chore: import upstream snapshot with attribution

python/ray/serve/__init__.py

@@ -0,0 +1,72 @@
+import ray._private.worker
+
+try:
+    from ray.serve._private.logging_utils import configure_default_serve_logger
+    from ray.serve.api import (
+        Application,
+        Deployment,
+        RunTarget,
+        _run,
+        _run_many,
+        delete,
+        deployment,
+        get_app_handle,
+        get_deployment_actor,
+        get_deployment_actor_context,
+        get_deployment_handle,
+        get_multiplexed_model_id,
+        get_replica_context,
+        ingress,
+        multiplexed,
+        run,
+        run_many,
+        shutdown,
+        shutdown_async,
+        start,
+        status,
+    )
+    from ray.serve.batching import batch
+    from ray.serve.config import ControllerOptions, HTTPOptions
+    from ray.serve.utils import get_trace_context
+
+except ModuleNotFoundError as e:
+    e.msg += (
+        '. You can run `pip install "ray[serve]"` to install all Ray Serve'
+        " dependencies."
+    )
+    raise e
+
+# Setup default ray.serve logger to ensure all serve module logs are captured.
+configure_default_serve_logger()
+
+# Mute the warning because Serve sometimes intentionally calls
+# ray.get inside async actors.
+ray._private.worker.blocking_get_inside_async_warned = True
+
+__all__ = [
+    "_run",
+    "_run_many",
+    "batch",
+    "start",
+    "ControllerOptions",
+    "HTTPOptions",
+    "get_replica_context",
+    "get_deployment_actor",
+    "get_deployment_actor_context",
+    "get_trace_context",
+    "shutdown",
+    "shutdown_async",
+    "ingress",
+    "deployment",
+    "run",
+    "run_many",
+    "RunTarget",
+    "delete",
+    "Application",
+    "Deployment",
+    "multiplexed",
+    "get_multiplexed_model_id",
+    "status",
+    "get_app_handle",
+    "get_deployment_handle",
+]