SwarmFL

Small Flower demo for authorized specialist consultation. Synthetic only; not a benchmark or clinical model.

Quickstart

pip install swarmfl==0.1.0
swarmfl-quickstart --output demo --feedback
python -c "import json; print(json.load(open('demo/result.json')))"

The command starts three local Flower nodes, registers their declarations, performs a selected one-peer consultation on a new case, and writes the fused probability and audit artifacts under demo/. The synthetic specialists use the ordered input views (x0,x1), (x2,x3), and (x4,x5).

The demo keeps specialist views separate, makes one selected peer request, and fuses the observed predictions.

python demo.py --feedback

If needed, install the package first:

pip install swarmfl==0.1.0

The public Hub release contains no research datasets, frozen tests, private checkpoints, or experiment outputs. See the repository for source and research context.