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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
View File

@@ -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)

14
tests/test_user_turn_completion_mixin.py
View File

@@ -12,7 +12,7 @@ from pipecat.frames.frames import (
LLMFullResponseEndFrame,
LLMMarkerFrame,
LLMTextFrame,
UserTurnCompletedFrame,
UserTurnInferenceCompletedFrame,
)
from pipecat.processors.frame_processor import FrameProcessor
from pipecat.services.llm_service import LLMService
@@ -61,8 +61,8 @@ class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase
self.assertEqual(marker_frames[0].marker, USER_TURN_COMPLETE_MARKER)
self.assertFalse(marker_frames[0].append_to_context_immediately)
# UserTurnCompletedFrame broadcast in both directions.
completed = [f for f in pushed_frames if isinstance(f, UserTurnCompletedFrame)]
# UserTurnInferenceCompletedFrame broadcast in both directions.
completed = [f for f in pushed_frames if isinstance(f, UserTurnInferenceCompletedFrame)]
self.assertEqual(len(completed), 2)
async def test_incomplete_short_marker_suppresses_text(self):
@@ -87,8 +87,8 @@ class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase
self.assertEqual(marker_frames[0].marker, USER_TURN_INCOMPLETE_SHORT_MARKER)
self.assertTrue(marker_frames[0].append_to_context_immediately)
# Incomplete markers do not emit UserTurnCompletedFrame.
completed = [f for f in pushed_frames if isinstance(f, UserTurnCompletedFrame)]
# Incomplete markers do not emit UserTurnInferenceCompletedFrame.
completed = [f for f in pushed_frames if isinstance(f, UserTurnInferenceCompletedFrame)]
self.assertEqual(len(completed), 0)
async def test_incomplete_long_marker_suppresses_text(self):
@@ -112,7 +112,7 @@ class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase
self.assertEqual(marker_frames[0].marker, USER_TURN_INCOMPLETE_LONG_MARKER)
self.assertTrue(marker_frames[0].append_to_context_immediately)
completed = [f for f in pushed_frames if isinstance(f, UserTurnCompletedFrame)]
completed = [f for f in pushed_frames if isinstance(f, UserTurnInferenceCompletedFrame)]
self.assertEqual(len(completed), 0)
async def test_text_buffered_until_marker_found(self):
@@ -135,7 +135,7 @@ class TestUserUserTurnCompletionLLMServiceMixin(unittest.IsolatedAsyncioTestCase
await processor._push_turn_text(f" {USER_TURN_COMPLETE_MARKER} How are you?")
# One LLMTextFrame for the spoken portion; one LLMMarkerFrame for
# the marker; UserTurnCompletedFrame broadcast in both directions.
# the marker; UserTurnInferenceCompletedFrame broadcast in both directions.
text_frames = [f for f in pushed_frames if isinstance(f, LLMTextFrame)]
self.assertEqual(len(text_frames), 1)
marker_frames = [f for f in pushed_frames if isinstance(f, LLMMarkerFrame)]