refactor(examples) Update authentication example (#4589)

Co-authored-by: jafermarq <[email protected]>

examples/flower-authentication/README.md

@@ -10,7 +10,7 @@ framework: [torch, torchvision]
 > 🧪 = This example covers experimental features that might change in future versions of Flower.
 > Please consult the regular PyTorch examples ([quickstart](https://github.com/adap/flower/tree/main/examples/quickstart-pytorch), [advanced](https://github.com/adap/flower/tree/main/examples/advanced-pytorch)) to learn how to use Flower with PyTorch.
 
-The following steps describe how to start a long-running Flower server (SuperLink+SuperExec) and a long-running Flower clients (SuperNode) with authentication enabled. The task is to train a simple CNN for image classification using PyTorch.
+The following steps describe how to start a long-running Flower server (SuperLink) and a long-running Flower clients (SuperNode) with authentication enabled. The task is to train a simple CNN for image classification using PyTorch.
 
 ## Project Setup
 
@@ -65,13 +65,13 @@ The script also generates a CSV file that includes each of the generated (client
 ./generate.sh {your_number_of_clients}
 ```
 
-## Start the long-running Flower server-side (SuperLink+SuperExec)
+## Start the long-running Flower server (SuperLink)
 
-Starting long-running Flower server-side components (SuperLink+SuperExec) and enable authentication is very easy; all you need to do is type
+Starting long-running Flower server component (SuperLink) and enable authentication is very easy; all you need to do is type
 `--auth-list-public-keys` containing file path to the known `client_public_keys.csv`, `--auth-superlink-private-key`
 containing file path to the SuperLink's private key `server_credentials`, and `--auth-superlink-public-key` containing file path to the SuperLink's public key `server_credentials.pub`. Notice that you can only enable authentication with a secure TLS connection.
 
-Let's first launche the `SuperLink`:
+Let's first launch the `SuperLink`:
 
 ```bash
 flower-superlink \
@@ -83,20 +83,9 @@ flower-superlink \
     --auth-superlink-public-key keys/server_credentials.pub
 ```
 
-Then launch the `SuperExec`:
+At this point your server-side is idling. Next, let's connect two `SuperNode`s, and then we'll start a run.
 
-```bash
-flower-superexec \
-    --ssl-ca-certfile certificates/ca.crt \
-    --ssl-certfile certificates/server.pem \
-    --ssl-keyfile certificates/server.key \
-    --executor-config "root-certificates='certificates/ca.crt'" \
-    --executor flwr.superexec.deployment:executor
-```
-
-At this point your server-side is idling. First, let's connect two `SuperNodes`, and then we'll start a run.
-
-## Start the long-running Flower client-side (SuperNode)
+## Start the long-running Flower client (SuperNode)
 
 > \[!NOTE\]
 > Typically each `SuperNode` runs in a different entity/organization which has access to a dataset. In this example we are going to artificially create N dataset splits and saved them into a new directory called `datasets/`. Then, each `SuperNode` will be pointed to the dataset it should load via the `--node-config` argument. We provide a script that does the download, partition and saving of CIFAR-10.
@@ -110,21 +99,21 @@ In a new terminal window, start the first long-running Flower client (SuperNode)
 ```bash
 flower-supernode \
     --root-certificates certificates/ca.crt \
-    --superlink 127.0.0.1:9092 \
     --auth-supernode-private-key keys/client_credentials_1 \
     --auth-supernode-public-key keys/client_credentials_1.pub \
-    --node-config 'dataset-path="datasets/cifar10_part_1"'
+    --node-config 'dataset-path="datasets/cifar10_part_1"' \
+    --clientappio-api-address="0.0.0.0:9094"
 ```
 
 In yet another new terminal window, start the second long-running Flower client:
 
 ```bash
 flower-supernode \
     --root-certificates certificates/ca.crt \
-    --superlink 127.0.0.1:9092 \
     --auth-supernode-private-key keys/client_credentials_2 \
     --auth-supernode-public-key keys/client_credentials_2.pub \
-    --node-config 'dataset-path="datasets/cifar10_part_2"'
+    --node-config 'dataset-path="datasets/cifar10_part_2"' \
+    --clientappio-api-address="0.0.0.0:9095"
 ```
 
 If you generated more than 2 client credentials, you can add more clients by opening new terminal windows and running the command
@@ -142,7 +131,7 @@ above. Don't forget to specify the correct client private and public keys for ea
 
 ## Run the Flower App
 
-With both the long-running server-side (SuperLink+SuperExec) and two SuperNodes up and running, we can now start run. Note that the command below points to a federation named `my-federation`. Its entry point is defined in the `pyproject.toml`.
+With both the long-running server (SuperLink) and two SuperNodes up and running, we can now start the run. Note that the command below points to a federation named `my-federation`. Its entry point is defined in the `pyproject.toml`.
 
 ```bash
 flwr run . my-federation

examples/flower-authentication/pyproject.toml

@@ -8,10 +8,10 @@ version = "1.0.0"
 description = "Federated Learning with PyTorch and authenticated Flower "
 license = "Apache-2.0"
 dependencies = [
-    "flwr==1.12.0",
-    "flwr-datasets[vision]>=0.3.0",
-    "torch==2.2.1",
-    "torchvision==0.17.1",
+    "flwr>=1.13.1",
+    "flwr-datasets[vision]>=0.4.0",
+    "torch>=2.5.0,<3.0.0",
+    "torchvision>=0.20.1,<0.21.0",
 ]
 
 [tool.hatch.build.targets.wheel]
@@ -32,8 +32,8 @@ learning-rate = 0.1
 batch-size = 32
 
 [tool.flwr.federations]
-default = "superexec"
+default = "my-federation"
 
 [tool.flwr.federations.my-federation]
-address = "127.0.0.1:9093" # Address of the SuperExec
+address = "127.0.0.1:9093" # Address of the Exec API
 root-certificates = "certificates/ca.crt"