mirror of
https://github.com/open-compass/opencompass.git
synced 2025-05-30 16:03:24 +08:00
6aaf3b91ec
* [Feature] Support chat style inferencer. * [Fix] use new prompt * [Fix] use new prompt --------- Co-authored-by: yingfhu <yingfhu@gmail.com>
72 lines
3.2 KiB
Python
72 lines
3.2 KiB
Python
from lagent.agents.react import ReAct
|
|
from lagent.schema import ActionReturn, ActionStatusCode, AgentReturn
|
|
|
|
|
|
class CIReAct(ReAct):
|
|
"""Code Interpreter version of ReAct. The success state is different from
|
|
ReAct.
|
|
|
|
Args:
|
|
llm (BaseModel or BaseAPIModel): a LLM service which can chat
|
|
and act as backend.
|
|
action_executor (ActionExecutor): an action executor to manage
|
|
all actions and their response.
|
|
protocol (ReActProtocol): a wrapper to generate prompt and
|
|
parse the response from LLM / actions.
|
|
max_turn (int): the maximum number of trails for LLM to generate
|
|
plans that can be successfully parsed by ReWOO protocol.
|
|
"""
|
|
|
|
def reset(self):
|
|
"""Reset history and reset action if suit the case."""
|
|
self._session_history = []
|
|
# hard code here
|
|
from opencompass.lagent.actions.ipython_interpreter import \
|
|
IPythonInterpreter
|
|
b = IPythonInterpreter()
|
|
b.reset()
|
|
|
|
def chat(self, message: str) -> AgentReturn:
|
|
self._inner_history = []
|
|
# append the user message for session history
|
|
self._session_history.append(dict(role='user', content=message))
|
|
agent_return = AgentReturn()
|
|
force_stop = False
|
|
default_response = '对不起，我无法回答你的问题'
|
|
for turn in range(self.max_turn):
|
|
prompt = self._protocol.format(
|
|
chat_history=self.session_history,
|
|
inner_step=self._inner_history,
|
|
action_executor=self._action_executor,
|
|
force_stop=force_stop)
|
|
response = self._llm.generate_from_template(prompt, 512)
|
|
self._inner_history.append(dict(role='assistant',
|
|
content=response))
|
|
thought, action, action_input = self._protocol.parse(
|
|
response, self._action_executor)
|
|
action_return: ActionReturn = self._action_executor(
|
|
action, action_input)
|
|
action_return.thought = thought
|
|
agent_return.actions.append(action_return)
|
|
if action_return.state == ActionStatusCode.SUCCESS:
|
|
# if success, stash model response and system response
|
|
self._session_history.append(
|
|
dict(role='assistant', content=response))
|
|
self._session_history.append(
|
|
dict(
|
|
role='system',
|
|
content=self._protocol.format_response(action_return)))
|
|
agent_return.response = action_return.result['text']
|
|
return agent_return
|
|
elif action_return.type == self._action_executor.invalid_action.name: # noqa
|
|
action_return.errmsg = 'The action is invalid, please check the action name.' # noqa
|
|
self._inner_history.append(
|
|
dict(role='system',
|
|
content=self._protocol.format_response(action_return)))
|
|
if turn == self.max_turn - 1:
|
|
force_stop = True
|
|
agent_return.response = default_response
|
|
self._session_history.append(
|
|
dict(role='assistant', content=agent_return.response))
|
|
return agent_return
|