text: from datetime import datetime, timezone
  
  from nmdc_runtime.api.models.workflow import Workflow
  
  _raw = [
      {
          "id": "metag-1.0.0",
          "created_at": datetime(2021, 8, 24, tzinfo=timezone.utc),
          "name": "Metagenome Analysis Workflow (v1.0.0)",
      },
      {
          "id": "readsqc-1.0.1",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Reads QC Workflow (v1.0.1)",
      },
      {
          "id": "rba-1.0.1",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Read-based Analysis (v1.0.1)",
      },
      {
          "id": "mgasmb-1.0.1",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Metagenome Assembly (v1.0.1)",
      },
      {
          "id": "mganno-1.0.0",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Metagenome Annotation (v1.0.0)",
      },
      {
          "id": "mgasmbgen-1.0.2",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Metagenome Assembled Genomes (v1.0.2)",
      },
      {
          "id": "metat-0.0.2",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Metatranscriptome (v0.0.2)",
      },
      {
          "id": "metap-1.0.0",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Metaproteomic (v1.0.0)",
      },
      {
          "id": "metab-2.1.0",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "Metabolomics  (v2.1.0)",
      },
      {
          "id": "gold-translation-1.0.0",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "GOLD db dump translation",
          "description": "Transform metadata obtained from the JGI GOLD database.",
      },
      {
          "id": "metap-metadata-1.0.0",
          "created_at": datetime(2021, 6, 1, tzinfo=timezone.utc),
          "name": "metaP metadata ETL",
          "description": "Ingest and validate metaP metadata",
      },
      {
          "id": "metadata-in-1.0.0",
          "created_at": datetime(2021, 10, 12, tzinfo=timezone.utc),
          "name": "general metadata ETL",
          "description": "Validate and ingest metadata from JSON files",
      },
      {
          "id": "test",
          "created_at": datetime(2021, 9, 9, tzinfo=timezone.utc),
          "name": "A test workflow",
          "description": "For use in unit and integration tests",
      },
      {
          "id": "gcms-metab-1.0.0",
          "created_at": datetime(2021, 9, 20, tzinfo=timezone.utc),
          "name": "GCMS-based metabolomics",
      },
      {
          "id": "nom-1.0.0",
          "created_at": datetime(2021, 9, 20, tzinfo=timezone.utc),
          "name": "Natural Organic Matter characterization",
      },
      {
          "id": "apply-changesheet-1.0.0",
          "created_at": datetime(2021, 9, 30, tzinfo=timezone.utc),
          "name": "apply metadata changesheet",
          "description": "Validate and apply metadata changes from TSV/CSV files",
      },
  ]
  
  
  def construct():
      models = []
      for kwargs in _raw:
          kwargs["capability_ids"] = []
          models.append(Workflow(**kwargs))
      return models
  