Cannot resume groupchat with tool calls

[hujoe17]

I have a multi-agents group chat following the logic in https://microsoft.github.io/autogen/docs/topics/groupchat/resuming_groupchat
But when the group chat involves tool calls, it is not able to restart the group chat. It will cause this error

BadRequestError: Error code: 400 - {'error': {'message': "Invalid parameter: messages with role 'tool' must be a response to a preceeding message with 'tool_calls'.", 'type': 'invalid_request_error', 'param': 'messages.[2].role', 'code': None}}

Steps to reproduce

from typing import Annotated
import autogen


def length_calculator(question: Annotated[str, "question"]) -> int:
    return len(question)

user_proxy = autogen.UserProxyAgent(
    name="User_proxy",
    system_message="A human admin.",
    code_execution_config={
        "work_dir": "groupchat",
        "use_docker": False,
    },  # Please set use_docker=True if docker is available to run the generated code. Using docker is safer than running the generated code directly.
    human_input_mode="NEVER",
)
coder = autogen.AssistantAgent(
    name="Coder",
    llm_config=gpt4_config,
    system_message="You are responsible for calculating the length of the question. Please use the registered calculator tool to help you.",
)
number_agent = autogen.AssistantAgent(
    name="number_agent",
    system_message="You are responsible for returning the length of the question to the user.",
    llm_config=gpt4_config,
)
autogen.register_function(
    length_calculator,
    caller=coder,  # The assistant agent can suggest calls to the calculator.
    executor=user_proxy,  # The user proxy agent can execute the calculator calls.
    name="length_calculator",  # By default, the function name is used as the tool name.
    description="A simple length calculator.",  # A description of the tool.
)
groupchat = autogen.GroupChat(agents=[user_proxy, coder, number_agent], messages=[], max_round=5)
manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=gpt4_config)

chat_result = user_proxy.initiate_chat(
    manager, message="how are you")
previous_state = manager.messages_to_string(manager.groupchat.messages)
# Prepare the group chat for resuming using the previous messages. We don't need to remove the TERMINATE string as we aren't using the last message for resuming.
last_agent, last_message = manager.resume(messages=previous_state)
# Resume the chat using a different agent and message
result = user_proxy.initiate_chat(
    recipient=manager,
    message="what is the length of the last question?",
    clear_history=False,
)

Model Used

gpt-4o-mini

Resume chat without tool calls

If I don't register the tool and run the code, it can successfully generate the results.

from typing import Annotated
import autogen


def length_calculator(question: Annotated[str, "question"]) -> int:
    return len(question)

user_proxy = autogen.UserProxyAgent(
    name="User_proxy",
    system_message="A human admin.",
    code_execution_config={
        "work_dir": "groupchat",
        "use_docker": False,
    },  # Please set use_docker=True if docker is available to run the generated code. Using docker is safer than running the generated code directly.
    human_input_mode="NEVER",
)
coder = autogen.AssistantAgent(
    name="Coder",
    llm_config=gpt4_config,
    system_message="You are responsible for calculating the length of the question. Please use the registered calculator tool to help you.",
)
number_agent = autogen.AssistantAgent(
    name="number_agent",
    system_message="You are responsible for returning the length of the question to the user.",
    llm_config=gpt4_config,
)
# autogen.register_function(
#     length_calculator,
#     caller=coder,  # The assistant agent can suggest calls to the calculator.
#     executor=user_proxy,  # The user proxy agent can execute the calculator calls.
#     name="length_calculator",  # By default, the function name is used as the tool name.
#     description="A simple length calculator.",  # A description of the tool.
# )
groupchat = autogen.GroupChat(agents=[user_proxy, coder, number_agent], messages=[], max_round=5)
manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=gpt4_config)
chat_result = user_proxy.initiate_chat(
    manager, message="how are you")
previous_state = manager.messages_to_string(manager.groupchat.messages)
# Prepare the group chat for resuming using the previous messages. We don't need to remove the TERMINATE string as we aren't using the last message for resuming.
last_agent, last_message = manager.resume(messages=previous_state)
# Resume the chat using a different agent and message
result = user_proxy.initiate_chat(
    recipient=manager,
    message="what is the length of the last question?",
    clear_history=False,
)

