292 lines
11 KiB
Python
292 lines
11 KiB
Python
"""M0 domain foundation.
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Revision ID: 20260824_0001
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Revises: None
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"""
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import sqlalchemy as sa
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from alembic import op
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from modelforge_api.persistence.models import Base
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revision = "20260824_0001"
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down_revision = None
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branch_labels = None
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depends_on = None
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def upgrade() -> None:
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# The declarative metadata is the reviewed M0 schema contract. create_all is
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# used only from this baseline migration; later changes require explicit ops.
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Base.metadata.create_all(bind=op.get_bind(), checkfirst=False)
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# BenchmarkRun was part of M0. The evolving metadata also contains RC-LAB-02's later
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# capability-target, actor/idempotency and environment fields, so rebuild its original
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# shape here; migration 0039 adds those fields at the correct historical boundary.
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op.drop_table("benchmark_runs")
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op.create_table(
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"benchmark_runs",
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sa.Column("id", sa.Uuid(), nullable=False),
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sa.Column("deployment_id", sa.Uuid(), nullable=False),
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sa.Column("suite_id", sa.Uuid(), nullable=False),
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sa.Column("model_revision_sha", sa.String(length=64), nullable=False),
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sa.Column("artifact_sha256", sa.String(length=64), nullable=False),
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sa.Column("runtime_type", sa.String(length=32), nullable=False),
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sa.Column("runtime_version", sa.String(length=128), nullable=False),
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sa.Column("runtime_image_digest", sa.String(length=71), nullable=True),
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sa.Column("launch_arguments", sa.JSON(), nullable=False),
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sa.Column("suite_revision", sa.String(length=128), nullable=False),
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sa.Column("dataset_revision", sa.String(length=255), nullable=False),
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sa.Column("environment_fingerprint", sa.JSON(), nullable=False),
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sa.Column("environment_digest", sa.String(length=64), nullable=False),
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sa.Column("seed", sa.Integer(), nullable=True),
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sa.Column("results", sa.JSON(), nullable=False),
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sa.Column("status", sa.String(length=32), nullable=False),
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sa.Column("comparable", sa.Boolean(), nullable=False),
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sa.Column("stale_reason", sa.Text(), nullable=True),
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sa.Column("started_at", sa.DateTime(timezone=True), nullable=False),
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sa.Column("completed_at", sa.DateTime(timezone=True), nullable=True),
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sa.ForeignKeyConstraint(["deployment_id"], ["deployments.id"], ondelete="RESTRICT"),
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sa.ForeignKeyConstraint(["suite_id"], ["benchmark_suites.id"], ondelete="RESTRICT"),
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sa.PrimaryKeyConstraint("id"),
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)
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op.create_index("ix_benchmark_runs_deployment_id", "benchmark_runs", ["deployment_id"])
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op.create_index("ix_benchmark_runs_suite_id", "benchmark_runs", ["suite_id"])
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op.create_index("ix_benchmark_runs_artifact_sha256", "benchmark_runs", ["artifact_sha256"])
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op.create_index(
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"ix_benchmark_runs_environment_digest", "benchmark_runs", ["environment_digest"]
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)
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op.create_index(
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"ix_benchmark_runs_deployment_completed",
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"benchmark_runs",
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["deployment_id", "completed_at"],
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)
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op.drop_constraint("ck_capability_serving_generation", "capability_contracts", type_="check")
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op.drop_column("capability_contracts", "serving_generation")
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# Freeze the original M0 shape even though the declarative metadata evolves.
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# Remove newer foreign-key columns before dropping the tables they target.
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for column in (
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"profile_config",
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"health_contract",
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"device_policy",
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"modality",
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"dtype",
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"version",
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"artifact_set_id",
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"runtime_environment_id",
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):
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op.drop_column("runtime_profiles", column)
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for table in (
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# Later milestone tables are present in the evolving declarative metadata
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# used to build this baseline. Drop dependants before their M5/M0 targets
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# so a fresh upgrade still reconstructs each historical revision exactly.
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"model_change_cases",
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"selected_model_comparisons",
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"external_creative_action_attestations",
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"external_creative_profile_observations",
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"external_creative_resources",
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"external_creative_allocations",
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"model_update_notices",
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"model_update_watches",
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"portfolio_repository_observations",
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"portfolio_reconciliation_runs",
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"platform_secret_activations",
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"platform_secret_tests",
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"platform_secret_versions",
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"platform_secret_state",
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"managed_operator_credential_activations",
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"managed_operator_credentials",
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"managed_operator_identities",
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"managed_operator_state",
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"configuration_revisions",
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"project_onboarding",
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"configuration_state",
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"audit_chain_heads",
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"node_decommission_operations",
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# M15 recovery tables come first: artifact_recovery_operations references
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# artifact_jobs, download_plans, artifact_sets, model_revisions and storage_roots,
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# all of which are dropped further down this list.
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"artifact_recovery_operations",
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"restore_operation_events",
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"restore_operations",
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"restore_plans",
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"backup_manifest_entries",
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"backup_sets",
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"recovery_asset_records",
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"recovery_policy_revisions",
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"incident_timeline_events",
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# The M37 outbox restricts deletion of its alert history parent.
