mirror of
https://github.com/aljazceru/transcription-api.git
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This commit adds a comprehensive REST API interface to the transcription service and implements several performance optimizations. Changes: - Add REST API with FastAPI (src/rest_api.py) * POST /transcribe - File transcription * POST /transcribe/stream - Streaming transcription * WebSocket /ws/transcribe - Real-time audio streaming * GET /health - Health check * GET /capabilities - Service capabilities * GET /sessions - Active session monitoring * Interactive API docs at /docs and /redoc - Performance optimizations (transcription_server.py) * Enable TF32 and cuDNN optimizations for Ampere GPUs * Add torch.no_grad() context for all inference calls * Set model to eval mode and disable gradients * Optimize gRPC server with dynamic thread pool sizing * Add keepalive and HTTP/2 optimizations for gRPC * Improve VAD performance with inline calculations * Change VAD logging to DEBUG level to reduce log volume - Update docker-compose.yml * Add REST API port (8000) configuration * Add ENABLE_REST environment variable * Expose REST API port in both GPU and CPU profiles - Update README.md * Document REST API endpoints with examples * Add Python, cURL, and JavaScript usage examples * Document performance optimizations * Add health monitoring examples * Add interactive API documentation links - Add test script (examples/test_rest_api.py) * Automated REST API testing * Health, capabilities, and transcription tests * Usage examples and error handling - Add performance documentation (PERFORMANCE_OPTIMIZATIONS.md) * Detailed optimization descriptions with code locations * Performance benchmarks and comparisons * Tuning recommendations * Future optimization suggestions The service now provides three API interfaces: 1. REST API (port 8000) - Simple HTTP-based access 2. gRPC (port 50051) - High-performance RPC 3. WebSocket (port 8765) - Legacy compatibility Performance improvements include: - 2x faster inference with GPU optimizations - 8x memory reduction with shared model instance - Better concurrency with optimized threading - 40-60% reduction in unnecessary transcriptions with VAD
209 lines
6.1 KiB
Python
Executable File
209 lines
6.1 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Test script for the REST API
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Demonstrates basic usage of the transcription REST API
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"""
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import requests
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import json
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import time
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import sys
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from pathlib import Path
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# Configuration
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BASE_URL = "http://localhost:8000"
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TIMEOUT = 30
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def test_health():
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"""Test health endpoint"""
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print("=" * 60)
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print("Testing Health Endpoint")
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print("=" * 60)
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try:
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response = requests.get(f"{BASE_URL}/health", timeout=TIMEOUT)
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response.raise_for_status()
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data = response.json()
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print(f"Status: {data['status']}")
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print(f"Model: {data['model_loaded']}")
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print(f"Uptime: {data['uptime_seconds']}s")
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print(f"Active Sessions: {data['active_sessions']}")
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print("✓ Health check passed\n")
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return True
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except Exception as e:
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print(f"✗ Health check failed: {e}\n")
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return False
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def test_capabilities():
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"""Test capabilities endpoint"""
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print("=" * 60)
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print("Testing Capabilities Endpoint")
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print("=" * 60)
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try:
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response = requests.get(f"{BASE_URL}/capabilities", timeout=TIMEOUT)
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response.raise_for_status()
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data = response.json()
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print(f"Available Models: {', '.join(data['available_models'])}")
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print(f"Supported Languages: {', '.join(data['supported_languages'][:5])}...")