Screenshots and logs

---------------------------------------------------------------------------
BadRequestError                           Traceback (most recent call last)
Cell In[38], line 7
      5 last_agent, last_message = manager.resume(messages=previous_state)
      6 # Resume the chat using a different agent and message
----> 7 result = user_proxy.initiate_chat(
      8     recipient=manager,
      9     message="what is the length of the last question?",
     10     clear_history=False,
     11 )

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:1018, in ConversableAgent.initiate_chat(self, recipient, clear_history, silent, cache, max_turns, summary_method, summary_args, message, **kwargs)
   1016     else:
   1017         msg2send = self.generate_init_message(message, **kwargs)
-> 1018     self.send(msg2send, recipient, silent=silent)
   1019 summary = self._summarize_chat(
   1020     summary_method,
   1021     summary_args,
   1022     recipient,
   1023     cache=cache,
   1024 )
   1025 for agent in [self, recipient]:

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:655, in ConversableAgent.send(self, message, recipient, request_reply, silent)
    653 valid = self._append_oai_message(message, "assistant", recipient)
    654 if valid:
--> 655     recipient.receive(message, self, request_reply, silent)
    656 else:
    657     raise ValueError(
    658         "Message can't be converted into a valid ChatCompletion message. Either content or function_call must be provided."
    659     )

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:818, in ConversableAgent.receive(self, message, sender, request_reply, silent)
    816 if request_reply is False or request_reply is None and self.reply_at_receive[sender] is False:
    817     return
--> 818 reply = self.generate_reply(messages=self.chat_messages[sender], sender=sender)
    819 if reply is not None:
    820     self.send(reply, sender, silent=silent)

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:1972, in ConversableAgent.generate_reply(self, messages, sender, **kwargs)
   1970     continue
   1971 if self._match_trigger(reply_func_tuple["trigger"], sender):
-> 1972     final, reply = reply_func(self, messages=messages, sender=sender, config=reply_func_tuple["config"])
   1973     if logging_enabled():
   1974         log_event(
   1975             self,
   1976             "reply_func_executed",
   (...)
   1980             reply=reply,
   1981         )

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\groupchat.py:1052, in GroupChatManager.run_chat(self, messages, sender, config)
   1050         iostream.print(colored(f"\nNext speaker: {speaker.name}\n", "green"), flush=True)
   1051     # let the speaker speak
-> 1052     reply = speaker.generate_reply(sender=self)
   1053 except KeyboardInterrupt:
   1054     # let the admin agent speak if interrupted
   1055     if groupchat.admin_name in groupchat.agent_names:
   1056         # admin agent is one of the participants

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:1972, in ConversableAgent.generate_reply(self, messages, sender, **kwargs)
   1970     continue
   1971 if self._match_trigger(reply_func_tuple["trigger"], sender):
-> 1972     final, reply = reply_func(self, messages=messages, sender=sender, config=reply_func_tuple["config"])
   1973     if logging_enabled():
   1974         log_event(
   1975             self,
   1976             "reply_func_executed",
   (...)
   1980             reply=reply,
   1981         )

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:1340, in ConversableAgent.generate_oai_reply(self, messages, sender, config)
   1338 if messages is None:
   1339     messages = self._oai_messages[sender]
-> 1340 extracted_response = self._generate_oai_reply_from_client(
   1341     client, self._oai_system_message + messages, self.client_cache
   1342 )
   1343 return (False, None) if extracted_response is None else (True, extracted_response)

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\agentchat\conversable_agent.py:1359, in ConversableAgent._generate_oai_reply_from_client(self, llm_client, messages, cache)
   1356         all_messages.append(message)
   1358 # TODO: #1143 handle token limit exceeded error
-> 1359 response = llm_client.create(
   1360     context=messages[-1].pop("context", None), messages=all_messages, cache=cache, agent=self
   1361 )
   1362 extracted_response = llm_client.extract_text_or_completion_object(response)[0]
   1364 if extracted_response is None:

