Code review fixes
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@@ -4,8 +4,7 @@
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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from datetime import datetime, timezone
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from typing import List
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from typing import List, Optional
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from loguru import logger
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@@ -20,6 +19,7 @@ from pipecat.frames.frames import (
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TTSTextFrame,
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)
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from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
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from pipecat.utils.time import time_now_iso8601
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class BaseTranscriptProcessor(FrameProcessor):
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@@ -86,22 +86,18 @@ class AssistantTranscriptProcessor(BaseTranscriptProcessor):
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"""Initialize processor with aggregation state."""
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super().__init__(**kwargs)
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self._current_text_parts: List[str] = []
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self._aggregation_start_time: datetime | None = None
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self._aggregation_start_time: Optional[str] | None = None
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async def _emit_aggregated_text(self):
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"""Emit aggregated text as a transcript message."""
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if self._current_text_parts and self._aggregation_start_time:
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content = " ".join(self._current_text_parts).strip()
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if content:
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# Format timestamp with 3 decimal places
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formatted_timestamp = (
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self._aggregation_start_time.strftime("%Y-%m-%dT%H:%M:%S.%f")[:-3] + "+00:00"
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)
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logger.debug(f"Emitting aggregated assistant message: {content}")
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message = TranscriptionMessage(
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role="assistant",
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content=content,
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timestamp=formatted_timestamp,
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timestamp=self._aggregation_start_time,
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)
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await self._emit_update([message])
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else:
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@@ -129,16 +125,12 @@ class AssistantTranscriptProcessor(BaseTranscriptProcessor):
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if isinstance(frame, TTSTextFrame):
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# Start timestamp on first text part
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if not self._aggregation_start_time:
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self._aggregation_start_time = datetime.now(timezone.utc)
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self._aggregation_start_time = time_now_iso8601()
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self._current_text_parts.append(frame.text)
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elif isinstance(frame, BotStoppedSpeakingFrame):
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# Emit accumulated text when bot finishes speaking
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await self._emit_aggregated_text()
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elif isinstance(frame, StartInterruptionFrame):
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# Emit any pending text when interrupted
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elif isinstance(frame, (BotStoppedSpeakingFrame, StartInterruptionFrame)):
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# Emit accumulated text when bot finishes speaking or is interrupted
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await self._emit_aggregated_text()
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elif isinstance(frame, EndFrame):
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