Phase 3: Speaker diarization and full transcription pipeline

- Implement DiarizeService with pyannote.audio speaker detection
- Build PipelineService combining transcribe → diarize → merge with
  overlap-based speaker assignment per segment
- Add pipeline.start and diarize.start IPC handlers
- Add run_pipeline Tauri command for full pipeline execution
- Wire frontend to use pipeline: speakers auto-created with colors,
  segments assigned to detected speakers
- Build SpeakerManager with rename support (double-click or edit button)
- Add speaker color coding throughout transcript display
- Add pyannote.audio dependency
- Tests: 24 Python (including merge logic), 6 Rust, 0 Svelte errors

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src-tauri/src/lib.rs

@@ -4,7 +4,7 @@ pub mod sidecar;
 pub mod state;
 
 use commands::project::{create_project, get_project, list_projects};
-use commands::transcribe::transcribe_file;
+use commands::transcribe::{run_pipeline, transcribe_file};
 
 #[cfg_attr(mobile, tauri::mobile_entry_point)]
 pub fn run() {
@@ -16,6 +16,7 @@ pub fn run() {
             get_project,
             list_projects,
             transcribe_file,
+            run_pipeline,
         ])
         .run(tauri::generate_context!())
         .expect("error while running tauri application");