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Fix Missing user message metrics (MetricsReport) due to early returns in _user_turn_completed_task and no initialization in on_end_of_turn #5437

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Fix Missing user message metrics (MetricsReport) due to early returns in _user_turn_completed_task and no initialization in on_end_of_turn #5437

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c1e6073
fix(agent_activity): enhance metrics reporting for user turn completion
hudson-worden Apr 13, 2026
6a21070
feat(agent_activity): enhance metrics initialization for end of turn …
hudson-worden Apr 13, 2026
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51 changes: 28 additions & 23 deletions livekit-agents/livekit/agents/voice/agent_activity.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1823,6 +1823,7 @@ def on_end_of_turn(self, info: _EndOfTurnInfo) -> bool:
content=[info.new_transcript],
transcript_confidence=info.transcript_confidence,
)
user_message.metrics = self._init_metrics_from_end_of_turn(info)
self._agent._chat_ctx.items.append(user_message)
self._session._conversation_item_added(user_message)

Expand Down Expand Up @@ -1877,6 +1878,11 @@ async def _user_turn_completed_task(
transcript_confidence=info.transcript_confidence,
)

metrics_report: llm.MetricsReport = self._init_metrics_from_end_of_turn(info)

if user_message is not None:
user_message.metrics = metrics_report

if isinstance(self.llm, llm.RealtimeModel):
if self.llm.capabilities.turn_detection:
return
Expand Down Expand Up @@ -1936,6 +1942,7 @@ async def _user_turn_completed_task(
return

on_user_turn_completed_delay = time.perf_counter() - start_time
metrics_report["on_user_turn_completed_delay"] = on_user_turn_completed_delay

if isinstance(self.llm, llm.RealtimeModel):
# ignore stt transcription for realtime model
Expand All @@ -1953,29 +1960,6 @@ async def _user_turn_completed_task(
self._session._conversation_item_added(user_message)
return

metrics_report: llm.MetricsReport = {}
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@hudson-worden hudson-worden Apr 14, 2026

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Being down here, we lose the opportunity to attach metrics for early returns above

if self.stt:
metrics_report["stt_metadata"] = {
"model_name": self.stt.model,
"model_provider": self.stt.provider,
}
if info.started_speaking_at is not None:
metrics_report["started_speaking_at"] = info.started_speaking_at

if info.stopped_speaking_at is not None:
metrics_report["stopped_speaking_at"] = info.stopped_speaking_at

if info.transcription_delay is not None:
metrics_report["transcription_delay"] = info.transcription_delay

if info.end_of_turn_delay is not None:
metrics_report["end_of_turn_delay"] = info.end_of_turn_delay

metrics_report["on_user_turn_completed_delay"] = on_user_turn_completed_delay

if user_message is not None:
user_message.metrics = metrics_report

speech_handle: SpeechHandle | None = None
if preemptive := self._preemptive_generation:
# make sure the on_user_turn_completed didn't change some request parameters
Expand Down Expand Up @@ -3401,6 +3385,27 @@ def _fallback_to_vad_interruption(self) -> None:
"falling back to VAD-based interruption"
)

def _init_metrics_from_end_of_turn(self, info: _EndOfTurnInfo) -> llm.MetricsReport:
metrics_report: llm.MetricsReport = {}
if self.stt:
metrics_report["stt_metadata"] = {
"model_name": self.stt.model,
"model_provider": self.stt.provider,
}
if info.started_speaking_at is not None:
metrics_report["started_speaking_at"] = info.started_speaking_at

if info.stopped_speaking_at is not None:
metrics_report["stopped_speaking_at"] = info.stopped_speaking_at

if info.transcription_delay is not None:
metrics_report["transcription_delay"] = info.transcription_delay

if info.end_of_turn_delay is not None:
metrics_report["end_of_turn_delay"] = info.end_of_turn_delay

return metrics_report

# move them to the end to avoid shadowing the same named modules for mypy
@property
def vad(self) -> vad.VAD | None:
Expand Down