import os, sys src_dir = os.path.join( os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) ) sys.path.append(src_dir) from configs.model_config import KB_ROOT_PATH, JUPYTER_WORK_PATH, LLM_MODEL from configs.server_config import SANDBOX_SERVER from coagent.tools import toLangchainTools, TOOL_DICT, TOOL_SETS from coagent.llm_models.llm_config import EmbedConfig, LLMConfig from coagent.connector.phase import BasePhase from coagent.connector.schema import Message # tools = toLangchainTools([TOOL_DICT[i] for i in TOOL_SETS if i in TOOL_DICT]) # log-level,print prompt和llm predict os.environ["log_verbose"] = "0" phase_name = "baseGroupPhase" llm_config = LLMConfig( model_name=LLM_MODEL, model_device="cpu",api_key=os.environ["OPENAI_API_KEY"], api_base_url=os.environ["API_BASE_URL"], temperature=0.3 ) embed_config = EmbedConfig( embed_engine="model", embed_model="text2vec-base-chinese", embed_model_path=os.path.join(src_dir, "embedding_models/text2vec-base-chinese") ) phase = BasePhase( phase_name, sandbox_server=SANDBOX_SERVER, jupyter_work_path=JUPYTER_WORK_PATH, embed_config=embed_config, llm_config=llm_config, kb_root_path=KB_ROOT_PATH, ) # round-1 query_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;然后画柱状图" # query_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" query = Message( role_name="human", role_type="user", tools=[], role_content=query_content, input_query=query_content, origin_query=query_content, ) # phase.pre_print(query) output_message, output_memory = phase.step(query) print(output_memory.to_str_messages(return_all=True, content_key="parsed_output_list"))