mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-21 04:39:06 +00:00
dailico track merge vibe
This commit is contained in:
Igor Loskutov
162
server/test_multitrack_ffmpeg_local.py
Normal file
162
server/test_multitrack_ffmpeg_local.py
Normal file
@@ -0,0 +1,162 @@
|
||||
#!/usr/bin/env python
|
||||
"""
|
||||
Test script to trigger multitrack recording processing with ffmpeg padding fix
|
||||
This version loads tracks from local filesystem instead of S3
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
|
||||
from reflector.pipelines.main_multitrack_pipeline import PipelineMainMultitrack
|
||||
|
||||
|
||||
async def test_processing():
|
||||
"""Manually trigger multitrack processing for the test recording"""
|
||||
|
||||
# Initialize database connection
|
||||
from reflector.db import get_database
|
||||
|
||||
db = get_database()
|
||||
await db.connect()
|
||||
|
||||
try:
|
||||
# Create a new transcript ID
|
||||
import uuid
|
||||
|
||||
transcript_id = str(uuid.uuid4())
|
||||
|
||||
# Create transcript directly with SQL
|
||||
from reflector.db.transcripts import (
|
||||
Transcript,
|
||||
transcripts,
|
||||
transcripts_controller,
|
||||
)
|
||||
|
||||
pipeline = PipelineMainMultitrack(transcript_id=transcript_id)
|
||||
|
||||
# Create transcript model
|
||||
transcript = Transcript(
|
||||
id=transcript_id,
|
||||
name="FFMPEG Test - Daily Multitrack Recording",
|
||||
source_kind="file",
|
||||
source_language="en",
|
||||
target_language="en",
|
||||
status="idle",
|
||||
events=[],
|
||||
title="",
|
||||
)
|
||||
# Insert into database
|
||||
query = transcripts.insert().values(**transcript.model_dump())
|
||||
await db.execute(query)
|
||||
print(f"Created transcript: {transcript_id}")
|
||||
|
||||
# Read track files from local filesystem (in the container they'll be at /app/)
|
||||
tracks_dir = "/app"
|
||||
track_files = [
|
||||
"1760988935484-52f7f48b-fbab-431f-9a50-87b9abfc8255-cam-audio-1760988935922.webm",
|
||||
"1760988935484-a37c35e3-6f8e-4274-a482-e9d0f102a732-cam-audio-1760988943823.webm",
|
||||
]
|
||||
|
||||
# Read track data
|
||||
track_datas = []
|
||||
for track_file in track_files:
|
||||
file_path = os.path.join(tracks_dir, track_file)
|
||||
if os.path.exists(file_path):
|
||||
with open(file_path, "rb") as f:
|
||||
track_datas.append(f.read())
|
||||
print(f"Loaded track: {track_file} ({len(track_datas[-1])} bytes)")
|
||||
else:
|
||||
print(f"Track file not found: {file_path}")
|
||||
track_datas.append(b"")
|
||||
|
||||
# Process the tracks using the pipeline
|
||||
print(f"\nProcessing multitrack recording with ffmpeg padding...")
|
||||
print(f"Track 0: ...935922.webm (expected to start at ~2s)")
|
||||
print(f"Track 1: ...943823.webm (expected to start at ~51s)")
|
||||
|
||||
# Call the process method directly with track data
|
||||
# We'll need to mock S3 operations and directly work with the data
|
||||
|
||||
# Save tracks to temporary files and process them
|
||||
|
||||
try:
|
||||
await pipeline.set_status(transcript_id, "processing")
|
||||
|
||||
# Create a mock bucket and keys setup
|
||||
bucket_name = "test-bucket"
|
||||
track_keys = ["track0.webm", "track1.webm"]
|
||||
|
||||
# Mock S3 client to return our local data
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
mock_s3 = MagicMock()
|
||||
|
||||
def mock_get_object(Bucket, Key):
|
||||
idx = 0 if "track0" in Key else 1
|
||||
return {"Body": MagicMock(read=lambda: track_datas[idx])}
|
||||
|
||||
mock_s3.get_object = mock_get_object
|
||||
|
||||
# Patch boto3.client to return our mock
|
||||
with patch("boto3.client", return_value=mock_s3):
|
||||
await pipeline.process(bucket_name, track_keys)
|
||||
|
||||
print(f"Processing complete!")
|
||||
except Exception as e:
|
||||
await pipeline.set_status(transcript_id, "error")
|
||||
print(f"Error during processing: {e}")
|
||||
import traceback
|
||||
|
||||
traceback.print_exc()
|
||||
raise
|
||||
|
||||
# Check the results
|
||||
final_transcript = await transcripts_controller.get(transcript_id)
|
||||
print(f"\nTranscript status: {final_transcript.status}")
|
||||
print(f"Transcript title: {final_transcript.title}")
|
||||
|
||||
# Extract timeline from events
|
||||
if final_transcript.events:
|
||||
for event in final_transcript.events:
|
||||
if event.get("event") == "TRANSCRIPT":
|
||||
text = event.get("data", {}).get("text", "")
|
||||
# Show first 500 chars to check if speakers are properly separated
|
||||
print(f"\nTranscript text (first 500 chars):")
|
||||
print(text[:500])
|
||||
|
||||
# Show last 500 chars too to see if second speaker is at the end
|
||||
print(f"\nTranscript text (last 500 chars):")
|
||||
print(text[-500:])
|
||||
|
||||
# Count words per speaker
|
||||
words = text.split()
|
||||
print(f"\nTotal words in transcript: {len(words)}")
|
||||
|
||||
# Check if text has proper speaker separation
|
||||
# Expected: First ~45% from speaker 0, then ~35% from speaker 1, then ~20% from speaker 0
|
||||
first_third = " ".join(words[: len(words) // 3])
|
||||
middle_third = " ".join(
|
||||
words[len(words) // 3 : 2 * len(words) // 3]
|
||||
)
|
||||
last_third = " ".join(words[2 * len(words) // 3 :])
|
||||
|
||||
print(f"\nFirst third preview: {first_third[:100]}...")
|
||||
print(f"Middle third preview: {middle_third[:100]}...")
|
||||
print(f"Last third preview: {last_third[:100]}...")
|
||||
break
|
||||
|
||||
return transcript_id
|
||||
finally:
|
||||
await db.disconnect()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
transcript_id = asyncio.run(test_processing())
|
||||
print(f"\n✅ Test complete! Transcript ID: {transcript_id}")
|
||||
print(f"\nExpected timeline:")
|
||||
print(f" Speaker 0: ~2s to ~49s (first participant speaks)")
|
||||
print(f" Speaker 1: ~51s to ~70s (second participant speaks)")
|
||||
print(f" Speaker 0: ~73s to end (first participant speaks again)")
|
||||
print(
|
||||
f"\nIf the text shows proper chronological order (not interleaved), the fix worked!"
|
||||
)
|
||||
Reference in New Issue
Block a user