Bump to 8.17.1 (#2632)

Fixes #2324

(cherry picked from commit 172180cb21)

Co-authored-by: Josh Mock <joshua.mock@elastic.co>

.buildkite/pipeline.yml

@@ -25,7 +25,7 @@ steps:
       provider: "gcp"
       image: family/core-ubuntu-2204
     plugins:
-      - junit-annotate#v2.5.0:
+      - junit-annotate#v2.4.1:
           artifacts: "junit-output/junit-*.xml"
           job-uuid-file-pattern: "junit-(.*).xml"
           fail-build-on-error: true

.github/make.sh

@@ -176,7 +176,7 @@ else
     --rm \
     $product \
     /bin/bash -c "cd /usr/src && \
-      git clone https://$CLIENTS_GITHUB_TOKEN@github.com/elastic/elastic-client-generator-js.git && \
+      git clone --branch $GENERATOR_BRANCH https://$CLIENTS_GITHUB_TOKEN@github.com/elastic/elastic-client-generator-js.git && \
       mkdir -p /usr/src/elastic-client-generator-js/output && \
       cd /usr/src/elasticsearch-js && \
       node .buildkite/make.mjs --task $TASK ${TASK_ARGS[*]}"

.github/stale.yml

@@ -0,0 +1,26 @@
+# Number of days of inactivity before an issue becomes stale
+daysUntilStale: 15
+
+# Number of days of inactivity before a stale issue is closed
+daysUntilClose: 7
+
+# Issues with these labels will never be considered stale
+exemptLabels:
+  - "discussion"
+  - "feature request"
+  - "bug"
+  - "todo"
+  - "good first issue"
+
+# Label to use when marking an issue as stale
+staleLabel: stale
+
+# Comment to post when marking an issue as stale. Set to `false` to disable
+markComment: |
+  We understand that this might be important for you, but this issue has been automatically marked as stale because it has not had recent activity either from our end or yours.
+  It will be closed if no further activity occurs, please write a comment if you would like to keep this going.
+
+  Note: in the past months we have built a new client, that has just landed in master. If you want to open an issue or a pr for the legacy client, you should do that in https://github.com/elastic/elasticsearch-js-legacy
+
+# Comment to post when closing a stale issue. Set to `false` to disable
+closeComment: false

.github/workflows/npm-publish.yml

@@ -23,18 +23,15 @@ jobs:
       - run: npm install -g npm
       - run: npm install
       - run: npm test
-      - run: npm publish --provenance --access public --tag alpha
+      - run: npm publish --provenance --access public
         env:
           NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
-      - name: Publish version on GitHub
-        run: |
+      - run: |
           version=$(jq -r .version package.json)
           gh release create \
-            -n "This is a 9.0.0 pre-release alpha. Changes may not be stable." \
-            --latest=false \
-            --prerelease \
+            -n "[Changelog](https://www.elastic.co/guide/en/elasticsearch/client/javascript-api/$BRANCH_NAME/changelog-client.html)" \
             --target "$BRANCH_NAME" \
-            --title "v$version" \
+            -t "v$version" \
             "v$version"
         env:
           BRANCH_NAME: ${{ github.event.inputs.branch }}

.github/workflows/serverless-patch.yml

@@ -42,7 +42,7 @@ jobs:
       - name: Apply patch from stack to serverless
         id: apply-patch
         run: $GITHUB_WORKSPACE/stack/.github/workflows/serverless-patch.sh
-      - uses: peter-evans/create-pull-request@5e914681df9dc83aa4e4905692ca88beb2f9e91f # v7
+      - uses: peter-evans/create-pull-request@c5a7806660adbe173f04e3e038b0ccdcd758773c # v6
         with:
           token: ${{ secrets.GH_TOKEN }}
           path: serverless

.github/workflows/stale.yml

@@ -1,21 +1,21 @@
 ---
-name: "Close stale issues and PRs"
+name: 'Close stale issues and PRs'
 on:
   schedule:
-    - cron: "30 1 * * *"
+    - cron: '30 1 * * *'
 
 jobs:
   stale:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@28ca1036281a5e5922ead5184a1bbf96e5fc984e # v9
+      - uses: actions/stale@1160a2240286f5da8ec72b1c0816ce2481aabf84 # v8
         with:
           stale-issue-label: stale
           stale-pr-label: stale
           days-before-stale: 90
           days-before-close: 14
-          exempt-issue-labels: "good first issue,tracking"
+          exempt-issue-labels: 'good first issue'
           close-issue-label: closed-stale
           close-pr-label: closed-stale
-          stale-issue-message: "This issue is stale because it has been open 90 days with no activity. Remove the `stale` label, or leave a comment, or this will be closed in 14 days."
-          stale-pr-message: "This pull request is stale because it has been open 90 days with no activity. Remove the `stale` label, or leave a comment, or this will be closed in 14 days."
+          stale-issue-message: 'This issue is stale because it has been open 90 days with no activity. Remove the `stale` label, or leave a comment, or this will be closed in 14 days.'
+          stale-pr-message: 'This pull request is stale because it has been open 90 days with no activity. Remove the `stale` label, or leave a comment, or this will be closed in 14 days.'

api-extractor.json

@@ -1,39 +0,0 @@
-{
-  "$schema": "https://developer.microsoft.com/json-schemas/api-extractor/v7/api-extractor.schema.json",
-  "mainEntryPointFilePath": "<projectFolder>/lib/client.d.ts",
-  "bundledPackages": [
-    "@elastic/*"
-  ],
-  "apiReport": {
-    "enabled": false
-  },
-  "docModel": {
-    "enabled": true,
-    "apiJsonFilePath": "<projectFolder>/api-extractor/<unscopedPackageName>.api.json",
-    "includeForgottenExports": true
-  },
-  "dtsRollup": {
-    "enabled": false
-  },
-  "tsdocMetadata": {
-    "enabled": true,
-    "tsdocMetadataFilePath": "<projectFolder>/api-extractor/tsdoc-metadata.json"
-  },
-  "messages": {
-    "compilerMessageReporting": {
-      "default": {
-        "logLevel": "warning"
-      }
-    },
-    "extractorMessageReporting": {
-      "default": {
-        "logLevel": "warning"
-      }
-    },
-    "tsdocMessageReporting": {
-      "default": {
-        "logLevel": "warning"
-      }
-    }
-  }
-}

docs/basic-config.asciidoc

@@ -85,7 +85,7 @@ _Default:_ `3`
 _Default:_ `30000`
 
 |`pingTimeout`
-|`number` - Max number of milliseconds a `ClusterConnectionPool` will wait when pinging nodes before marking them dead. +
+|`number` - Max ping request timeout in milliseconds for each request. +
 _Default:_ `3000`
 
 |`sniffInterval`
@@ -105,13 +105,17 @@ _Default:_ `'_nodes/_all/http'`
 _Default:_ `false`
 
 |`resurrectStrategy`
-|`string` - Strategy for resurrecting dead nodes when using `ClusterConnectionPool`. 'ping' will issue a test request to a node and resurrect it if it responds. 'optimistic' marks a node as alive without testing it. 'none' will never attempt to revive a dead connection. +
+|`string` - Configure the node resurrection strategy. +
 _Options:_ `'ping'`, `'optimistic'`, `'none'` +
 _Default:_ `'ping'`
 
