[Serve] Support basic Starlette response types (#12811)

doc/source/serve/index.rst

@@ -37,7 +37,7 @@ Since Serve is built on Ray, it also allows you to scale to many machines, in yo
 Installation
 ============
 
-Ray Serve supports Python versions 3.6 and higher. To install Ray Serve:
+Ray Serve supports Python versions 3.6 through 3.8. To install Ray Serve:
 
 .. code-block:: bash
 

doc/source/serve/key-concepts.rst

@@ -19,7 +19,11 @@ Backends
 Backends define the implementation of your business logic or models that will handle requests when queries come in to :ref:`serve-endpoint`.
 In order to support seamless scalability backends can have many replicas, which are individual processes running in the Ray cluster to handle requests.
 To define a backend, first you must define the "handler" or the business logic you'd like to respond with.
-The handler should take as input a `Flask Request object <https://flask.palletsprojects.com/en/1.1.x/api/?highlight=request#flask.Request>`_ and return any JSON-serializable object as output.
+The handler should take as input a `Flask Request object <https://flask.palletsprojects.com/en/1.1.x/api/?highlight=request#flask.Request>`_. 
+The handler should return any JSON-serializable object as output.  For a more customizable response type, the handler may return a 
+`Starlette Response object <https://www.starlette.io/responses/>`_.  
+In the future, Ray Serve will support `Starlette Request objects <https://www.starlette.io/requests/>`_ as input as well.
+
 A backend is defined using :mod:`client.create_backend <ray.serve.api.Client.create_backend>`, and the implementation can be defined as either a function or a class.
 Use a function when your response is stateless and a class when you might need to maintain some state (like a model).
 When using a class, you can specify arguments to be passed to the constructor in :mod:`client.create_backend <ray.serve.api.Client.create_backend>`, shown below.