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
71 lines
1.9 KiB
Python
71 lines
1.9 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""Test Whisper model loading and minimal transcription."""
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import sys
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import os
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import time
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import whisper
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def test_model_load():
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print("Testing Whisper model loading...")
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# Test loading tiny model
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start = time.time()
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try:
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model = whisper.load_model("tiny", device="cpu")
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elapsed = time.time() - start
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print(f"✓ Model loaded successfully in {elapsed:.2f}s")
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# Test transcription on a tiny audio file
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# Create a 1-second silent audio file or use a test file
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import tempfile
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import subprocess
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# Create a 1-second silent WAV file using sox or ffmpeg
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
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temp_wav = f.name
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# Create silent audio using ffmpeg
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cmd = [
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"ffmpeg",
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"-f",
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"lavfi",
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"-i",
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"anullsrc=r=16000:cl=mono",
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"-t",
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"1",
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"-acodec",
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"pcm_s16le",
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temp_wav,
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"-y",
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]
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try:
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subprocess.run(cmd, capture_output=True, check=True)
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print(f"✓ Created test audio file: {temp_wav}")
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# Try transcription
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print("Testing transcription...")
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start_trans = time.time()
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result = model.transcribe(temp_wav, beam_size=5)
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elapsed_trans = time.time() - start_trans
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print(f"✓ Transcription successful in {elapsed_trans:.2f}s")
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print(f" Segments: {len(result['segments'])}")
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os.unlink(temp_wav)
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except Exception as e:
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print(f"✗ Failed to create test audio: {e}")
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if os.path.exists(temp_wav):
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os.unlink(temp_wav)
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except Exception as e:
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print(f"✗ Model loading failed: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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test_model_load()
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