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imporve HITL (#2169)
* imporve HITL * fix failing test * fix failing test part 2 * Drop extra logs that were causing confusion --------- Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
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@@ -114,10 +114,15 @@ class CrewAgentExecutorMixin:
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prompt = (
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"\n\n=====\n"
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"## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n"
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"Respond with 'looks good' to accept or provide specific improvement requests.\n"
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"You can provide multiple rounds of feedback until satisfied.\n"
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"Please follow these guidelines:\n"
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" - If you are happy with the result, simply hit Enter without typing anything.\n"
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" - Otherwise, provide specific improvement requests.\n"
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" - You can provide multiple rounds of feedback until satisfied.\n"
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"=====\n"
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)
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self._printer.print(content=prompt, color="bold_yellow")
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return input()
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response = input()
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if response.strip() != "":
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self._printer.print(content="\nProcessing your feedback...", color="cyan")
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return response
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@@ -548,10 +548,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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self, initial_answer: AgentFinish, feedback: str
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) -> AgentFinish:
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"""Process feedback for training scenarios with single iteration."""
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self._printer.print(
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content="\nProcessing training feedback.\n",
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color="yellow",
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)
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self._handle_crew_training_output(initial_answer, feedback)
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self.messages.append(
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self._format_msg(
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@@ -571,9 +567,8 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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answer = current_answer
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while self.ask_for_human_input:
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response = self._get_llm_feedback_response(feedback)
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if not self._feedback_requires_changes(response):
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# If the user provides a blank response, assume they are happy with the result
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if feedback.strip() == "":
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self.ask_for_human_input = False
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else:
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answer = self._process_feedback_iteration(feedback)
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@@ -581,27 +576,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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return answer
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def _get_llm_feedback_response(self, feedback: str) -> Optional[str]:
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"""Get LLM classification of whether feedback requires changes."""
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prompt = self._i18n.slice("human_feedback_classification").format(
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feedback=feedback
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)
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message = self._format_msg(prompt, role="system")
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for retry in range(MAX_LLM_RETRY):
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try:
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response = self.llm.call([message], callbacks=self.callbacks)
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return response.strip().lower() if response else None
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except Exception as error:
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self._log_feedback_error(retry, error)
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self._log_max_retries_exceeded()
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return None
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def _feedback_requires_changes(self, response: Optional[str]) -> bool:
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"""Determine if feedback response indicates need for changes."""
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return response == "true" if response else False
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def _process_feedback_iteration(self, feedback: str) -> AgentFinish:
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"""Process a single feedback iteration."""
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self.messages.append(
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