         user_profile_subagent
     ]
     main_agent = create_deep_agent(
-        model=main_llm,
+        model=build_main_llm(enable_thinking=enable_thinking),
         system_prompt=build_system_prompt(use_report=use_report),
         subagents=subagents,
         checkpointer=checkpointer,
@@ -58,7 +58,7 @@ def build_main_agent(use_report, workspace_dir):
         ),
         middleware=[
             SummarizationMiddleware(
-                model=main_llm,
+                model=build_main_llm(enable_thinking=enable_thinking),
                 trigger=("tokens", 3000),
                 keep=("messages", 100),
             ),

src/server/deep_agent/init_llm.py

@@ -22,13 +22,18 @@ title_llm = ChatQwen(
     api_key=settings.QWEN_API_KEY
 )
 
+
+def build_main_llm(enable_thinking):
     main_llm = ChatQwen(
+        enable_thinking=enable_thinking,
         model="qwen3.5-flash",
         temperature=0.2,
         max_tokens=3_000,
         timeout=None,
         max_retries=2,
         api_key=settings.QWEN_API_KEY)
+    return main_llm
+
 
 suggested_llm = ChatQwen(
     model="qwen-plus",

src/server/deep_agent/tools/conversation_title_tool.py

@@ -22,8 +22,6 @@ async def conversation_title(agent, config):
 
         if user_msg and ai_msg:
             break
-    if not user_msg or not ai_msg:
-        return None
 
     prompt = f"""
     请根据以下首次对话内容，生成一个简洁、精准的标题（2-15个字）：