diff --git a/pilot/base_modules/agent/commands/command_mange.py b/pilot/base_modules/agent/commands/command_mange.py index 7e1f48194..dd95ee2db 100644 --- a/pilot/base_modules/agent/commands/command_mange.py +++ b/pilot/base_modules/agent/commands/command_mange.py @@ -370,7 +370,8 @@ class ApiCall: return html else: api_call_element = ET.Element("chart-view") - api_call_element.set("content", self.__to_antv_vis_param(api_status)) + api_call_element.attrib["content"] = self.__to_antv_vis_param(api_status) + # api_call_element.set("content", self.__to_antv_vis_param(api_status)) # api_call_element.text = self.__to_antv_vis_param(api_status) result = ET.tostring(api_call_element, encoding="utf-8") return result.decode("utf-8") diff --git a/pilot/model/model_adapter.py b/pilot/model/model_adapter.py index 8c4eac537..bed62a34d 100644 --- a/pilot/model/model_adapter.py +++ b/pilot/model/model_adapter.py @@ -158,8 +158,15 @@ class LLMModelAdaper: else: raise ValueError(f"Unknown role: {role}") - can_use_system = "" + can_use_systems:[] = [] if system_messages: + if len(system_messages) > 1: + ## Compatible with dbgpt complex scenarios, the last system will protect more complete information entered by the current user + user_messages[-1] = system_messages[-1] + can_use_systems = system_messages[:-1] + else: + can_use_systems = system_messages + for i in range(len(user_messages)): # TODO vicuna 兼容 测试完放弃 user_messages[-1] = system_messages[-1] if len(system_messages) > 1: @@ -171,8 +178,10 @@ class LLMModelAdaper: conv.append_message(conv.roles[1], ai_messages[i]) if isinstance(conv, Conversation): - conv.set_system_message(can_use_system) + conv.set_system_message("".join(can_use_systems)) else: + conv.update_system_message("".join(can_use_systems)) + conv.update_system_message(can_use_system) # Add a blank message for the assistant. diff --git a/pilot/model/proxy/llms/chatgpt.py b/pilot/model/proxy/llms/chatgpt.py index 9e6d1a20a..97699897c 100644 --- a/pilot/model/proxy/llms/chatgpt.py +++ b/pilot/model/proxy/llms/chatgpt.py @@ -58,6 +58,42 @@ def _initialize_openai(params: ProxyModelParameters): return openai_params +def __convert_2_gpt_messages(messages: List[ModelMessage]): + + chat_round = 0 + gpt_messages = [] + + last_usr_message = "" + system_messages = [] + + for message in messages: + if message.role == ModelMessageRoleType.HUMAN: + last_usr_message = message.content + elif message.role == ModelMessageRoleType.SYSTEM: + system_messages.append(message.content) + elif message.role == ModelMessageRoleType.AI: + last_ai_message = message.content + gpt_messages.append({"role": "user", "content": last_usr_message}) + gpt_messages.append({"role": "assistant", "content": last_ai_message}) + + # build last user messge + + if len(system_messages) >0: + if len(system_messages) > 1: + end_message = system_messages[-1] + else: + last_message = messages[-1] + if last_message.role == ModelMessageRoleType.HUMAN: + end_message = system_messages[-1] + "\n" + last_message.content + else: + end_message = system_messages[-1] + else: + last_message = messages[-1] + end_message = last_message.content + gpt_messages.append({"role": "user", "content": end_message}) + return gpt_messages, system_messages + + def _initialize_openai_v1(params: ProxyModelParameters): try: from openai import OpenAI diff --git a/pilot/scene/chat_agent/auto_gen.py b/pilot/scene/chat_agent/auto_gen.py deleted file mode 100644 index 9f5bda05c..000000000 --- a/pilot/scene/chat_agent/auto_gen.py +++ /dev/null @@ -1,64 +0,0 @@ -import autogen -from autogen import oai, AssistantAgent, UserProxyAgent, config_list_from_json -from openai.openai_object import OpenAIObject - -config_list = [ - { - "model": "gpt-3.5-turbo", - "api_base": "http://43.156.9.162:3001/api/openai/v1", - "api_type": "open_ai", - "api_key": "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", - } -] -llm_config = { - "request_timeout": 600, - "seed": 45, # change the seed for different trials - "config_list": config_list, - "temperature": 0, - "max_tokens": 3000, -} - -# assistant = AssistantAgent("assistant", llm_config=llm_config) -# user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding"}) -# - -assistant = autogen.AssistantAgent( - name="assistant", - llm_config=llm_config, - is_termination_msg=lambda x: True if "TERMINATE" in x.get("content") else False, -) - -# 创建名为 user_proxy 的用户代理实例，这里定义为进行干预 -user_proxy = autogen.UserProxyAgent( - name="user_proxy", - human_input_mode="TERMINATE", - max_consecutive_auto_reply=1, - is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"), - code_execution_config={"work_dir": "web"}, - llm_config=llm_config, - system_message="""Reply TERMINATE if the task has been solved at full satisfaction. -Otherwise, reply CONTINUE, or the reason why the task is not solved yet.""", -) - -task1 = """今天是星期几？