update api to 8.4

elasticsearch/_async/client/__init__.py

@@ -3409,6 +3409,7 @@ async def search(
         indices_boost: t.Optional[
             t.Union[t.List[t.Mapping[str, float]], t.Tuple[t.Mapping[str, float], ...]]
         ] = None,
+        knn: t.Optional[t.Mapping[str, t.Any]] = None,
         lenient: t.Optional[bool] = None,
         max_concurrent_shard_requests: t.Optional[int] = None,
         min_compatible_shard_node: t.Optional[str] = None,
@@ -3538,6 +3539,7 @@ async def search(
         :param ignore_unavailable: Whether specified concrete indices should be ignored
             when unavailable (missing or closed)
         :param indices_boost: Boosts the _score of documents from specified indices.
+        :param knn: Defines the approximate kNN search to run.
         :param lenient: Specify whether format-based query failures (such as providing
             text to a numeric field) should be ignored
         :param max_concurrent_shard_requests: The number of concurrent shard requests
@@ -3682,6 +3684,8 @@ async def search(
             __query["ignore_unavailable"] = ignore_unavailable
         if indices_boost is not None:
             __body["indices_boost"] = indices_boost
+        if knn is not None:
+            __body["knn"] = knn
         if lenient is not None:
             __query["lenient"] = lenient
         if max_concurrent_shard_requests is not None:

elasticsearch/_async/client/async_search.py

@@ -215,6 +215,7 @@ async def submit(
         ] = None,
         keep_alive: t.Optional[t.Union["t.Literal[-1]", "t.Literal[0]", str]] = None,
         keep_on_completion: t.Optional[bool] = None,
+        knn: t.Optional[t.Mapping[str, t.Any]] = None,
         lenient: t.Optional[bool] = None,
         max_concurrent_shard_requests: t.Optional[int] = None,
         min_compatible_shard_node: t.Optional[str] = None,
@@ -350,6 +351,7 @@ async def submit(
         :param keep_on_completion: Control whether the response should be stored in the
             cluster if it completed within the provided [wait_for_completion] time (default:
             false)
+        :param knn: Defines the approximate kNN search to run.
         :param lenient: Specify whether format-based query failures (such as providing
             text to a numeric field) should be ignored
         :param max_concurrent_shard_requests: The number of concurrent shard requests
@@ -492,6 +494,8 @@ async def submit(
             __query["keep_alive"] = keep_alive
         if keep_on_completion is not None:
             __query["keep_on_completion"] = keep_on_completion
+        if knn is not None:
+            __body["knn"] = knn
         if lenient is not None:
             __query["lenient"] = lenient
         if max_concurrent_shard_requests is not None:

elasticsearch/_async/client/ml.py

@@ -3671,6 +3671,7 @@ async def start_trained_model_deployment(
         self,
         *,
         model_id: str,
+        cache_size: t.Optional[t.Union[int, str]] = None,
         error_trace: t.Optional[bool] = None,
         filter_path: t.Optional[
             t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]
@@ -3692,6 +3693,9 @@ async def start_trained_model_deployment(
 
         :param model_id: The unique identifier of the trained model. Currently, only
             PyTorch models are supported.
+        :param cache_size: The inference cache size (in memory outside the JVM heap)
+            per node for the model. The default value is the same size as the `model_size_bytes`.
+            To disable the cache, `0b` can be provided.
         :param number_of_allocations: The number of model allocations on each node where
             the model is deployed. All allocations on a node share the same copy of the
             model in memory but use a separate set of threads to evaluate the model.
@@ -3715,6 +3719,8 @@ async def start_trained_model_deployment(
             raise ValueError("Empty value passed for parameter 'model_id'")
         __path = f"/_ml/trained_models/{_quote(model_id)}/deployment/_start"
         __query: t.Dict[str, t.Any] = {}
+        if cache_size is not None:
+            __query["cache_size"] = cache_size
         if error_trace is not None:
             __query["error_trace"] = error_trace
         if filter_path is not None:

elasticsearch/_async/client/security.py

@@ -2502,6 +2502,66 @@ async def suggest_user_profiles(
             "POST", __path, params=__query, headers=__headers, body=__body
         )
 
