chore: import upstream snapshot with attribution

doc/source/serve/doc_code/quickstart.py

@@ -0,0 +1,26 @@
+import requests
+from starlette.requests import Request
+from typing import Dict
+
+from ray import serve
+
+
+# 1: Define a Ray Serve application.
+@serve.deployment
+class MyModelDeployment:
+    def __init__(self, msg: str):
+        # Initialize model state: could be very large neural net weights.
+        self._msg = msg
+
+    def __call__(self, request: Request) -> Dict:
+        return {"result": self._msg}
+
+
+app = MyModelDeployment.bind(msg="Hello world!")
+
+# 2: Deploy the application locally.
+serve.run(app, route_prefix="/")
+
+# 3: Query the application and print the result.
+print(requests.get("http://localhost:8000/").json())
+# {'result': 'Hello world!'}