"""M0 domain foundation.

Revision ID: 20260824_0001
Revises: None
"""

import sqlalchemy as sa

from alembic import op
from modelforge_api.persistence.models import Base

revision = "20260824_0001"
down_revision = None
branch_labels = None
depends_on = None


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


def downgrade() -> None:
    existing = set(sa.inspect(op.get_bind()).get_table_names())
    for table in reversed(Base.metadata.sorted_tables):
        if table.name in existing:
            op.drop_table(table.name)