b54c2def30
- Add database migrations (006-028) for face recognition, identity, file_uuid - Add test scripts for ASR, face, search, processing - Add portal frontend (Tauri) - Add config, benchmark, and monitoring utilities - Add model checkpoints and pretrained model references
152 lines
4.7 KiB
Python
152 lines
4.7 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""Test ASR processor directly (not via subprocess)."""
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import sys
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import os
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import tempfile
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import json
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# Add scripts directory to path
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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# Import the run_asr function
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try:
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from scripts.asr_processor_debug import run_asr
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print("✓ Imported run_asr from asr_processor_debug")
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except ImportError as e:
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print(f"✗ Failed to import: {e}")
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# Try alternative import
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try:
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import scripts.asr_processor_debug as asr_module
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run_asr = asr_module.run_asr
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print("✓ Imported module")
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except Exception as e2:
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print(f"✗ Failed: {e2}")
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sys.exit(1)
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def test_small_video():
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"""Test on a small video file (should work)."""
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test_video = "/Users/accusys/test_video/20250209_212949.mp4"
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if not os.path.exists(test_video):
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print(f"Test video not found: {test_video}")
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return
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print(f"Testing on small video: {test_video}")
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# Create temp output file
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with tempfile.NamedTemporaryFile(suffix=".json", delete=False) as f:
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output_path = f.name
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try:
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# Run ASR directly (no subprocess)
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print("Calling run_asr...")
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run_asr(
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video_path=test_video,
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output_path=output_path,
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uuid="test_direct",
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chunk_duration=600, # 10 minutes
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max_direct_duration=1200, # 20 minutes
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model_size="tiny",
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compute_type="int8",
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monitor_interval=60,
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)
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# Check output
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if os.path.exists(output_path):
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with open(output_path, "r") as f:
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output = json.load(f)
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print(f"✓ ASR completed successfully")
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print(f" Segments: {len(output.get('segments', []))}")
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print(f" Language: {output.get('language')}")
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else:
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print("✗ Output file not created")
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except Exception as e:
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print(f"✗ ASR failed: {e}")
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import traceback
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traceback.print_exc()
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finally:
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if os.path.exists(output_path):
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os.unlink(output_path)
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print("✓ Cleaned up output file")
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def test_large_video_chunk():
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"""Test on a large video but with small chunk duration to debug hang."""
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# Use a large video file
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test_video = "/Users/accusys/test_video/1636719d-c31f-78ac-f1dd-8ab0b0b36c66.mov"
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if not os.path.exists(test_video):
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print(f"Large test video not found: {test_video}")
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return
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print(f"\nTesting on large video with 60s chunks (debug): {test_video}")
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# Create temp output file
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with tempfile.NamedTemporaryFile(suffix=".json", delete=False) as f:
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output_path = f.name
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try:
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# Run with very short chunk duration to see if we can get past first chunk
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print("Calling run_asr with 60s chunks...")
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# We'll run in a separate thread with timeout
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import threading
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import time
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result = {"success": False, "error": None, "output": None}
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def run_asr_thread():
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try:
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run_asr(
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video_path=test_video,
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output_path=output_path,
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uuid="test_large_debug",
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chunk_duration=60, # 1 minute chunks (smaller for debugging)
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max_direct_duration=120, # 2 minutes
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model_size="tiny",
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compute_type="int8",
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monitor_interval=30,
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)
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result["success"] = True
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except Exception as e:
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result["error"] = str(e)
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result["traceback"] = traceback.format_exc()
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thread = threading.Thread(target=run_asr_thread)
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thread.daemon = True
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thread.start()
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# Wait for 30 seconds max
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thread.join(timeout=30)
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if thread.is_alive():
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print("✗ ASR is hanging (thread still alive after 30 seconds)")
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result["timeout"] = True
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else:
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if result["success"]:
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print("✓ ASR completed within 30 seconds")
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if os.path.exists(output_path):
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with open(output_path, "r") as f:
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output = json.load(f)
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print(f" Segments: {len(output.get('segments', []))}")
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else:
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print(f"✗ ASR failed: {result.get('error')}")
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except Exception as e:
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print(f"✗ Test failed: {e}")
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import traceback
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traceback.print_exc()
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finally:
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if os.path.exists(output_path):
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os.unlink(output_path)
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print("✓ Cleaned up output file")
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if __name__ == "__main__":
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test_small_video()
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test_large_video_chunk()
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