labs.create_cloud_connection() Bug - Not able to authenticate when creating a connection against Lakehouse

[DieselAnalytics]

Describe the bug
I am attempting to use labs.create_cloud_connection() to create connection to a lakehouse using the code below:

conn = labs.create_cloud_connection(
    name=f"CloudConn-{lakehouse_name}-SQL",
    server_name = lakehouse_sql_endpoint,
    database_name = lakehouse_name,
    user_name="placeholder",
    password="placeholder",    
    privacy_level="Organizational"
)

I get the following error when I try to execute the above code:

FabricHTTPException: 400 Bad Request for url: https://api.fabric.microsoft.com//v1/connections
Error: {"requestId":"013ee7de-9af8-43e2-b0f4-51e30989fb7d","errorCode":"DM_GWPipeline_Gateway_DataSourceAccessError","moreDetails":[{"errorCode":"DM_ErrorDetailNameCode_UnderlyingErrorCode","message":"-2146232060"},{"errorCode":"DM_ErrorDetailNameCode_UnderlyingErrorMessage","message":"Could not login because the authentication failed."},{"errorCode":"DM_ErrorDetailNameCode_UnderlyingHResult","message":"-2146232060"},{"errorCode":"DM_ErrorDetailNameCode_UnderlyingNativeErrorCode","message":"18456"}],"message":"PowerBI service client received error HTTP response. HttpStatus: 400. PowerBIErrorCode: DM_GWPipeline_Gateway_DataSourceAccessError"}
Headers: {'Cache-Control': 'no-store, must-revalidate, no-cache', 'Pragma': 'no-cache', 'Transfer-Encoding': 'chunked', 'Content-Type': 'application/json; charset=utf-8', 'x-ms-public-api-error-code': 'DM_GWPipeline_Gateway_DataSourceAccessError', 'Strict-Transport-Security': 'max-age=31536000; includeSubDomains', 'X-Frame-Options': 'deny', 'X-Content-Type-Options': 'nosniff', 'RequestId': '013ee7de-9af8-43e2-b0f4-51e30989fb7d', 'Access-Control-Expose-Headers': 'RequestId', 'request-redirected': 'true', 'home-cluster-uri': 'https://wabi-west-us3-a-primary-redirect.analysis.windows.net/', 'Date': 'Wed, 07 Jan 2026 23:13:41 GMT'}

My ultimate goal is to do the following:

1. Create an empty semantic model
2. Add a connection based on a lakehouse to the semantic model created in Step 1. The connection will use the lakehouse's SQL endpoint and the semantic model will use import mode.
3. Add the tables in the lakehosue to the semantic model in import mode

[m-kovalsky]

I tried as well and I'm honestly not sure what it wants regarding the server/database parameters. May need to reach out to the product team to find out.