Karti Tripathi
30 lines
1.6 KiB
Markdown
30 lines
1.6 KiB
Markdown
# Lumbridge Compute roadmap
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Lumbridge Compute is the resident AI workload control plane for unified-memory machines.
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## Core contracts
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1. **Models** — local vetted launch recipes with immutable revisions and measured footprints.
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2. **Scenes** — named workload sets activated through admission control.
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3. **Evals** — versioned datasets, prompts, harnesses, assertions, and portable results.
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4. **Artifacts** — resumable weights, adapters, checkpoints, datasets, and result bundles.
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5. **Jobs** — inference, evaluation, download, conversion, SFT, and RL lifecycles.
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## Near term
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- Resumable, checksum-verified `lumbridge-compute model pull` with leases and progress state.
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- Eval comparison, regression thresholds, warmup policy, concurrency/load tests,
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server-native Prometheus metrics, and hardware/config provenance.
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- Scene hooks for preflight, post-activation eval gates, rollback, and schedules.
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- Gateway aliases so clients follow the active scene without configuration changes.
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- Training scenes and a Prime Intellect adapter for Qwen 0.6B/1.7B experiments.
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- Checkpoint discovery, pause/resume, retention, and promotion into the model registry.
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## Open-source readiness
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- Keep public scene/eval manifests command-free; commands remain in the trusted local registry.
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- Add CI across x86_64 and aarch64, unit/integration tests, security policy,
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contribution guide, code of conduct, changelog, and versioned JSON schemas.
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- Remove private hostnames, voices, paths, and finance datasets from public fixtures;
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ship generic examples and keep personal overlays outside the repository.
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