Files
reflector/server/tests/test_pipeline_main_file.py
Mathieu Virbel 8fcfac80fa fix: resolve session management issues in tests and WebSocket endpoints
- Add missing db_session parameter to test_pipeline_main_file.py tests
- Fix WebSocket endpoint missing session dependency injection
- Update test fixtures to pass session as first argument to pipeline.process()
- Add required imports (Depends, AsyncSession, get_session) to transcripts_websocket.py

Note: 2 WebRTC tests still failing due to known asyncio event loop issues with SQLAlchemy
2025-09-25 12:52:30 -06:00

659 lines
23 KiB
Python

"""
Tests for PipelineMainFile - file-based processing pipeline
This test verifies the complete file processing pipeline without mocking much,
ensuring all processors are correctly invoked and the happy path works correctly.
"""
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock, patch
from uuid import uuid4
import pytest
from reflector.pipelines.main_file_pipeline import PipelineMainFile
from reflector.processors.file_diarization import FileDiarizationOutput
from reflector.processors.types import (
DiarizationSegment,
TitleSummary,
Word,
)
from reflector.processors.types import (
Transcript as TranscriptType,
)
@pytest.fixture
async def dummy_file_transcript():
"""Mock FileTranscriptAutoProcessor for file processing"""
from reflector.processors.file_transcript import FileTranscriptProcessor
class TestFileTranscriptProcessor(FileTranscriptProcessor):
async def _transcript(self, data):
return TranscriptType(
text="Hello world. How are you today?",
words=[
Word(start=0.0, end=0.5, text="Hello", speaker=0),
Word(start=0.5, end=0.6, text=" ", speaker=0),
Word(start=0.6, end=1.0, text="world", speaker=0),
Word(start=1.0, end=1.1, text=".", speaker=0),
Word(start=1.1, end=1.2, text=" ", speaker=0),
Word(start=1.2, end=1.5, text="How", speaker=0),
Word(start=1.5, end=1.6, text=" ", speaker=0),
Word(start=1.6, end=1.8, text="are", speaker=0),
Word(start=1.8, end=1.9, text=" ", speaker=0),
Word(start=1.9, end=2.1, text="you", speaker=0),
Word(start=2.1, end=2.2, text=" ", speaker=0),
Word(start=2.2, end=2.5, text="today", speaker=0),
Word(start=2.5, end=2.6, text="?", speaker=0),
],
)
with patch(
"reflector.processors.file_transcript_auto.FileTranscriptAutoProcessor.__new__"
) as mock_auto:
mock_auto.return_value = TestFileTranscriptProcessor()
yield
@pytest.fixture
async def dummy_file_diarization():
"""Mock FileDiarizationAutoProcessor for file processing"""
from reflector.processors.file_diarization import FileDiarizationProcessor
class TestFileDiarizationProcessor(FileDiarizationProcessor):
async def _diarize(self, data):
return FileDiarizationOutput(
diarization=[
DiarizationSegment(start=0.0, end=1.1, speaker=0),
DiarizationSegment(start=1.2, end=2.6, speaker=1),
]
)
with patch(
"reflector.processors.file_diarization_auto.FileDiarizationAutoProcessor.__new__"
) as mock_auto:
mock_auto.return_value = TestFileDiarizationProcessor()
yield
@pytest.fixture
async def mock_transcript_in_db(tmpdir):
"""Create a mock transcript in the database"""
from reflector.db.transcripts import Transcript
from reflector.settings import settings
# Set the DATA_DIR to our tmpdir
original_data_dir = settings.DATA_DIR
settings.DATA_DIR = str(tmpdir)
transcript_id = str(uuid4())
data_path = Path(tmpdir) / transcript_id
data_path.mkdir(parents=True, exist_ok=True)
# Create mock transcript object
transcript = Transcript(
id=transcript_id,
name="Test Transcript",
status="processing",
source_kind="file",
source_language="en",
target_language="en",
)
# Mock all transcripts controller methods that are used in the pipeline
try:
with patch(
"reflector.pipelines.main_file_pipeline.transcripts_controller.get_by_id"
) as mock_get:
mock_get.return_value = transcript
with patch(
"reflector.pipelines.main_file_pipeline.transcripts_controller.update"
) as mock_update:
mock_update.return_value = transcript
with patch(
"reflector.pipelines.main_file_pipeline.transcripts_controller.set_status"
) as mock_set_status:
mock_set_status.return_value = None
with patch(
"reflector.pipelines.main_file_pipeline.transcripts_controller.upsert_topic"
) as mock_upsert_topic:
mock_upsert_topic.return_value = None
with patch(
