diff --git a/app/server/ChatbotAgent/agent_server.py b/app/server/ChatbotAgent/agent_server.py
index 3e44e9d..db0b73f 100644
--- a/app/server/ChatbotAgent/agent_server.py
+++ b/app/server/ChatbotAgent/agent_server.py
@@ -44,7 +44,6 @@ class LCAgent(ls.LitAPI):
             'max_len': 9,
             'gemini_model_name': settings.LLM_MODEL_NAME
         }
-        self.outfit_ids = []
 
     async def decode_request(self, request: AgentRequestModel):
         """
@@ -62,15 +61,17 @@ class LCAgent(ls.LitAPI):
 
     async def predict(self, request):
 
-        self.outfit_ids = [str(uuid.uuid4()) for _ in range(request.num_outfits)]
+        outfit_ids = [str(uuid.uuid4()) for _ in range(request.num_outfits)]
 
-        asyncio.create_task(self.background_run(request))
-        return {"status": "Task initiated in background.", "outfit_ids": self.outfit_ids}
+        asyncio.create_task(self.background_run(request, outfit_ids))
+
+        logger.info({"status": "Task initiated in background.", "outfit_ids": outfit_ids})
+        return {"status": "Task initiated in background.", "outfit_ids": outfit_ids}
 
     async def encode_response(self, output):
         return output
 
-    async def background_run(self, request: AgentRequestModel):
+    async def background_run(self, request: AgentRequestModel, outfit_ids):
         # 1. 根据用户ID查询对话历史，总结对话内容
         request_summary = await self.get_conversation_summary(request.session_id)
         logger.info(f"request_summary: {request_summary}")
@@ -83,7 +84,8 @@ class LCAgent(ls.LitAPI):
                                                              user_id=request.user_id,
                                                              gender=request.gender,
                                                              callback_url=request.callback_url,
-                                                             max_len=request.max_len)
+                                                             max_len=request.max_len,
+                                                             outfit_ids=outfit_ids)
         logger.info("--- Final Recommendation Results ---")
         for i, path in enumerate(recommendation_results.get("successful_outfits", [])):
             logger.info(f"✅ Outfit {i + 1} saved to: {path}")
@@ -104,7 +106,7 @@ class LCAgent(ls.LitAPI):
         return summary
 
     async def recommend_outfit(self, request_summary: str, stylist_name: str, start_outfit=None, num_outfits: int = 1,
-                               user_id: str = "test", gender: str = "male", callback_url: str = None, max_len: int = 9):
+                               user_id: str = "test", gender: str = "male", callback_url: str = None, max_len: int = 9, outfit_ids=None):
         """
         基于用户的对话历史和需求，推荐一套搭配。
 
@@ -112,14 +114,18 @@ class LCAgent(ls.LitAPI):
             request_summary: 用户的request
             start_outfit: 可选的初始搭配列表，每个元素包含 'item_id' 和 'category'。
         """
+        if outfit_ids is None:
+            outfit_ids = []
         if start_outfit is None:
             start_outfit = []
         tasks = []
         task_map = {}
+
+        stylist_agent_kwages = self.stylist_agent_kwages.copy()
         for i in range(num_outfits):
-            self.stylist_agent_kwages['outfit_id'] = self.outfit_ids[i]
-            self.stylist_agent_kwages['max_len'] = max_len
-            agent = AsyncStylistAgent(**self.stylist_agent_kwages)
+            stylist_agent_kwages['outfit_id'] = outfit_ids[i]
+            stylist_agent_kwages['max_len'] = max_len
+            agent = AsyncStylistAgent(**stylist_agent_kwages)
             task = agent.run_styling_process(
                 request_summary=request_summary,
                 stylist_path=stylist_name,
@@ -129,7 +135,7 @@ class LCAgent(ls.LitAPI):
                 gender=gender,
             )
             tasks.append(task)
-            task_map[task] = {"outfit_id": self.outfit_ids[i], "retries": 0}
+            task_map[task] = {"outfit_id": outfit_ids[i], "retries": 0}
         logger.info(f"--- Starting {num_outfits} concurrent outfit generation tasks. ---")
 
         # 2. 任务执行与重试循环
@@ -157,8 +163,8 @@ class LCAgent(ls.LitAPI):
                             logger.info(f"--- Retrying outfit {outfit_id} (Attempt {current_retries + 1}/{retry_limit}). ---")
 
                             # 重新创建任务 (可能需要短暂延迟，例如 time.sleep(1)，但在此异步环境中，我们会通过重新创建 agent/task 来实现)
-                            self.stylist_agent_kwages['outfit_id'] = outfit_id
-                            agent = AsyncStylistAgent(**self.stylist_agent_kwages)
+                            stylist_agent_kwages['outfit_id'] = outfit_id
+                            agent = AsyncStylistAgent(**stylist_agent_kwages)
                             new_task = agent.run_styling_process(
                                 request_summary=request_summary,
                                 stylist_path=stylist_name,