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
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Warren
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benchmark_realistic.py
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151
benchmark_realistic.py
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#!/usr/bin/env python3
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"""Benchmark ASR with realistic chunk sizes."""
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import sys
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import os
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import subprocess
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import json
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import tempfile
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import time
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import shutil
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import statistics
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VIDEO_SOURCE = "../test_video/BigBuckBunny_320x180.mp4" # 10 minutes, 62MB
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if not os.path.exists(VIDEO_SOURCE):
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print(f"Video not found: {VIDEO_SOURCE}")
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sys.exit(1)
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def run_asr_mode(mode_name, max_direct_duration, chunk_duration, description):
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"""Run ASR processor with given parameters, return timing."""
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clip_path = os.path.join(temp_dir, f"clip_{mode_name}.mp4")
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output_path = os.path.join(temp_dir, f"output_{mode_name}.json")
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# Copy source video to clip path
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shutil.copy2(VIDEO_SOURCE, clip_path)
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env = os.environ.copy()
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env["MOMENTRY_ASR_MAX_DIRECT_DURATION"] = str(max_direct_duration)
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env["MOMENTRY_ASR_CHUNK_DURATION"] = str(chunk_duration)
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env["MOMENTRY_ASR_MODEL_SIZE"] = "tiny"
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env["MOMENTRY_ASR_COMPUTE_TYPE"] = "int8"
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cmd = [
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"/opt/homebrew/bin/python3.11",
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"scripts/asr_processor.py",
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clip_path,
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output_path,
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"--uuid",
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f"bench_{mode_name}",
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]
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start_time = time.time()
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proc = subprocess.run(cmd, capture_output=True, env=env, text=True)
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elapsed = time.time() - start_time
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returncode = proc.returncode
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# Read output
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segments = []
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language = ""
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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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data = json.load(f)
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segments = data.get("segments", [])
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language = data.get("language", "")
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# Clean up
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try:
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os.unlink(clip_path)
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os.unlink(output_path)
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except:
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pass
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return {
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"mode": mode_name,
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"description": description,
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"elapsed": elapsed,
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"returncode": returncode,
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"segments": len(segments),
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"language": language,
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"stderr": proc.stderr[:200] if proc.stderr else "",
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}
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# Create temporary directory
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temp_dir = tempfile.mkdtemp(prefix="asr_bench_real_")
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print(f"Benchmark directory: {temp_dir}")
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try:
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# Test 1: Direct transcription (video is 10 min, max_direct=30 min)
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print("\n1. Direct transcription (max_direct=1800s, chunk=600s):")
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direct = run_asr_mode(
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"direct",
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max_direct_duration=1800,
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chunk_duration=600,
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description="Direct (video < 30min threshold)",
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)
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print(f" Time: {direct['elapsed']:.1f}s, Segments: {direct['segments']}")
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# Test 2: Chunked with 1 chunk (force chunked but chunk size = video duration)
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print("\n2. Chunked with 1 chunk (max_direct=300s, chunk=600s):")
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chunked1 = run_asr_mode(
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"chunked1",
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max_direct_duration=300,
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chunk_duration=600,
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description="Chunked with 1 chunk (10 min)",
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)
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print(f" Time: {chunked1['elapsed']:.1f}s, Segments: {chunked1['segments']}")
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# Test 3: Chunked with 2 chunks (5 min each)
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print("\n3. Chunked with 2 chunks (max_direct=300s, chunk=300s):")
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chunked2 = run_asr_mode(
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"chunked2",
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max_direct_duration=300,
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chunk_duration=300,
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description="Chunked with 2 chunks (5 min each)",
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)
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print(f" Time: {chunked2['elapsed']:.1f}s, Segments: {chunked2['segments']}")
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# Test 4: Chunked with 5 chunks (2 min each) - worst case
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print("\n4. Chunked with 5 chunks (max_direct=300s, chunk=120s):")
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chunked5 = run_asr_mode(
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"chunked5",
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max_direct_duration=300,
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chunk_duration=120,
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description="Chunked with 5 chunks (2 min each)",
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)
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print(f" Time: {chunked5['elapsed']:.1f}s, Segments: {chunked5['segments']}")
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# Calculate overheads
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print("\n" + "=" * 60)
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print("OVERHEAD ANALYSIS (compared to direct transcription)")
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print("=" * 60)
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for test in [chunked1, chunked2, chunked5]:
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if direct["elapsed"] > 0:
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overhead = (test["elapsed"] - direct["elapsed"]) / direct["elapsed"] * 100
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status = "✅ ≤5%" if overhead <= 5 else "❌ >5%"
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print(f"\n{test['description']}:")
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print(f" Time: {test['elapsed']:.1f}s (direct: {direct['elapsed']:.1f}s)")
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print(f" Overhead: {overhead:.2f}% {status}")
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print(f" Segments: {test['segments']} (direct: {direct['segments']})")
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if test["segments"] != direct["segments"]:
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print(f" ⚠️ Segment count mismatch!")
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# Summary
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print("\n" + "=" * 60)
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print("SUMMARY")
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print("=" * 60)
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print(f"Video: {os.path.basename(VIDEO_SOURCE)} (~10 minutes)")
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print(f"\nKey finding: Overhead depends heavily on chunk count.")
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print(f"With realistic chunk sizes (10 min), overhead should be minimal.")
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except Exception as e:
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print(f"Benchmark failed: {e}")
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import traceback
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traceback.print_exc()
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finally:
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# Clean up directory
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shutil.rmtree(temp_dir, ignore_errors=True)
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print(f"\nCleaned up {temp_dir}")
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