Auto-generated code for 8.18

src/api/api/cluster.ts

@@ -469,7 +469,7 @@ export default class Cluster {
   }
 
   /**
-    * Get remote cluster information. Get information about configured remote clusters. The API returns connection and endpoint information keyed by the configured remote cluster alias. > info > This API returns information that reflects current state on the local cluster. > The `connected` field does not necessarily reflect whether a remote cluster is down or unavailable, only whether there is currently an open connection to it. > Elasticsearch does not spontaneously try to reconnect to a disconnected remote cluster. > To trigger a reconnection, attempt a cross-cluster search, ES|QL cross-cluster search, or try the [resolve cluster endpoint](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-indices-resolve-cluster).
+    * Get remote cluster information. Get information about configured remote clusters. The API returns connection and endpoint information keyed by the configured remote cluster alias. > info > This API returns information that reflects current state on the local cluster. > The `connected` field does not necessarily reflect whether a remote cluster is down or unavailable, only whether there is currently an open connection to it. > Elasticsearch does not spontaneously try to reconnect to a disconnected remote cluster. > To trigger a reconnection, attempt a cross-cluster search, ES|QL cross-cluster search, or try the `/_resolve/cluster` endpoint.
     * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/cluster-remote-info.html | Elasticsearch API documentation}
     */
   async remoteInfo (this: That, params?: T.ClusterRemoteInfoRequest | TB.ClusterRemoteInfoRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.ClusterRemoteInfoResponse>

src/api/api/esql.ts

@@ -53,7 +53,7 @@ export default class Esql {
   async asyncQuery (this: That, params: T.EsqlAsyncQueryRequest | TB.EsqlAsyncQueryRequest, options?: TransportRequestOptions): Promise<T.EsqlAsyncQueryResponse>
   async asyncQuery (this: That, params: T.EsqlAsyncQueryRequest | TB.EsqlAsyncQueryRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = []
-    const acceptedBody: string[] = ['columnar', 'filter', 'locale', 'params', 'profile', 'query', 'tables', 'include_ccs_metadata', 'wait_for_completion_timeout']
+    const acceptedBody: string[] = ['columnar', 'filter', 'locale', 'params', 'profile', 'query', 'tables', 'include_ccs_metadata', 'wait_for_completion_timeout', 'keep_alive', 'keep_on_completion']
     const querystring: Record<string, any> = {}
     // @ts-expect-error
     const userBody: any = params?.body

src/api/api/fleet.ts

@@ -139,7 +139,7 @@ export default class Fleet {
   }
 
   /**
-    * Executes several [fleet searches](https://www.elastic.co/guide/en/elasticsearch/reference/current/fleet-search.html) with a single API request. The API follows the same structure as the [multi search](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-multi-search.html) API. However, similar to the fleet search API, it supports the wait_for_checkpoints parameter.
+    * Executes several fleet searches with a single API request. The API follows the same structure as the multi search (`_msearch`) API. However, similar to the fleet search API, it supports the `wait_for_checkpoints` parameter.
     * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/fleet-multi-search.html | Elasticsearch API documentation}
     */
   async msearch<TDocument = unknown> (this: That, params: T.FleetMsearchRequest | TB.FleetMsearchRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.FleetMsearchResponse<TDocument>>

src/api/api/indices.ts

@@ -79,7 +79,7 @@ export default class Indices {
 
   /**
     * Get tokens from text analysis. The analyze API performs analysis on a text string and returns the resulting tokens. Generating excessive amount of tokens may cause a node to run out of memory. The `index.analyze.max_token_count` setting enables you to limit the number of tokens that can be produced. If more than this limit of tokens gets generated, an error occurs. The `_analyze` endpoint without a specified index will always use `10000` as its limit.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/indices-analyze.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/docs/api/doc/elasticsearch/v8/operation/operation-indices-analyze | Elasticsearch API documentation}
     */
   async analyze (this: That, params?: T.IndicesAnalyzeRequest | TB.IndicesAnalyzeRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.IndicesAnalyzeResponse>
   async analyze (this: That, params?: T.IndicesAnalyzeRequest | TB.IndicesAnalyzeRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.IndicesAnalyzeResponse, unknown>>

