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"""Integration tests for the complete audio processing pipeline."""
import os
import tempfile
import time
import pytest
from pathlib import Path
from unittest.mock import Mock, patch, MagicMock
from typing import Dict, Any, Optional
from src.application.services.audio_processing_service import AudioProcessingApplicationService
from src.application.dtos.audio_upload_dto import AudioUploadDto
from src.application.dtos.processing_request_dto import ProcessingRequestDto
from src.application.dtos.processing_result_dto import ProcessingResultDto
from src.infrastructure.config.dependency_container import DependencyContainer
from src.infrastructure.config.app_config import AppConfig
from src.domain.models.audio_content import AudioContent
from src.domain.models.text_content import TextContent
from src.domain.models.voice_settings import VoiceSettings
from src.domain.exceptions import (
SpeechRecognitionException,
TranslationFailedException,
SpeechSynthesisException
)
class TestAudioProcessingPipeline:
"""Integration tests for the complete audio processing pipeline."""
@pytest.fixture
def temp_dir(self):
"""Create temporary directory for test files."""
with tempfile.TemporaryDirectory() as temp_dir:
yield temp_dir
@pytest.fixture
def mock_config(self, temp_dir):
"""Create mock configuration for testing."""
config = Mock(spec=AppConfig)
# Processing configuration
config.get_processing_config.return_value = {
'max_file_size_mb': 50,
'supported_audio_formats': ['wav', 'mp3', 'flac'],
'temp_dir': temp_dir,
'cleanup_temp_files': True
}
# Logging configuration
config.get_logging_config.return_value = {
'level': 'INFO',
'enable_file_logging': False,
'log_file_path': os.path.join(temp_dir, 'test.log'),
'format': '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
}
# STT configuration
config.get_stt_config.return_value = {
'preferred_providers': ['parakeet', 'whisper-small', 'whisper-medium']
}
# TTS configuration
config.get_tts_config.return_value = {
'preferred_providers': ['kokoro', 'dia', 'cosyvoice2', 'dummy']
}
return config
@pytest.fixture
def mock_container(self, mock_config):
"""Create mock dependency container for testing."""
container = Mock(spec=DependencyContainer)
container.resolve.return_value = mock_config
# Mock STT provider
mock_stt_provider = Mock()
mock_stt_provider.transcribe.return_value = TextContent(
text="Hello, this is a test transcription.",
language="en"
)
container.get_stt_provider.return_value = mock_stt_provider
# Mock translation provider
mock_translation_provider = Mock()
mock_translation_provider.translate.return_value = TextContent(
text="Hola, esta es una transcripción de prueba.",
language="es"
)
container.get_translation_provider.return_value = mock_translation_provider
# Mock TTS provider
mock_tts_provider = Mock()
mock_audio_content = AudioContent(
data=b"fake_audio_data",
format="wav",
sample_rate=22050,
duration=2.5
)
mock_tts_provider.synthesize.return_value = mock_audio_content
container.get_tts_provider.return_value = mock_tts_provider
return container
@pytest.fixture
def audio_service(self, mock_container, mock_config):
"""Create audio processing service for testing."""
return AudioProcessingApplicationService(mock_container, mock_config)
@pytest.fixture
def sample_audio_upload(self):
"""Create sample audio upload DTO."""
return AudioUploadDto(
filename="test_audio.wav",
content=b"fake_wav_audio_data",
content_type="audio/wav",
size=1024
)
@pytest.fixture
def sample_processing_request(self, sample_audio_upload):
"""Create sample processing request DTO."""
return ProcessingRequestDto(
audio=sample_audio_upload,
asr_model="whisper-small",
target_language="es",
source_language="en",
voice="kokoro",
speed=1.0,
requires_translation=True
)
def test_complete_pipeline_success(self, audio_service, sample_processing_request):
"""Test successful execution of the complete audio processing pipeline."""