+|`suggestCompression`
+|`boolean` - Adds `accept-encoding` header to every request. +
+_Default:_ `false`
+
 |`compression`
 |`string, boolean` - Enables gzip request body compression. +
-_Options:_ `true`, `false` +
+_Options:_ `'gzip'`, `false` +
 _Default:_ `false`
 
 |`tls`

docs/changelog.asciidoc

@@ -2,15 +2,59 @@
 == Release notes
 
 [discrete]
-=== 9.0.0
+=== 8.17.1
 
 [discrete]
-==== Breaking changes
+==== Fixes
 
 [discrete]
-===== Drop support for deprecated `body` parameter
+===== Improved support for Elasticsearch `v8.17`
 
-In 8.0, the top-level `body` parameter that was available on all API functions <<remove-body-key,was deprecated>>. In 9.0 this property is completely removed.
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
+[discrete]
+===== Report correct transport connection type in telemetry
+
+The client's telemetry reporting mechanism was incorrectly reporting all traffic as using `HttpConnection` when the default is `UndiciConnection`. https://github.com/elastic/elasticsearch-js/issues/2324[#2324]
+
+[discrete]
+=== 8.17.0
+
+[discrete]
+==== Features
+
+[discrete]
+===== Support for Elasticsearch `v8.17`
+
+You can find all the API changes
+https://www.elastic.co/guide/en/elasticsearch/reference/8.17/release-notes-8.17.0.html[here].
+
+[discrete]
+=== 8.16.4
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.16`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
+[discrete]
+===== Report correct transport connection type in telemetry
+
+The client's telemetry reporting mechanism was incorrectly reporting all traffic as using `HttpConnection` when the default is `UndiciConnection`. https://github.com/elastic/elasticsearch-js/issues/2324[#2324]
+
+[discrete]
+=== 8.16.3
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.16`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
 
 [discrete]
 === 8.16.2
@@ -118,7 +162,8 @@ https://www.elastic.co/guide/en/elasticsearch/reference/8.15/release-notes-8.15.
 ===== OpenTelemetry zero-code instrumentation support
 
 For those that use an observability service that supports OpenTelemetry spans, the client will now automatically generate traces for each Elasticsearch request it makes.
-See <<o11y-otel,the docs>> for more information.
+See {jsclient}/observability.html#_opentelemetry[the docs]
+for more information.
 
 [discrete]
 === 8.14.1
@@ -328,7 +373,7 @@ https://www.elastic.co/guide/en/elasticsearch/reference/8.9/release-notes-8.9.0.
 [discrete]
 ===== Allow document to be overwritten in `onDocument` iteratee of bulk helper https://github.com/elastic/elasticsearch-js/pull/1732[#1732]
 
-In the <<bulk-helper,bulk helper>>, documents could not be modified before being sent to Elasticsearch. It is now possible to <<bulk-modify-doc,modify a document>> before sending it.
+In the {jsclient}/client-helpers.html#bulk-helper[bulk helper], documents could not be modified before being sent to Elasticsearch. It is now possible to {jsclient}/client-helpers.html#_modifying_a_document_before_operation[modify a document] before sending it.
 
 [discrete]
 ==== Fixes
@@ -655,7 +700,6 @@ ac.abort()
 ----
 
 [discrete]
-[[remove-body-key]]
 ===== Remove the body key from the request
 
 *Breaking: Yes* | *Migration effort: Small*

docs/doc_examples/00ad41bde67beac991534ae0e04b1296.asciidoc

@@ -0,0 +1,11 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.getDataStream({
+  name: "my-data-stream",
+  filter_path: "data_streams.indices.index_name",
+});
+console.log(response);
+----

docs/doc_examples/0722b302b2b3275a988d858044f99d5d.asciidoc

@@ -0,0 +1,10 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.getMapping({
+  index: "kibana_sample_data_ecommerce",
+});
+console.log(response);
+----

docs/doc_examples/074e4602d1ca54412380a40867d078bc.asciidoc

@@ -11,6 +11,8 @@ const response = await client.indices.putSettings({
     "index.indexing.slowlog.threshold.index.debug": "2s",
     "index.indexing.slowlog.threshold.index.trace": "500ms",
     "index.indexing.slowlog.source": "1000",
+    "index.indexing.slowlog.reformat": true,
+    "index.indexing.slowlog.include.user": true,
   },
 });
 console.log(response);

docs/doc_examples/082e78c7a2061a7c4a52b494e5ede0e8.asciidoc

@@ -0,0 +1,42 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "my-rank-vectors-bit",
+  mappings: {
+    properties: {
+      my_vector: {
+        type: "rank_vectors",
+        element_type: "bit",
+      },
+    },
+  },
+});
+console.log(response);
+
+const response1 = await client.bulk({
+  index: "my-rank-vectors-bit",
+  refresh: "true",
+  operations: [
+    {
+      index: {
+        _id: "1",
+      },
+    },
+    {
+      my_vector: [127, -127, 0, 1, 42],
+    },
+    {
+      index: {
+        _id: "2",
+      },
+    },
+    {
+      my_vector: "8100012a7f",
+    },
+  ],
+});
+console.log(response1);
+----

docs/doc_examples/0c52af573c9401a2a687e86a4beb182b.asciidoc

@@ -10,7 +10,7 @@ const response = await client.ingest.putPipeline({
     {
       attachment: {
         field: "data",
-        remove_binary: false,
+        remove_binary: true,
       },
     },
   ],

docs/doc_examples/0f028f71f04c1d569fab402869565a84.asciidoc

@@ -4,9 +4,11 @@
 [source, js]
 ----
 const response = await client.indices.putSettings({
-  index: "my-index-000001",
+  index: ".reindexed-v9-ml-anomalies-custom-example",
   settings: {
-    "index.blocks.read_only_allow_delete": null,
+    index: {
+      number_of_replicas: "<original_number_of_replicas>",
+    },
   },
 });
 console.log(response);

docs/doc_examples/120fcf9f55128d6a81d5e87a9c235bbd.asciidoc

@@ -0,0 +1,20 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_inference/chat_completion/openai-completion/_stream",
+  body: {
+    model: "gpt-4o",
+    messages: [
+      {
+        role: "user",
+        content: "What is Elastic?",
+      },
+    ],
+  },
+});
+console.log(response);
+----

