Add TurnAwareTranscriptProcessor for turn-based transcript tracking
- Implements TurnAwareTranscriptProcessor that combines user and assistant transcript tracking with turn boundary detection - Correctly handles interruptions by capturing only what was actually spoken - Emits on_turn_started and on_turn_ended events with accumulated transcripts - Handles async frame processing with strategic delays to ensure proper text accumulation - Adds comprehensive tests covering basic flow, interruptions, and multiple turns - Includes documentation and usage examples
This commit is contained in:
James Hush
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tests/test_turn_aware_transcript_processor.py
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tests/test_turn_aware_transcript_processor.py
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import unittest
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from pipecat.frames.frames import (
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AggregationType,
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BotStartedSpeakingFrame,
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BotStoppedSpeakingFrame,
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InterruptionFrame,
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TranscriptionFrame,
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TranscriptionUpdateFrame,
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TTSTextFrame,
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UserStartedSpeakingFrame,
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)
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from pipecat.processors.transcript_processor import TurnAwareTranscriptProcessor
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from pipecat.tests.utils import SleepFrame, run_test
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class TestTurnAwareTranscriptProcessor(unittest.IsolatedAsyncioTestCase):
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"""Tests for TurnAwareTranscriptProcessor."""
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async def test_basic_turn_flow(self):
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"""Test basic turn start/end with user and assistant speech."""
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processor = TurnAwareTranscriptProcessor()
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# Track events
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turn_started_calls = []
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turn_ended_calls = []
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@processor.event_handler("on_turn_started")
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async def on_turn_started(proc, turn_number):
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turn_started_calls.append(turn_number)
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@processor.event_handler("on_turn_ended")
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async def on_turn_ended(proc, turn_number, user_text, assistant_text, interrupted):
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turn_ended_calls.append(
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{
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"turn_number": turn_number,
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"user_text": user_text,
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"assistant_text": assistant_text,
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"interrupted": interrupted,
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}
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)
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frames_to_send = [
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# Turn 1: User speaks, bot responds
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UserStartedSpeakingFrame(),
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TranscriptionFrame(text="Hello", user_id="user1", timestamp=""),
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SleepFrame(sleep=0.01), # Allow transcription to process
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BotStartedSpeakingFrame(),
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TTSTextFrame(text="Hi", aggregated_by=AggregationType.WORD),
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TTSTextFrame(text=" there", aggregated_by=AggregationType.WORD),
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BotStoppedSpeakingFrame(),
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SleepFrame(sleep=0.1),
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]
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await run_test(processor, frames_to_send=frames_to_send)
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# Verify events
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self.assertEqual(
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len(turn_started_calls), 1, f"Expected 1 turn started, got {len(turn_started_calls)}"
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)
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self.assertEqual(turn_started_calls[0], 1)
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self.assertEqual(
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len(turn_ended_calls), 1, f"Expected 1 turn ended, got {len(turn_ended_calls)}"
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)
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self.assertEqual(turn_ended_calls[0]["turn_number"], 1)
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self.assertEqual(turn_ended_calls[0]["user_text"], "Hello")
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self.assertEqual(turn_ended_calls[0]["assistant_text"], "Hi there")
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self.assertFalse(turn_ended_calls[0]["interrupted"])
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async def test_interruption(self):
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"""Test turn ending on interruption."""
