diff --git a/rag2_0/dify/WorkorderToDify.py b/rag2_0/dify/WorkorderToDify.py
index 3e1bcaf..c3e56f7 100644
--- a/rag2_0/dify/WorkorderToDify.py
+++ b/rag2_0/dify/WorkorderToDify.py
@@ -4,7 +4,8 @@ import datetime
 import logging
 import concurrent.futures
 import threading
-
+from dotenv import load_dotenv
+load_dotenv()
 # 配置日志
 logging.basicConfig(
     level=logging.INFO,
@@ -22,7 +23,7 @@ import pandas as pd
 
 
 class WorkorderToDify:
-    def __init__(self, excel_path="data/excel/2025.1-6月工单(人工整理后).xlsx"):
+    def __init__(self, excel_path="data/excel/2025.1-6月工单(已补充标签)-人工删减.xlsx"):
         self.pd_data = pd.read_excel(excel_path)
         self.dify_api = DifyApi.DifyApi()
         self.dataset_ids = {}
@@ -162,9 +163,6 @@ class WorkorderToDify:
             result_workorders = []
             for query, data in merged_workorders.items():
                 workorder = data["workorder"].copy()
-                # 合并所有内容，使用换行符和分隔符分隔
-                if len(data["contents"])>1:
-                    breakpoint()
                 merged_content = "\n\n---\n\n".join(data["contents"])
                 workorder["content"] = merged_content
                 result_workorders.append(workorder)
@@ -174,6 +172,11 @@ class WorkorderToDify:
         
         logging.info("所有技能组工单去重处理完成")
     
+    def del_all_document(self):
+        """删除所有文档"""
+        for skill_group, dataset_id in self.dataset_ids.items():
+            self.dify_api.remove_dataset_all_doc(dataset_id)
+
     def upload_workorders(self):
         """上传每个技能组的工单作为独立文档"""
         logging.info("开始上传工单文档")
@@ -185,7 +188,7 @@ class WorkorderToDify:
         lock = threading.Lock()
         
         # 创建一个线程池
-        max_workers = min(20, os.cpu_count() * 5)  # 最多20个线程，或者CPU核心数的5倍
+        max_workers = min(20, os.cpu_count() * 2)  # 最多20个线程，或者CPU核心数的5倍
         logging.info(f"创建线程池，最大线程数: {max_workers}")
         
         def upload_document(args):
@@ -260,6 +263,7 @@ class WorkorderToDify:
         self.check_and_create_metadata()
         self.classify_workorders()
         self.deduplicate_workorders()
+        # self.del_all_document()
         self.upload_workorders()
 
 
diff --git a/rag2_0/dify/intent_recognition_api.py b/rag2_0/dify/intent_recognition_api.py
index ccccb0a..c0687f6 100755
--- a/rag2_0/dify/intent_recognition_api.py
+++ b/rag2_0/dify/intent_recognition_api.py
@@ -67,6 +67,7 @@ class IntentRecognizeResponse(BaseModel):
     has_slot_filling: bool = False
     slot_filling: SlotFillingResponse = Field(default_factory=SlotFillingResponse)
     query_expand: QueryExpandResponse = Field(default_factory=QueryExpandResponse)
+    dinge_qingdan_info: Dict[str, Any] = Field(default_factory=dict)
 
 # 创建FastAPI应用
 app = FastAPI(
@@ -118,6 +119,7 @@ async def intent_recognize(request: IntentRecognizeRequest):
             enable_query_expansion=enable_query_expansion,
             cur_soft_name=current_softname
         )
+        dinge_qingdan_info = result["dinge_qingdan_info"]
         
         end_time = time.time()
         current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S %z")
@@ -152,7 +154,8 @@ async def intent_recognize(request: IntentRecognizeRequest):
                 missing_slots=slot_filling.get("missing_slots", {}),
                 filled_data=slot_filling.get("filled_data", {})
             ),
-            query_expand=QueryExpandResponse(**result["query_expand"])
+            query_expand=QueryExpandResponse(**result["query_expand"]),
+            dinge_qingdan_info=dinge_qingdan_info
         )
         
         return response
@@ -174,7 +177,7 @@ if __name__ == "__main__":
     uvicorn.run(
         "rag2_0.dify.intent_recognition_api:app", 
         host="0.0.0.0", 
-        port=8001, 
+        port=9001, 
         reload=True,  # 开发环境启用热重载
         workers=1     # 生产环境可以增加worker数量
     )
diff --git a/rag2_0/intent_recognition/IntentRecognition.py b/rag2_0/intent_recognition/IntentRecognition.py
index 8c04089..53c33fc 100755
--- a/rag2_0/intent_recognition/IntentRecognition.py
+++ b/rag2_0/intent_recognition/IntentRecognition.py
@@ -64,7 +64,7 @@ class AsyncIntentRecognizer:
         model_name = os.getenv("MODEL_NAME", "gpt-3.5-turbo")
         # 初始化LLM
         llm_params = {
-            "temperature": 0.2,  # 降低随机性，使结果更确定
+            "temperature": 0.4,  # 降低随机性，使结果更确定
             "top_p": 0.7,
             "model": model_name,
             "api_key": api_key,
diff --git a/rag2_0/intent_recognition/PromptTemplates.py b/rag2_0/intent_recognition/PromptTemplates.py
index 6ceb363..03ed6cc 100755
--- a/rag2_0/intent_recognition/PromptTemplates.py
+++ b/rag2_0/intent_recognition/PromptTemplates.py
@@ -54,10 +54,14 @@ classification_info="""【垂直领域分类】：
 3. 安装下载类：安装下载咨询、组件(插件)选择、环境配置、安装包下载、政策文件(规范文件)下载等
 4. 问题排查类：软件安装下载失败、报错，系统兼容性问题等
 
-【固定话术类包括以下一类】：
-1. 规费咨询：咨询规费(规费、社保费、公积金费等)费用考虑、构成、设置等。才属于该类
-规费报表在哪显示-->属于软件功能
-规费怎么设置、社保费是多少-->属于规费咨询
+【固定话术类包括以下类】：
+
+1. 规费咨询
+   **以下两种情况才属于该类**
+   1、当询问规费（如社会保障费和住房公积金）费率是/填多少
+   2、去哪里获取规费费率
+   **其余涉及规费的属于其他垂直领域分类**
+
 【其他】:
 1. 其他