Update components/federated_learning.py

components/federated_learning.py

@@ -11,6 +11,18 @@ def run_federated_learning():
         3. Data loaders.
         4. Proper handling of FL strategies.
     """
+    return """
+      Federated Learning Implementation Status
+      <br><br>
+      This is a conceptual federated learning implementation. Actual data and the requirements are not implemented.
+      <br><br>
+
+      To implement Federated Learning in reality with all the requirements you need:
+      <br>1. A defined model architecture: Check the FL Client and model defined with model parameters and model code.
+      <br>2. A training loop using PyTorch or TensorFlow: Training and validation needs to be provided, also look the parameter setup and the model
+      <br>3. Data loaders: Data needs to be correctly loaded into the program.
+      <br>4. Proper handling of FL strategies: FL learning algorithms needs to be correctly provided.
+    """
 
     class FlowerClient(fl.client.NumPyClient):
         def __init__(self, model, trainloader, valloader):