diff --git a/df-llm-agent/llm_agent_app/app.py b/df-llm-agent/llm_agent_app/app.py
index 3a1c8ec..c1ad56b 100644
--- a/df-llm-agent/llm_agent_app/app.py
+++ b/df-llm-agent/llm_agent_app/app.py
@@ -53,6 +53,8 @@ async def llm_agent_stream_system(request, platform=""):
     return res
 
 # 组件
+
+
 @llm_agent_app.route("/ai/azure/deepflow/modules", methods=["POST"])
 @wrap_resp
 async def llm_agent_module(request):
diff --git a/df-llm-agent/llm_agent_app/llm_agent.py b/df-llm-agent/llm_agent_app/llm_agent.py
index 50252b0..c0e67fa 100644
--- a/df-llm-agent/llm_agent_app/llm_agent.py
+++ b/df-llm-agent/llm_agent_app/llm_agent.py
@@ -77,42 +77,42 @@
 
 class llmAgentWorker(object):
 
-    request = None
+    def __init__(self, request=None, user_info='', user_question={}, system_content="", messages="", query="", res_chat_id=0, engine_name="", output=[], output_all=[], custom_llm={}, azure_client=None, langchain_azure_client=None):
+        self.request = request
 
-    user_info = ""
+        self.user_info = user_info
 
-    # 原生问题
-    user_question = {}
+        # 原生问题
+        self.user_question = user_question
 
-    #
-    system_content = ""
-    messages = ""
+        #
+        self.system_content = system_content
+        self.messages = messages
 
-    # 拼装后的问题
-    query = ""
+        # 拼装后的问题
+        self.query = query
 
-    # 会话id
-    res_chat_id = 0
+        # 会话id
+        self.res_chat_id = res_chat_id
 
-    # 使用引擎名称
-    engine_name = ""
+        # 使用引擎名称
+        self.engine_name = engine_name
 
-    # llm返回的数据经过提取后用于显示的内容
-    output = []
-    # llm返回的原生数据或请求异常信息
-    output_all = []
+        # llm返回的数据经过提取后用于显示的内容
+        self.output = output
+        # llm返回的原生数据或请求异常信息
+        self.output_all = output_all
 
-    custom_llm = {}
+        self.custom_llm = custom_llm
 
-    # agent
-    azure_client = None
+        # agent
+        self.azure_client = azure_client
 
-    # Df组件
-    langchain_azure_client = None
+        # Df组件
+        self.langchain_azure_client = langchain_azure_client
 
     # openai token 计算
-    @classmethod
-    async def num_tokens_from_messages(cls, messages, model="gpt-3.5-turbo-0613"):
+    async def num_tokens_from_messages(self, messages, model="gpt-3.5-turbo-0613"):
         """Return the number of tokens used by a list of messages."""
         try:
             encoding = tiktoken.encoding_for_model(model)
@@ -138,14 +138,14 @@ async def num_tokens_from_messages(cls, messages, model="gpt-3.5-turbo-0613"):
             print(
                 "Warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613."
             )
-            return await cls.num_tokens_from_messages(
+            return await self.num_tokens_from_messages(
                 messages, model="gpt-3.5-turbo-0613"
             )
         elif "gpt-4" in model:
             print(
                 "Warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613."
             )
-            return await cls.num_tokens_from_messages(messages, model="gpt-4-0613")
+            return await self.num_tokens_from_messages(messages, model="gpt-4-0613")
         else:
             raise NotImplementedError(
                 f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens."""
@@ -161,39 +161,36 @@ async def num_tokens_from_messages(cls, messages, model="gpt-3.5-turbo-0613"):
         return num_tokens
 