+    @_rewrite_parameters(
+        body_fields=True,
+    )
+    async def update_api_key(
+        self,
+        *,
+        id: str,
+        error_trace: t.Optional[bool] = None,
+        filter_path: t.Optional[
+            t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]
+        ] = None,
+        human: t.Optional[bool] = None,
+        metadata: t.Optional[t.Mapping[str, t.Any]] = None,
+        pretty: t.Optional[bool] = None,
+        role_descriptors: t.Optional[t.Mapping[str, t.Mapping[str, t.Any]]] = None,
+    ) -> ObjectApiResponse[t.Any]:
+        """
+        Updates attributes of an existing API key.
+
+        `<https://www.elastic.co/guide/en/elasticsearch/reference/8.4/security-api-update-api-key.html>`_
+
+        :param id: The ID of the API key to update.
+        :param metadata: Arbitrary metadata that you want to associate with the API key.
+            It supports nested data structure. Within the metadata object, keys beginning
+            with _ are reserved for system usage.
+        :param role_descriptors: An array of role descriptors for this API key. This
+            parameter is optional. When it is not specified or is an empty array, then
+            the API key will have a point in time snapshot of permissions of the authenticated
+            user. If you supply role descriptors then the resultant permissions would
+            be an intersection of API keys permissions and authenticated user’s permissions
+            thereby limiting the access scope for API keys. The structure of role descriptor
+            is the same as the request for create role API. For more details, see create
+            or update roles API.
+        """
+        if id in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'id'")
+        __path = f"/_security/api_key/{_quote(id)}"
+        __query: t.Dict[str, t.Any] = {}
+        __body: t.Dict[str, t.Any] = {}
+        if error_trace is not None:
+            __query["error_trace"] = error_trace
+        if filter_path is not None:
+            __query["filter_path"] = filter_path
+        if human is not None:
+            __query["human"] = human
+        if metadata is not None:
+            __body["metadata"] = metadata
+        if pretty is not None:
+            __query["pretty"] = pretty
+        if role_descriptors is not None:
+            __body["role_descriptors"] = role_descriptors
+        if not __body:
+            __body = None  # type: ignore[assignment]
+        __headers = {"accept": "application/json"}
+        if __body is not None:
+            __headers["content-type"] = "application/json"
+        return await self.perform_request(  # type: ignore[return-value]
+            "PUT", __path, params=__query, headers=__headers, body=__body
+        )
+
     @_rewrite_parameters(
         body_fields=True,
     )

elasticsearch/_sync/client/__init__.py

@@ -3407,6 +3407,7 @@ def search(
         indices_boost: t.Optional[
             t.Union[t.List[t.Mapping[str, float]], t.Tuple[t.Mapping[str, float], ...]]
         ] = None,
+        knn: t.Optional[t.Mapping[str, t.Any]] = None,
         lenient: t.Optional[bool] = None,
         max_concurrent_shard_requests: t.Optional[int] = None,
         min_compatible_shard_node: t.Optional[str] = None,
@@ -3536,6 +3537,7 @@ def search(
         :param ignore_unavailable: Whether specified concrete indices should be ignored
             when unavailable (missing or closed)
         :param indices_boost: Boosts the _score of documents from specified indices.
+        :param knn: Defines the approximate kNN search to run.
         :param lenient: Specify whether format-based query failures (such as providing
             text to a numeric field) should be ignored
         :param max_concurrent_shard_requests: The number of concurrent shard requests
@@ -3680,6 +3682,8 @@ def search(
             __query["ignore_unavailable"] = ignore_unavailable
         if indices_boost is not None:
             __body["indices_boost"] = indices_boost
+        if knn is not None:
+            __body["knn"] = knn
         if lenient is not None:
             __query["lenient"] = lenient
         if max_concurrent_shard_requests is not None:

elasticsearch/_sync/client/async_search.py

@@ -215,6 +215,7 @@ def submit(
         ] = None,
         keep_alive: t.Optional[t.Union["t.Literal[-1]", "t.Literal[0]", str]] = None,
         keep_on_completion: t.Optional[bool] = None,
+        knn: t.Optional[t.Mapping[str, t.Any]] = None,
         lenient: t.Optional[bool] = None,
         max_concurrent_shard_requests: t.Optional[int] = None,
         min_compatible_shard_node: t.Optional[str] = None,
@@ -350,6 +351,7 @@ def submit(
         :param keep_on_completion: Control whether the response should be stored in the
             cluster if it completed within the provided [wait_for_completion] time (default:
             false)
+        :param knn: Defines the approximate kNN search to run.
         :param lenient: Specify whether format-based query failures (such as providing
             text to a numeric field) should be ignored
         :param max_concurrent_shard_requests: The number of concurrent shard requests
@@ -492,6 +494,8 @@ def submit(
             __query["keep_alive"] = keep_alive
         if keep_on_completion is not None:
             __query["keep_on_completion"] = keep_on_completion
+        if knn is not None:
+            __body["knn"] = knn
         if lenient is not None:
             __query["lenient"] = lenient
         if max_concurrent_shard_requests is not None:

