TL-System

license

Apache-2.0(OSI

source

public(the whole framework)

core features withheld

no — a university research framework with no paid edition

Plato is an Apache-2.0 research framework with no paid tier or held-back component.

• https://raw.githubusercontent.com/TL-System/plato/HEAD/LICENSE recorded 2026-09-27

  The LICENSE body: the verbatim Apache License, Version 2.0 text with no added clause.

• https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TL-System%2Fplato recorded 2026-09-27

  Repository record for TL-System/plato: license apache-2.0, description "Plato: A Research Framework for Federated Learning", not archived, not a fork, pushed 2026-06-08, 399 stars.

• https://ungh.cc/repos/TL-System/plato/files/main recorded 2026-09-27

  The 883-file tree of TL-System/plato at `main`: one root LICENSE, and no ee/, enterprise/, commercial/, proprietary/ or premium/ path anywhere in it. Path absence only, paired with the statement cited beside it.

PyPI downloads of `plato-learn`, the framework's package.

• https://pypistats.org/api/packages/plato-learn/recent recorded 2026-09-27

  last_month = 84 downloads for the package `plato-learn`.

Plato can run a real federation, with a server behind HTTPS that remote clients reach over the network. Its deployment guide secures the server alone and has no way to identify the parties, which keeps it one step below Flower.

• https://platodocs.netlify.app/deployment/ recorded 2026-09-27

  Deployment: "The Plato federated learning server is designed to use Socket.IO over HTTP and HTTPS, and can be easily deployed in a production server environment in the public cloud"; the guide configures the server's certificate behind nginx and Cloudflare, with no client identity step.

• https://platodocs.netlify.app/examples/algorithms/2.%20Secure%20Aggregation%20with%20Homomorphic%20Encryption/ recorded 2026-09-27

  "MaskCrypt is a secure federated learning system based on homomorphic encryption" that encrypts only a subset of the model updates.

• https://platodocs.netlify.app/examples/case-studies/1.%20LoRA/ recorded 2026-09-27

  "Plato now provides first-class support for parameter-efficient LoRA fine-tuning of HuggingFace causal language models."