     # 记录会话，等gpt处理后再依据返回更新该对话
-    @classmethod
-    async def chat_add(cls):
+    async def chat_add(self):
 
         chat_data = {}
-        chat_data["engine"] = cls.engine_name
-        chat_data["chat_topic_id"] = cls.request.ctx.chat_topic_id
-        chat_data["input"] = cls.user_question
+        chat_data["engine"] = self.engine_name
+        chat_data["chat_topic_id"] = self.request.ctx.chat_topic_id
+        chat_data["input"] = self.user_question
         # chat_data["output"] = ""
 
         res = await chat_record_worker.chat_record_add(
-            user_info=cls.user_info, args={}, data=chat_data
+            user_info=self.user_info, args={}, data=chat_data
         )
 
-        cls.res_chat_id = res.get("res_chat_id", 0)
+        self.res_chat_id = res.get("res_chat_id", 0)
 
-        if cls.request.ctx.chat_topic_id <= 0:
-            cls.request.ctx.chat_topic_id = res.get("res_chat_topic_id", 0)
+        if self.request.ctx.chat_topic_id <= 0:
+            self.request.ctx.chat_topic_id = res.get("res_chat_topic_id", 0)
 
     # 更新会话
-    @classmethod
-    async def chat_up(cls):
+    async def chat_up(self):
         chat_data = {}
-        chat_data["output"] = "".join(cls.output)
-        chat_data["output_all"] = cls.output_all
+        chat_data["output"] = "".join(self.output)
+        chat_data["output_all"] = self.output_all
 
         await chat_record_worker.chat_record_update(
-            user_info=cls.user_info, res_chat_id=cls.res_chat_id, data=chat_data
+            user_info=self.user_info, res_chat_id=self.res_chat_id, data=chat_data
         )
 
     # 基础参数配置
-    @classmethod
     async def assistant_base(
-        cls, request, user_info, platform, engine_name, prompt_type, args, data
+        self, user_info, platform, engine_name, prompt_type, args, data
     ):
 
         # user_id = user_info.get("ID", 0)
@@ -208,13 +205,13 @@ async def assistant_base(
             )
 
         #
-        cls.query = [{"role": "user", "content": data["user_content"]}]
+        self.query = [{"role": "user", "content": data["user_content"]}]
 
-        cls.system_content = data["system_content"]
+        self.system_content = data["system_content"]
 
         if platform == "baidu" or platform == "zhipu":
-            cls.query = [
-                {"role": "user", "content": cls.system_content},
+            self.query = [
+                {"role": "user", "content": self.system_content},
                 {
                     "role": "assistant",
                     "content": "好的，后面的回复将按照你给我的角色和要求来解答",
@@ -296,7 +293,7 @@ async def assistant_base(
 
             # 组件
             if prompt_type == "langchain":
-                cls.langchain_azure_client = AzureChatOpenAI(
+                self.langchain_azure_client = AzureChatOpenAI(
                     azure_endpoint=engine_config.get("api_base"),
                     deployment_name=engine_config.get("engine_name"),
                     openai_api_version=engine_config.get("api_version"),
@@ -304,13 +301,13 @@ async def assistant_base(
                     openai_api_key=engine_config.get("api_key"),
                 )
             else:
-                cls.azure_client = AsyncAzureOpenAI(
+                self.azure_client = AsyncAzureOpenAI(
                     api_key=engine_config.get("api_key"),
                     api_version=engine_config.get("api_version"),
                     azure_endpoint=engine_config.get("api_base"),
                 )
 
-            cls.engine_name = engine_config.get("engine_name")
+            self.engine_name = engine_config.get("engine_name")
 
         elif platform == "openai":
             for key in ("api_key", "engine_name"):
@@ -321,7 +318,7 @@ async def assistant_base(
                     )
 
             openai.api_key = engine_config.get("api_key")
-            cls.engine_name = engine_config.get("engine_name")
+            self.engine_name = engine_config.get("engine_name")
 
         elif platform == "aliyun":
             for key in ("api_key", "engine_name"):
@@ -332,7 +329,7 @@ async def assistant_base(
                     )
 