elasticsearch/_sync/client/ml.py

@@ -3671,6 +3671,7 @@ def start_trained_model_deployment(
         self,
         *,
         model_id: str,
+        cache_size: t.Optional[t.Union[int, str]] = None,
         error_trace: t.Optional[bool] = None,
         filter_path: t.Optional[
             t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]
@@ -3692,6 +3693,9 @@ def start_trained_model_deployment(
 
         :param model_id: The unique identifier of the trained model. Currently, only
             PyTorch models are supported.
+        :param cache_size: The inference cache size (in memory outside the JVM heap)
+            per node for the model. The default value is the same size as the `model_size_bytes`.
+            To disable the cache, `0b` can be provided.
         :param number_of_allocations: The number of model allocations on each node where
             the model is deployed. All allocations on a node share the same copy of the
             model in memory but use a separate set of threads to evaluate the model.
@@ -3715,6 +3719,8 @@ def start_trained_model_deployment(
             raise ValueError("Empty value passed for parameter 'model_id'")
         __path = f"/_ml/trained_models/{_quote(model_id)}/deployment/_start"
         __query: t.Dict[str, t.Any] = {}
+        if cache_size is not None:
+            __query["cache_size"] = cache_size
         if error_trace is not None:
             __query["error_trace"] = error_trace
         if filter_path is not None:

elasticsearch/_sync/client/security.py

@@ -2502,6 +2502,66 @@ def suggest_user_profiles(
             "POST", __path, params=__query, headers=__headers, body=__body
         )
 
+    @_rewrite_parameters(
+        body_fields=True,
+    )
+    def update_api_key(
+        self,
+        *,
+        id: str,
+        error_trace: t.Optional[bool] = None,
+        filter_path: t.Optional[
+            t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]
+        ] = None,
+        human: t.Optional[bool] = None,
+        metadata: t.Optional[t.Mapping[str, t.Any]] = None,
+        pretty: t.Optional[bool] = None,
+        role_descriptors: t.Optional[t.Mapping[str, t.Mapping[str, t.Any]]] = None,
+    ) -> ObjectApiResponse[t.Any]:
+        """
+        Updates attributes of an existing API key.
+
+        `<https://www.elastic.co/guide/en/elasticsearch/reference/8.4/security-api-update-api-key.html>`_
+
+        :param id: The ID of the API key to update.
+        :param metadata: Arbitrary metadata that you want to associate with the API key.
+            It supports nested data structure. Within the metadata object, keys beginning
+            with _ are reserved for system usage.
+        :param role_descriptors: An array of role descriptors for this API key. This
+            parameter is optional. When it is not specified or is an empty array, then
+            the API key will have a point in time snapshot of permissions of the authenticated
+            user. If you supply role descriptors then the resultant permissions would
+            be an intersection of API keys permissions and authenticated user’s permissions
+            thereby limiting the access scope for API keys. The structure of role descriptor
+            is the same as the request for create role API. For more details, see create
+            or update roles API.
+        """
+        if id in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'id'")
+        __path = f"/_security/api_key/{_quote(id)}"
+        __query: t.Dict[str, t.Any] = {}
+        __body: t.Dict[str, t.Any] = {}
+        if error_trace is not None:
+            __query["error_trace"] = error_trace
+        if filter_path is not None:
+            __query["filter_path"] = filter_path
+        if human is not None:
+            __query["human"] = human
+        if metadata is not None:
+            __body["metadata"] = metadata
+        if pretty is not None:
+            __query["pretty"] = pretty
+        if role_descriptors is not None:
+            __body["role_descriptors"] = role_descriptors
+        if not __body:
+            __body = None  # type: ignore[assignment]
+        __headers = {"accept": "application/json"}
+        if __body is not None:
+            __headers["content-type"] = "application/json"
+        return self.perform_request(  # type: ignore[return-value]
+            "PUT", __path, params=__query, headers=__headers, body=__body
+        )
+
     @_rewrite_parameters(
         body_fields=True,
     )