This plugin packages a Flower SuperNode inside a ChRIS-friendly container. Run the commands below from inside plugins/supernode_plugin/. The actual training loop only knows how to fit a local logistic regression model; Flower merely orchestrates the parameter exchange.
docker build -t fedmed/pl-supernode .docker run --rm --name fedmed-supernode --network fedmed-net \
-v $(pwd)/demo/client-in:/incoming:ro \
-v $(pwd)/demo/client-out:/outgoing:rw \
fedmed/pl-supernode \
fedmed-pl-supernode \
--cid 0 \
--total-clients 3 \
--superlink-host ${FEDMED_SUPERLINK_IP} \
--data-seed 13 \
/incoming /outgoingMake sure ${FEDMED_SUPERLINK_IP} is populated via docker inspect fedmed-superlink (see the SuperLink README). After the Flower round completes, the plugin writes client_metrics.json into /outgoing so downstream ChRIS components (or you) can inspect the results.
--cid(default: 0)--total-clients(default: 3)--superlink-host(default:fedmed-pl-superlink)--data-seed(default: 13)
All other options (SuperLink port 9092, ClientApp host 0.0.0.0/port 9094, metrics filename, transport, FLWR state path) are now fixed to defaults and no longer exposed as CLI flags.