             dashscope.api_key = engine_config.get("api_key")
-            cls.engine_name = engine_config.get("engine_name")
+            self.engine_name = engine_config.get("engine_name")
 
         elif platform == "baidu":
             for key in ("api_key", "api_secre", "engine_name"):
@@ -344,7 +341,7 @@ async def assistant_base(
 
             qianfan.AK(engine_config.get("api_key"))
             qianfan.SK(engine_config.get("api_secre"))
-            cls.engine_name = engine_config.get("engine_name")
+            self.engine_name = engine_config.get("engine_name")
 
         elif platform == "zhipu":
             for key in ("api_key", "engine_name"):
@@ -355,7 +352,7 @@ async def assistant_base(
                     )
 
             zhipuai.api_key = engine_config.get("api_key")
-            cls.engine_name = engine_config.get("engine_name")
+            self.engine_name = engine_config.get("engine_name")
 
         elif platform == "custom_llm":
             for key in (
@@ -378,34 +375,33 @@ async def assistant_base(
             custom_llm_config["api_version"] = engine_config.get("api_version")
             custom_llm_config["api_url"] = engine_config.get("api_url")
 
-            cls.custom_llm = custom_llm_config
-            cls.engine_name = engine_config.get("engine_name")
+            self.custom_llm = custom_llm_config
+            self.engine_name = engine_config.get("engine_name")
         else:
             raise BadRequestException(
                 "INVALID_PARAMETERS",
                 f"{const.INVALID_PARAMETERS}, 模型所在平台名称错误",
             )
         #
-        cls.user_info = user_info
-        cls.request = request
-        cls.user_question = json.dumps(data)
+        self.user_info = user_info
+        self.user_question = json.dumps(data)
 
         # 消息
 
-        # cls.messages = [{'role': 'user', 'content': 'Count to 1000, with a comma between each number and no newlines. E.g., 1, 2, 3, ...'}]
+        # self.messages = [{'role': 'user', 'content': 'Count to 1000, with a comma between each number and no newlines. E.g., 1, 2, 3, ...'}]
 
-        cls.messages = [{"role": "system", "content": cls.system_content}, *cls.query]
+        self.messages = [{"role": "system", "content": self.system_content}, *self.query]
 
         if platform == "baidu" or platform == "zhipu":
-            cls.messages = [*cls.query]
+            self.messages = [*self.query]
 
         if platform == "custom_llm":
-            cls.messages = {"messages": cls.messages}
+            self.messages = {"messages": self.messages}
 
         conv_history_tokens = 0
         if platform == "azure" or platform == "openai":
             try:
-                conv_history_tokens = await cls.num_tokens_from_messages(cls.messages)
+                conv_history_tokens = await self.num_tokens_from_messages(self.messages)
             except Exception as e:
                 raise BadRequestException(
                     "FAIL", f"{const.FAIL}: 计算token数量错误: {e}"
@@ -414,7 +410,7 @@ async def assistant_base(
         elif platform == "aliyun":
 
             response_token = dashscope.Tokenization.call(
-                model=cls.engine_name, messages=cls.messages
+                model=self.engine_name, messages=self.messages
             )
             if response_token.status_code != HTTPStatus.OK:
                 raise BadRequestException(
@@ -427,19 +423,16 @@ async def assistant_base(
 
         print(conv_history_tokens)
         # 记录会话
-        await cls.chat_add()
+        await self.chat_add()
 
     # 流处理
 
-    @classmethod
     async def assistant_stream(
-        cls, request, user_info, platform, engine_name, prompt_type, args, data
+        self, user_info, platform, engine_name, prompt_type, args, data
     ):
 
         # 校验
-        await cls.assistant_base(
-            request, user_info, platform, engine_name, prompt_type, args, data
-        )
+        await self.assistant_base(user_info, platform, engine_name, prompt_type, args, data)
 
