import os
from woodwide import WoodWide

client = WoodWide(
    api_key=os.environ.get("WOOD_WIDE_AI_API_KEY"),  # This is the default and can be omitted
)
model_public = client.api.models.embedding.train(
    model_name="model_name",
)
print(model_public.id)

{
  "id": "<string>",
  "type": "<string>",
  "training_status": "<string>",
  "name": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "input_schema": {
    "columns": [
      {
        "name": "<string>",
        "type": "<string>",
        "values": [
          "<unknown>"
        ]
      }
    ]
  },
  "label_schema": {
    "columns": [
      {
        "name": "<string>",
        "type": "<string>",
        "values": [
          "<unknown>"
        ]
      }
    ]
  }
}