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
229 lines
7.9 KiB
Python
229 lines
7.9 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""Test limited number of chunks to verify fix works end-to-end."""
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import subprocess
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import tempfile
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import os
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import time
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import sys
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import json
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def test_limited_chunks():
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"""Test processing only first 3 chunks (30 minutes) of large video."""
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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"Test video not found: {test_video}")
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return
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print(f"Testing first 3 chunks (30 minutes) of large video:")
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print(f" Video: {os.path.basename(test_video)}")
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print(f" Expected: 3 chunks × 10 minutes = 30 minutes audio")
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print("-" * 60)
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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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# We'll modify the script to only process 3 chunks
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# First, let's check if we can process with a smaller max_direct_duration
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# to force chunked mode but limit total processing time
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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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test_video,
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output_path,
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"--uuid",
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"test_limited",
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"--chunk-duration",
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"600", # 10 minutes
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"--max-direct-duration",
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"300", # Force chunked mode
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]
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env = os.environ.copy()
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env["MOMENTRY_DISABLE_REDIS"] = "1"
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env["ASR_DEBUG"] = "1"
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env["MOMENTRY_ASR_CHUNK_TIMEOUT"] = "60" # 1 minute per chunk
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print(f"Command: {' '.join(cmd)}")
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print(f"Environment: ASR_DEBUG=1, MOMENTRY_ASR_CHUNK_TIMEOUT=60")
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print("-" * 60)
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start = time.time()
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proc = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True,
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bufsize=1,
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env=env,
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)
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timeout = 300 # 5 minutes max for 3 chunks
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killed = False
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stderr_lines = []
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from select import select
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chunk_success_count = 0
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chunk_error_count = 0
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while True:
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if proc.poll() is not None:
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remaining_stderr = proc.stderr.read()
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if remaining_stderr:
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for line in remaining_stderr.split("\n"):
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if line:
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stderr_lines.append(line)
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break
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if time.time() - start > timeout:
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print(f"\n⏱️ TOTAL TIMEOUT after {timeout}s - killing process")
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proc.kill()
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killed = True
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break
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readable, _, _ = select([proc.stderr], [], [], 0.1)
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if readable:
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line = proc.stderr.readline()
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if line:
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line = line.rstrip("\n")
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stderr_lines.append(line)
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# Count chunk successes in real-time
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if "transcribe_chunk succeeded" in line:
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chunk_success_count += 1
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print(f" ✓ Chunk {chunk_success_count} succeeded")
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elif "error" in line.lower() and "debug" not in line:
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chunk_error_count += 1
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print(f" ✗ Error: {line}")
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elif "Chunk" in line and "extracting audio" in line:
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# Show progress
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print(f" Processing chunk...")
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time.sleep(0.05)
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if killed:
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proc.wait()
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elapsed = time.time() - start
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print(f"\n" + "=" * 60)
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print(f"Results:")
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print(f" Elapsed time: {elapsed:.1f}s")
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print(f" Killed: {killed}")
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print(f" Return code: {proc.returncode}")
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print(f" Chunks succeeded: {chunk_success_count}")
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print(f" Chunks with errors: {chunk_error_count}")
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# Analyze stderr for detailed results
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print(f"\nDetailed analysis:")
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# Count various events
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extract_success = [l for l in stderr_lines if "extract_chunk succeeded" in l]
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transcribe_success = [
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l for l in stderr_lines if "transcribe_chunk succeeded" in l
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]
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timeout_warnings = [l for l in stderr_lines if "timeout" in l.lower()]
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print(f" Audio extractions: {len(extract_success)}")
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print(f" Transcriptions: {len(transcribe_success)}")
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print(f" Timeout warnings: {len(timeout_warnings)}")
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if timeout_warnings:
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print(f" ⚠️ Timeout warnings detected:")
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for warning in timeout_warnings[:3]:
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print(f" {warning}")
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# Check if output was created
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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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processing_mode = data.get("processing_mode", "unknown")
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chunk_count = data.get("chunk_count", 0)
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print(f"\nOutput analysis:")
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print(f" Processing mode: {processing_mode}")
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print(f" Chunk count: {chunk_count}")
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print(f" Total segments: {len(segments)}")
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if segments:
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# Calculate audio coverage
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first_start = segments[0].get("start", 0)
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last_end = segments[-1].get("end", 0)
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total_duration = last_end - first_start
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print(f" First segment: {first_start:.1f}s")
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print(f" Last segment: {last_end:.1f}s")
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print(
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f" Total transcribed duration: {total_duration:.1f}s ({total_duration / 60:.1f} minutes)"
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)
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# Expected: ~1800 seconds for 3 chunks (30 minutes)
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expected_duration = 1800 # 30 minutes
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coverage = (
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(total_duration / expected_duration) * 100
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if expected_duration > 0
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else 0
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)
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print(f" Coverage of 30-minute target: {coverage:.1f}%")
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if coverage >= 90:
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print(f" ✅ Good coverage of target audio")
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elif coverage >= 50:
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print(f" ⚠️ Partial coverage")
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else:
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print(f" ❌ Low coverage")
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# Check segment quality
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empty_segments = [s for s in segments if not s.get("text", "").strip()]
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print(f" Empty segments: {len(empty_segments)}")
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# Sample first few segments
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print(f"\n Sample segments:")
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for i, seg in enumerate(segments[:5]):
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text = seg.get("text", "")
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if len(text) > 100:
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text = text[:97] + "..."
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print(
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f" {i + 1}. [{seg.get('start', 0):.1f}-{seg.get('end', 0):.1f}s]: {text}"
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)
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else:
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print(f"\n ❌ Output file not created")
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# Print last 20 lines of stderr for debugging
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print(f"\n Last 20 lines of stderr:")
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for line in stderr_lines[-20:]:
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if line.strip():
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print(f" {line}")
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print(f"\n" + "=" * 60)
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# Overall assessment
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if chunk_success_count >= 3 and not killed:
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print(f"✅ SUCCESS: Processed {chunk_success_count} chunks successfully")
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print(f" The fix appears to work correctly")
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elif chunk_success_count > 0:
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print(f"⚠️ PARTIAL: Processed {chunk_success_count} chunks")
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print(f" Some chunks succeeded, but not all")
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else:
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print(f"❌ FAILED: No chunks processed successfully")
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except Exception as e:
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print(f"✗ Error: {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(f"✓ Cleaned up output file")
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if __name__ == "__main__":
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test_limited_chunks()
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