diff --git a/docutranslate/agents/glossary_agent.py b/docutranslate/agents/glossary_agent.py
index d521e49..b752bfc 100644
--- a/docutranslate/agents/glossary_agent.py
+++ b/docutranslate/agents/glossary_agent.py
@@ -18,6 +18,7 @@ class GlossaryAgentConfig(AgentConfig):
 class GlossaryAgent(Agent):
     def __init__(self, config: GlossaryAgentConfig):
         super().__init__(config)
+        self.to_lang=config.to_lang
         self.system_prompt = f"""
 # Role
 You are a professional machine translation engine.
@@ -26,12 +27,12 @@ You are a professional machine translation engine.
 
 # Task
 你会收到一个json格式的段落表，其中键是段落的序号，值是段落的内容。
-你需要从这些段落中提取**人名**和**地名**，并翻译这些名词为{config.to_lang}语言。
+你需要从这些段落中提取**人名**和**地名**，并翻译这些名词为{self.to_lang}语言。
 最终输出一个名词原文:名词译文的术语表
 
 # Requirements
 - 特殊标签、形如`<ph-xxxxxx>`的标签不要添加到术语表
-- 输出术语表的src必须与名词原文完全一致，dst是该名词的{config.to_lang}的译文
+- 输出术语表的src必须与名词原文完全一致，dst是该名词的{self.to_lang}的译文
 - 相同的src仅在术语表中添加一次，不能重复
 
 # Output
@@ -67,7 +68,7 @@ You are a professional machine translation engine.
             return origin_prompt
 
     def send_segments(self, segments: list[str], chunk_size: int):
-        self.logger.info("开始提取术语表")
+        self.logger.info(f"开始提取术语表,to_lang:{self.to_lang}")
         result = {}
         indexed_originals, chunks, merged_indices_list = segments2json_chunks(segments, chunk_size)
         prompts = [json.dumps(chunk, ensure_ascii=False) for chunk in chunks]
@@ -87,7 +88,7 @@ You are a professional machine translation engine.
         return result
 
     async def send_segments_async(self, segments: list[str], chunk_size: int):
-        self.logger.info("开始术语表提取")
+        self.logger.info(f"开始提取术语表,to_lang:{self.to_lang}")
         result = {}
         indexed_originals, chunks, merged_indices_list = await asyncio.to_thread(segments2json_chunks, segments,
                                                                                  chunk_size)
diff --git a/docutranslate/app.py b/docutranslate/app.py
index 0a5cc6f..3a35061 100644
--- a/docutranslate/app.py
+++ b/docutranslate/app.py
@@ -227,6 +227,7 @@ class GlossaryAgentConfigPayload(BaseModel):
     baseurl: str = Field(..., description="用于术语表生成的Agent的LLM API基础URL。", examples=["https://api.openai.com/v1"])
     key: str = Field(..., description="用于术语表生成的Agent的LLM API密钥。", examples=["sk-agent-api-key"])
     model_id: str = Field(..., description="用于术语表生成的Agent的模型ID。", examples=["gpt-4-turbo"])
+    to_lang: str = Field(..., description="术语表生成的目标语言。", examples=["简体中文", "English"])
     temperature: float = Field(default=0.7, description="用于术语表生成的Agent的温度参数。")
     max_concurrent: int = Field(default=30, description="Agent的最大并发请求数。")
     timeout: int = Field(default=2000, description="Agent的API调用超时时间。")
@@ -399,7 +400,7 @@ class TranslateServiceRequest(BaseModel):
                 {
                     "summary": "Markdown 工作流示例",
                     "value": {
-                        "file_name": "annual_report_2023.pdf",
+                        "file_name": "annual_report_203.pdf",
                         "file_content": "JVBERi0xLjcKJeLjz9MKMSAwIG9iago8PC9...",
                         "payload": {
                             "workflow_type": "markdown_based",
@@ -466,6 +467,7 @@ class TranslateServiceRequest(BaseModel):
                                 "baseurl": "https://api.openai.com/v1",
                                 "key": "sk-your-agent-key-for-glossary",
                                 "model_id": "gpt-4-turbo",
+                                "to_lang": "简体中文",
                                 "temperature": 0.5
                             }
                         }
@@ -575,7 +577,6 @@ async def _perform_translation(
                 agent_payload = payload.glossary_agent_config
                 return GlossaryAgentConfig(
                     logger=task_logger,
-                    to_lang=payload.to_lang,
                     **agent_payload.model_dump()
                 )
             return None