1  from mlflow.exceptions import MlflowException
 2  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
 3  
 4  LOCAL = "local"
 5  CONDA = "conda"
 6  VIRTUALENV = "virtualenv"
 7  UV = "uv"
 8  
 9  
10  def validate(env_manager):
11      allowed_values = [LOCAL, CONDA, VIRTUALENV, UV]
12      if env_manager not in allowed_values:
13          raise MlflowException(
14              f"Invalid value for `env_manager`: {env_manager}. Must be one of {allowed_values}",
15              error_code=INVALID_PARAMETER_VALUE,
16          )