import os, sys, requests src_dir = os.path.join( os.path.dirname(os.path.dirname(os.path.abspath(__file__))) ) sys.path.append(src_dir) from dev_opsgpt.tools import ( toLangchainTools, get_tool_schema, DDGSTool, DocRetrieval, TOOL_DICT, TOOL_SETS ) from configs.model_config import * from dev_opsgpt.connector.phase import BasePhase from dev_opsgpt.connector.agents import BaseAgent from dev_opsgpt.connector.chains import BaseChain from dev_opsgpt.connector.connector_schema import ( Message, load_role_configs, load_phase_configs, load_chain_configs ) from dev_opsgpt.connector.configs import AGETN_CONFIGS, CHAIN_CONFIGS, PHASE_CONFIGS import importlib print(src_dir) tools = toLangchainTools([TOOL_DICT[i] for i in TOOL_SETS if i in TOOL_DICT]) role_configs = load_role_configs(AGETN_CONFIGS) chain_configs = load_chain_configs(CHAIN_CONFIGS) phase_configs = load_phase_configs(PHASE_CONFIGS) agent_module = importlib.import_module("dev_opsgpt.connector.agents") # agent的测试 query = Message(role_name="tool_react", role_type="human", role_content="我有一份时序数据，[0.857, 2.345, 1.234, 4.567, 3.456, 9.876, 5.678, 7.890, 6.789, 8.901, 10.987, 12.345, 11.234, 14.567, 13.456, 19.876, 15.678, 17.890, 16.789, \ 18.901, 20.987, 22.345, 21.234, 24.567, 23.456, 29.876, 25.678, 27.890, 26.789, 28.901, 30.987, 32.345, 31.234, 34.567, 33.456, 39.876, 35.678, 37.890, 36.789, 38.901, 40.987]，\ 我不知道这份数据是否存在问题，请帮我判断一下", tools=tools) query = Message(role_name="tool_react", role_type="human", role_content="帮我确认下127.0.0.1这个服务器的在10点是否存在异常，请帮我判断一下", tools=tools) query = Message(role_name="code_react", role_type="human", role_content="帮我确认当前目录下有哪些文件", tools=tools) # "给我一份冒泡排序的代码" query = Message(role_name="intention_recognizer", role_type="human", role_content="对employee_data.csv进行数据分析", tools=tools) # role = role_configs["general_planner"] # agent_class = getattr(agent_module, role.role.agent_type) # agent = agent_class(role.role, # task = None, # memory = None, # chat_turn=role.chat_turn, # do_search = role.do_search, # do_doc_retrieval = role.do_doc_retrieval, # do_tool_retrieval = role.do_tool_retrieval,) # message = agent.run(query) # print(message.role_content) # chain的测试 # query = Message(role_name="deveploer", role_type="human", role_content="编写冒泡排序，并生成测例") # query = Message(role_name="general_planner", role_type="human", role_content="对employee_data.csv进行数据分析") # query = Message(role_name="tool_react", role_type="human", role_content="我有一份时序数据，[0.857, 2.345, 1.234, 4.567, 3.456, 9.876, 5.678, 7.890, 6.789, 8.901, 10.987, 12.345, 11.234, 14.567, 13.456, 19.876, 15.678, 17.890, 16.789, 18.901, 20.987, 22.345, 21.234, 24.567, 23.456, 29.876, 25.678, 27.890, 26.789, 28.901, 30.987, 32.345, 31.234, 34.567, 33.456, 39.876, 35.678, 37.890, 36.789, 38.901, 40.987]，\我不知道这份数据是否存在问题，请帮我判断一下", tools=tools) # role = role_configs[query.role_name] role1 = role_configs["planner"] role2 = role_configs["code_react"] agents = [ getattr(agent_module, role1.role.agent_type)(role1.role, task = None, memory = None, do_search = role1.do_search, do_doc_retrieval = role1.do_doc_retrieval, do_tool_retrieval = role1.do_tool_retrieval,), getattr(agent_module, role2.role.agent_type)(role2.role, task = None, memory = None, do_search = role2.do_search, do_doc_retrieval = role2.do_doc_retrieval, do_tool_retrieval = role2.do_tool_retrieval,), ] query = Message(role_name="user", role_type="human", role_content="确认本地是否存在employee_data.csv，并查看它有哪些列和数据类型，分析这份数据的内容，根据这个数据预测未来走势", tools=tools) query = Message(role_name="user", role_type="human", role_content="确认本地是否存在employee_data.csv，并查看它有哪些列和数据类型", tools=tools) chain = BaseChain(chain_configs["dataAnalystChain"], agents, do_code_exec=False) # message = chain.step(query) # print(message.role_content) # print("\n".join("\n".join([": ".join(j) for j in i]) for i in chain.get_agents_memory())) # print("\n".join(": ".join(i) for i in chain.get_memory())) # print( chain.get_agents_memory_str()) # print( chain.get_memory_str()) # 测试 phase phase_name = "toolReactPhase" # phase_name = "codeReactPhase" # phase_name = "chatPhase" phase = BasePhase(phase_name, task = None, phase_config = PHASE_CONFIGS, chain_config = CHAIN_CONFIGS, role_config = AGETN_CONFIGS, do_summary=False, do_code_retrieval=False, do_doc_retrieval=True, do_search=False, ) query = Message(role_name="user", role_type="human", role_content="确认本地是否存在employee_data.csv，并查看它有哪些列和数据类型，并选择合适的数值列画出折线图") query = Message(role_name="user", role_type="human", role_content="判断下127.0.0.1这个服务器的在10点的监控数据，是否存在异常", tools=tools) # 根据其他类似的类，新开发个 ExceptionComponent2，继承 AbstractTrafficComponent # query = Message(role_name="human", role_type="human", role_content="langchain有什么用") # output_message = phase.step(query) # print(phase.get_chains_memory(content_key="step_content")) # print(phase.get_chains_memory_str(content_key="step_content")) # print(output_message.to_tuple_message(return_all=True)) from dev_opsgpt.tools import DDGSTool, CodeRetrieval # print(DDGSTool.run("langchain是什么", 3)) # print(CodeRetrieval.run("dsadsadsa", query.role_content, code_limit=3, history_node_list=[])) # from dev_opsgpt.chat.agent_chat import AgentChat # agentChat = AgentChat() # value = { # "query": "帮我确认下127.0.0.1这个服务器的在10点是否存在异常，请帮我判断一下", # "phase_name": "toolReactPhase", # "chain_name": "", # "history": [], # "doc_engine_name": "DSADSAD", # "search_engine_name": "duckduckgo", # "top_k": 3, # "score_threshold": 1.0, # "stream": False, # "local_doc_url": False, # "do_search": False, # "do_doc_retrieval": False, # "do_code_retrieval": False, # "do_tool_retrieval": False, # "custom_phase_configs": {}, # "custom_chain_configs": {}, # "custom_role_configs": {}, # "choose_tools": list(TOOL_SETS) # } # answer = agentChat.chat(**value) # print(answer)