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https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
self-review round
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@@ -455,25 +455,6 @@ async def generate_waveform(input: PipelineInput, ctx: Context) -> WaveformResul
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transcripts_controller,
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)
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# Cleanup temporary padded S3 files (deferred until after mixdown)
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track_result = ctx.task_output(process_tracks)
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created_padded_files = track_result.created_padded_files
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if created_padded_files:
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ctx.log(f"Cleaning up {len(created_padded_files)} temporary S3 files")
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storage = _spawn_storage()
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cleanup_tasks = []
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for storage_path in created_padded_files:
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cleanup_tasks.append(storage.delete_file(storage_path))
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cleanup_results = await asyncio.gather(*cleanup_tasks, return_exceptions=True)
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for storage_path, result in zip(created_padded_files, cleanup_results):
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if isinstance(result, Exception):
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logger.warning(
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"[Hatchet] Failed to cleanup temporary padded track",
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storage_path=storage_path,
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error=str(result),
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)
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mixdown_result = ctx.task_output(mixdown_tracks)
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audio_key = mixdown_result.audio_key
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@@ -714,6 +695,23 @@ async def finalize(input: PipelineInput, ctx: Context) -> FinalizeResult:
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duration = mixdown_result.duration
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all_words = track_result.all_words
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# Cleanup temporary padded S3 files (deferred until finalize for semantic parity with Celery)
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created_padded_files = track_result.created_padded_files
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if created_padded_files:
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ctx.log(f"Cleaning up {len(created_padded_files)} temporary S3 files")
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storage = _spawn_storage()
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cleanup_results = await asyncio.gather(
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*[storage.delete_file(path) for path in created_padded_files],
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return_exceptions=True,
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)
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for storage_path, result in zip(created_padded_files, cleanup_results):
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if isinstance(result, Exception):
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logger.warning(
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"[Hatchet] Failed to cleanup temporary padded track",
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storage_path=storage_path,
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error=str(result),
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)
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async with fresh_db_connection():
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from reflector.db.transcripts import ( # noqa: PLC0415
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TranscriptDuration,
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@@ -767,22 +765,97 @@ async def finalize(input: PipelineInput, ctx: Context) -> FinalizeResult:
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)
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@with_error_handling("cleanup_consent", set_error_status=False)
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async def cleanup_consent(input: PipelineInput, ctx: Context) -> ConsentResult:
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"""Check and handle consent requirements."""
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"""Check consent and delete audio files if any participant denied."""
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ctx.log(f"cleanup_consent: transcript_id={input.transcript_id}")
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async with fresh_db_connection():
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from reflector.db.meetings import meetings_controller # noqa: PLC0415
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from reflector.db.meetings import ( # noqa: PLC0415
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meeting_consent_controller,
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meetings_controller,
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)
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from reflector.db.recordings import recordings_controller # noqa: PLC0415
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from reflector.db.transcripts import transcripts_controller # noqa: PLC0415
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from reflector.storage import get_transcripts_storage # noqa: PLC0415
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transcript = await transcripts_controller.get_by_id(input.transcript_id)
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if transcript and transcript.meeting_id:
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if not transcript:
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ctx.log("cleanup_consent: transcript not found")
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return ConsentResult()
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consent_denied = False
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if transcript.meeting_id:
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meeting = await meetings_controller.get_by_id(transcript.meeting_id)
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if meeting:
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# Check consent logic here
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# For now just mark as checked
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pass
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consent_denied = await meeting_consent_controller.has_any_denial(
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meeting.id
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)
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ctx.log(f"cleanup_consent complete: transcript_id={input.transcript_id}")
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if not consent_denied:
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ctx.log("cleanup_consent: consent approved, keeping all files")
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return ConsentResult()
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ctx.log("cleanup_consent: consent denied, deleting audio files")
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input_track_keys = set(t["s3_key"] for t in input.tracks)
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# Detect if recording.track_keys was manually modified after workflow started
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if transcript.recording_id:
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recording = await recordings_controller.get_by_id(transcript.recording_id)
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if recording and recording.track_keys:
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db_track_keys = set(filter_cam_audio_tracks(recording.track_keys))
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if input_track_keys != db_track_keys:
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added = db_track_keys - input_track_keys
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removed = input_track_keys - db_track_keys
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logger.warning(
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"[Hatchet] Track keys mismatch: DB changed since workflow start",
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transcript_id=input.transcript_id,
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recording_id=transcript.recording_id,
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input_count=len(input_track_keys),
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db_count=len(db_track_keys),
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added_in_db=list(added) if added else None,
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removed_from_db=list(removed) if removed else None,
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)
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ctx.log(
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f"WARNING: track_keys mismatch - "
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f"input has {len(input_track_keys)}, DB has {len(db_track_keys)}. "
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f"Using input tracks for deletion."
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)
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deletion_errors = []
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if input_track_keys and input.bucket_name:
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master_storage = get_transcripts_storage()
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for key in input_track_keys:
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try:
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await master_storage.delete_file(key, bucket=input.bucket_name)
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ctx.log(f"Deleted recording file: {input.bucket_name}/{key}")
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except Exception as e:
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error_msg = f"Failed to delete {key}: {e}"
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logger.error(error_msg, exc_info=True)
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deletion_errors.append(error_msg)
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if transcript.audio_location == "storage":
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storage = get_transcripts_storage()
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try:
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await storage.delete_file(transcript.storage_audio_path)
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ctx.log(f"Deleted processed audio: {transcript.storage_audio_path}")
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except Exception as e:
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error_msg = f"Failed to delete processed audio: {e}"
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logger.error(error_msg, exc_info=True)
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deletion_errors.append(error_msg)
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if deletion_errors:
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logger.warning(
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"[Hatchet] cleanup_consent completed with errors",
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transcript_id=input.transcript_id,
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error_count=len(deletion_errors),
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errors=deletion_errors,
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)
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ctx.log(f"cleanup_consent completed with {len(deletion_errors)} errors")
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else:
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await transcripts_controller.update(transcript, {"audio_deleted": True})
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ctx.log("cleanup_consent: all audio deleted successfully")
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return ConsentResult()
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