feat: add migrations, test scripts, and utility tools

- 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

test_transcribe.py

@@ -0,0 +1,66 @@
+#!/usr/bin/env python3
+"""
+Test transcription on extracted audio.
+"""
+
+import sys
+import time
+from pathlib import Path
+
+# Add scripts directory to path
+sys.path.insert(0, str(Path(__file__).parent / "scripts"))
+
+
+def test_transcribe(audio_path):
+    """Test transcription using faster_whisper."""
+    print(f"Testing transcription on: {audio_path}")
+    print(f"Size: {Path(audio_path).stat().st_size / 1024 / 1024:.1f} MB")
+
+    # Import faster_whisper
+    try:
+        from faster_whisper import WhisperModel
+    except ImportError as e:
+        print(f"Failed to import faster_whisper: {e}")
+        return False
+
+    # Load model
+    print("Loading Whisper model (tiny, cpu, int8)...")
+    start = time.time()
+    try:
+        model = WhisperModel("tiny", device="cpu", compute_type="int8")
+        load_time = time.time() - start
+        print(f"Model loaded in {load_time:.1f}s")
+    except Exception as e:
+        print(f"Model loading failed: {e}")
+        return False
+
+    # Transcribe first 30 seconds
+    print("Transcribing first 30 seconds...")
+    start = time.time()
+    try:
+        segments, info = model.transcribe(audio_path, beam_size=5)
+        # Convert generator to list to force processing
+        segments = list(segments)
+        transcribe_time = time.time() - start
+        print(f"Transcription completed in {transcribe_time:.1f}s")
+        print(
+            f"Detected language: {info.language} (prob {info.language_probability:.2f})"
+        )
+        print(f"Segments found: {len(segments)}")
+        for i, seg in enumerate(segments[:3]):
+            print(f"  [{i}] {seg.start:.1f}-{seg.end:.1f}: {seg.text[:80]}...")
+        return True
+    except Exception as e:
+        print(f"Transcription failed: {e}")
+        import traceback
+
+        traceback.print_exc()
+        return False
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print(f"Usage: {sys.argv[0]} <audio_file>")
+        sys.exit(1)
+    success = test_transcribe(sys.argv[1])
+    sys.exit(0 if success else 1)