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fix: fix trainig_data error (#820)
* fix: fix trainig_data error * fix: fix lack crew on agent * fix: fix lack crew on agent executor
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@@ -241,7 +241,7 @@ class Agent(BaseModel):
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self.agent_executor.tools_description = render_text_description(parsed_tools)
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self.agent_executor.tools_names = self.__tools_names(parsed_tools)
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if self.crew._train:
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if self.crew and self.crew._train:
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task_prompt = self._training_handler(task_prompt=task_prompt)
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else:
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task_prompt = self._use_trained_data(task_prompt=task_prompt)
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@@ -250,7 +250,7 @@ class CrewAgentExecutor(AgentExecutor):
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if self.should_ask_for_human_input:
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human_feedback = self._ask_human_input(output.return_values["output"])
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if self.crew._train:
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if self.crew and self.crew._train:
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self._handle_crew_training_output(output, human_feedback)
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# Making sure we only ask for it once, so disabling for the next thought loop
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@@ -268,7 +268,7 @@ class CrewAgentExecutor(AgentExecutor):
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return
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else:
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if self.crew._train:
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if self.crew and self.crew._train:
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self._handle_crew_training_output(output)
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yield output
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@@ -323,9 +323,10 @@ class CrewAgentExecutor(AgentExecutor):
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agent_id = str(self.crew_agent.id)
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if (
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training_data := CrewTrainingHandler(TRAINING_DATA_FILE).load()
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CrewTrainingHandler(TRAINING_DATA_FILE).load()
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and not self.should_ask_for_human_input
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):
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training_data = CrewTrainingHandler(TRAINING_DATA_FILE).load()
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if training_data.get(agent_id):
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training_data[agent_id][self.crew._train_iteration][
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"improved_output"
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