docs/doc_examples/12adea5d76f73d94d80d42f53f67563f.asciidoc

@@ -0,0 +1,11 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.addBlock({
+  index: ".ml-anomalies-custom-example",
+  block: "read_only",
+});
+console.log(response);
+----

docs/doc_examples/141ef0ebaa3b0772892b79b9bb85efb0.asciidoc

@@ -3,11 +3,13 @@
 
 [source, js]
 ----
-const response = await client.inference.inference({
+const response = await client.inference.put({
   task_type: "my-inference-endpoint",
   inference_id: "_update",
-  service_settings: {
-    api_key: "<API_KEY>",
+  inference_config: {
+    service_settings: {
+      api_key: "<API_KEY>",
+    },
   },
 });
 console.log(response);

docs/doc_examples/1ead35c954963e83f89872048dabdbe9.asciidoc

@@ -0,0 +1,19 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.security.queryRole({
+  query: {
+    bool: {
+      must_not: {
+        term: {
+          "metadata._reserved": true,
+        },
+      },
+    },
+  },
+  sort: ["name"],
+});
+console.log(response);
+----

docs/doc_examples/246763219ec06172f7aa57bba28d344a.asciidoc

@@ -0,0 +1,67 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "my-rank-vectors-bit",
+  mappings: {
+    properties: {
+      my_vector: {
+        type: "rank_vectors",
+        element_type: "bit",
+      },
+    },
+  },
+});
+console.log(response);
+
+const response1 = await client.bulk({
+  index: "my-rank-vectors-bit",
+  refresh: "true",
+  operations: [
+    {
+      index: {
+        _id: "1",
+      },
+    },
+    {
+      my_vector: [127, -127, 0, 1, 42],
+    },
+    {
+      index: {
+        _id: "2",
+      },
+    },
+    {
+      my_vector: "8100012a7f",
+    },
+  ],
+});
+console.log(response1);
+
+const response2 = await client.search({
+  index: "my-rank-vectors-bit",
+  query: {
+    script_score: {
+      query: {
+        match_all: {},
+      },
+      script: {
+        source: "maxSimDotProduct(params.query_vector, 'my_vector')",
+        params: {
+          query_vector: [
+            [
+              0.35, 0.77, 0.95, 0.15, 0.11, 0.08, 0.58, 0.06, 0.44, 0.52, 0.21,
+              0.62, 0.65, 0.16, 0.64, 0.39, 0.93, 0.06, 0.93, 0.31, 0.92, 0,
+              0.66, 0.86, 0.92, 0.03, 0.81, 0.31, 0.2, 0.92, 0.95, 0.64, 0.19,
+              0.26, 0.77, 0.64, 0.78, 0.32, 0.97, 0.84,
+            ],
+          ],
+        },
+      },
+    },
+  },
+});
+console.log(response2);
+----

docs/doc_examples/272e27bf1fcc4fe5dbd4092679dd0342.asciidoc

@@ -0,0 +1,11 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.addBlock({
+  index: ".ml-anomalies-custom-example",
+  block: "write",
+});
+console.log(response);
+----

docs/doc_examples/2a21674c40f9b182a8944769d20b2357.asciidoc

@@ -0,0 +1,26 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "my-rank-vectors-float",
+  query: {
+    script_score: {
+      query: {
+        match_all: {},
+      },
+      script: {
+        source: "maxSimDotProduct(params.query_vector, 'my_vector')",
+        params: {
+          query_vector: [
+            [0.5, 10, 6],
+            [-0.5, 10, 10],
+          ],
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/2a67608dadbf220a2f040f3a79d3677d.asciidoc

@@ -0,0 +1,35 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.ingest.putPipeline({
+  id: "attachment",
+  description: "Extract attachment information including original binary",
+  processors: [
+    {
+      attachment: {
+        field: "data",
+        remove_binary: false,
+      },
+    },
+  ],
+});
+console.log(response);
+
+const response1 = await client.index({
+  index: "my-index-000001",
+  id: "my_id",
+  pipeline: "attachment",
+  document: {
+    data: "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0=",
+  },
+});
+console.log(response1);
+
+const response2 = await client.get({
+  index: "my-index-000001",
+  id: "my_id",
+});
+console.log(response2);
+----

docs/doc_examples/2afd49985950cbcccf727fa858d00067.asciidoc

@@ -0,0 +1,24 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "test-index",
+  query: {
+    match: {
+      my_field: "Which country is Paris in?",
+    },
+  },
+  highlight: {
+    fields: {
+      my_field: {
+        type: "semantic",
+        number_of_fragments: 2,
+        order: "score",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/2f72a63c73dd672ac2dc3997ad15dd41.asciidoc

@@ -0,0 +1,23 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "test-index",
+  mappings: {
+    properties: {
+      source_field: {
+        type: "text",
+        fields: {
+          infer_field: {
+            type: "semantic_text",
+            inference_id: ".elser-2-elasticsearch",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/31832bd71c31c46a1ccf8d1c210d89d4.asciidoc

@@ -0,0 +1,28 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "my-index-*",
+  query: {
+    bool: {
+      must: [
+        {
+          match: {
+            "user.id": "kimchy",
+          },
+        },
+      ],
+      must_not: [
+        {
+          terms: {
+            _index: ["my-index-01"],
+          },
+        },
+      ],
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/32c8c86702ccd68eb70f1573409c2a1f.asciidoc

@@ -0,0 +1,31 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.ilm.putLifecycle({
+  name: "my_policy",
+  policy: {
+    phases: {
+      hot: {
+        actions: {
+          rollover: {
+            max_primary_shard_size: "50gb",
+          },
+          searchable_snapshot: {
+            snapshot_repository: "backing_repo",
+            replicate_for: "14d",
+          },
+        },
+      },
+      delete: {
+        min_age: "28d",
+        actions: {
+          delete: {},
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/3312c82f81816bf76629db9582991812.asciidoc

@@ -14,6 +14,7 @@ const response = await client.indices.putSettings({
     "index.search.slowlog.threshold.fetch.info": "800ms",
     "index.search.slowlog.threshold.fetch.debug": "500ms",
     "index.search.slowlog.threshold.fetch.trace": "200ms",
+    "index.search.slowlog.include.user": true,
   },
 });
 console.log(response);

docs/doc_examples/36792c81c053e0555407d1e83e7e054f.asciidoc

@@ -0,0 +1,70 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "movies",
+  size: 10,
+  retriever: {
+    rescorer: {
+      rescore: {
+        window_size: 50,
+        query: {
+          rescore_query: {
+            script_score: {
+              query: {
+                match_all: {},
+              },
+              script: {
+                source:
+                  "cosineSimilarity(params.queryVector, 'product-vector_final_stage') + 1.0",
+                params: {
+                  queryVector: [-0.5, 90, -10, 14.8, -156],
+                },
+              },
+            },
+          },
+        },
+      },
+      retriever: {
+        rrf: {
+          rank_window_size: 100,
+          retrievers: [
+            {
+              standard: {
+                query: {
+                  sparse_vector: {
+                    field: "plot_embedding",
+                    inference_id: "my-elser-model",
+                    query: "films that explore psychological depths",
+                  },
+                },
+              },
+            },
+            {
+              standard: {
+                query: {
+                  multi_match: {
+                    query: "crime",
+                    fields: ["plot", "title"],
+                  },
+                },
+              },
+            },
+            {
+              knn: {
+                field: "vector",
+                query_vector: [10, 22, 77],
+                k: 10,
+                num_candidates: 10,
+              },
+            },
+          ],
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/3722dad876023e0757138dd5a6d3240e.asciidoc

