Implement AI Host functionality with model caching and job management

- Added ai_host.py to handle AI tasks with FastAPI integration.
- Introduced HostState and ModelCache classes for managing client connections and model loading.
- Implemented job submission and cancellation endpoints in the AI host.
- Enhanced tests for AI host functionality, including client tracking and job cancellation.
- Updated existing tests to accommodate changes in the operator and command structure.
- Refactored runtime commands to use request-based architecture instead of command-line arguments.
- Improved model loading logic to handle CUDA memory management and reuse models efficiently.

tests/test_worker.py

@@ -47,6 +47,20 @@ class WorkerTest(unittest.TestCase):
             source.index("import torch"),
         )
 
+    def test_ai_tasks_support_cooperative_cancellation(self):
+        with self.assertRaises(self.worker.TaskCancelled):
+            self.worker.check_cancelled(lambda: True)
+
+        self.worker.check_cancelled(lambda: False)
+        self.assertIn(
+            "cancel_check=cancel_check",
+            inspect.getsource(self.worker.reconstruct),
+        )
+        self.assertIn(
+            "cancel_check=cancel_check",
+            inspect.getsource(self.worker.remove_background),
+        )
+
     def test_optional_background_removal_runs_before_da3_model_load(self):
         source = inspect.getsource(self.worker.reconstruct)