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The AML Dashboard is a web-based tool that allows users, developers, and researchers to interact with the AML framework.

This tutorial showcases the fetching process of an AML model using the AML Dashboard.

Prerequisites

Ensure you have installed the AML Dashboard using one of the following methods:

• Linux Installation
• Docker Image Installation

For more information, check the AML Dashboard Interfaces and AML Dashboard Usage sections.

Running the demo

To run the necessary components for fetching a model using the AML Dashboard, follow these steps:

Start the backend server

1. Navigate to the backend directory.

cd backend

2. Load the AML-IP environment.

source /AML-IP/install/setup.bash

3. Start the server:

python3 server.py

Start the Model Manager Sender Node

1. Load the AML-IP environment.

source /AML-IP/install/setup.bash

2. Navigate to the backend directory

cd backend

3. Start the Model Manager Sender Node:

python3 sender.py

To stop the Model Manager Sender Node, press Ctrl + C.

Start the AML Dashboard

1. Navigate to the frontend/aml_dashboard directory.

cd frontend/aml_dashboard

2. Start the AML Dashboard:

 npm run dev

3. Access the dashboard at http://localhost:5173/.

Fetching the Model

To fetch a model using the AML Dashboard, follow these steps:

1. Click on the Fetching tab.
2. Click on the Search for statistics button in the AML Statistics Fetcher.
3. Once the statistics are received, the status will appear as Statistics received ! in the AML Collaborative Learning Status.
4. Click on the Request model button in the AML Model Fetcher.
5. Once the model is received, the status will change to Model received ! in the AML Collaborative Learning Status.

Note

Make sure that at least one Model Manager Sender Node is running to facilitate the model fetching process.

Next Steps

In the following tutorial we will guide you through the process of making predictions using AML-Dashboard. Stay tuned!

By Denisa Alexandru from eProsima

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