doc: fix async reducer README examples

examples/reduce/README.md

@@ -7,11 +7,13 @@ For creating a reducer UDF we can use two different approaches:
   kwargs that the custom reducer class requires.
   - Finally we need to call the `start` method on the `ReduceAsyncServer` instance to start the reducer server.
   ```python
-    from numaflow import Reducer, ReduceAsyncServer
-    class Example(Reducer):
+  from collections.abc import AsyncIterable
+  from pynumaflow.reducer import Reducer, ReduceAsyncServer, Datum, Message, Messages, Metadata
+
+  class Example(Reducer):
       def __init__(self, counter):
           self.counter = counter
-    
+
       async def handler(
           self, keys: list[str], datums: AsyncIterable[Datum], md: Metadata
       ) -> Messages:
@@ -25,13 +27,13 @@ For creating a reducer UDF we can use two different approaches:
           )
           return Messages(Message(str.encode(msg), keys=keys))
 
-    if __name__ == "__main__":
-    # Here we are using the class instance as the reducer_instance
-    # which will be used to invoke the handler function.
-    # We are passing the init_args for the class instance.
-    grpc_server = ReduceAsyncServer(Example, init_args=(0,))
-    grpc_server.start()
-  ``` 
+  if __name__ == "__main__":
+      # Here we are using the class instance as the reducer_instance
+      # which will be used to invoke the handler function.
+      # We are passing the init_args for the class instance.
+      grpc_server = ReduceAsyncServer(Example, init_args=(0,))
+      grpc_server.start()
+  ```
 
 - Function based reducer
     For the function based reducer we need to create a function of the signature
@@ -43,23 +45,23 @@ For creating a reducer UDF we can use two different approaches:
     - Finally we need to call the `start` method on the `ReduceAsyncServer` instance to start the reducer server.
     - We must ensure that no init_args or init_kwargs are passed to the `ReduceAsyncServer` instance as they are not used for function based reducers.
     ```python
-        from numaflow import ReduceAsyncServer
-        async def handler(keys: list[str], datums: AsyncIterable[Datum], md: Metadata) -> Messages:
-            counter = 0
-            interval_window = md.interval_window
-            async for _ in datums:
-                counter += 1
-            msg = (
-                f"counter:{counter} interval_window_start:{interval_window.start} "
-                f"interval_window_end:{interval_window.end}"
-            )
-            return Messages(Message(str.encode(msg), keys=keys))
-
-        if __name__ == "__main__":
+    from collections.abc import AsyncIterable
+    from pynumaflow.reducer import ReduceAsyncServer, Datum, Message, Messages, Metadata
+
+    async def handler(keys: list[str], datums: AsyncIterable[Datum], md: Metadata) -> Messages:
+        counter = 0
+        interval_window = md.interval_window
+        async for _ in datums:
+            counter += 1
+        msg = (
+            f"counter:{counter} interval_window_start:{interval_window.start} "
+            f"interval_window_end:{interval_window.end}"
+        )
+        return Messages(Message(str.encode(msg), keys=keys))
+
+    if __name__ == "__main__":
         # Here we are using the function as the reducer_instance
         # which will be used to invoke the handler function.
         grpc_server = ReduceAsyncServer(handler)
         grpc_server.start()
     ```
-
-