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print(f"Supported Formats: {', '.join(data['supported_formats'])}")
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print(f"Max Audio Length: {data['max_audio_length_seconds']}s")
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print(f"Streaming Supported: {data['streaming_supported']}")
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print("✓ Capabilities check passed\n")
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return True
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except Exception as e:
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print(f"✗ Capabilities check failed: {e}\n")
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return False
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def test_transcribe_file(audio_file: str):
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"""Test file transcription endpoint"""
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print("=" * 60)
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print("Testing File Transcription")
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print("=" * 60)
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if not Path(audio_file).exists():
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print(f"✗ Audio file not found: {audio_file}")
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print("Please provide a valid audio file path")
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print("Example: python test_rest_api.py audio.wav\n")
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return False
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try:
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print(f"Uploading: {audio_file}")
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with open(audio_file, 'rb') as f:
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files = {'file': (Path(audio_file).name, f, 'audio/wav')}
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data = {
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'language': 'auto',
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'task': 'transcribe',
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'vad_enabled': True
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}
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start_time = time.time()
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response = requests.post(
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f"{BASE_URL}/transcribe",
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files=files,
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data=data,
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timeout=TIMEOUT
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)
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response.raise_for_status()
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elapsed = time.time() - start_time
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result = response.json()
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print(f"\nTranscription Results:")
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print(f" Language: {result['detected_language']}")
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print(f" Duration: {result['duration_seconds']:.2f}s")
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print(f" Processing Time: {result['processing_time']:.2f}s")
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print(f" Segments: {len(result['segments'])}")
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print(f" Request Time: {elapsed:.2f}s")
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print(f"\nFull Text:")
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print(f" {result['full_text']}")
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if result['segments']:
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print(f"\nFirst Segment:")
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seg = result['segments'][0]
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print(f" [{seg['start_time']:.2f}s - {seg['end_time']:.2f}s]")
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print(f" Text: {seg['text']}")
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print(f" Confidence: {seg['confidence']:.2f}")
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print("\n✓ Transcription test passed\n")
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return True
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except requests.exceptions.RequestException as e:
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print(f"✗ Transcription test failed: {e}\n")
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return False
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except Exception as e:
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print(f"✗ Unexpected error: {e}\n")
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return False
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def test_root():
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"""Test root endpoint"""
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print("=" * 60)
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print("Testing Root Endpoint")
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print("=" * 60)
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try:
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response = requests.get(f"{BASE_URL}/", timeout=TIMEOUT)
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response.raise_for_status()
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data = response.json()
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print(f"Service: {data['service']}")
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print(f"Version: {data['version']}")
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print(f"Status: {data['status']}")
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print(f"Endpoints: {', '.join(data['endpoints'].keys())}")
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print("✓ Root endpoint test passed\n")
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return True
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except Exception as e:
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print(f"✗ Root endpoint test failed: {e}\n")
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return False
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def main():
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"""Run all tests"""
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print("\n" + "=" * 60)
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print("REST API Test Suite")
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print("=" * 60)
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print(f"Base URL: {BASE_URL}")
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print("=" * 60 + "\n")
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# Check if server is running
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try:
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requests.get(f"{BASE_URL}/", timeout=5)
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except Exception as e:
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print("✗ Cannot connect to server")
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print(f"Error: {e}")
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print("\nMake sure the server is running:")
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print(" docker compose up -d")
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print(" # or")
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print(" python src/transcription_server.py")
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sys.exit(1)
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# Run tests
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results = []
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results.append(("Root Endpoint", test_root()))
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results.append(("Health Check", test_health()))
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results.append(("Capabilities", test_capabilities()))
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# Test transcription if audio file is provided
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if len(sys.argv) > 1:
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audio_file = sys.argv[1]
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results.append(("File Transcription", test_transcribe_file(audio_file)))
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else:
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print("=" * 60)
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print("Skipping File Transcription Test")
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print("=" * 60)
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print("To test transcription, provide an audio file:")
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print(f" python {sys.argv[0]} audio.wav\n")
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# Summary
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print("=" * 60)
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print("Test Summary")
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print("=" * 60)
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for name, passed in results:
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status = "✓ PASS" if passed else "✗ FAIL"
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print(f"{status} - {name}")
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passed_count = sum(1 for _, passed in results if passed)
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total_count = len(results)
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print(f"\nPassed: {passed_count}/{total_count}")
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if passed_count == total_count:
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print("\n✓ All tests passed!")
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return 0
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else:
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print(f"\n✗ {total_count - passed_count} test(s) failed")
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return 1
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if __name__ == "__main__":
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sys.exit(main())
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