45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
import os, sys, requests
|
||
|
||
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
|
||
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
|
||
|
||
# log-level，print prompt和llm predict
|
||
os.environ["log_verbose"] = "2"
|
||
|
||
phase_name = "toolReactPhase"
|
||
llm_config = LLMConfig(
|
||
model_name="gpt-3.5-turbo", 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
|
||
tools = toLangchainTools([TOOL_DICT[i] for i in TOOL_SETS if i in TOOL_DICT])
|
||
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=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")) |