@@ -0,0 +1,23 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "my-index",
+  settings: {
+    index: {
+      number_of_shards: 3,
+      "blocks.write": true,
+    },
+  },
+  mappings: {
+    properties: {
+      field1: {
+        type: "text",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/38ba93890494bfa7beece58dffa44f98.asciidoc

@@ -1,23 +0,0 @@
-// This file is autogenerated, DO NOT EDIT
-// Use `node scripts/generate-docs-examples.js` to generate the docs examples
-
-[source, js]
-----
-const response = await client.bulk({
-  index: "test-index",
-  operations: [
-    {
-      update: {
-        _id: "1",
-      },
-    },
-    {
-      doc: {
-        infer_field: "updated inference field",
-        source_field: "updated source field",
-      },
-    },
-  ],
-});
-console.log(response);
-----

docs/doc_examples/3a204b57072a104d9b50f3a9e064a8f6.asciidoc

@@ -0,0 +1,19 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: ".ml-anomalies-custom-example",
+  size: 0,
+  aggs: {
+    job_ids: {
+      terms: {
+        field: "job_id",
+        size: 100,
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/3bc4a3681e3ea9cb3de49f72085807d8.asciidoc

@@ -0,0 +1,61 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "retrievers_example",
+  retriever: {
+    linear: {
+      retrievers: [
+        {
+          retriever: {
+            standard: {
+              query: {
+                function_score: {
+                  query: {
+                    term: {
+                      topic: "ai",
+                    },
+                  },
+                  functions: [
+                    {
+                      script_score: {
+                        script: {
+                          source: "doc['timestamp'].value.millis",
+                        },
+                      },
+                    },
+                  ],
+                  boost_mode: "replace",
+                },
+              },
+              sort: {
+                timestamp: {
+                  order: "asc",
+                },
+              },
+            },
+          },
+          weight: 2,
+          normalizer: "minmax",
+        },
+        {
+          retriever: {
+            knn: {
+              field: "vector",
+              query_vector: [0.23, 0.67, 0.89],
+              k: 3,
+              num_candidates: 5,
+            },
+          },
+          weight: 1.5,
+        },
+      ],
+      rank_window_size: 10,
+    },
+  },
+  _source: false,
+});
+console.log(response);
+----

docs/doc_examples/3ea4c971b3f47735dcc207ee2645fa03.asciidoc

@@ -0,0 +1,16 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.updateAliases({
+  actions: [
+    {
+      remove_index: {
+        index: "my-index-2099.05.06-000001",
+      },
+    },
+  ],
+});
+console.log(response);
+----

docs/doc_examples/3f9dcf2aa42f3ecfb5ebfe48c1774103.asciidoc

@@ -0,0 +1,18 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    order_stats: {
+      stats: {
+        field: "taxful_total_price",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/41d24383d29b2808a65258a0a3256e96.asciidoc

@@ -4,16 +4,12 @@
 [source, js]
 ----
 const response = await client.indices.create({
-  index: "semantic-embeddings",
+  index: "jinaai-index",
   mappings: {
     properties: {
-      semantic_text: {
-        type: "semantic_text",
-        inference_id: "my-elser-endpoint",
-      },
       content: {
-        type: "text",
-        copy_to: "semantic_text",
+        type: "semantic_text",
+        inference_id: "jinaai-embeddings",
       },
     },
   },

docs/doc_examples/45954b8aaedfed57012be8b6538b0a24.asciidoc

@@ -0,0 +1,47 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_inference/chat_completion/openai-completion/_stream",
+  body: {
+    messages: [
+      {
+        role: "user",
+        content: [
+          {
+            type: "text",
+            text: "What's the price of a scarf?",
+          },
+        ],
+      },
+    ],
+    tools: [
+      {
+        type: "function",
+        function: {
+          name: "get_current_price",
+          description: "Get the current price of a item",
+          parameters: {
+            type: "object",
+            properties: {
+              item: {
+                id: "123",
+              },
+            },
+          },
+        },
+      },
+    ],
+    tool_choice: {
+      type: "function",
+      function: {
+        name: "get_current_price",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/48e142e6c69014e0509d4c9251749d77.asciidoc

@@ -10,7 +10,8 @@ const response = await client.inference.put({
     service: "openai",
     service_settings: {
       api_key: "<api_key>",
-      model_id: "text-embedding-ada-002",
+      model_id: "text-embedding-3-small",
+      dimensions: 128,
     },
   },
 });

docs/doc_examples/4de4bb55bbc0a76c75d256f245a3ee3f.asciidoc

@@ -5,16 +5,11 @@
 ----
 const response = await client.inference.put({
   task_type: "sparse_embedding",
-  inference_id: "my-elser-endpoint",
+  inference_id: "elser-model-eis",
   inference_config: {
-    service: "elser",
+    service: "elastic",
     service_settings: {
-      adaptive_allocations: {
-        enabled: true,
-        min_number_of_allocations: 3,
-        max_number_of_allocations: 10,
-      },
-      num_threads: 1,
+      model_name: "elser",
     },
   },
 });

docs/doc_examples/519e46350316a33162740e5d7968aa2c.asciidoc

@@ -3,15 +3,18 @@
 
 [source, js]
 ----
-const response = await client.knnSearch({
-  index: "my-index",
+const response = await client.search({
+  index: "image-index",
   knn: {
-    field: "image_vector",
-    query_vector: [0.3, 0.1, 1.2],
+    field: "image-vector",
+    query_vector: [-5, 9, -12],
     k: 10,
     num_candidates: 100,
+    rescore_vector: {
+      oversample: 2,
+    },
   },
-  _source: ["name", "file_type"],
+  fields: ["title", "file-type"],
 });
 console.log(response);
 ----

docs/doc_examples/537bce129338d9227bccb6a0283dab45.asciidoc

@@ -5,7 +5,7 @@
 ----
 const response = await client.cluster.putSettings({
   persistent: {
-    "cluster.routing.allocation.disk.watermark.low": "30gb",
+    "migrate.data_stream_reindex_max_request_per_second": 10000,
   },
 });
 console.log(response);

docs/doc_examples/53d9d2ec9cb8d211772d764e76fe6890.asciidoc

@@ -0,0 +1,18 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.ingest.simulate({
+  id: "query_helper_pipeline",
+  docs: [
+    {
+      _source: {
+        content:
+          "artificial intelligence in medicine articles published in the last 12 months",
+      },
+    },
+  ],
+});
+console.log(response);
+----

docs/doc_examples/5836b09198feb1269ed12839b416123d.asciidoc

@@ -0,0 +1,16 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "jinaai-index",
+  query: {
+    semantic: {
+      field: "content",
+      query: "who inspired taking care of the sea?",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/59aa5216630f80c5dc298fc5bba4a819.asciidoc

