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Refactor agent executor to delegate human interactions to a provider: add messages and ask_for_human_input properties, implement _invoke_loop and _format_feedback_message, and replace the internal iterative/training feedback logic with a call to get_provider().handle_feedback. Make LLMGuardrail kickoff coroutine-aware by detecting coroutines and running them via asyncio.run so both sync and async agents are supported. Make telemetry more robust by safely handling missing task.output (use empty string) and returning early if span is None before setting attributes. Improve serialization to detect circular references via an _ancestors set, propagate it through recursive calls, and pass exclude/max_depth/_current_depth consistently to prevent infinite recursion and produce stable serializable output.