class_docstr: Client for interacting with Databricks serving endpoints.
  
  Example:
  
  First, set up credentials for authentication:
  
  .. code-block:: bash
  
      export DATABRICKS_HOST=...
      export DATABRICKS_TOKEN=...
  
  .. seealso::
  
      See https://docs.databricks.com/en/dev-tools/auth.html for other authentication methods.
  
  Then, create a deployment client and use it to interact with Databricks serving endpoints:
  
  .. code-block:: python
  
      from mlflow.deployments import get_deploy_client
  
      client = get_deploy_client("databricks")
      endpoints = client.list_endpoints()
      assert endpoints == [
          {
              "name": "chat",
              "creator": "alice@company.com",
              "creation_timestamp": 0,
              "last_updated_timestamp": 0,
              "state": {...},
              "config": {...},
              "tags": [...],
              "id": "88fd3f75a0d24b0380ddc40484d7a31b",
          },
      ]
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docstr: .. warning::
  
      This method is not implemented for `DatabricksDeploymentClient`.
docstr_tok: ["..","warning",":",":","This","method","is","not","implemented","for","`","DatabricksDeploymentClient","`","."]
code: def create_deployment(
      self, name, model_uri, flavor=None, config=None, endpoint=None
  ):
      """
      .. warning::
  
          This method is not implemented for `DatabricksDeploymentClient`.
      """
      raise NotImplementedError
  
imports: import posixpath
  from typing import Any, Dict, Optional
  from mlflow.deployments import BaseDeploymentClient
  from mlflow.deployments.constants import MLFLOW_DEPLOYMENT_CLIENT_REQUEST_RETRY_CODES, MLFLOW_DEPLOYMENT_PREDICT_TIMEOUT
  from mlflow.environment_variables import MLFLOW_HTTP_REQUEST_TIMEOUT
  from mlflow.utils import AttrDict
  from mlflow.utils.annotations import experimental
  from mlflow.utils.databricks_utils import get_databricks_host_creds
  from mlflow.utils.rest_utils import augmented_raise_for_status, http_request
label_desc: Use image node_id 1 for calling the DatabricksDeploymentClient obj's underlying member method code with example usage: obj.create_deployment(name, model_uri, flavor, config, endpoint) without return types