,还有几天周末？请告诉我答案。""" - -if __name__ == "__main__": - user_proxy.initiate_chat(assistant, message=task1) - # user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.") - - # response: OpenAIObject = oai.Completion.create( - # config_list=[ - # { - # "model": "gpt-3.5-turbo", - # "api_base": "http://43.156.9.162:3001/api/openai/v1", - # "api_type": "open_ai", - # "api_key": "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", - # } - # ], - # prompt="你好呀！", - # ) - # - # print(response) - # - # text = response.get("choices")[0].get("text") - # print(text) diff --git a/pilot/scene/chat_agent/auto_gen2.py b/pilot/scene/chat_agent/auto_gen2.py deleted file mode 100644 index 0ff65f939..000000000 --- a/pilot/scene/chat_agent/auto_gen2.py +++ /dev/null @@ -1,94 +0,0 @@ -import autogen - -config_list = [ - { - "model": "gpt-3.5-turbo", - "api_base": "http://43.156.9.162:3001/api/openai/v1", - "api_type": "open_ai", - "api_key": "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", - } -] -llm_config = { - "functions": [ - { - "name": "python", - "description": "run cell in ipython and return the execution result.", - "parameters": { - "type": "object", - "properties": { - "cell": { - "type": "string", - "description": "Valid Python cell to execute.", - } - }, - "required": ["cell"], - }, - }, - { - "name": "sh", - "description": "run a shell script and return the execution result.", - "parameters": { - "type": "object", - "properties": { - "script": { - "type": "string", - "description": "Valid shell script to execute.", - } - }, - "required": ["script"], - }, - }, - ], - "config_list": config_list, - "request_timeout": 120, - "max_tokens": 3000, -} -chatbot = autogen.AssistantAgent( - name="chatbot", - system_message="For coding tasks, only use the functions you have been provided with. Reply TERMINATE when the task is done.", - llm_config=llm_config, -) - -# create a UserProxyAgent instance named "user_proxy" -user_proxy = autogen.UserProxyAgent( - name="user_proxy", - is_termination_msg=lambda x: x.get("content", "") - and x.get("content", "").rstrip().endswith("TERMINATE"), - human_input_mode="NEVER", - max_consecutive_auto_reply=10, - code_execution_config={"work_dir": "coding"}, -) - -# define functions according to the function description -from IPython import get_ipython - - -def exec_python(cell): - ipython = get_ipython() - result = ipython.run_cell(cell) - log = str(result.result) - if result.error_before_exec is not None: - log += f"\n{result.error_before_exec}" - if result.error_in_exec is not None: - log += f"\n{result.error_in_exec}" - return log - - -def exec_sh(script): - return user_proxy.execute_code_blocks([("sh", script)]) - - -# register the functions -user_proxy.register_function( - function_map={ - "python": exec_python, - "sh": exec_sh, - } -) - -if __name__ == "__main__": - # start the conversation - user_proxy.initiate_chat( - chatbot, - message="Draw two agents chatting with each other with an example dialog. Don't add plt.show().", - ) diff --git a/pilot/scene/chat_data/chat_excel/excel_analyze/prompt.py b/pilot/scene/chat_data/chat_excel/excel_analyze/prompt.py index 0af8b3c3a..14c743ef5 100644 --- a/pilot/scene/chat_data/chat_excel/excel_analyze/prompt.py +++ b/pilot/scene/chat_data/chat_excel/excel_analyze/prompt.py @@ -19,7 +19,7 @@ Constraint: 2.Please choose the best one from the display methods given below for data rendering, and put the type name into the name parameter value that returns the required format. If you cannot find the most suitable one, use 'Table' as the display method. , the available data display methods are as follows: {disply_type} 3.The table name that needs to be used in SQL is: {table_name}. Please check the sql you generated and do not use column names that are not in the data structure. 4.Give priority to answering using data analysis. If the user's question does not involve data analysis, you can answer according to your understanding. - 5.The part of the required output format needs to be parsed by the code. Please ensure that this part of the content is output as required. + 5.All analysis sql content is converted to: [data display method][correct duckdb data analysis sql] content like this, and answer in the following format. 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