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\oai\client.py:697, in OpenAIWrapper.create(self, **config)
    695 try:
    696     request_ts = get_current_ts()
--> 697     response = client.create(params)
    698 except APITimeoutError as err:
    699     logger.debug(f"config {i} timed out", exc_info=True)

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\autogen\oai\client.py:306, in OpenAIClient.create(self, params)
    304     params = params.copy()
    305     params["stream"] = False
--> 306     response = completions.create(**params)
    308 return response

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\openai\_utils\_utils.py:277, in required_args.<locals>.inner.<locals>.wrapper(*args, **kwargs)
    275             msg = f"Missing required argument: {quote(missing[0])}"
    276     raise TypeError(msg)
--> 277 return func(*args, **kwargs)

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\openai\resources\chat\completions.py:606, in Completions.create(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, parallel_tool_calls, presence_penalty, response_format, seed, stop, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)
    573 @required_args(["messages", "model"], ["messages", "model", "stream"])
    574 def create(
    575     self,
   (...)
    604     timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
    605 ) -> ChatCompletion | Stream[ChatCompletionChunk]:
--> 606     return self._post(
    607         "/chat/completions",
    608         body=maybe_transform(
    609             {
    610                 "messages": messages,
    611                 "model": model,
    612                 "frequency_penalty": frequency_penalty,
    613                 "function_call": function_call,
    614                 "functions": functions,
    615                 "logit_bias": logit_bias,
    616                 "logprobs": logprobs,
    617                 "max_tokens": max_tokens,
    618                 "n": n,
    619                 "parallel_tool_calls": parallel_tool_calls,
    620                 "presence_penalty": presence_penalty,
    621                 "response_format": response_format,
    622                 "seed": seed,
    623                 "stop": stop,
    624                 "stream": stream,
    625                 "stream_options": stream_options,
    626                 "temperature": temperature,
    627                 "tool_choice": tool_choice,
    628                 "tools": tools,
    629                 "top_logprobs": top_logprobs,
    630                 "top_p": top_p,
    631                 "user": user,
    632             },
    633             completion_create_params.CompletionCreateParams,
    634         ),
    635         options=make_request_options(
    636             extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
    637         ),
    638         cast_to=ChatCompletion,
    639         stream=stream or False,
    640         stream_cls=Stream[ChatCompletionChunk],
    641     )

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\openai\_base_client.py:1240, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls)
   1226 def post(
   1227     self,
   1228     path: str,
   (...)
   1235     stream_cls: type[_StreamT] | None = None,
   1236 ) -> ResponseT | _StreamT:
   1237     opts = FinalRequestOptions.construct(
   1238         method="post", url=path, json_data=body, files=to_httpx_files(files), **options
   1239     )
-> 1240     return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\openai\_base_client.py:921, in SyncAPIClient.request(self, cast_to, options, remaining_retries, stream, stream_cls)
    912 def request(
    913     self,
    914     cast_to: Type[ResponseT],
   (...)
    919     stream_cls: type[_StreamT] | None = None,
    920 ) -> ResponseT | _StreamT:
--> 921     return self._request(
    922         cast_to=cast_to,
    923         options=options,
    924         stream=stream,
    925         stream_cls=stream_cls,
    926         remaining_retries=remaining_retries,
    927     )

File c:\Users\user_name\AppData\Local\anaconda3\envs\myenv\Lib\site-packages\openai\_base_client.py:1020, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
   1017         err.response.read()
   1019     log.debug("Re-raising status error")
-> 1020     raise self._make_status_error_from_response(err.response) from None
   1022 return self._process_response(
   1023     cast_to=cast_to,
   1024     options=options,
   (...)
   1027     stream_cls=stream_cls,
   1028 )

BadRequestError: Error code: 400 - {'error': {'message': "Invalid parameter: messages with role 'tool' must be a response to a preceeding message with 'tool_calls'.", 'type': 'invalid_request_error', 'param': 'messages.[2].role', 'code': None}}

Additional Information

autogen version: '0.2.31'
Python 3.11