# Execute the pipeline
result = audio_service.process_audio_pipeline(sample_processing_request)
# Verify successful result
assert isinstance(result, ProcessingResultDto)
assert result.success is True
assert result.error_message is None
assert result.original_text == "Hello, this is a test transcription."
assert result.translated_text == "Hola, esta es una transcripción de prueba."
assert result.audio_path is not None
assert result.processing_time > 0
assert result.metadata is not None
assert 'correlation_id' in result.metadata
def test_pipeline_without_translation(self, audio_service, sample_audio_upload):
"""Test pipeline execution without translation (same language)."""
request = ProcessingRequestDto(
audio=sample_audio_upload,
asr_model="whisper-small",
target_language="en",
source_language="en",
voice="kokoro",
speed=1.0,
requires_translation=False
)
result = audio_service.process_audio_pipeline(request)
assert result.success is True
assert result.original_text == "Hello, this is a test transcription."
assert result.translated_text is None # No translation performed
assert result.audio_path is not None
def test_pipeline_with_different_voice_settings(self, audio_service, sample_audio_upload):
"""Test pipeline with different voice settings."""
request = ProcessingRequestDto(
audio=sample_audio_upload,
asr_model="whisper-medium",
target_language="fr",
source_language="en",
voice="dia",
speed=1.5,
requires_translation=True
)
result = audio_service.process_audio_pipeline(request)
assert result.success is True
assert result.metadata['voice'] == "dia"
assert result.metadata['speed'] == 1.5
assert result.metadata['asr_model'] == "whisper-medium"
def test_pipeline_performance_metrics(self, audio_service, sample_processing_request):
"""Test that pipeline captures performance metrics."""
start_time = time.time()
result = audio_service.process_audio_pipeline(sample_processing_request)
end_time = time.time()
assert result.success is True
assert result.processing_time > 0
assert result.processing_time <= (end_time - start_time) + 0.1 # Allow small margin
assert 'correlation_id' in result.metadata
def test_pipeline_with_large_file(self, audio_service, mock_config):
"""Test pipeline behavior with large audio files."""
# Create large audio upload
large_audio = AudioUploadDto(
filename="large_audio.wav",
content=b"x" * (10 * 1024 * 1024), # 10MB
content_type="audio/wav",
size=10 * 1024 * 1024
)
request = ProcessingRequestDto(
audio=large_audio,
asr_model="whisper-small",
target_language="es",
voice="kokoro",
speed=1.0,
requires_translation=True
)
result = audio_service.process_audio_pipeline(request)
assert result.success is True
assert result.metadata['file_size'] == 10 * 1024 * 1024
def test_pipeline_file_cleanup(self, audio_service, sample_processing_request, temp_dir):
"""Test that temporary files are properly cleaned up."""
# Count files before processing
files_before = len(list(Path(temp_dir).rglob("*")))
result = audio_service.process_audio_pipeline(sample_processing_request)
# Verify processing succeeded
assert result.success is True
# Verify cleanup occurred (no additional temp files)
files_after = len(list(Path(temp_dir).rglob("*")))
assert files_after <= files_before + 1 # Allow for output file
def test_pipeline_correlation_id_tracking(self, audio_service, sample_processing_request):
"""Test that correlation IDs are properly tracked throughout the pipeline."""
result = audio_service.process_audio_pipeline(sample_processing_request)
assert result.success is True
assert 'correlation_id' in result.metadata
correlation_id = result.metadata['correlation_id']
assert isinstance(correlation_id, str)
assert len(correlation_id) > 0
# Verify correlation ID is used in status tracking
status = audio_service.get_processing_status(correlation_id)
assert status['correlation_id'] == correlation_id
def test_pipeline_metadata_completeness(self, audio_service, sample_processing_request):
"""Test that pipeline result contains complete metadata."""
result = audio_service.process_audio_pipeline(sample_processing_request)
assert result.success is True
assert result.metadata is not None
expected_metadata_keys = [
'correlation_id', 'asr_model', 'target_language',
'voice', 'speed', 'translation_required'
]
for key in expected_metadata_keys:
assert key in result.metadata
def test_pipeline_supported_configurations(self, audio_service):
"""Test retrieval of supported pipeline configurations."""
config = audio_service.get_supported_configurations()
assert 'asr_models' in config
assert 'voices' in config
assert 'languages' in config
assert 'audio_formats' in config
assert 'max_file_size_mb' in config
assert 'speed_range' in config
assert isinstance(config['asr_models'], list)
assert isinstance(config['voices'], list)
assert isinstance(config['languages'], list)
assert len(config['asr_models']) > 0
assert len(config['voices']) > 0
def test_pipeline_context_manager(self, mock_container, mock_config):
"""Test audio service as context manager."""
with AudioProcessingApplicationService(mock_container, mock_config) as service:
assert service is not None
# Service should be usable within context
config = service.get_supported_configurations()
assert config is not None
def test_pipeline_multiple_requests(self, audio_service, sample_audio_upload):
"""Test processing multiple requests in sequence."""
