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_model_load.py

@@ -0,0 +1,70 @@
+#!/opt/homebrew/bin/python3.11
+"""Test Whisper model loading and minimal transcription."""
+
+import sys
+import os
+import time
+import whisper
+
+
+def test_model_load():
+    print("Testing Whisper model loading...")
+
+    # Test loading tiny model
+    start = time.time()
+    try:
+        model = whisper.load_model("tiny", device="cpu")
+        elapsed = time.time() - start
+        print(f"✓ Model loaded successfully in {elapsed:.2f}s")
+
+        # Test transcription on a tiny audio file
+        # Create a 1-second silent audio file or use a test file
+        import tempfile
+        import subprocess
+
+        # Create a 1-second silent WAV file using sox or ffmpeg
+        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
+            temp_wav = f.name
+
+        # Create silent audio using ffmpeg
+        cmd = [
+            "ffmpeg",
+            "-f",
+            "lavfi",
+            "-i",
+            "anullsrc=r=16000:cl=mono",
+            "-t",
+            "1",
+            "-acodec",
+            "pcm_s16le",
+            temp_wav,
+            "-y",
+        ]
+        try:
+            subprocess.run(cmd, capture_output=True, check=True)
+            print(f"✓ Created test audio file: {temp_wav}")
+
+            # Try transcription
+            print("Testing transcription...")
+            start_trans = time.time()
+            result = model.transcribe(temp_wav, beam_size=5)
+            elapsed_trans = time.time() - start_trans
+            print(f"✓ Transcription successful in {elapsed_trans:.2f}s")
+            print(f"  Segments: {len(result['segments'])}")
+
+            os.unlink(temp_wav)
+
+        except Exception as e:
+            print(f"✗ Failed to create test audio: {e}")
+            if os.path.exists(temp_wav):
+                os.unlink(temp_wav)
+
+    except Exception as e:
+        print(f"✗ Model loading failed: {e}")
+        import traceback
+
+        traceback.print_exc()
+
+
+if __name__ == "__main__":
+    test_model_load()