- Aggregator must decide and share the model architecture with the clients.
- Aggregator will also provide a seed model weights which will be fine-tuned by each participant.

**3. Setup the FL config**

Create a `fl_config.json` configuration file including the following information:

- `"project_name"`: name assigned to the FL experiment.
- `"aggregator"`: designated aggregator datasite.
- `"participants"`: list of the designated client datasites.
- `"rounds"`: number of FL training rounds.
- `"model_arch"`: the Python module containing the ML model implementation.
- `"model_weight"`: model parameters file
- `"epoch"`: number of training epochs to run on each clients,
- `"learning_rate"`: learning rate of the optimizer.

Please see `samples/launch_config/fl_config.json` for an example configuration file:

```json
{
"project_name": "MNIST_FL",
"aggregator": "a@openmined.org",
"participants": ["b@openmined.org","c@openmined.org"],
"rounds": 3,
"model_arch": "model.py",
"model_weight": "global_model_weight.pt",
"epoch": 10,
"learning_rate": 0.1
}
```

**4. Start the FL experiment**

1. To start the FL experiment, the following files needs to be copied in
`/datasites//api_data/fl_aggregator/launch` directory:

- `fl_config.json`
- `global_model_weight.pt`
- `model.py`

2. Copy the test dataset to `/datasites//private/fl_aggregator`

An example test dataset could be found in `./samples/test_data`.

If this directory isn't available, either run the syftbox client with fl_aggregator API installed OR create it manually.

Once the files are in the `launch` folder, the API will create a folder named after the `project_name` specified in the `file_config.json` in the `running` folder.

Inside this folder the API will create a folder for each client datasite, where received updates in each round are gathered.
Each of these folders will have a `._syftperm` file containing the appropriate permissions granting read/write access to the folder.

Finally, the API send a request to each participant to join the FL flow.

Please see below an example of the resulting folders structure during the FL execution.

```plaintext
api_data
└── fl_aggregator
├── launch
│ ├── config.json
│ ├── model_arch.py
│ ├── global_model_weights.py
└── running
└── my_cool_fl_proj
├── fl_clients
│ ├── a@openmined.org
│ ├── b@openmined.org
│ ├── c@openmined.org
├── agg_weights # to store aggregator's weights for each round
├── config.json # moved from the launch folder after the app start
├── global_model_weights.pt
├── model_arch.py # moved from the launch folder
└── state.json
└── done
└── my_cool_fl_proj
└── aggregated_model_weights.pt
```

**5. Monitoring the FL experiment**

- Visit the aggregator's dashboard to monitor the FL progress
which is available at `http://server_url/datasites//fl//`, with `` matches the name of the FL experiment setup in the `fl_config.json` file.

The server_url depends on which the server the client is running on.
- `syftbox.openmined.org` (for the public server)
- `localhost:5001` (when running locally, with default configuration)

## Running in dev mode

> ⚠️ Make sure you have the latest version of the SyftBox repository cloned on your local machine:
>
> ```bash
> git clone https://github.com/OpenMined/syft.git
> ```
> Also, make sure you have [just](https://github.com/casey/just) installed.

**Note**: The following commands need to be run within the `syft` directory (the repository root), unless otherwise indicated.

### **Set up**:

First launch a local SyftBox server, and clients for all datasites participating in the FL flow:

- `just rs`: run SyftBox local dev server on port `5001`
- `just rc a`: creates a SyftBox client for `a@openmined.org`. (Repeat this for all the clients)

Each of those commands need to be run in a separate terminal session, or within the same terminal
using tools like [`tmux`](https://github.com/tmux/tmux/wiki) (recommended!).

### **Install the aggregator and the client APIs**:

Aggregator:
- `git clone https://github.com/OpenMined/fl_aggregator`
- `cp -R ./fl_aggregator ./.clients/a@openmined.org/apis`

Client(s):