requests = []
for i in range(3):
request = ProcessingRequestDto(
audio=sample_audio_upload,
asr_model="whisper-small",
target_language="es",
voice="kokoro",
speed=1.0,
requires_translation=True
)
requests.append(request)
results = []
for request in requests:
result = audio_service.process_audio_pipeline(request)
results.append(result)
# Verify all requests succeeded
for result in results:
assert result.success is True
assert result.original_text is not None
assert result.translated_text is not None
# Verify each request has unique correlation ID
correlation_ids = [r.metadata['correlation_id'] for r in results]
assert len(set(correlation_ids)) == 3 # All unique
def test_pipeline_concurrent_processing(self, audio_service, sample_processing_request):
"""Test pipeline behavior under concurrent processing."""
import threading
import queue
results_queue = queue.Queue()
def process_request():
try:
result = audio_service.process_audio_pipeline(sample_processing_request)
results_queue.put(result)
except Exception as e:
results_queue.put(e)
# Start multiple threads
threads = []
for _ in range(3):
thread = threading.Thread(target=process_request)
threads.append(thread)
thread.start()
# Wait for completion
for thread in threads:
thread.join()
# Verify all results
results = []
while not results_queue.empty():
result = results_queue.get()
if isinstance(result, Exception):
pytest.fail(f"Concurrent processing failed: {result}")
results.append(result)
assert len(results) == 3
for result in results:
assert result.success is True
def test_pipeline_memory_usage(self, audio_service, sample_processing_request):
"""Test pipeline memory usage and cleanup."""
import psutil
import os
process = psutil.Process(os.getpid())
memory_before = process.memory_info().rss
# Process multiple requests
for _ in range(5):
result = audio_service.process_audio_pipeline(sample_processing_request)
assert result.success is True
memory_after = process.memory_info().rss
memory_increase = memory_after - memory_before
# Memory increase should be reasonable (less than 50MB for test data)
assert memory_increase < 50 * 1024 * 1024
def test_pipeline_with_streaming_synthesis(self, audio_service, sample_processing_request, mock_container):
"""Test pipeline with streaming TTS synthesis."""
# Mock streaming TTS provider
mock_tts_provider = mock_container.get_tts_provider.return_value
def mock_stream():
for i in range(3):
yield AudioContent(
data=f"chunk_{i}".encode(),
format="wav",
sample_rate=22050,
duration=0.5
)
mock_tts_provider.synthesize_stream.return_value = mock_stream()
result = audio_service.process_audio_pipeline(sample_processing_request)
assert result.success is True
assert result.audio_path is not None
def test_pipeline_configuration_validation(self, audio_service):
"""Test pipeline configuration validation."""
config = audio_service.get_supported_configurations()
# Verify configuration structure
assert isinstance(config['asr_models'], list)
assert isinstance(config['voices'], list)
assert isinstance(config['languages'], list)
assert isinstance(config['audio_formats'], list)
assert isinstance(config['max_file_size_mb'], (int, float))
assert isinstance(config['speed_range'], dict)
# Verify speed range
speed_range = config['speed_range']
assert 'min' in speed_range
assert 'max' in speed_range
assert speed_range['min'] < speed_range['max']
assert speed_range['min'] > 0
assert speed_range['max'] <= 3.0
def test_pipeline_error_recovery_logging(self, audio_service, sample_processing_request, mock_container):
"""Test that error recovery attempts are properly logged."""
# Mock STT provider to fail first time, succeed second time
mock_stt_provider = mock_container.get_stt_provider.return_value
mock_stt_provider.transcribe.side_effect = [
SpeechRecognitionException("First attempt failed"),
TextContent(text="Recovered transcription", language="en")
]
with patch('src.application.services.audio_processing_service.logger') as mock_logger:
result = audio_service.process_audio_pipeline(sample_processing_request)
assert result.success is True
# Verify error and recovery were logged
mock_logger.warning.assert_called()
mock_logger.info.assert_called()
def test_pipeline_end_to_end_timing(self, audio_service, sample_processing_request):
"""Test end-to-end pipeline timing and performance."""
start_time = time.time()
result = audio_service.process_audio_pipeline(sample_processing_request)
end_time = time.time()
total_time = end_time - start_time
assert result.success is True
assert result.processing_time > 0
assert result.processing_time <= total_time
# For mock providers, processing should be fast
assert total_time < 5.0 # Should complete within 5 seconds
# Verify timing metadata
assert 'correlation_id' in result.metadata
timing_info = result.metadata
assert timing_info is not None |