diff --git a/agent/guideline_middleware.py b/agent/guideline_middleware.py
index 9ddfb17..a9b2911 100644
--- a/agent/guideline_middleware.py
+++ b/agent/guideline_middleware.py
@@ -6,7 +6,7 @@ from utils.fastapi_utils import (extract_block_from_system_prompt, format_messag
 from langchain.chat_models import BaseChatModel
 from langgraph.runtime import Runtime
 
-from langchain_core.messages import SystemMessage
+from langchain_core.messages import SystemMessage, HumanMessage
 from typing import Any, Callable
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.outputs import LLMResult
@@ -124,10 +124,11 @@ Action: Provide concise, friendly, and personified natural responses.
         response.additional_kwargs["message_tag"] = "THINK"
         response.content = f"<think>{response.content}</think>"
 
-        # 将响应添加到原始消息列表
-        state['messages'] = state['messages'] + [response]
+        # 将响应添加到原始消息列表，并追加 HumanMessage 确保消息以 user 结尾
+        # 某些模型不支持 assistant message prefill，要求最后一条消息必须是 user
+        state['messages'] = state['messages'] + [response, HumanMessage(content=self._get_follow_up_prompt())]
         return state
-        
+
     async def abefore_agent(self, state: AgentState, runtime: Runtime) -> dict[str, Any] | None:
         if not self.guidelines:
             return None
@@ -148,10 +149,23 @@ Action: Provide concise, friendly, and personified natural responses.
         response.additional_kwargs["message_tag"] = "THINK"
         response.content = f"<think>{response.content}</think>"
 
-        # 将响应添加到原始消息列表
-        state['messages'] = state['messages'] + [response]
+        # 将响应添加到原始消息列表，并追加 HumanMessage 确保消息以 user 结尾
+        # 某些模型不支持 assistant message prefill，要求最后一条消息必须是 user
+        state['messages'] = state['messages'] + [response, HumanMessage(content=self._get_follow_up_prompt())]
         return state
 
+    def _get_follow_up_prompt(self) -> str:
+        """根据语言返回引导主 agent 回复的提示"""
+        prompts = {
+            "ja": "以上の分析に基づいて、ユーザーに返信してください。",
+            "jp": "以上の分析に基づいて、ユーザーに返信してください。",
+            "zh": "请根据以上分析，回复用户。",
+            "zh-TW": "請根據以上分析，回覆用戶。",
+            "ko": "위 분석을 바탕으로 사용자에게 답변해 주세요.",
+            "en": "Based on the above analysis, please respond to the user.",
+        }
+        return prompts.get(self.language, prompts["en"])
+
     def wrap_model_call(
         self,
         request: ModelRequest,