chore(fix): Resolve regressions in history logic, track startup, and GUI performance

src/app_controller.py

@@ -2840,6 +2840,9 @@ class AppController:
   self._tool_stats.clear()
   self._comms_log.clear()
   self.disc_entries.clear()
+  self.files.clear()
+  self.context_files.clear()
+  self.tracks.clear()
   # Clear history in ALL discussions to be safe
   disc_sec = self.project.get("discussion", {})
   discussions = disc_sec.get("discussions", {})
@@ -3205,14 +3208,15 @@ class AppController:
    try:
    # Use a local copy of files to avoid concurrent modification issues
     files_to_scan = list(self.files)
-    for i, file_path in enumerate(files_to_scan):
+    for i, f_item in enumerate(files_to_scan):
      try:
       self.ai_status = f"Phase 2: Scanning files ({i+1}/{len(files_to_scan)})..."
-      abs_path = Path(self.active_project_root) / file_path
+      f_path = f_item.path if hasattr(f_item, 'path') else str(f_item)
+      abs_path = Path(self.active_project_root) / f_path
       if abs_path.exists() and abs_path.suffix == ".py":
        with open(abs_path, "r", encoding="utf-8") as f:
         code = f.read()
-        generated_skeletons += f"\nFile: {file_path}\n{parser.get_skeleton(code)}\n"
+        generated_skeletons += f"\nFile: {f_path}\n{parser.get_skeleton(code)}\n"
      except Exception as e:
       pass
    except Exception as e:
@@ -3220,10 +3224,12 @@ class AppController:
     return # Exit if skeleton generation fails
    # Now loop through tracks and call _start_track_logic with generated skeletons
    total_tracks = len(self.proposed_tracks)
+   print(f"[DEBUG] _cb_accept_tracks: Starting {total_tracks} tracks...")
    for i, track_data in enumerate(self.proposed_tracks):
     title = track_data.get("title") or track_data.get("goal", "Untitled Track")
     self.ai_status = f"Processing track {i+1} of {total_tracks}: '{title}'..."
     self._start_track_logic(track_data, skeletons_str=generated_skeletons) # Pass skeletons
+   print(f"[DEBUG] _cb_accept_tracks: All {total_tracks} tracks processed.")
    with self._pending_gui_tasks_lock:
     self._pending_gui_tasks.append({'action': 'refresh_from_project'}) # Ensure UI refresh after tracks are started
    self.ai_status = f"All {total_tracks} tracks accepted and execution started."
@@ -3326,16 +3332,24 @@ class AppController:
    self.tracks.append({"id": track_id, "title": title, "status": "todo"})
    with self._pending_gui_tasks_lock:
     self._pending_gui_tasks.append({'action': 'refresh_from_project'})
-    # 4. Initialize ConductorEngine and run loop
+   # 4. Initialize ConductorEngine and run loop
+   sys.stderr.write(f"[DEBUG] _start_track_logic: Initializing engine for {track_id}...\n")
+   sys.stderr.flush()
    engine = multi_agent_conductor.ConductorEngine(track, self.event_queue, auto_queue=not self.mma_step_mode)
    self.engines[track.id] = engine
    # Use current full markdown context for the track execution
    track_id_param = track.id
    flat = project_manager.flat_config(self.project, self.active_discussion, track_id=track_id_param)
    flat.setdefault("files", {})["paths"] = self.context_files
+   sys.stderr.write(f"[DEBUG] _start_track_logic: Aggregating context for {track_id}...\n")
+   sys.stderr.flush()
    full_md, _, _ = aggregate.run(flat)
+   sys.stderr.write(f"[DEBUG] _start_track_logic: Starting engine thread for {track_id}...\n")
+   sys.stderr.flush()
    # Start the engine in a separate thread
    threading.Thread(target=engine.run, kwargs={"md_content": full_md}, daemon=True).start()
+   sys.stderr.write(f"[DEBUG] _start_track_logic: Engine thread spawned for {track_id}.\n")
+   sys.stderr.flush()
   except Exception as e:
    self.ai_status = f"Track start error: {e}"
    print(f"ERROR in _start_track_logic: {e}")