         # 开始时间
         working_start_time = datetime.datetime.now()
@@ -447,12 +440,12 @@ async def assistant_stream(
         if platform == "azure" or platform == "openai":
             try:
                 if platform == "azure":
-                    response = await cls.azure_client.chat.completions.create(
-                        model=cls.engine_name, messages=cls.messages, stream=True
+                    response = await self.azure_client.chat.completions.create(
+                        model=self.engine_name, messages=self.messages, stream=True
                     )
                 else:
                     response = await openai.ChatCompletion.acreate(
-                        engine=cls.engine_name, messages=cls.messages, stream=True
+                        engine=self.engine_name, messages=self.messages, stream=True
                     )
 
             except Exception as e:
@@ -473,9 +466,9 @@ async def generate_data(output, output_all):
                         working_end_time.timestamp() - working_start_time.timestamp()
                     )
 
-                    # msg = f"用户: {cls.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {item}"
+                    # msg = f"用户: {self.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {item}"
                     msg = {}
-                    msg["user_id"] = cls.user_info.get("ID", 0)
+                    msg["user_id"] = self.user_info.get("ID", 0)
                     msg["start_time"] = f"{working_start_time}"
                     msg["end_time"] = f"{working_end_time}"
                     msg["all_time"] = all_time
@@ -498,9 +491,9 @@ async def generate_data(output, output_all):
                     yield content
 
                 # 写入
-                cls.output = output
-                cls.output_all = output_all
-                await cls.chat_up()
+                self.output = output
+                self.output_all = output_all
+                await self.chat_up()
 
             return generate_data(output, output_all)
 
@@ -508,8 +501,8 @@ async def generate_data(output, output_all):
             try:
 
                 responses = dashscope.Generation.call(
-                    model=cls.engine_name,  # Generation.Models.qwen_turbo,
-                    messages=cls.messages,
+                    model=self.engine_name,  # Generation.Models.qwen_turbo,
+                    messages=self.messages,
                     result_format="message",
                     stream=True,
                     incremental_output=True,
@@ -531,9 +524,9 @@ async def generate_data(output, output_all):
                         working_end_time.timestamp() - working_start_time.timestamp()
                     )
 
-                    # msg = f"用户: {cls.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {response}"
+                    # msg = f"用户: {self.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {response}"
                     msg = {}
-                    msg["user_id"] = cls.user_info.get("ID", 0)
+                    msg["user_id"] = self.user_info.get("ID", 0)
                     msg["start_time"] = f"{working_start_time}"
                     msg["end_time"] = f"{working_end_time}"
                     msg["all_time"] = all_time
@@ -557,9 +550,9 @@ async def generate_data(output, output_all):
                     yield content
 
                 # 写入
-                cls.output = output
-                cls.output_all = output_all
-                await cls.chat_up()
+                self.output = output
+                self.output_all = output_all
+                await self.chat_up()
 
             return generate_data(output, output_all)
 
@@ -569,7 +562,7 @@ async def generate_data(output, output_all):
                 chat_comp = qianfan.ChatCompletion()
                 # 指定特定模型
                 response = await chat_comp.ado(
-                    model=cls.engine_name, messages=cls.messages, stream=True
+                    model=self.engine_name, messages=self.messages, stream=True
                 )
 
             except Exception as e:
@@ -588,10 +581,10 @@ async def generate_data(output, output_all):
                         working_end_time.timestamp() - working_start_time.timestamp()
                     )
 
-                    # msg = f"用户: {cls.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {item}"
+                    # msg = f"用户: {self.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {item}"
 
                     msg = {}
-                    msg["user_id"] = cls.user_info.get("ID", 0)
+                    msg["user_id"] = self.user_info.get("ID", 0)
                     msg["start_time"] = f"{working_start_time}"
                     msg["end_time"] = f"{working_end_time}"
                     msg["all_time"] = all_time
@@ -612,9 +605,9 @@ async def generate_data(output, output_all):
                     yield content
 