"reflector.pipelines.main_file_pipeline.transcripts_controller.append_event"
) as mock_append_event:
mock_append_event.return_value = None
with patch(
"reflector.pipelines.main_live_pipeline.transcripts_controller.get_by_id"
) as mock_get2:
mock_get2.return_value = transcript
with patch(
"reflector.pipelines.main_live_pipeline.transcripts_controller.update"
) as mock_update2:
mock_update2.return_value = None
yield transcript
finally:
# Restore original DATA_DIR
settings.DATA_DIR = original_data_dir
@pytest.fixture
async def mock_storage():
"""Mock storage for file uploads"""
from reflector.storage.base import Storage
class TestStorage(Storage):
async def _put_file(self, path, data):
return None
async def _get_file_url(self, path):
return f"http://test-storage/{path}"
async def _get_file(self, path):
return b"test_audio_data"
async def _delete_file(self, path):
return None
storage = TestStorage()
# Add mock tracking for verification
storage._put_file = AsyncMock(side_effect=storage._put_file)
storage._get_file_url = AsyncMock(side_effect=storage._get_file_url)
with patch(
"reflector.pipelines.main_file_pipeline.get_transcripts_storage"
) as mock_get:
mock_get.return_value = storage
yield storage
@pytest.fixture
async def mock_audio_file_writer():
"""Mock AudioFileWriterProcessor to avoid actual file writing"""
with patch(
"reflector.pipelines.main_file_pipeline.AudioFileWriterProcessor"
) as mock_writer_class:
mock_writer = AsyncMock()
mock_writer.push = AsyncMock()
mock_writer.flush = AsyncMock()
mock_writer_class.return_value = mock_writer
yield mock_writer
@pytest.fixture
async def mock_waveform_processor():
"""Mock AudioWaveformProcessor"""
with patch(
"reflector.pipelines.main_file_pipeline.AudioWaveformProcessor"
) as mock_waveform_class:
mock_waveform = AsyncMock()
mock_waveform.set_pipeline = MagicMock()
mock_waveform.flush = AsyncMock()
mock_waveform_class.return_value = mock_waveform
yield mock_waveform
@pytest.fixture
async def mock_topic_detector():
"""Mock TranscriptTopicDetectorProcessor"""
with patch(
"reflector.pipelines.main_file_pipeline.TranscriptTopicDetectorProcessor"
) as mock_topic_class:
mock_topic = AsyncMock()
mock_topic.set_pipeline = MagicMock()
mock_topic.push = AsyncMock()
mock_topic.flush_called = False
# When flush is called, simulate topic detection by calling the callback
async def flush_with_callback():
mock_topic.flush_called = True
if hasattr(mock_topic, "_callback"):
# Create a minimal transcript for the TitleSummary
test_transcript = TranscriptType(words=[], text="test transcript")
await mock_topic._callback(
TitleSummary(
title="Test Topic",
summary="Test topic summary",
timestamp=0.0,
duration=10.0,
transcript=test_transcript,
)
)
mock_topic.flush = flush_with_callback
def init_with_callback(callback=None):
mock_topic._callback = callback
return mock_topic
mock_topic_class.side_effect = init_with_callback
yield mock_topic
@pytest.fixture
async def mock_title_processor():
"""Mock TranscriptFinalTitleProcessor"""
with patch(
"reflector.pipelines.main_file_pipeline.TranscriptFinalTitleProcessor"
) as mock_title_class:
mock_title = AsyncMock()
mock_title.set_pipeline = MagicMock()
mock_title.push = AsyncMock()
mock_title.flush_called = False
# When flush is called, simulate title generation by calling the callback
async def flush_with_callback():
mock_title.flush_called = True
if hasattr(mock_title, "_callback"):
from reflector.processors.types import FinalTitle
await mock_title._callback(FinalTitle(title="Test Title"))
mock_title.flush = flush_with_callback
def init_with_callback(callback=None):
mock_title._callback = callback
return mock_title
mock_title_class.side_effect = init_with_callback
yield mock_title
@pytest.fixture
async def mock_summary_processor():
"""Mock TranscriptFinalSummaryProcessor"""
with patch(
"reflector.pipelines.main_file_pipeline.TranscriptFinalSummaryProcessor"
) as mock_summary_class:
mock_summary = AsyncMock()
mock_summary.set_pipeline = MagicMock()
mock_summary.push = AsyncMock()
mock_summary.flush_called = False
# When flush is called, simulate summary generation by calling the callbacks
async def flush_with_callback():
mock_summary.flush_called = True
from reflector.processors.types import FinalLongSummary, FinalShortSummary
if hasattr(mock_summary, "_callback"):
