[Question] Can I use AgentUniverse Manager in threading.Thread?

[powerfooI]

I call AgentUniverse().start() in a separate working Thread besides main thread. It's expected for working thread to poll tasks, get instance object from AgentManager and call agent.run(). While error TypeError: cannot pickle '_thread.RLock' object occurs when an agent is called the second time and the AU never recovers until I kill the process and restart it.

[powerfooI]

The traceback stack is as following,

Traceback (most recent call last):
  File "/app/my_server/web/task_worker.py", line 206, in task_worker
    output_object: OutputObject = my_agent.run(
                                  ^^^^^^^^^^^^^
  File "/root/.cache/pypoetry/virtualenvs/ob-dba-agent-9TtSrW0h-py3.12/lib/python3.12/site-packages/agentuniverse/agent/agent.py", line 80, in run
    planner_result = self.execute(input_object, agent_input)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.cache/pypoetry/virtualenvs/ob-dba-agent-9TtSrW0h-py3.12/lib/python3.12/site-packages/agentuniverse/agent/agent.py", line 100, in execute
    planner_result = planner_base.invoke(self.agent_model, agent_input, input_object)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.cache/pypoetry/virtualenvs/ob-dba-agent-9TtSrW0h-py3.12/lib/python3.12/site-packages/agentuniverse/agent/plan/planner/planning_planner/planning_planner.py", line 42, in invoke
    llm: LLM = self.handle_llm(agent_model)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.cache/pypoetry/virtualenvs/ob-dba-agent-9TtSrW0h-py3.12/lib/python3.12/site-packages/agentuniverse/agent/plan/planner/planner.py", line 145, in handle_llm
    llm: LLM = LLMManager().get_instance_obj(component_instance_name=llm_name, new_instance=True)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.cache/pypoetry/virtualenvs/ob-dba-agent-9TtSrW0h-py3.12/lib/python3.12/site-packages/agentuniverse/base/component/component_manager_base.py", line 46, in get_instance_obj
    return copy.deepcopy(self._instance_obj_map.get(instance_code))
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 143, in deepcopy
    y = copier(memo)
        ^^^^^^^^^^^^
  File "/root/.cache/pypoetry/virtualenvs/ob-dba-agent-9TtSrW0h-py3.12/lib/python3.12/site-packages/pydantic/main.py", line 777, in __deepcopy__
    _object_setattr(m, '__dict__', deepcopy(self.__dict__, memo=memo))
                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 136, in deepcopy
    y = copier(x, memo)
        ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 221, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
                             ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 162, in deepcopy
    y = _reconstruct(x, memo, *rv)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 259, in _reconstruct
    state = deepcopy(state, memo)
            ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 136, in deepcopy
    y = copier(x, memo)
        ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 221, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
                             ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 162, in deepcopy
    y = _reconstruct(x, memo, *rv)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 259, in _reconstruct
    state = deepcopy(state, memo)
            ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 136, in deepcopy
    y = copier(x, memo)
        ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 221, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
                             ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 162, in deepcopy
    y = _reconstruct(x, memo, *rv)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 259, in _reconstruct
    state = deepcopy(state, memo)
            ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 136, in deepcopy
    y = copier(x, memo)
        ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 221, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
                             ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 162, in deepcopy
    y = _reconstruct(x, memo, *rv)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 259, in _reconstruct
    state = deepcopy(state, memo)
            ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 136, in deepcopy
    y = copier(x, memo)
        ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 221, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
                             ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/copy.py", line 151, in deepcopy
    rv = reductor(4)
         ^^^^^^^^^^^
TypeError: cannot pickle '_thread.RLock' object

[LandJerry]

I call AgentUniverse().start() in a separate working Thread besides main thread. It's expected for working thread to poll tasks, get instance object from AgentManager and call agent.run(). While error TypeError: cannot pickle '_thread.RLock' object occurs when an agent is called the second time and the AU never recovers until I kill the process and restart it.