src/api/api/inference.ts

@@ -262,7 +262,7 @@ export default class Inference {
   }
 
   /**
-    * Create an inference endpoint. IMPORTANT: The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Mistral, Azure OpenAI, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.
+    * Create an inference endpoint. IMPORTANT: The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Mistral, Azure OpenAI, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs. The following integrations are available through the inference API. You can find the available task types next to the integration name: * AlibabaCloud AI Search (`completion`, `rerank`, `sparse_embedding`, `text_embedding`) * Amazon Bedrock (`completion`, `text_embedding`) * Anthropic (`completion`) * Azure AI Studio (`completion`, `text_embedding`) * Azure OpenAI (`completion`, `text_embedding`) * Cohere (`completion`, `rerank`, `text_embedding`) * Elasticsearch (`rerank`, `sparse_embedding`, `text_embedding` - this service is for built-in models and models uploaded through Eland) * ELSER (`sparse_embedding`) * Google AI Studio (`completion`, `text_embedding`) * Google Vertex AI (`rerank`, `text_embedding`) * Hugging Face (`text_embedding`) * Mistral (`text_embedding`) * OpenAI (`chat_completion`, `completion`, `text_embedding`) * VoyageAI (`text_embedding`, `rerank`) * Watsonx inference integration (`text_embedding`) * JinaAI (`text_embedding`, `rerank`)
     * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/put-inference-api.html | Elasticsearch API documentation}
     */
   async put (this: That, params: T.InferencePutRequest | TB.InferencePutRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.InferencePutResponse>
@@ -352,7 +352,7 @@ export default class Inference {
   }
 
   /**
-    * Create an Amazon Bedrock inference endpoint. Creates an inference endpoint to perform an inference task with the `amazonbedrock` service. >info > You need to provide the access and secret keys only once, during the inference model creation. The get inference API does not retrieve your access or secret keys. After creating the inference model, you cannot change the associated key pairs. If you want to use a different access and secret key pair, delete the inference model and recreate it with the same name and the updated keys.
+    * Create an Amazon Bedrock inference endpoint. Create an inference endpoint to perform an inference task with the `amazonbedrock` service. >info > You need to provide the access and secret keys only once, during the inference model creation. The get inference API does not retrieve your access or secret keys. After creating the inference model, you cannot change the associated key pairs. If you want to use a different access and secret key pair, delete the inference model and recreate it with the same name and the updated keys.
     * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/infer-service-amazon-bedrock.html | Elasticsearch API documentation}
     */
   async putAmazonbedrock (this: That, params: T.InferencePutAmazonbedrockRequest | TB.InferencePutAmazonbedrockRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.InferencePutAmazonbedrockResponse>

src/api/types.ts

@@ -10618,8 +10618,6 @@ export interface EsqlAsyncQueryRequest extends RequestBase {
   delimiter?: string
   drop_null_columns?: boolean
   format?: EsqlQueryEsqlFormat
-  keep_alive?: Duration
-  keep_on_completion?: boolean
   columnar?: boolean
   filter?: QueryDslQueryContainer
   locale?: string
@@ -10629,6 +10627,8 @@ export interface EsqlAsyncQueryRequest extends RequestBase {
   tables?: Record<string, Record<string, EsqlTableValuesContainer>>
   include_ccs_metadata?: boolean
   wait_for_completion_timeout?: Duration
+  keep_alive?: Duration
+  keep_on_completion?: boolean
 }
 
 export type EsqlAsyncQueryResponse = EsqlResult

src/api/typesWithBodyKey.ts

@@ -10789,8 +10789,6 @@ export interface EsqlAsyncQueryRequest extends RequestBase {
   delimiter?: string
   drop_null_columns?: boolean
   format?: EsqlQueryEsqlFormat
-  keep_alive?: Duration
-  keep_on_completion?: boolean
   /** @deprecated The use of the 'body' key has been deprecated, move the nested keys to the top level object. */
   body?: {
     columnar?: boolean
@@ -10802,6 +10800,8 @@ export interface EsqlAsyncQueryRequest extends RequestBase {
     tables?: Record<string, Record<string, EsqlTableValuesContainer>>
     include_ccs_metadata?: boolean
     wait_for_completion_timeout?: Duration
+    keep_alive?: Duration
+    keep_on_completion?: boolean
   }
 }