from meibelai import Meibelai
import os


with Meibelai(
    api_key_header=os.getenv("MEIBELAI_API_KEY_HEADER", ""),
) as m_client:

    res = m_client.datasources.rag.reprocess_datasource_metadata(datasource_id="<id>", metadata_model={
        "type": "<value>",
        "model_id": "<id>",
        "fields": [
            {
                "name": "<value>",
                "type": "<value>",
                "description": "meaningfully regarding excitedly emerge whereas scram",
            },
        ],
    })

    # Handle response
    print(res)

{
  "workflow_id": "<string>"
}