chore: import upstream snapshot with attribution

doc/source/serve/doc_code/quickstart_composed.py

@@ -0,0 +1,51 @@
+import requests
+import starlette
+from typing import Dict
+from ray import serve
+from ray.serve.handle import DeploymentHandle
+
+
+# 1. Define the models in our composition graph and an ingress that calls them.
+@serve.deployment
+class Adder:
+    def __init__(self, increment: int):
+        self.increment = increment
+
+    def add(self, inp: int):
+        return self.increment + inp
+
+
+@serve.deployment
+class Combiner:
+    def average(self, *inputs) -> float:
+        return sum(inputs) / len(inputs)
+
+
+@serve.deployment
+class Ingress:
+    def __init__(
+        self,
+        adder1: DeploymentHandle,
+        adder2: DeploymentHandle,
+        combiner: DeploymentHandle,
+    ):
+        self._adder1 = adder1
+        self._adder2 = adder2
+        self._combiner = combiner
+
+    async def __call__(self, request: starlette.requests.Request) -> Dict[str, float]:
+        input_json = await request.json()
+        final_result = await self._combiner.average.remote(
+            self._adder1.add.remote(input_json["val"]),
+            self._adder2.add.remote(input_json["val"]),
+        )
+        return {"result": final_result}
+
+
+# 2. Build the application consisting of the models and ingress.
+app = Ingress.bind(Adder.bind(increment=1), Adder.bind(increment=2), Combiner.bind())
+serve.run(app)
+
+# 3: Query the application and print the result.
+print(requests.post("http://localhost:8000/", json={"val": 100.0}).json())
+# {"result": 101.5}