class_docstr: Client for interacting with the MLflow Deployments Server.
  
  Example:
  
  First, start the MLflow Deployments Server:
  
  .. code-block:: bash
  
      mlflow deployments start-server --config-path path/to/config.yaml
  
  Then, create a client and use it to interact with the server:
  
  .. code-block:: python
  
      from mlflow.deployments import get_deploy_client
  
      client = get_deploy_client("http://localhost:5000")
      endpoints = client.list_endpoints()
      assert [e.dict() for e in endpoints] == [
          {
              "name": "chat",
              "endpoint_type": "llm/v1/chat",
              "model": {"name": "gpt-3.5-turbo", "provider": "openai"},
              "endpoint_url": "http://localhost:5000/gateway/chat/invocations",
          },
      ]
docstr: .. warning::
      This method is not implemented for `MlflowDeploymentClient`.
docstr_tok: ["..","warning",":",":","This","method","is","not","implemented","for","`","MlflowDeploymentClient","`","."]
code: def delete_deployment(self, name, config=None, endpoint=None):
      """
      .. warning::
          This method is not implemented for `MlflowDeploymentClient`.
      """
      raise NotImplementedError
  
imports: from typing import TYPE_CHECKING, Any, Dict, List, Optional
  import requests
  from mlflow import MlflowException
  from mlflow.deployments import BaseDeploymentClient
  from mlflow.deployments.constants import MLFLOW_DEPLOYMENT_CLIENT_REQUEST_RETRY_CODES, MLFLOW_DEPLOYMENT_PREDICT_TIMEOUT
  from mlflow.deployments.server.config import Endpoint
  from mlflow.deployments.server.constants import MLFLOW_DEPLOYMENTS_CRUD_ENDPOINT_BASE, MLFLOW_DEPLOYMENTS_ENDPOINTS_BASE, MLFLOW_DEPLOYMENTS_QUERY_SUFFIX
  from mlflow.deployments.utils import resolve_endpoint_url
  from mlflow.environment_variables import MLFLOW_HTTP_REQUEST_TIMEOUT
  from mlflow.protos.databricks_pb2 import BAD_REQUEST
  from mlflow.store.entities.paged_list import PagedList
  from mlflow.tracking._tracking_service.utils import _get_default_host_creds
  from mlflow.utils.annotations import experimental
  from mlflow.utils.rest_utils import augmented_raise_for_status, http_request
  from mlflow.utils.uri import join_paths
label_desc: Use image node_id 3 for calling the MlflowDeploymentClient obj's underlying member method code with example usage: obj.delete_deployment(name, config, endpoint) without return types