Initial public ModelForge release
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# Capability Deployments
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## M9 shared-GPU admission
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OCR, visual embedding and ASR deployments use the existing lease/residency scheduler. Manifest resource classes explain expected pressure, but an exact measured `CapabilityResourceEnvelope`, external GPU observation and fixed reserve determine admission. Heavy work fails with `INSUFFICIENT_SCHEDULABLE_VRAM`; ModelForge never evicts unmanaged Ollama, Tdarr or Plex workloads.
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A CapabilityDeployment is the immutable production binding between CapabilityContract,
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DeploymentCandidate, production approval, exact ArtifactSet, RuntimeProfile, ComputeNode,
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accelerator, EmbeddingSpace and measured ResourceEnvelope. Lifecycle states are stable, draining,
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deprecated and archived; LAB_READY remains a separate non-production candidate state.
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Promotion rejects missing or stale runtime evidence, non-verified artifacts, non-production nodes,
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incomplete supply-chain review and mismatched deployment facts. The active M5 deployment is
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`420f11de-4906-4751-bfd4-923849fc7d9d`, pinned to candidate
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`c6824408-84d1-45bf-b431-a3893e57fd52` and worker image
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`sha256:e707953d1cc6fe3e66e4571ea1381f37e5a88bc71a31dac896b98bccf56dbac0`.
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## M12 lifecycle overlay
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Lifecycle subjects reference deployments rather than replacing them. A partial unique database
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index prevents two `production=true, status=stable` rows for one capability contract. Promotion
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execution additionally uses subject-version compare-and-swap and idempotency keys. Platform-stable
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does not grant a project production binding; that change requires its own project policy and fit
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evidence.
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