@@ -0,0 +1,10 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.getSettings({
+  index: ".reindexed-v9-ml-anomalies-custom-example",
+});
+console.log(response);
+----

docs/doc_examples/6b67c6121efb86ee100d40c2646f77b5.asciidoc

@@ -0,0 +1,15 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.putSettings({
+  index: "*",
+  settings: {
+    "index.search.slowlog.include.user": true,
+    "index.search.slowlog.threshold.fetch.warn": "30s",
+    "index.search.slowlog.threshold.query.warn": "30s",
+  },
+});
+console.log(response);
+----

docs/doc_examples/6baf72c04d48cb04c2f8be609ff3b3b5.asciidoc

@@ -6,14 +6,15 @@
 const response = await client.search({
   index: "test-index",
   query: {
-    nested: {
-      path: "inference_field.inference.chunks",
-      query: {
-        sparse_vector: {
-          field: "inference_field.inference.chunks.embeddings",
-          inference_id: "my-inference-id",
-          query: "mountain lake",
-        },
+    match: {
+      my_semantic_field: "Which country is Paris in?",
+    },
+  },
+  highlight: {
+    fields: {
+      my_semantic_field: {
+        number_of_fragments: 2,
+        order: "score",
       },
     },
   },

docs/doc_examples/6e498b9dc753b94abf2618c407fa5cd8.asciidoc

@@ -0,0 +1,16 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.reindex({
+  wait_for_completion: "false",
+  source: {
+    index: ".ml-anomalies-custom-example",
+  },
+  dest: {
+    index: ".reindexed-v9-ml-anomalies-custom-example",
+  },
+});
+console.log(response);
+----

docs/doc_examples/6fa02c2ad485bbe91f44b321158250f3.asciidoc

@@ -12,6 +12,13 @@ const response = await client.search({
       fields: ["my_field", "my_field._2gram", "my_field._3gram"],
     },
   },
+  highlight: {
+    fields: {
+      my_field: {
+        matched_fields: ["my_field._index_prefix"],
+      },
+    },
+  },
 });
 console.log(response);
 ----

docs/doc_examples/730045fae3743c39b612813a42c330c3.asciidoc

@@ -0,0 +1,24 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "my-index-000001",
+  query: {
+    prefix: {
+      full_name: {
+        value: "ki",
+      },
+    },
+  },
+  highlight: {
+    fields: {
+      full_name: {
+        matched_fields: ["full_name._index_prefix"],
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/7478ff69113fb53f41ea07cdf911fa67.asciidoc

@@ -0,0 +1,33 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    daily_sales: {
+      date_histogram: {
+        field: "order_date",
+        calendar_interval: "day",
+      },
+      aggs: {
+        daily_revenue: {
+          sum: {
+            field: "taxful_total_price",
+          },
+        },
+        smoothed_revenue: {
+          moving_fn: {
+            buckets_path: "daily_revenue",
+            window: 3,
+            script: "MovingFunctions.unweightedAvg(values)",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/74b229a6e020113e5749099451979c89.asciidoc

@@ -1,26 +0,0 @@
-// This file is autogenerated, DO NOT EDIT
-// Use `node scripts/generate-docs-examples.js` to generate the docs examples
-
-[source, js]
-----
-const response = await client.search({
-  index: "test-index",
-  query: {
-    nested: {
-      path: "inference_field.inference.chunks",
-      query: {
-        knn: {
-          field: "inference_field.inference.chunks.embeddings",
-          query_vector_builder: {
-            text_embedding: {
-              model_id: "my_inference_id",
-              model_text: "mountain lake",
-            },
-          },
-        },
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/77cebba946fe648873a1e7375c13df41.asciidoc

@@ -5,10 +5,8 @@
 ----
 const response = await client.cluster.putSettings({
   persistent: {
-    "cluster.routing.allocation.disk.watermark.low": "100gb",
-    "cluster.routing.allocation.disk.watermark.high": "50gb",
-    "cluster.routing.allocation.disk.watermark.flood_stage": "10gb",
-    "cluster.info.update.interval": "1m",
+    "cluster.routing.allocation.disk.watermark.low": "90%",
+    "cluster.routing.allocation.disk.watermark.high": "95%",
   },
 });
 console.log(response);

docs/doc_examples/790684b45bef2bb848ea932f0fd0cfbd.asciidoc

@@ -0,0 +1,35 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  query: {
+    intervals: {
+      my_text: {
+        all_of: {
+          ordered: false,
+          max_gaps: 1,
+          intervals: [
+            {
+              match: {
+                query: "my favorite food",
+                max_gaps: 0,
+                ordered: true,
+              },
+            },
+            {
+              match: {
+                query: "cold porridge",
+                max_gaps: 4,
+                ordered: true,
+              },
+            },
+          ],
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/7bdc283b96c7a965fae23013647b8578.asciidoc

@@ -7,14 +7,14 @@ const response = await client.indices.create({
   index: "test-index",
   mappings: {
     properties: {
-      infer_field: {
-        type: "semantic_text",
-        inference_id: "my-elser-endpoint",
-      },
       source_field: {
         type: "text",
         copy_to: "infer_field",
       },
+      infer_field: {
+        type: "semantic_text",
+        inference_id: ".elser-2-elasticsearch",
+      },
     },
   },
 });

docs/doc_examples/7dd0d9cc6c5982a2c003d301e90feeba.asciidoc

@@ -0,0 +1,37 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    daily_sales: {
+      date_histogram: {
+        field: "order_date",
+        calendar_interval: "day",
+        format: "yyyy-MM-dd",
+      },
+      aggs: {
+        revenue: {
+          sum: {
+            field: "taxful_total_price",
+          },
+        },
+        unique_customers: {
+          cardinality: {
+            field: "customer_id",
+          },
+        },
+        avg_basket_size: {
+          avg: {
+            field: "total_quantity",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/80135e8c644e34cc70ce8a4e7915d1a2.asciidoc