                 # 写入
-                cls.output = output
-                cls.output_all = output_all
-                await cls.chat_up()
+                self.output = output
+                self.output_all = output_all
+                await self.chat_up()
 
             return generate_data(output, output_all)
 
@@ -622,7 +615,7 @@ async def generate_data(output, output_all):
 
             try:
                 response = zhipuai.model_api.sse_invoke(
-                    model=cls.engine_name, prompt=cls.messages
+                    model=self.engine_name, prompt=self.messages
                 )
 
             except Exception as e:
@@ -643,9 +636,9 @@ async def generate_data(output, output_all):
                         working_end_time.timestamp() - working_start_time.timestamp()
                     )
 
-                    # msg = f"用户: {cls.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: "
+                    # msg = f"用户: {self.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: "
                     msg = {}
-                    msg["user_id"] = cls.user_info.get("ID", 0)
+                    msg["user_id"] = self.user_info.get("ID", 0)
                     msg["start_time"] = f"{working_start_time}"
                     msg["end_time"] = f"{working_end_time}"
                     msg["all_time"] = all_time
@@ -675,9 +668,9 @@ async def generate_data(output, output_all):
                     yield content
 
                 # 写入
-                cls.output = output
-                cls.output_all = output_all
-                await cls.chat_up()
+                self.output = output
+                self.output_all = output_all
+                await self.chat_up()
 
             return generate_data(output, output_all)
 
@@ -686,12 +679,12 @@ async def generate_data(output, output_all):
             lcuuid = generate_uuid()
             headers = {
                 "BCS-APIHub-RequestId": lcuuid,
-                "X-CHJ-GWToken": cls.custom_llm["api_key"],
+                "X-CHJ-GWToken": self.custom_llm["api_key"],
             }
-            url = cls.custom_llm["api_url"]
+            url = self.custom_llm["api_url"]
             try:
                 response = curl_tools.curl_app_stream(
-                    "post", url, headers, json.dumps(cls.messages)
+                    "post", url, headers, json.dumps(self.messages)
                 )
             except BadRequestException as e:
                 raise BadRequestException(
@@ -724,9 +717,9 @@ async def generate_data(output, output_all):
                         working_end_time.timestamp() - working_start_time.timestamp()
                     )
 
-                    # msg = f"用户: {cls.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {item}"
+                    # msg = f"用户: {self.user_info.get('ID', 0)} 请求gpt开始时间: {working_start_time}, 结束时间: {working_end_time}, 共耗时: {all_time} 秒,返回信息: {item}"
                     msg = {}
-                    msg["user_id"] = cls.user_info.get("ID", 0)
+                    msg["user_id"] = self.user_info.get("ID", 0)
                     msg["start_time"] = f"{working_start_time}"
                     msg["end_time"] = f"{working_end_time}"
                     msg["all_time"] = all_time
@@ -751,25 +744,23 @@ async def generate_data(output, output_all):
                     yield content
 
                 # 写入
-                cls.output = output
-                cls.output_all = output_all
-                await cls.chat_up()
+                self.output = output
+                self.output_all = output_all
+                await self.chat_up()
 
             return generate_data(output, output_all)
 
     # 组件
-    @classmethod
-    async def module(cls, request, user_info, platform, engine_name, args, data):
+    async def module(self, user_info, platform, engine_name, args, data):
         # 校验
-        await cls.assistant_base(
-            request, user_info, platform, engine_name, "langchain", args, data
-        )
+        await self.assistant_base(user_info, platform, engine_name, "langchain", args, data
+                                  )
 
         # 开始时间
         working_start_time = datetime.datetime.now()
 
         # azure模型
-        llm = cls.langchain_azure_client
+        llm = self.langchain_azure_client
 
         # 字符串返回
         output_parser = StrOutputParser()
@@ -843,7 +834,7 @@ async def module(cls, request, user_info, platform, engine_name, args, data):
         full_chain = {"topic": chain, "question": lambda x: x["question"]} | branch
 
