Stream transcript segments to frontend as they are transcribed

Send each segment to the frontend immediately after transcription via
a new pipeline.segment IPC message, then send speaker assignments as a
batch pipeline.speaker_update message after diarization completes. This
lets the UI display segments progressively instead of waiting for the
entire pipeline to finish.

Changes:
- Add partial_segment_message and speaker_update_message IPC factories
- Add on_segment callback parameter to TranscribeService.transcribe()
- Emit partial segments and speaker updates from PipelineService.run()
- Add send_and_receive_with_progress to SidecarManager (Rust)
- Route pipeline.segment/speaker_update events in run_pipeline command
- Listen for streaming events in Svelte frontend (+page.svelte)
- Add tests for new message types, callback signature, and update logic

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

python/voice_to_notes/services/pipeline.py

@@ -7,7 +7,11 @@ import time
 from dataclasses import dataclass, field
 from typing import Any
 
-from voice_to_notes.ipc.messages import progress_message
+from voice_to_notes.ipc.messages import (
+    partial_segment_message,
+    progress_message,
+    speaker_update_message,
+)
 from voice_to_notes.ipc.protocol import write_message
 from voice_to_notes.services.diarize import DiarizeService, SpeakerSegment
 from voice_to_notes.services.transcribe import (
@@ -82,6 +86,15 @@ class PipelineService:
             progress_message(request_id, 0, "pipeline", "Starting transcription pipeline...")
         )
 
+        def _emit_segment(seg: SegmentResult, index: int) -> None:
+            write_message(partial_segment_message(request_id, {
+                "index": index,
+                "text": seg.text,
+                "start_ms": seg.start_ms,
+                "end_ms": seg.end_ms,
+                "words": [{"word": w.word, "start_ms": w.start_ms, "end_ms": w.end_ms, "confidence": w.confidence} for w in seg.words],
+            }))
+
         transcription = self._transcribe_service.transcribe(
             request_id=request_id,
             file_path=file_path,
@@ -89,6 +102,7 @@ class PipelineService:
             device=device,
             compute_type=compute_type,
             language=language,
+            on_segment=_emit_segment,
         )
 
         if skip_diarization:
@@ -140,6 +154,10 @@ class PipelineService:
             flush=True,
         )
 
+        updates = [{"index": i, "speaker": seg.speaker} for i, seg in enumerate(result.segments) if seg.speaker]
+        if updates:
+            write_message(speaker_update_message(request_id, updates))
+
         write_message(
             progress_message(request_id, 100, "done", "Pipeline complete")
         )

python/voice_to_notes/services/transcribe.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 import sys
 import time
+from collections.abc import Callable
 from dataclasses import dataclass, field
 from typing import Any
 
@@ -90,6 +91,7 @@ class TranscribeService:
         device: str = "cpu",
         compute_type: str = "int8",
         language: str | None = None,
+        on_segment: Callable[[SegmentResult, int], None] | None = None,
     ) -> TranscriptionResult:
         """Transcribe an audio file with word-level timestamps.
 
@@ -145,6 +147,9 @@ class TranscribeService:
                 )
             )
 
+            if on_segment:
+                on_segment(result.segments[-1], segment_count - 1)
+
             # Send progress every few segments
             if segment_count % 5 == 0:
                 write_message(