@@ -12,7 +12,7 @@ const response = await client.ingest.putPipeline({
         field: "data",
         indexed_chars: 11,
         indexed_chars_field: "max_size",
-        remove_binary: false,
+        remove_binary: true,
       },
     },
   ],

docs/doc_examples/82bb6c61dab959f4446dc5ecab7ecbdf.asciidoc

@@ -0,0 +1,34 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_inference/chat_completion/openai-completion/_stream",
+  body: {
+    messages: [
+      {
+        role: "assistant",
+        content: "Let's find out what the weather is",
+        tool_calls: [
+          {
+            id: "call_KcAjWtAww20AihPHphUh46Gd",
+            type: "function",
+            function: {
+              name: "get_current_weather",
+              arguments: '{"location":"Boston, MA"}',
+            },
+          },
+        ],
+      },
+      {
+        role: "tool",
+        content: "The weather is cold",
+        tool_call_id: "call_KcAjWtAww20AihPHphUh46Gd",
+      },
+    ],
+  },
+});
+console.log(response);
+----

docs/doc_examples/8621c05cc7cf3880bde751f6670a0c3a.asciidoc

@@ -4,9 +4,11 @@
 [source, js]
 ----
 const response = await client.indices.putSettings({
-  index: "my-index-000001",
+  index: ".reindexed-v9-ml-anomalies-custom-example",
   settings: {
-    "index.search.slowlog.include.user": true,
+    index: {
+      number_of_replicas: 0,
+    },
   },
 });
 console.log(response);

docs/doc_examples/89f547649895176c246bb8c41313ff21.asciidoc

@@ -0,0 +1,12 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.esql.query({
+  query:
+    '\nFROM library\n| EVAL year = DATE_EXTRACT("year", release_date)\n| WHERE page_count > ? AND match(author, ?, {"minimum_should_match": ?})\n| LIMIT 5\n',
+  params: [300, "Frank Herbert", 2],
+});
+console.log(response);
+----

docs/doc_examples/8c47c80139f40f25db44f5781ca2dfbe.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.indices.unfreeze({
-  index: "my-index-000001",
+const response = await client.indices.getAlias({
+  index: ".ml-anomalies-custom-example",
 });
 console.log(response);
 ----

docs/doc_examples/8c639d3eef5c2de29e12bd9c6a42d3d4.asciidoc

@@ -0,0 +1,39 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    categories: {
+      terms: {
+        field: "category.keyword",
+        size: 5,
+        order: {
+          total_revenue: "desc",
+        },
+      },
+      aggs: {
+        total_revenue: {
+          sum: {
+            field: "taxful_total_price",
+          },
+        },
+        avg_order_value: {
+          avg: {
+            field: "taxful_total_price",
+          },
+        },
+        total_items: {
+          sum: {
+            field: "total_quantity",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/9250ac57ec81d5192e8ad4c462438489.asciidoc

@@ -0,0 +1,42 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.bulk({
+  index: "jinaai-index",
+  operations: [
+    {
+      index: {
+        _index: "jinaai-index",
+        _id: "1",
+      },
+    },
+    {
+      content:
+        "Sarah Johnson is a talented marine biologist working at the Oceanographic Institute. Her groundbreaking research on coral reef ecosystems has garnered international attention and numerous accolades.",
+    },
+    {
+      index: {
+        _index: "jinaai-index",
+        _id: "2",
+      },
+    },
+    {
+      content:
+        "She spends months at a time diving in remote locations, meticulously documenting the intricate relationships between various marine species. ",
+    },
+    {
+      index: {
+        _index: "jinaai-index",
+        _id: "3",
+      },
+    },
+    {
+      content:
+        "Her dedication to preserving these delicate underwater environments has inspired a new generation of conservationists.",
+    },
+  ],
+});
+console.log(response);
+----

docs/doc_examples/931817b168e055ecf738785c721125dd.asciidoc

@@ -0,0 +1,32 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.ingest.putPipeline({
+  id: "query_helper_pipeline",
+  processors: [
+    {
+      script: {
+        source:
+          "ctx.prompt = 'Please generate an elasticsearch search query on index `articles_index` for the following natural language query. Dates are in the field `@timestamp`, document types are in the field `type` (options are `news`, `publication`), categories in the field `category` and can be multiple (options are `medicine`, `pharmaceuticals`, `technology`), and document names are in the field `title` which should use a fuzzy match. Ignore fields which cannot be determined from the natural language query context: ' + ctx.content",
+      },
+    },
+    {
+      inference: {
+        model_id: "openai_chat_completions",
+        input_output: {
+          input_field: "prompt",
+          output_field: "query",
+        },
+      },
+    },
+    {
+      remove: {
+        field: "prompt",
+      },
+    },
+  ],
+});
+console.log(response);
+----

docs/doc_examples/948418e0ef1b7e7cfee2f11be715d7d2.asciidoc

@@ -5,6 +5,9 @@
 ----
 const response = await client.indices.create({
   index: "retrievers_example_nested",
+  settings: {
+    number_of_shards: 1,
+  },
   mappings: {
     properties: {
       nested_field: {
@@ -18,6 +21,9 @@ const response = await client.indices.create({
             dims: 3,
             similarity: "l2_norm",
             index: true,
+            index_options: {
+              type: "flat",
+            },
           },
         },
       },

docs/doc_examples/9cc952d4a03264b700136cbc45abc8c6.asciidoc

@@ -0,0 +1,30 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "my-rank-vectors-byte",
+  mappings: {
+    properties: {
+      my_vector: {
+        type: "rank_vectors",
+        element_type: "byte",
+      },
+    },
+  },
+});
+console.log(response);
+
+const response1 = await client.index({
+  index: "my-rank-vectors-byte",
+  id: 1,
+  document: {
+    my_vector: [
+      [1, 2, 3],
+      [4, 5, 6],
+    ],
+  },
+});
+console.log(response1);
+----

docs/doc_examples/a46f566ca031375658c22f89b87dc6d2.asciidoc

@@ -0,0 +1,12 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.cat.indices({
+  index: ".ml-anomalies-custom-example",
+  v: "true",
+  h: "index,store.size",
+});
+console.log(response);
+----

docs/doc_examples/a675fafa7c688cb3ea1be09bf887ebf0.asciidoc

@@ -0,0 +1,12 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.get({
+  index: ".migrated-ds-my-data-stream-2025.01.23-000001",
+  human: "true",
+  filter_path: "*.settings.index.version.created_string",
+});
+console.log(response);
+----

docs/doc_examples/b590241c4296299b836fbb5a95bdd2dc.asciidoc

@@ -0,0 +1,18 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    avg_order_value: {
+      avg: {
+        field: "taxful_total_price",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/b6d278737d27973e498ac61cda9e5126.asciidoc

@@ -0,0 +1,21 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    daily_orders: {
+      date_histogram: {
+        field: "order_date",
+        calendar_interval: "day",
+        format: "yyyy-MM-dd",
+        min_doc_count: 0,
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/ba0e7e0b18fc9ec6c623d40186d1f61b.asciidoc

