import json

from django.core.management.base import BaseCommand, CommandError

from control_plane.model_studio.models import ModelPromotionPolicy, TrainingProject
from control_plane.model_studio.services import ModelStudioService


class Command(BaseCommand):
    help = "Create a bounded Model Studio overnight program. --dry-run never allocates training compute."

    def add_arguments(self, parser):
        parser.add_argument("--project", required=True, help="TrainingProject slug")
        parser.add_argument("--dry-run", action="store_true")
        parser.add_argument("--wall-seconds", type=int, default=8 * 3600)
        parser.add_argument("--max-runs", type=int, default=8)

    def handle(self, *args, **options):
        project = TrainingProject.objects.filter(slug=options["project"]).first()
        if project is None:
            raise CommandError("TrainingProject not found.")
        policy = ModelPromotionPolicy.objects.filter(training_project=project, active=True).order_by("-created_at").first()
        if policy is None:
            raise CommandError("Create a ModelPromotionPolicy before starting an overnight program.")
        service = ModelStudioService()
        if options["dry_run"]:
            rows = list(project.experiments.filter(status__in=["PROPOSED", "QUEUED"]).order_by("-experiment_value_score").values("experiment_id", "title", "experiment_value_score", "estimated_runtime_seconds"))
            blockers = []
            if project.status != "READY":
                blockers.append(f"training project status is {project.status}")
            if not project.metadata.get("spark_working_directory_verified"):
                blockers.append("Spark Guard working directory is not verified")
            if project.baseline_evaluation_id is None:
                blockers.append("fresh Champion baseline is missing")
            self.stdout.write(json.dumps({"dry_run": True, "champion": str(project.current_champion_id or ""), "experiments": rows, "status": project.status, "blockers": blockers, "estimated_window_seconds": options["wall_seconds"], "maximum_runs": options["max_runs"]}, indent=2, default=str))
            return
        program = service.create_program(project, policy, wall_seconds=options["wall_seconds"], max_runs=options["max_runs"])
        self.stdout.write(self.style.SUCCESS(f"Created overnight program {program.id}; execution is intentionally queued for scoped worker supervision."))