await mock_summary._callback(
FinalLongSummary(long_summary="Test long summary", duration=10.0)
)
if hasattr(mock_summary, "_on_short_summary"):
await mock_summary._on_short_summary(
FinalShortSummary(short_summary="Test short summary", duration=10.0)
)
mock_summary.flush = flush_with_callback
def init_with_callback(transcript=None, callback=None, on_short_summary=None):
mock_summary._callback = callback
mock_summary._on_short_summary = on_short_summary
return mock_summary
mock_summary_class.side_effect = init_with_callback
yield mock_summary
@pytest.mark.asyncio
async def test_pipeline_main_file_process(
db_session,
tmpdir,
mock_transcript_in_db,
dummy_file_transcript,
dummy_file_diarization,
mock_storage,
mock_audio_file_writer,
mock_waveform_processor,
mock_topic_detector,
mock_title_processor,
mock_summary_processor,
):
"""
Test the complete PipelineMainFile processing pipeline.
This test verifies:
1. Audio extraction and writing
2. Audio upload to storage
3. Parallel processing of transcription, diarization, and waveform
4. Assembly of transcript with diarization
5. Topic detection
6. Title and summary generation
"""
# Create a test audio file
test_audio_path = Path(__file__).parent / "records" / "test_mathieu_hello.wav"
# Copy test audio to the transcript's data path as if it was uploaded
upload_path = mock_transcript_in_db.data_path / "upload.wav"
upload_path.write_bytes(test_audio_path.read_bytes())
# Also create the audio.mp3 file that would be created by AudioFileWriterProcessor
# Since we're mocking AudioFileWriterProcessor, we need to create this manually
mp3_path = mock_transcript_in_db.data_path / "audio.mp3"
mp3_path.write_bytes(b"mock_mp3_data")
# Track callback invocations
callback_marks = {
"on_status": [],
"on_duration": [],
"on_waveform": [],
"on_topic": [],
"on_title": [],
"on_long_summary": [],
"on_short_summary": [],
}
# Create pipeline with mocked callbacks
pipeline = PipelineMainFile(transcript_id=mock_transcript_in_db.id)
# Override callbacks to track invocations
async def track_callback(name, data):
callback_marks[name].append(data)
# Call the original callback
original = getattr(PipelineMainFile, name)
return await original(pipeline, data)
for callback_name in callback_marks.keys():
setattr(
pipeline,
callback_name,
lambda data, n=callback_name: track_callback(n, data),
)
# Mock av.open for audio processing
with patch("reflector.pipelines.main_file_pipeline.av.open") as mock_av:
# Mock container for checking video streams
mock_container = MagicMock()
mock_container.streams.video = [] # No video streams (audio only)
mock_container.close = MagicMock()
# Mock container for decoding audio frames
mock_decode_container = MagicMock()
mock_decode_container.decode.return_value = iter(
[MagicMock()]
) # One mock audio frame
mock_decode_container.close = MagicMock()
# Return different containers for different calls
mock_av.side_effect = [mock_container, mock_decode_container]
# Run the pipeline
await pipeline.process(db_session, upload_path)
# Verify audio extraction and writing
assert mock_audio_file_writer.push.called
assert mock_audio_file_writer.flush.called
# Verify storage upload
assert mock_storage._put_file.called
assert mock_storage._get_file_url.called
# Verify waveform generation
assert mock_waveform_processor.flush.called
assert mock_waveform_processor.set_pipeline.called
# Verify topic detection
assert mock_topic_detector.push.called
assert mock_topic_detector.flush_called
# Verify title generation
assert mock_title_processor.push.called
assert mock_title_processor.flush_called
# Verify summary generation
assert mock_summary_processor.push.called
assert mock_summary_processor.flush_called
# Verify callbacks were invoked
assert len(callback_marks["on_topic"]) > 0, "Topic callback should be invoked"
assert len(callback_marks["on_title"]) > 0, "Title callback should be invoked"
assert (
len(callback_marks["on_long_summary"]) > 0
), "Long summary callback should be invoked"
assert (
len(callback_marks["on_short_summary"]) > 0
), "Short summary callback should be invoked"
print(f"Callback marks: {callback_marks}")
# Verify the pipeline completed successfully
assert pipeline.logger is not None
print("PipelineMainFile test completed successfully!")
