Lorenzejay/byoa #776
Lorenzejay/byoa #776
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…nd added to the crew agent doc page
| def __init__(__pydantic_self__, **data): | ||
| config = data.pop("config", {}) | ||
| super().__init__(**config, **data) | ||
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If we aren't going to make gpt-4o the default llm for everything. We need to add a model_validator that checks to make sure the agent has an LLM and isn't none.
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I agree. Other agents may not be supporting 4o yet. but I do think a validator for llm not being none is best.
| tools_list = [] | ||
| try: | ||
| # tentatively try to import from crewai_tools import BaseTool as CrewAITool |
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@lorenzejay , drop this comment.
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note to me: from crewai_tools import BaseTool as CrewAITool
| if not self._rpm_controller: | ||
| self._rpm_controller = rpm_controller | ||
| self.create_agent_executor() | ||
| def format_log_to_str( |
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@lorenzejay should this be a ABC in BaseAgent?
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done abstractmethod set
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| return copied_agent | ||
| def get_output_converter(self, llm, text, model, instructions): |
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Should this be a ABC in BaseAgent as well?
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| class CrewAgentExecutorMixin: | ||
| def _should_force_answer(self) -> bool: | ||
| return ( | ||
| self.iterations == self.force_answer_max_iterations |
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None of these attributes exist on this class. You need to move these attributes over from executor.py and delete them over there.
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| def _create_short_term_memory(self, output) -> None: | ||
| if ( | ||
| self.crew |
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Need to move over crew to this class instead of executor.py.
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| def _create_long_term_memory(self, output) -> None: | ||
| if self.crew and self.crew.memory: | ||
| ltm_agent = TaskEvaluator(self.crew_agent) |
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Need to move over crew_agent from executor.py.
| coworker = self._get_coworker(coworker, **kwargs) | ||
| return self._execute(coworker, question, context) | ||
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| def _execute(self, agent_role: Optional[str], task: str, context: str): |
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We need to add back in the clean up that's in this image to support weaker models.
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main does not have these changes. think we can this later ?
src/crewai/crew.py
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| @@ -435,17 +446,23 @@ def _run_hierarchical_process(self) -> Union[str, Dict[str, Any]]: | |||
| ) | |||
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| self._logger.log("debug", f"[{manager.role}] Task output: {task_output}") | |||
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| if hasattr(task.agent, "_token_process"): | |||
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WHy do we have to do this check in hierarchical but not sequential?
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attachment of an agent and task not required will give NoneTypes
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heirarchial does not need an agent in task
| @@ -302,14 +302,13 @@ def _export_output(self, result: str) -> Any: | |||
| pass | |||
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| # type: ignore # Item "None" of "Agent | None" has no attribute "function_calling_llm" | |||
| llm = self.agent.function_calling_llm or self.agent.llm | |||
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| llm = getattr(self.agent, "function_calling_llm", None) or self.agent.llm | |||
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To prevent us from making these checks. Maybe we could update the base_agent to have a function_calling_llm but it would be set to None.
this ticket aims to bring your own AI agent whether its a custom langchain one or one like llamaindex and still work with crew or any custom agent.
BaseAgentas an abstraction to adhere to the crew flow.