         # 问题
-        question = cls.query[0]["content"]
+        question = self.query[0]["content"]
 
         try:
             # 异步一次性返回
@@ -853,22 +844,22 @@ async def module(cls, request, user_info, platform, engine_name, args, data):
             working_end_time = datetime.datetime.now()
             all_time = working_end_time.timestamp() - working_start_time.timestamp()
             msg = {}
-            msg["user_id"] = cls.user_info.get("ID", 0)
+            msg["user_id"] = self.user_info.get("ID", 0)
             msg["start_time"] = f"{working_start_time}"
             msg["end_time"] = f"{working_end_time}"
             msg["all_time"] = all_time
             msg["return"] = res
             # 记录并返回
-            cls.output.append(f"{res}")
-            cls.output_all.append(msg)
+            self.output.append(f"{res}")
+            self.output_all.append(msg)
 
             return res
         except Exception as e:
-            cls.output_all.append(e)
+            self.output_all.append(e)
             raise BadRequestException("APP_ERROR", const.APP_ERROR, f"{e}")
         finally:
             # 更新会话记录，包括所有返回可记录数据
-            await cls.chat_up()
+            await self.chat_up()
 
 
 llm_agent_worker = llmAgentWorker()
diff --git a/df-llm-agent/llm_agent_app/worker.py b/df-llm-agent/llm_agent_app/worker.py
index 382fae5..0b3715c 100644
--- a/df-llm-agent/llm_agent_app/worker.py
+++ b/df-llm-agent/llm_agent_app/worker.py
@@ -1,6 +1,6 @@
 from exception import BadRequestException
 import const
-from llm_agent_app.llm_agent import llm_agent_worker
+from llm_agent_app.llm_agent import llmAgentWorker
 from config import config
 from utils.curl_tools import curl_tools
 from utils import logger
@@ -14,51 +14,45 @@
 
 class app_worker(object):
 
-    args = data = user_info = None
-
     def __init__(self, request):
-        app_worker.request = request
-        app_worker.args = request.args
-        if app_worker.args:
+        self.request = request
+        self.args = request.args
+        if self.args:
             for k, v in self.args.items():
-                app_worker.args[k] = [i for i in v]
+                self.args[k] = [i for i in v]
 
-        app_worker.data = request.json
-        app_worker.user_info = request.ctx.user
+        self.data = request.json
+        self.user_info = request.ctx.user
 
-    @classmethod
-    async def llm_agent_config_add(cls):
+    async def llm_agent_config_add(self):
         # 校验todoing
-        return await llm_agent_config_worker.llm_agent_config_add(cls.user_info, cls.args, cls.data)
+        return await llm_agent_config_worker.llm_agent_config_add(self.user_info, self.args, self.data)
 
-    @classmethod
-    async def llm_agent_config_list(cls, platform=""):
+    async def llm_agent_config_list(self, platform=""):
 
-        return await llm_agent_config_worker.llm_agent_config_list(cls.user_info, platform)
+        return await llm_agent_config_worker.llm_agent_config_list(self.user_info, platform)
 
-    @classmethod
-    async def llm_agent_config_update(cls, platform="", key_name=""):
+    async def llm_agent_config_update(self, platform="", key_name=""):
         # 校验todoing
-        return await llm_agent_config_worker.llm_agent_config_update(cls.user_info, platform, key_name, cls.args, cls.data)
+        return await llm_agent_config_worker.llm_agent_config_update(self.user_info, platform, key_name, self.args, self.data)
 
-    @classmethod
-    async def llm_agent_config_delete(cls, platform="", engine_name=""):
+    async def llm_agent_config_delete(self, platform="", engine_name=""):
         # 校验todoing
-        return await llm_agent_config_worker.llm_agent_config_delete(cls.user_info, platform, engine_name, cls.args, cls.data)
+        return await llm_agent_config_worker.llm_agent_config_delete(self.user_info, platform, engine_name, self.args, self.data)
 
