compute/docs/roadmap.md

Lumbridge Compute roadmap

Lumbridge Compute is the resident AI workload control plane for unified-memory machines.

Core contracts

1. Models — local vetted launch recipes with immutable revisions and measured footprints.
2. Scenes — named workload sets activated through admission control.
3. Evals — versioned datasets, prompts, harnesses, assertions, and portable results.
4. Artifacts — resumable weights, adapters, checkpoints, datasets, and result bundles.
5. Jobs — inference, evaluation, download, conversion, SFT, and RL lifecycles.

Near term

• Resumable, checksum-verified lumbridge-compute model pull with leases and progress state.
• Eval comparison, regression thresholds, warmup policy, concurrency/load tests, server-native Prometheus metrics, and hardware/config provenance.
• Scene hooks for preflight, post-activation eval gates, rollback, and schedules.
• Gateway aliases so clients follow the active scene without configuration changes.
• Training scenes and a Prime Intellect adapter for Qwen 0.6B/1.7B experiments.
• Checkpoint discovery, pause/resume, retention, and promotion into the model registry.

Open-source readiness

• Keep public scene/eval manifests command-free; commands remain in the trusted local registry.
• Add CI across x86_64 and aarch64, unit/integration tests, security policy, contribution guide, code of conduct, changelog, and versioned JSON schemas.
• Remove private hostnames, voices, paths, and finance datasets from public fixtures; ship generic examples and keep personal overlays outside the repository.