@pytest.mark.asyncio
async def test_pipeline_main_file_with_video(
db_session,
tmpdir,
mock_transcript_in_db,
dummy_file_transcript,
dummy_file_diarization,
mock_storage,
mock_audio_file_writer,
mock_waveform_processor,
mock_topic_detector,
mock_title_processor,
mock_summary_processor,
):
"""
Test PipelineMainFile with video input (verifies audio extraction).
"""
# Create a test audio file
test_audio_path = Path(__file__).parent / "records" / "test_mathieu_hello.wav"
# Copy test audio to the transcript's data path as if it was a video upload
upload_path = mock_transcript_in_db.data_path / "upload.mp4"
upload_path.write_bytes(test_audio_path.read_bytes())
# Also create the audio.mp3 file that would be created by AudioFileWriterProcessor
mp3_path = mock_transcript_in_db.data_path / "audio.mp3"
mp3_path.write_bytes(b"mock_mp3_data")
# Create pipeline
pipeline = PipelineMainFile(transcript_id=mock_transcript_in_db.id)
# Mock av.open for video processing
with patch("reflector.pipelines.main_file_pipeline.av.open") as mock_av:
# Mock container for checking video streams
mock_container = MagicMock()
mock_container.streams.video = [MagicMock()] # Has video streams
mock_container.close = MagicMock()
# Mock container for decoding audio frames
mock_decode_container = MagicMock()
mock_decode_container.decode.return_value = iter(
[MagicMock()]
) # One mock audio frame
mock_decode_container.close = MagicMock()
# Return different containers for different calls
mock_av.side_effect = [mock_container, mock_decode_container]
# Run the pipeline
await pipeline.process(db_session, upload_path)
# Verify audio extraction from video
assert mock_audio_file_writer.push.called
assert mock_audio_file_writer.flush.called
# Verify the rest of the pipeline completed
assert mock_storage._put_file.called
assert mock_waveform_processor.flush.called
assert mock_topic_detector.push.called
assert mock_title_processor.push.called
assert mock_summary_processor.push.called
print("PipelineMainFile video test completed successfully!")
@pytest.mark.asyncio
async def test_pipeline_main_file_no_diarization(
db_session,
tmpdir,
mock_transcript_in_db,
dummy_file_transcript,
mock_storage,
mock_audio_file_writer,
mock_waveform_processor,
mock_topic_detector,
mock_title_processor,
mock_summary_processor,
):
"""
Test PipelineMainFile with diarization disabled.
"""
from reflector.settings import settings
# Disable diarization
with patch.object(settings, "DIARIZATION_BACKEND", None):
# Create a test audio file
test_audio_path = Path(__file__).parent / "records" / "test_mathieu_hello.wav"
# Copy test audio to the transcript's data path
upload_path = mock_transcript_in_db.data_path / "upload.wav"
upload_path.write_bytes(test_audio_path.read_bytes())
# Also create the audio.mp3 file
mp3_path = mock_transcript_in_db.data_path / "audio.mp3"
mp3_path.write_bytes(b"mock_mp3_data")
# Create pipeline
pipeline = PipelineMainFile(transcript_id=mock_transcript_in_db.id)
# Mock av.open for audio processing
with patch("reflector.pipelines.main_file_pipeline.av.open") as mock_av:
# Mock container for checking video streams
mock_container = MagicMock()
mock_container.streams.video = [] # No video streams
mock_container.close = MagicMock()
# Mock container for decoding audio frames
mock_decode_container = MagicMock()
mock_decode_container.decode.return_value = iter([MagicMock()])
mock_decode_container.close = MagicMock()
# Return different containers for different calls
mock_av.side_effect = [mock_container, mock_decode_container]
# Run the pipeline
await pipeline.process(db_session, upload_path)
# Verify the pipeline completed without diarization
assert mock_storage._put_file.called
assert mock_waveform_processor.flush.called
assert mock_topic_detector.push.called
assert mock_title_processor.push.called
assert mock_summary_processor.push.called
print("PipelineMainFile no-diarization test completed successfully!")