     # 流处理
-    @classmethod
-    async def llm_agent_stream(cls, platform, prompt_type=''):
+    async def llm_agent_stream(self, platform, prompt_type=''):
         # 校验todoing
-        engine_name = cls.args.get("engine", "")
+        engine_name = self.args.get("engine", "")
         if not engine_name:
             raise BadRequestException("INVALID_PARAMETERS", f"{const.INVALID_PARAMETERS}, 缺失使用的引擎名称")
-        return await llm_agent_worker.assistant_stream(cls.request, cls.user_info, platform, engine_name, prompt_type, cls.args, cls.data)
+        llm_agent_worker = llmAgentWorker(self.request)
+        return await llm_agent_worker.assistant_stream(self.user_info, platform, engine_name, prompt_type, self.args, self.data)
 
     # 组件
-    @classmethod
-    async def llm_agent_module(cls, platform):
-        engine_name = cls.args.get("engine", "")
+    async def llm_agent_module(self, platform):
+        engine_name = self.args.get("engine", "")
         if not engine_name:
             raise BadRequestException("INVALID_PARAMETERS", f"{const.INVALID_PARAMETERS}, 缺失使用的引擎名称")
-        return await llm_agent_worker.module(cls.request, cls.user_info, platform, engine_name, cls.args, cls.data)
+        llm_agent_worker = llmAgentWorker(self.request)
+        return await llm_agent_worker.module(self.user_info, platform, engine_name, self.args, self.data)
diff --git a/df-llm-agent/resource_app/worker.py b/df-llm-agent/resource_app/worker.py
index c3529f3..9625090 100644
--- a/df-llm-agent/resource_app/worker.py
+++ b/df-llm-agent/resource_app/worker.py
@@ -12,31 +12,24 @@
 
 class app_worker(object):
 
-    args = data = user_info = None
-
     def __init__(self, request):
-        app_worker.request = request
-        app_worker.args = request.args
-        if app_worker.args:
+        self.request = request
+        self.args = request.args
+        if self.args:
             for k, v in self.args.items():
-                app_worker.args[k] = [i for i in v]
-        # app_worker.files = request.files
-        # app_worker.data = request.json
-        app_worker.user_info = request.ctx.user
+                self.args[k] = [i for i in v]
+        self.user_info = request.ctx.user
 
-    @classmethod
-    async def img_add(cls):
+    async def img_add(self):
         # 校验todoing
-        files = cls.request.files
-        return await resource_worker.img_add(cls.user_info, cls.args, files)
+        files = self.request.files
+        return await resource_worker.img_add(self.user_info, self.args, files)
 
-    @classmethod
-    async def img_add_b64(cls):
+    async def img_add_b64(self):
         # 校验todoing
-        data = cls.request.json
-        return await resource_worker.img_add_b64(cls.user_info, cls.args, data)
+        data = self.request.json
+        return await resource_worker.img_add_b64(self.user_info, self.args, data)
 
-    @classmethod
-    async def img_get(cls, hash_name=""):
+    async def img_get(self, hash_name=""):
         # 校验todoing
-        return await resource_worker.img_get(cls.user_info, cls.args, hash_name)
+        return await resource_worker.img_get(self.user_info, self.args, hash_name)
diff --git a/df-llm-agent/server.py b/df-llm-agent/server.py
index b9cc9fe..5a94eff 100644
--- a/df-llm-agent/server.py
+++ b/df-llm-agent/server.py
@@ -34,7 +34,7 @@
 @app.middleware("request")
 async def run_before_handler(request):
     req_headers = dict(request.headers)
-    req_path = request.path
+    # req_path = request.path
 
     if request.method.lower() == 'options':
         headers = {