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Rename UserTurnCompletedFrame to UserTurnInferenceCompletedFrame

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The old name overlapped semantically with `UserStoppedSpeakingFrame`:
both could be read as "the user's turn is done." They're at different
layers — `UserStoppedSpeakingFrame` is the acoustic stop signal,
while this frame is the post-judgment "inference about the turn is
now complete (turn is semantically final)" signal emitted by the LLM
mixin (on ✓), an end-of-turn classifier, or a custom producer.

The new name pairs naturally with the existing
`on_user_turn_inference_triggered` event vocabulary and removes the
ambiguity with `UserStoppedSpeakingFrame`.
This commit is contained in:
Aleix Conchillo Flaqué
2026-05-06 11:17:56 -07:00
parent 952dddca8b
commit b78cecf7b2
8 changed files with 29 additions and 29 deletions
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16
tests/test_context_aggregators_universal.py
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@@ -570,7 +570,7 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase):
async def test_inference_triggered_event_fires_on_default_strategies(self):
"""Default flow fires inference-triggered before stopped, both with the same strategy."""
from pipecat.frames.frames import UserTurnCompletedFrame # noqa: F401
from pipecat.frames.frames import UserTurnInferenceCompletedFrame # noqa: F401
context = LLMContext()
user_aggregator = LLMUserAggregator(
@@ -649,8 +649,8 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase):
self.assertIsInstance(stop_strategies[1], LLMTurnCompletionUserTurnStopStrategy)
async def test_llm_completion_strategy_finalizes_on_complete_marker(self):
"""LLMTurnCompletionUserTurnStopStrategy finalizes only on UserTurnCompletedFrame(complete)."""
from pipecat.frames.frames import UserTurnCompletedFrame
"""LLMTurnCompletionUserTurnStopStrategy finalizes only on UserTurnInferenceCompletedFrame(complete)."""
from pipecat.frames.frames import UserTurnInferenceCompletedFrame
from pipecat.turns.user_stop import LLMTurnCompletionUserTurnStopStrategy, deferred
gating = LLMTurnCompletionUserTurnStopStrategy()
@@ -678,7 +678,7 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase):
pipeline = Pipeline([user_aggregator])
# Drive the pipeline. Inference fires after the upstream
# strategy's timeout. Stop fires only when UserTurnCompletedFrame
# strategy's timeout. Stop fires only when UserTurnInferenceCompletedFrame
# arrives (producer absence == "not yet complete").
frames_to_send = [
VADUserStartedSpeakingFrame(),
@@ -687,7 +687,7 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase):
VADUserStoppedSpeakingFrame(),
SleepFrame(sleep=TRANSCRIPTION_TIMEOUT + 0.1),
# At this point inference_triggered should have fired but NOT stopped.
UserTurnCompletedFrame(),
UserTurnInferenceCompletedFrame(),
SleepFrame(),
]
await run_test(pipeline, frames_to_send=frames_to_send)
@@ -703,7 +703,7 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase):
and the conversation context should reflect the full user
utterance, not just the segment from the last inference.
"""
from pipecat.frames.frames import UserTurnCompletedFrame
from pipecat.frames.frames import UserTurnInferenceCompletedFrame
from pipecat.turns.user_stop import LLMTurnCompletionUserTurnStopStrategy, deferred
gating = LLMTurnCompletionUserTurnStopStrategy()
@@ -747,8 +747,8 @@ class TestLLMUserAggregator(unittest.IsolatedAsyncioTestCase):
VADUserStoppedSpeakingFrame(),
SleepFrame(sleep=TRANSCRIPTION_TIMEOUT + 0.1),
# Second inference fired here. Now the LLM returns ✓ and the
# turn finalizes via UserTurnCompletedFrame.
UserTurnCompletedFrame(),
# turn finalizes via UserTurnInferenceCompletedFrame.
UserTurnInferenceCompletedFrame(),
SleepFrame(),
]
await run_test(pipeline, frames_to_send=frames_to_send)