From ea7a2d7849fd69541cab8243e527d19614603c2d Mon Sep 17 00:00:00 2001
From: Viktor Valadi <42983197+viktorvaladi@users.noreply.github.com>
Date: Thu, 18 Apr 2024 15:15:02 +0200
Subject: [PATCH] Docs/SK-796 | Update flower readme (#582)

---
 examples/flower-client/README.rst           | 51 ++++++++++++++-------
 examples/flower-client/client/entrypoint.py |  2 +-
 2 files changed, 35 insertions(+), 18 deletions(-)

diff --git a/examples/flower-client/README.rst b/examples/flower-client/README.rst
index 2093caf3f..dfe0bca8f 100644
--- a/examples/flower-client/README.rst
+++ b/examples/flower-client/README.rst
@@ -1,12 +1,12 @@
-Using Flower ClientApps in FEDn
--------------------------------
+FEDn Project: Flower ClientApps in FEDn
+---------------------------------------
 
 This example demonstrates how to run a Flower 'ClientApp' on FEDn.
 
 The FEDn compute package 'client/entrypoint' 
 uses a built-in Flower compatibiltiy adapter for convenient wrapping of the Flower client.
 See `flwr_client.py` and `flwr_task.py` for the Flower client code (which is adapted from 
-https://github.com/adap/flower/tree/main/examples/app-pytorch). 
+https://github.com/adap/flower/tree/main/examples/app-pytorch).
 
 
 Running the example
@@ -42,19 +42,19 @@ Next, generate a seed model (the first model in the global model trail):
 
    fedn run build --path client
 
-Next, you will upload the compute package and seed model to
+This creates a seed.npz in the root of the project folder. Next, you will upload the compute package and seed model to
 a FEDn network. Here you have two main options: using FEDn Studio 
-(recommended for new users), or a pseudo-local deployment
+(recommended for new users), or a self-managed pseudo-distributed deployment
 on your own machine. 
 
 If you are using FEDn Studio (recommended):
------------------------------------------------------
+-------------------------------------------
 
 Follow instructions here to register for Studio and start a project: https://fedn.readthedocs.io/en/stable/studio.html.
 
 In your Studio project: 
 
-- From the "Sessions" menu, upload the compute package and seed model. 
+- From the "Sessions" menu, upload the compute package (package.tgz) and seed model (seed.npz). 
 - Register a client and obtain the corresponding 'client.yaml'.  
 
 On your local machine / client, start the FEDn client: 
@@ -62,9 +62,7 @@ On your local machine / client, start the FEDn client:
 
 .. code-block::
 
-   export FEDN_AUTH_SCHEME=Bearer
-   export FEDN_PACKAGE_EXTRACT_DIR=package
-   CLIENT_NUMBER=0 fedn run client -in client.yaml --secure=True --force-ssl
+   fedn run client -in client.yaml --secure=True --force-ssl
 
 
 Or, if you prefer to use Docker (this might take a long time):
@@ -74,15 +72,14 @@ Or, if you prefer to use Docker (this might take a long time):
    docker run \
    -v $PWD/client.yaml:/app/client.yaml \
    -e CLIENT_NUMBER=0 \
-   -e FEDN_AUTH_SCHEME=Bearer \
    -e FEDN_PACKAGE_EXTRACT_DIR=package \
-   ghcr.io/scaleoutsystems/fedn/fedn:master run client -in client.yaml --secure=True --force-ssl
+   ghcr.io/scaleoutsystems/fedn/fedn:0.9.0 run client -in client.yaml --secure=True --force-ssl
 
 
-If you are running FEDn in pseudo-local mode:
-------------------------------------------------------------------
+If you are running FEDn in local development mode:
+--------------------------------------------------
 
-Deploy a FEDn network on local host (see `https://fedn.readthedocs.io/en/stable/quickstart.html`). 
+Deploy a FEDn network on local host (see `https://fedn.readthedocs.io/en/stable/quickstart.html#local-development-deployment-using-docker-compose`). 
 
 Use the FEDn API Client to initalize FEDn with the compute package and seed model: 
 
@@ -107,6 +104,26 @@ Then start the client (using Docker)
    -v $PWD/client.yaml:/app/client.yaml \
    --network=fedn_default \
    -e CLIENT_NUMBER=0 \
-   -e FEDN_AUTH_SCHEME=Bearer \
    -e FEDN_PACKAGE_EXTRACT_DIR=package \
-   ghcr.io/scaleoutsystems/fedn/fedn:master run client -in client.yaml
+   ghcr.io/scaleoutsystems/fedn/fedn:0.9.0 run client -in client.yaml
+
+
+Scaling to multiple clients
+------------------------------------------------------------------
+
+To scale the experiment with additional clients on the same host, execute the run command
+again from another terminal. If running from another host, add another 'client.yaml', install 
+fedn, and execute the run command. In both cases inject a client number as an environment 
+varible which is used for distributing data (see 'flwr_task.py').
+
+For Unix Operating Systems:
+
+.. code-block::
+
+   CLIENT_NUMBER=0 fedn run client -in client.yaml --secure=True --force-ssl
+
+Using Windows PowerShell:
+
+.. code-block::
+
+   & { $env:CLIENT_NUMBER="0"; fedn run client -in client.yaml --secure=$true --force-ssl }
diff --git a/examples/flower-client/client/entrypoint.py b/examples/flower-client/client/entrypoint.py
index 24f20773e..e80e7d4b5 100755
--- a/examples/flower-client/client/entrypoint.py
+++ b/examples/flower-client/client/entrypoint.py
@@ -30,7 +30,7 @@ def save_parameters(out_path, parameters_np):
     helper.save(parameters_np, out_path)
 
 
-def init_seed(out_path="seed.npz"):
+def init_seed(out_path="../seed.npz"):
     """Initialize seed model and save it to file.
 
     :param out_path: The path to save the seed model to.