GraphCanon updated Oct 3, 2026 · GitHub synced Oct 3, 2026
43views this month
Decision brief
Harmonia supports federated learning with differential privacy modules and GitOps-inspired architecture, designed for both research and production usage.
Good fit when
- When needing frameworks that incorporate differential privacy directly into federated learning processes
- For environments preferring a container-based plug-in architecture to integrate existing ML workflows
Avoid when
- If GitOps-inspired workflows are not aligned with your team's operational practices
- In scenarios where the use of Go is less preferred among development teams
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (2202d since push)
- As of Oct 3, 2026
- Provenance
- Not a fork · Organization account
- As of Oct 3, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
go get github.com/ailabstw/harmoniaSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Harmonia is an open-source project that includes systems/infrastructures and libraries to facilitate the adoption of federated learning for researches and production usage. It supports differential privacy modules and GitOps-inspired architecture.
Capability facts
- Languages
- go
Source: github.language · Oct 3, 2026
Categories
Tags
README
Harmonia Harmonia is an open source project aiming at developing systems/infrastructures and libraries to ease the adoption of federated learning (abbreviated to FL) for researches and production usage. It is named Harmonia, the Greek goddess of harmony, to reflect the spirit of...
For agents
This page has a .md twin and JSON over the API.