@@ -6,6 +6,7 @@
 const response = await client.indices.resolveCluster({
   name: "not-present,clust*:my-index*,oldcluster:*",
   ignore_unavailable: "false",
+  timeout: "5s",
 });
 console.log(response);
 ----

docs/doc_examples/bccd4eb26b1a325d103b12e198a13c08.asciidoc

@@ -0,0 +1,12 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.getSettings({
+  index: "_all",
+  expand_wildcards: "all",
+  filter_path: "*.settings.index.*.slowlog",
+});
+console.log(response);
+----

docs/doc_examples/bcd1afb793240b1dddd9fa5d3f21192b.asciidoc

@@ -6,15 +6,11 @@
 const response = await client.update({
   index: "test",
   id: 1,
-  script: {
-    source: "ctx._source.counter += params.count",
-    lang: "painless",
-    params: {
-      count: 4,
-    },
+  doc: {
+    product_price: 100,
   },
   upsert: {
-    counter: 1,
+    product_price: 50,
   },
 });
 console.log(response);

docs/doc_examples/bdc55256fa5f701680631a149dbb75a9.asciidoc

@@ -0,0 +1,22 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    sales_by_category: {
+      terms: {
+        field: "category.keyword",
+        size: 5,
+        order: {
+          _count: "desc",
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/bdd28276618235487ac96bd6679bc206.asciidoc

@@ -0,0 +1,31 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "kibana_sample_data_ecommerce",
+  size: 0,
+  aggs: {
+    daily_sales: {
+      date_histogram: {
+        field: "order_date",
+        calendar_interval: "day",
+      },
+      aggs: {
+        revenue: {
+          sum: {
+            field: "taxful_total_price",
+          },
+        },
+        cumulative_revenue: {
+          cumulative_sum: {
+            buckets_path: "revenue",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/bf3c3bc41c593a80faebef1df353e483.asciidoc

@@ -0,0 +1,22 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.inference.put({
+  task_type: "rerank",
+  inference_id: "jinaai-rerank",
+  inference_config: {
+    service: "jinaai",
+    service_settings: {
+      api_key: "<api_key>",
+      model_id: "jina-reranker-v2-base-multilingual",
+    },
+    task_settings: {
+      top_n: 10,
+      return_documents: true,
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/c3b77e11b16e37e9e37e28dec922432e.asciidoc

@@ -0,0 +1,11 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.esql.query({
+  query:
+    '\nFROM library\n| WHERE match(author, "Frank Herbert", {"minimum_should_match": 2, "operator": "AND"})\n| LIMIT 5\n',
+});
+console.log(response);
+----

docs/doc_examples/cdb7613b445e6ed6e8b473f9cae1af90.asciidoc

@@ -0,0 +1,35 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  query: {
+    intervals: {
+      my_text: {
+        all_of: {
+          ordered: true,
+          max_gaps: 1,
+          intervals: [
+            {
+              match: {
+                query: "my favorite food",
+                max_gaps: 0,
+                ordered: true,
+              },
+            },
+            {
+              match: {
+                query: "cold porridge",
+                max_gaps: 4,
+                ordered: true,
+              },
+            },
+          ],
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/cecfaa659af6646b3b67d7b311586fa0.asciidoc

@@ -14,7 +14,7 @@ const response = await client.ingest.putPipeline({
           attachment: {
             target_field: "_ingest._value.attachment",
             field: "_ingest._value.data",
-            remove_binary: false,
+            remove_binary: true,
           },
         },
       },

docs/doc_examples/d2e7dead222cfbebbd2c21a7cc1893b4.asciidoc

@@ -0,0 +1,11 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.cluster.state({
+  metric: "metadata",
+  filter_path: "metadata.indices.*.system",
+});
+console.log(response);
+----

docs/doc_examples/d3672a87a857ddb87519788236e57497.asciidoc

@@ -0,0 +1,28 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "jinaai-index",
+  retriever: {
+    text_similarity_reranker: {
+      retriever: {
+        standard: {
+          query: {
+            semantic: {
+              field: "content",
+              query: "who inspired taking care of the sea?",
+            },
+          },
+        },
+      },
+      field: "content",
+      rank_window_size: 100,
+      inference_id: "jinaai-rerank",
+      inference_text: "who inspired taking care of the sea?",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/d3a0f648d0fd50b54a4e9ebe363c5047.asciidoc

@@ -0,0 +1,44 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "retrievers_example",
+  retriever: {
+    linear: {
+      retrievers: [
+        {
+          retriever: {
+            standard: {
+              query: {
+                query_string: {
+                  query: "(information retrieval) OR (artificial intelligence)",
+                  default_field: "text",
+                },
+              },
+            },
+          },
+          weight: 2,
+          normalizer: "minmax",
+        },
+        {
+          retriever: {
+            knn: {
+              field: "vector",
+              query_vector: [0.23, 0.67, 0.89],
+              k: 3,
+              num_candidates: 5,
+            },
+          },
+          weight: 1.5,
+          normalizer: "minmax",
+        },
+      ],
+      rank_window_size: 10,
+    },
+  },
+  _source: false,
+});
+console.log(response);
+----

docs/doc_examples/d5242b1ab0213f25e5e0742032274ce6.asciidoc

@@ -10,7 +10,7 @@ const response = await client.ingest.putPipeline({
     {
       attachment: {
         field: "data",
-        remove_binary: false,
+        remove_binary: true,
       },
     },
   ],

docs/doc_examples/d6a4548b29e939fb197189c20c7c016f.asciidoc

@@ -0,0 +1,17 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.inference.put({
+  task_type: "chat_completion",
+  inference_id: "chat-completion-endpoint",
+  inference_config: {
+    service: "elastic",
+    service_settings: {
+      model_id: "model-1",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/dd16c9c981551c9da47ebb5ef5105fa0.asciidoc

@@ -0,0 +1,57 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.updateAliases({
+  actions: [
+    {
+      add: {
+        index: ".reindexed-v9-ml-anomalies-custom-example",
+        alias: ".ml-anomalies-example1",
+        filter: {
+          term: {
+            job_id: {
+              value: "example1",
+            },
+          },
+        },
+        is_hidden: true,
+      },
+    },
+    {
+      add: {
+        index: ".reindexed-v9-ml-anomalies-custom-example",
+        alias: ".ml-anomalies-example2",
+        filter: {
+          term: {
+            job_id: {
+              value: "example2",
+            },
+          },
+        },
+        is_hidden: true,
+      },
+    },
+    {
+      remove: {
+        index: ".ml-anomalies-custom-example",
+        aliases: ".ml-anomalies-*",
+      },
+    },
+    {
+      remove_index: {
+        index: ".ml-anomalies-custom-example",
+      },
+    },
+    {
+      add: {
+        index: ".reindexed-v9-ml-anomalies-custom-example",
+        alias: ".ml-anomalies-custom-example",
+        is_hidden: true,
+      },
+    },
+  ],
+});
+console.log(response);
+----

