feat: Diarization cli (#509)

* diarisation cli

* feat: s3 upload for modal diarisation cli call

* chore: cleanup

* chore: s3 cleanup improvement

* chore: lint

* chore: cleanup

* chore: cleanup

* chore: cleanup

* chore: cleanup

server/reflector/tools/test_diarization.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python3
+"""
+@vibe-generated
+Test script for the diarization CLI tool
+=========================================
+
+This script helps test the diarization functionality with sample audio files.
+"""
+
+import asyncio
+import json
+import sys
+from pathlib import Path
+
+from reflector.logger import logger
+
+
+async def test_diarization(audio_file: str):
+    """Test the diarization functionality"""
+    
+    # Import the processing function
+    from process_with_diarization import process_audio_file_with_diarization
+    
+    # Collect events
+    events = []
+    
+    async def event_callback(event):
+        events.append({
+            "processor": event.processor,
+            "data": event.data
+        })
+        logger.info(f"Event from {event.processor}")
+    
+    # Process the audio file
+    logger.info(f"Processing audio file: {audio_file}")
+    
+    try:
+        await process_audio_file_with_diarization(
+            audio_file,
+            event_callback,
+            only_transcript=False,
+            source_language="en",
+            target_language="en",
+            enable_diarization=True,
+            diarization_backend="modal",
+        )
+        
+        # Analyze results
+        logger.info(f"Processing complete. Received {len(events)} events")
+        
+        # Look for diarization results
+        diarized_topics = []
+        for event in events:
+            if "TitleSummary" in event["processor"]:
+                # Check if words have speaker information
+                if hasattr(event["data"], "transcript") and event["data"].transcript:
+                    words = event["data"].transcript.words
+                    if words and hasattr(words[0], "speaker"):
+                        speakers = set(w.speaker for w in words if hasattr(w, "speaker"))
+                        logger.info(f"Found {len(speakers)} speakers in topic: {event['data'].title}")
+                        diarized_topics.append(event["data"])
+        
+        if diarized_topics:
+            logger.info(f"Successfully diarized {len(diarized_topics)} topics")
+            
+            # Print sample output
+            sample_topic = diarized_topics[0]
+            logger.info("Sample diarized output:")
+            for i, word in enumerate(sample_topic.transcript.words[:10]):
+                logger.info(f"  Word {i}: '{word.text}' - Speaker {word.speaker}")
+        else:
+            logger.warning("No diarization results found in output")
+        
+        return events
+        
+    except Exception as e:
+        logger.error(f"Error during processing: {e}")
+        raise
+
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: python test_diarization.py <audio_file>")
+        sys.exit(1)
+    
+    audio_file = sys.argv[1]
+    if not Path(audio_file).exists():
+        print(f"Error: Audio file '{audio_file}' not found")
+        sys.exit(1)
+    
+    # Run the test
+    asyncio.run(test_diarization(audio_file))
+
+
+if __name__ == "__main__":
+    main()