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Fix type issues pointed out by lorenze
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@@ -100,6 +100,12 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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try:
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formatted_answer = self._invoke_loop()
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except AssertionError:
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self._printer.print(
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content="Agent failed to reach a final answer. This is likely a bug - please report it.",
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color="red",
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)
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raise
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except Exception as e:
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if e.__class__.__module__.startswith("litellm"):
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# Do not retry on litellm errors
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@@ -115,7 +121,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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self._create_long_term_memory(formatted_answer)
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return {"output": formatted_answer.output}
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def _invoke_loop(self):
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def _invoke_loop(self) -> AgentFinish:
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"""
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Main loop to invoke the agent's thought process until it reaches a conclusion
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or the maximum number of iterations is reached.
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@@ -161,6 +167,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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finally:
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self.iterations += 1
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# During the invoke loop, formatted_answer alternates between AgentAction
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# (when the agent is using tools) and eventually becomes AgentFinish
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# (when the agent reaches a final answer). This assertion confirms we've
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# reached a final answer and helps type checking understand this transition.
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assert isinstance(formatted_answer, AgentFinish)
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self._show_logs(formatted_answer)
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return formatted_answer
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@@ -292,8 +303,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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self._printer.print(
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content=f"\033[1m\033[95m# Agent:\033[00m \033[1m\033[92m{agent_role}\033[00m"
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)
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description = (
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getattr(self.task, "description") if self.task else "Not Found"
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)
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self._printer.print(
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content=f"\033[95m## Task:\033[00m \033[92m{self.task.description}\033[00m"
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content=f"\033[95m## Task:\033[00m \033[92m{description}\033[00m"
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)
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def _show_logs(self, formatted_answer: Union[AgentAction, AgentFinish]):
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