Add priority queue to ai-service and STATUS.md workflow

- Introduce async priority queue service in ai-service; all /chat calls now route through it
- Refactor chat router to separate execute_chat (core logic) from the HTTP handler
- Add /queue endpoints (status, pause, resume, cancel) for queue management
- Update ai-service config to use Pydantic v2 model_config style
- Add STATUS.md files for backend, ai-service, doc-service, and frontend
- Document STATUS.md workflow in CLAUDE.md
- Update doc-service documents router and schemas; frontend DocumentsPage and API client

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

features/ai-service/app/main.py

@@ -5,7 +5,9 @@ from fastapi import FastAPI
 
 from app.core.config import settings
 from app.routers import chat, health
+from app.routers import queue as queue_router
 from app.services.config_reader import load_ai_config
+from app.services.queue import queue_service
 
 logger = logging.getLogger("ai-service")
 
@@ -16,10 +18,18 @@ async def lifespan(app: FastAPI):
     provider = config.get("provider", "lmstudio")
     model = config.get(provider, {}).get("model", "unknown")
     logger.info("[ai-service] active provider: %s  model: %s", provider, model)
+
+    queue_service.start()
+    logger.info("[ai-service] queue worker started")
+
     yield
 
+    queue_service.stop()
+    logger.info("[ai-service] queue worker stopped")
+
 
 app = FastAPI(title=settings.PROJECT_NAME, lifespan=lifespan)
 
 app.include_router(chat.router, tags=["chat"])
 app.include_router(health.router, tags=["health"])
+app.include_router(queue_router.router)