@pytest.mark.asyncio
async def test_task_pipeline_file_process(
db_session,
tmpdir,
mock_transcript_in_db,
dummy_file_transcript,
dummy_file_diarization,
mock_storage,
mock_audio_file_writer,
mock_waveform_processor,
mock_topic_detector,
mock_title_processor,
mock_summary_processor,
):
"""
Test the Celery task entry point for file pipeline processing.
"""
# Direct import of the underlying async function, bypassing the asynctask decorator
# Create a test audio file in the transcript's data path
test_audio_path = Path(__file__).parent / "records" / "test_mathieu_hello.wav"
upload_path = mock_transcript_in_db.data_path / "upload.wav"
upload_path.write_bytes(test_audio_path.read_bytes())
# Also create the audio.mp3 file
mp3_path = mock_transcript_in_db.data_path / "audio.mp3"
mp3_path.write_bytes(b"mock_mp3_data")
# Mock av.open for audio processing
with patch("reflector.pipelines.main_file_pipeline.av.open") as mock_av:
# Mock container for checking video streams
mock_container = MagicMock()
mock_container.streams.video = [] # No video streams
mock_container.close = MagicMock()
# Mock container for decoding audio frames
mock_decode_container = MagicMock()
mock_decode_container.decode.return_value = iter([MagicMock()])
mock_decode_container.close = MagicMock()
# Return different containers for different calls
mock_av.side_effect = [mock_container, mock_decode_container]
# Get the original async function without the asynctask decorator
# The function is wrapped, so we need to call it differently
# For now, we test the pipeline directly since the task is just a thin wrapper
from reflector.pipelines.main_file_pipeline import PipelineMainFile
pipeline = PipelineMainFile(transcript_id=mock_transcript_in_db.id)
await pipeline.process(db_session, upload_path)
# Verify the pipeline was executed through the task
assert mock_audio_file_writer.push.called
assert mock_audio_file_writer.flush.called
assert mock_storage._put_file.called
assert mock_waveform_processor.flush.called
assert mock_topic_detector.push.called
assert mock_title_processor.push.called
assert mock_summary_processor.push.called
print("task_pipeline_file_process test completed successfully!")
@pytest.mark.asyncio
async def test_pipeline_file_process_no_transcript():
"""
Test the pipeline with a non-existent transcript.
"""
from reflector.pipelines.main_file_pipeline import PipelineMainFile
# Mock the controller to return None (transcript not found)
with patch(
"reflector.pipelines.main_file_pipeline.transcripts_controller.get_by_id"
) as mock_get:
mock_get.return_value = None
pipeline = PipelineMainFile(transcript_id=str(uuid4()))
# Should raise an exception for missing transcript when get_transcript is called
with pytest.raises(Exception, match="Transcript not found"):
# Use a mock session - the controller is mocked to return None anyway
from unittest.mock import MagicMock
mock_session = MagicMock()
await pipeline.get_transcript(mock_session)
@pytest.mark.asyncio
async def test_pipeline_file_process_no_audio_file(
db_session,
mock_transcript_in_db,
):
"""
Test the pipeline when no audio file is found.
"""
from reflector.pipelines.main_file_pipeline import PipelineMainFile
# Don't create any audio files in the data path
# The pipeline's process should handle missing files gracefully
pipeline = PipelineMainFile(transcript_id=mock_transcript_in_db.id)
# Try to process a non-existent file
non_existent_path = mock_transcript_in_db.data_path / "nonexistent.wav"
# This should fail when trying to open the file with av
with pytest.raises(Exception):
await pipeline.process(db_session, non_existent_path)