from lagent.actions.action_executor import ActionExecutor

from lagent.actions.python_interpreter import PythonInterpreter

from lagent.agents.react import ReAct

from lagent.llms.huggingface import HFTransformer

model = HFTransformer(

path='internlm/internlm-chat-7b-v1_1',

meta_template=[

dict(role='system', begin='<|System|>:', end='<TOKENS_UNUSED_2>\n'),

dict(role='user', begin='<|User|>:', end='<eoh>\n'),

dict(role='assistant', begin='<|Bot|>:', end='<eoa>\n', generate=True)

],

)

chatbot = ReAct(

llm=model,

action_executor=ActionExecutor(actions=[PythonInterpreter()]),

)

def input_prompt():

print('\ndouble enter to end input >>> ', end='')

sentinel = '' # ends when this string is seen

return '\n'.join(iter(input, sentinel))

while True:

try:

prompt = input_prompt()

except UnicodeDecodeError:

print('UnicodeDecodeError')

continue

if prompt == 'exit':

exit(0)

agent_return = chatbot.chat(prompt)

print(agent_return.response)