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"alert_notification_deliveries",
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"alert_history_events",
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"operational_alerts",
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"operational_incidents",
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"maintenance_windows",
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"alert_rule_revisions",
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"slo_evaluations",
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"slo_policy_revisions",
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"service_level_indicators",
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"capacity_aggregates",
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"capacity_snapshots",
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"migration_events",
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"migration_cutover_operations",
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"migration_rollback_snapshots",
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"migration_shadow_sessions",
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"migration_validation_snapshots",
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"migration_batch_checkpoints",
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"migration_plans",
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"migration_validation_policy_revisions",
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"artifact_location_removal_records",
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"lifecycle_canary_runs",
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"lifecycle_operations",
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"lifecycle_rollback_snapshots",
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"lifecycle_promotion_plans",
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"lifecycle_approval_evidence",
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"lifecycle_approval_requests",
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"lifecycle_cleanup_plans",
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"lifecycle_retention_records",
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"retention_policy_revisions",
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"lifecycle_events",
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"lifecycle_policy_revisions",
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"lifecycle_subjects",
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"project_fit_evidence",
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"scheduler_evictions",
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"co_residency_evidence",
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"placement_plans",
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"scheduler_policy_revisions",
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"scheduler_accelerator_states",
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"capability_evaluation_runs",
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"capability_evaluation_suites",
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"reranking_case_results",
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"reranking_evaluation_runs",
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"retrieval_candidate_pools",
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"advisor_recommendations",
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"retrieval_pipeline_identities",
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"discovery_candidate_assessments",
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"advisor_policies",
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"model_comparisons",
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"evaluation_comparisons",
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"evaluation_case_results",
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"evaluation_runs",
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"evaluation_cases",
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"evaluation_suite_revisions",
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"evaluation_suites",
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"embedding_migrations",
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"project_evaluation_bindings",
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"serving_gpu_leases",
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"serving_jobs",
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# M38 durable LAB history owns a restrictive reference to gateway_requests;
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# drop it before the M0 gateway table while reconstructing the historical baseline.
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"lab_execution_runs",
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"gateway_requests",
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"residency_allocations",
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"service_credentials",
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"service_clients",
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"capability_resource_envelopes",
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"capability_experiment_routes",
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"capability_deployments",
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"embedding_spaces",
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"production_execution_approvals",
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"deployment_candidates",
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"runtime_probe_metrics",
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"runtime_probes",
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"execution_approvals",
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"runtime_compatibility_assessments",
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"artifact_set_members",
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"artifact_inspections",
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"artifact_job_attempts",
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"artifact_jobs",
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"download_plan_files",
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"download_plans",
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"artifact_sets",
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"upstream_files",
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"upstream_snapshots",
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"artifact_locations",
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"derived_artifact_sources",
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"storage_roots",
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):
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op.drop_table(table)
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op.drop_table("runtime_environments")
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for column in ("source_type", "upstream_metadata", "local_metadata", "interpretation_metadata", "description"):
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op.drop_column("models", column)
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op.drop_column("model_revisions", "archived_at")
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op.drop_column("audit_events", "canonical_payload")
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op.drop_column("audit_events", "hash_format")
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for column in ("status", "verification_details", "archived_at"):
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op.drop_column("model_artifacts", column)
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for column in ("transformation_type", "environment_snapshot", "status", "verification_details"):
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op.drop_column("derived_artifacts", column)
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for table in (
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"node_credentials",
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"node_enrollments",
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"hardware_inventory_runs",
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"storage_volume_states",
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"accelerator_telemetry_latest",
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"host_telemetry_latest",
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):
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op.drop_table(table)
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for column in (
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"inventory_at",
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"last_seen_at",
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"first_seen_at",
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"inventory_source",
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"status_reason",
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"status",
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"mig_mode_current",
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"total_vram_bytes",
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"compute_capability_minor",
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"compute_capability_major",
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"architecture",
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"vendor",
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"pci_bus_id",
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):
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op.drop_column("accelerators", column)
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for column in (
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"decommissioned_by",
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"decommission_reason",
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"decommissioned_at",
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"generation",
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"telemetry_sequence",
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"inventory_sequence",
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"last_connection_error",
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"last_telemetry_observed_at",
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"last_telemetry_received_at",
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"last_inventory_observed_at",
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"last_inventory_received_at",
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"last_heartbeat_at",
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"agent_started_at",
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"agent_capabilities",
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"agent_protocol_version",
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"liveness_state",
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"observation_source",
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"benchmark_eligible",
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"lab_eligible",
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"production_eligible",
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"labels",
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"role",
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"enabled",
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):
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op.drop_column("compute_nodes", column)
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for column in (
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"inventory_at",
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"first_seen_at",
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"status_reason",
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"agent_version",
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"total_ram_bytes",
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"physical_core_count",
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"logical_cpu_count",
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"cpu_model",
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"kernel_version",
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"architecture",
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"os_version",
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"os_name",
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"identity_source",
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"display_name",
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):
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op.drop_column("compute_nodes", column)
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def downgrade() -> None:
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existing = set(sa.inspect(op.get_bind()).get_table_names())
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for table in reversed(Base.metadata.sorted_tables):
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if table.name in existing:
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op.drop_table(table.name)
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