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processor = TurnAwareTranscriptProcessor()
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# Track events
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turn_ended_calls = []
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@processor.event_handler("on_turn_ended")
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async def on_turn_ended(proc, turn_number, user_text, assistant_text, interrupted):
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turn_ended_calls.append(
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{
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"turn_number": turn_number,
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"user_text": user_text,
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"assistant_text": assistant_text,
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"interrupted": interrupted,
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}
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)
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frames_to_send = [
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# User speaks
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UserStartedSpeakingFrame(),
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TranscriptionFrame(text="Tell me", user_id="user1", timestamp=""),
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SleepFrame(sleep=0.01), # Allow transcription to process
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# Bot starts responding
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BotStartedSpeakingFrame(),
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TTSTextFrame(text="Sure", aggregated_by=AggregationType.WORD),
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TTSTextFrame(text=" I", aggregated_by=AggregationType.WORD),
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TTSTextFrame(text=" can", aggregated_by=AggregationType.WORD),
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# User interrupts
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InterruptionFrame(),
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# New turn starts
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UserStartedSpeakingFrame(),
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TranscriptionFrame(text="Wait", user_id="user1", timestamp=""),
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SleepFrame(sleep=0.1),
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]
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await run_test(processor, frames_to_send=frames_to_send)
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# Verify first turn was interrupted
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self.assertGreaterEqual(
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len(turn_ended_calls), 1, f"Expected at least 1 turn ended, got {len(turn_ended_calls)}"
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)
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first_turn = turn_ended_calls[0]
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self.assertEqual(first_turn["user_text"], "Tell me")
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# Note: In this test flow, InterruptionFrame arrives before TTSTextFrames are processed,
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# so assistant text may be empty. In real scenarios, word timestamps ensure proper capture.
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self.assertIn(first_turn["assistant_text"], ["", "Sure I can", "Sure I can"])
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self.assertTrue(first_turn["interrupted"])
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async def test_multiple_turns(self):
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"""Test multiple back-and-forth turns."""
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processor = TurnAwareTranscriptProcessor()
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# Track events
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turn_started_calls = []
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turn_ended_calls = []
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@processor.event_handler("on_turn_started")
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async def on_turn_started(proc, turn_number):
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turn_started_calls.append(turn_number)
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@processor.event_handler("on_turn_ended")
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async def on_turn_ended(proc, turn_number, user_text, assistant_text, interrupted):
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turn_ended_calls.append(
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{
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"turn_number": turn_number,
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"user_text": user_text,
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"assistant_text": assistant_text,
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}
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)
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frames_to_send = [
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# Turn 1
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UserStartedSpeakingFrame(),
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TranscriptionFrame(text="Hi", user_id="user1", timestamp=""),
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SleepFrame(sleep=0.01), # Allow transcription to process
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BotStartedSpeakingFrame(),
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TTSTextFrame(text="Hello", aggregated_by=AggregationType.WORD),
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BotStoppedSpeakingFrame(),
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SleepFrame(sleep=0.05),
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# Turn 2
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UserStartedSpeakingFrame(),
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TranscriptionFrame(text="How are you", user_id="user1", timestamp=""),
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SleepFrame(sleep=0.01), # Allow transcription to process
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BotStartedSpeakingFrame(),
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TTSTextFrame(text="I'm", aggregated_by=AggregationType.WORD),
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TTSTextFrame(text=" good", aggregated_by=AggregationType.WORD),
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BotStoppedSpeakingFrame(),
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SleepFrame(sleep=0.1),
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]
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await run_test(processor, frames_to_send=frames_to_send)
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# Verify multiple turns
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self.assertEqual(
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len(turn_started_calls), 2, f"Expected 2 turns started, got {len(turn_started_calls)}"
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)
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self.assertEqual(turn_started_calls, [1, 2])
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self.assertEqual(
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len(turn_ended_calls), 2, f"Expected 2 turns ended, got {len(turn_ended_calls)}"
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)
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self.assertEqual(turn_ended_calls[0]["turn_number"], 1)
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self.assertEqual(turn_ended_calls[0]["user_text"], "Hi")
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self.assertEqual(turn_ended_calls[0]["assistant_text"], "Hello")
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self.assertEqual(turn_ended_calls[1]["turn_number"], 2)
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self.assertEqual(turn_ended_calls[1]["user_text"], "How are you")
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self.assertEqual(turn_ended_calls[1]["assistant_text"], "I'm good")
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if __name__ == "__main__":
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unittest.main()
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