What is your version number? Upgrading to version 0.0.11 can resolve the issue.

[powerfooI]

Thanks a lot! The error disappears after I upgrade agentUniverse to 0.0.11.

[aadd1989]

I have updated version 0.0.11, but I still have this issue

[LandJerry]

I have updated version 0.0.11, but I still have this issue

Can you display the error stack to see if it matches the previous error? And if it does, can you confirm if the running version is indeed 0.0.11?

[aadd1989]

I have updated version 0.0.11, but I still have this issue

Can you display the error stack to see if it matches the previous error? And if it does, can you confirm if the running version is indeed 0.0.11?

| ERROR | [default] | app.bootstarp.flask_server:handle_exception:153 | Traceback (most recent call last): File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/flask/app.py", line 1484, in full_dispatch_request rv = self.dispatch_request() ^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/flask/app.py", line 1469, in dispatch_request return self.ensure_sync(self.view_functions[rule.endpoint])(*view_args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/agent_serve/web/web_util.py", line 50, in wrapper return func(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/nlpProjects/llm-multi-agent/app/bootstarp/flask_server.py", line 51, in service_run result = request_task.run() ^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/agent_serve/web/request_task.py", line 136, in run raise e File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/agent_serve/web/request_task.py", line 129, in run result = self.func(self.kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/agent_serve/service_instance.py", line 34, in run return self.__service.run(kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/agent_serve/service.py", line 49, in run return self.agent.run(kwargs).to_json_str() ^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/nlpProjects/llm-multi-agent/app/core/agent/judge_rag_agent/case_rag_agent.py", line 44, in run planner_result = self.execute(input_object, agent_input) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/agent/agent.py", line 106, in execute planner_result = planner_base.invoke(self.agent_model, agent_input, input_object) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/nlpProjects/llm-multi-agent/app/core/planner/judge_rag_planner.py", line 47, in invoke llm: LLM = self.handle_llm(agent_model, planner_input) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/nlpProjects/llm-multi-agent/app/core/planner/judge_rag_planner.py", line 109, in handle_llm llm: LLM = LLMManager().get_instance_obj(component_instance_name=llm_name, new_instance=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/agentuniverse/base/component/component_manager_base.py", line 46, in get_instance_obj return copy.deepcopy(self._instance_obj_map.get(instance_code)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 153, in deepcopy y = copier(memo) ^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/site-packages/pydantic/main.py", line 760, in deepcopy _object_setattr(m, 'dict', deepcopy(self.dict, memo=memo)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 146, in deepcopy y = copier(x, memo) ^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 231, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 172, in deepcopy y = _reconstruct(x, memo, rv) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 271, in _reconstruct state = deepcopy(state, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 146, in deepcopy y = copier(x, memo) ^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 231, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 172, in deepcopy y = _reconstruct(x, memo, rv) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 271, in _reconstruct state = deepcopy(state, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 146, in deepcopy y = copier(x, memo) ^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 231, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 172, in deepcopy y = _reconstruct(x, memo, rv) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 271, in _reconstruct state = deepcopy(state, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 146, in deepcopy y = copier(x, memo) ^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 231, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 172, in deepcopy y = _reconstruct(x, memo, rv) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 271, in _reconstruct state = deepcopy(state, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 146, in deepcopy y = copier(x, memo) ^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 231, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) ^^^^^^^^^^^^^^^^^^^^^ File "/mnt/raid5/anaconda3/lib/python3.11/copy.py", line 161, in deepcopy rv = reductor(4) ^^^^^^^^^^^ TypeError: cannot pickle '_thread.RLock' object

[aadd1989]

[EdwinInAu]

@aadd1989 the issue lies in your handle_llm method of the judge_rag_planner planner. Please adjust to LLMManager().get_instance_obj(component_instance_name=llm_name, new_instance=False) and try again.