@@ -1091,13 +1091,57 @@ async def ml_trained_models(
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] = None ,
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format : t .Optional [str ] = None ,
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from_ : t .Optional [int ] = None ,
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- h : t .Optional [t .Union [str , t .Union [t .List [str ], t .Tuple [str , ...]]]] = None ,
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+ h : t .Optional [
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+ t .Union [
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+ t .Union [
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+ "t.Literal['create_time', 'created_by', 'data_frame_analytics_id', 'description', 'heap_size', 'id', 'ingest.count', 'ingest.current', 'ingest.failed', 'ingest.pipelines', 'ingest.time', 'license', 'operations', 'version']" ,
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+ str ,
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+ ],
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+ t .Union [
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+ t .List [
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+ t .Union [
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+ "t.Literal['create_time', 'created_by', 'data_frame_analytics_id', 'description', 'heap_size', 'id', 'ingest.count', 'ingest.current', 'ingest.failed', 'ingest.pipelines', 'ingest.time', 'license', 'operations', 'version']" ,
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+ str ,
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+ ]
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+ ],
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+ t .Tuple [
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+ t .Union [
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+ "t.Literal['create_time', 'created_by', 'data_frame_analytics_id', 'description', 'heap_size', 'id', 'ingest.count', 'ingest.current', 'ingest.failed', 'ingest.pipelines', 'ingest.time', 'license', 'operations', 'version']" ,
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+ str ,
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+ ],
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+ ...,
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+ ],
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+ ],
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+ ]
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+ ] = None ,
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help : t .Optional [bool ] = None ,
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human : t .Optional [bool ] = None ,
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local : t .Optional [bool ] = None ,
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master_timeout : t .Optional [t .Union [int , str ]] = None ,
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pretty : t .Optional [bool ] = None ,
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- s : t .Optional [t .Union [str , t .Union [t .List [str ], t .Tuple [str , ...]]]] = None ,
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+ s : t .Optional [
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+ t .Union [
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+ t .Union [
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+ "t.Literal['create_time', 'created_by', 'data_frame_analytics_id', 'description', 'heap_size', 'id', 'ingest.count', 'ingest.current', 'ingest.failed', 'ingest.pipelines', 'ingest.time', 'license', 'operations', 'version']" ,
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+ str ,
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+ ],
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+ t .Union [
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+ t .List [
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+ t .Union [
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+ "t.Literal['create_time', 'created_by', 'data_frame_analytics_id', 'description', 'heap_size', 'id', 'ingest.count', 'ingest.current', 'ingest.failed', 'ingest.pipelines', 'ingest.time', 'license', 'operations', 'version']" ,
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+ str ,
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+ ]
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+ ],
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+ t .Tuple [
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+ t .Union [
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+ "t.Literal['create_time', 'created_by', 'data_frame_analytics_id', 'description', 'heap_size', 'id', 'ingest.count', 'ingest.current', 'ingest.failed', 'ingest.pipelines', 'ingest.time', 'license', 'operations', 'version']" ,
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+ str ,
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+ ],
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+ ...,
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+ ],
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+ ],
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+ ]
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+ ] = None ,
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size : t .Optional [int ] = None ,
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v : t .Optional [bool ] = None ,
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) -> t .Union [ObjectApiResponse [t .Any ], TextApiResponse ]:
@@ -1114,17 +1158,15 @@ async def ml_trained_models(
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:param format: Specifies the format to return the columnar data in, can be set
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to `text`, `json`, `cbor`, `yaml`, or `smile`.
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:param from_: skips a number of trained models
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- :param h: List of columns to appear in the response. Supports simple wildcards.
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+ :param h: Comma-separated list of column names to display
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:param help: When set to `true` will output available columns. This option can't
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be combined with any other query string option.
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:param local: If `true`, the request computes the list of selected nodes from
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the local cluster state. If `false` the list of selected nodes are computed
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from the cluster state of the master node. In both cases the coordinating
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node will send requests for further information to each selected node.
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:param master_timeout: Period to wait for a connection to the master node.
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- :param s: List of columns that determine how the table should be sorted. Sorting
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- defaults to ascending and can be changed by setting `:asc` or `:desc` as
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- a suffix to the column name.
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+ :param s: Comma-separated list of column names or column aliases to sort by
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:param size: specifies a max number of trained models to get
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:param v: When set to `true` will enable verbose output.
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"""
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