docs/doc_examples/df81b88a2192dd6f9912e0c948a44487.asciidoc

@@ -7,7 +7,7 @@ const response = await client.inference.put({
   task_type: "sparse_embedding",
   inference_id: "elser_embeddings",
   inference_config: {
-    service: "elser",
+    service: "elasticsearch",
     service_settings: {
       num_allocations: 1,
       num_threads: 1,

docs/doc_examples/e375c7da666276c4df6664c6821cd5f4.asciidoc

@@ -0,0 +1,29 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.create({
+  index: "my-rank-vectors-float",
+  mappings: {
+    properties: {
+      my_vector: {
+        type: "rank_vectors",
+      },
+    },
+  },
+});
+console.log(response);
+
+const response1 = await client.index({
+  index: "my-rank-vectors-float",
+  id: 1,
+  document: {
+    my_vector: [
+      [0.5, 10, 6],
+      [-0.5, 10, 10],
+    ],
+  },
+});
+console.log(response1);
+----

docs/doc_examples/e715fb8c792bf09ac98f0ceca99beb84.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.security.queryRole({
-  sort: ["name"],
+const response = await client.migration.deprecations({
+  index: ".ml-anomalies-*",
 });
 console.log(response);
 ----

docs/doc_examples/e77c2f41a7eca765b0c5f734a66d919f.asciidoc

@@ -11,7 +11,7 @@ const response = await client.ingest.putPipeline({
       attachment: {
         field: "data",
         properties: ["content", "title"],
-        remove_binary: false,
+        remove_binary: true,
       },
     },
   ],

docs/doc_examples/ea8c4229afa6dd4f1321355542be9912.asciidoc

@@ -12,7 +12,7 @@ const response = await client.ingest.putPipeline({
         field: "data",
         indexed_chars: 11,
         indexed_chars_field: "max_size",
-        remove_binary: false,
+        remove_binary: true,
       },
     },
   ],

docs/doc_examples/ec4b43c3ebd8816799fa004596b2f0cb.asciidoc

@@ -4,9 +4,10 @@
 [source, js]
 ----
 const response = await client.indices.putSettings({
-  index: "my-index-000001",
+  index: "*",
   settings: {
     "index.indexing.slowlog.include.user": true,
+    "index.indexing.slowlog.threshold.index.warn": "30s",
   },
 });
 console.log(response);

docs/doc_examples/f994498dd6576be657dedce2822d2b9e.asciidoc

@@ -30,6 +30,13 @@ const response = await client.search({
       ],
     },
   },
+  highlight: {
+    fields: {
+      semantic_text: {
+        number_of_fragments: 2,
+      },
+    },
+  },
 });
 console.log(response);
 ----

docs/doc_examples/ffda10edaa7ce087703193c3cb95a426.asciidoc

@@ -5,6 +5,9 @@
 ----
 const response = await client.indices.create({
   index: "retrievers_example",
+  settings: {
+    number_of_shards: 1,
+  },
   mappings: {
     properties: {
       vector: {
@@ -12,6 +15,9 @@ const response = await client.indices.create({
         dims: 3,
         similarity: "l2_norm",
         index: true,
+        index_options: {
+          type: "flat",
+        },
       },
       text: {
         type: "text",
@@ -22,6 +28,9 @@ const response = await client.indices.create({
       topic: {
         type: "keyword",
       },
+      timestamp: {
+        type: "date",
+      },
     },
   },
 });
@@ -35,6 +44,7 @@ const response1 = await client.index({
     text: "Large language models are revolutionizing information retrieval by boosting search precision, deepening contextual understanding, and reshaping user experiences in data-rich environments.",
     year: 2024,
     topic: ["llm", "ai", "information_retrieval"],
+    timestamp: "2021-01-01T12:10:30",
   },
 });
 console.log(response1);
@@ -47,6 +57,7 @@ const response2 = await client.index({
     text: "Artificial intelligence is transforming medicine, from advancing diagnostics and tailoring treatment plans to empowering predictive patient care for improved health outcomes.",
     year: 2023,
     topic: ["ai", "medicine"],
+    timestamp: "2022-01-01T12:10:30",
   },
 });
 console.log(response2);
@@ -59,6 +70,7 @@ const response3 = await client.index({
     text: "AI is redefining security by enabling advanced threat detection, proactive risk analysis, and dynamic defenses against increasingly sophisticated cyber threats.",
     year: 2024,
     topic: ["ai", "security"],
+    timestamp: "2023-01-01T12:10:30",
   },
 });
 console.log(response3);
@@ -71,6 +83,7 @@ const response4 = await client.index({
     text: "Elastic introduces Elastic AI Assistant, the open, generative AI sidekick powered by ESRE to democratize cybersecurity and enable users of every skill level.",
     year: 2023,
     topic: ["ai", "elastic", "assistant"],
+    timestamp: "2024-01-01T12:10:30",
   },
 });
 console.log(response4);
@@ -83,6 +96,7 @@ const response5 = await client.index({
     text: "Learn how to spin up a deployment of our hosted Elasticsearch Service and use Elastic Observability to gain deeper insight into the behavior of your applications and systems.",
     year: 2024,
     topic: ["documentation", "observability", "elastic"],
+    timestamp: "2025-01-01T12:10:30",
   },
 });
 console.log(response5);

docs/doc_examples/fff86117c47f974074284644e8a97a99.asciidoc

@@ -0,0 +1,18 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.inference.put({
+  task_type: "text_embedding",
+  inference_id: "jinaai-embeddings",
+  inference_config: {
+    service: "jinaai",
+    service_settings: {
+      model_id: "jina-embeddings-v3",
+      api_key: "<api_key>",
+    },
+  },
+});
+console.log(response);
+----

docs/examples/bulk.asciidoc

@@ -1,10 +1,10 @@
 [[bulk_examples]]
 === Bulk
 
-With the <<client.bulk,`bulk` API>>, you can perform multiple index/delete operations in a
+With the {jsclient}/api-reference.html#_bulk[`bulk` API], you can perform multiple index/delete operations in a 
 single API call. The `bulk` API significantly increases indexing speed.
 
-NOTE: You can also use the <<bulk-helper,bulk helper>>.
+NOTE: You can also use the {jsclient}/client-helpers.html[bulk helper].
 
 [source,js]
 ----

docs/examples/scroll.asciidoc

@@ -1,25 +1,25 @@
 [[scroll_examples]]
 === Scroll
 
-While a search request returns a single “page” of results, the scroll API can be
-used to retrieve large numbers of results (or even all results) from a single
-search request, in much the same way as you would use a cursor on a traditional
+While a search request returns a single “page” of results, the scroll API can be 
+used to retrieve large numbers of results (or even all results) from a single 
+search request, in much the same way as you would use a cursor on a traditional 
 database.
 
-Scrolling is not intended for real time user requests, but rather for processing
-large amounts of data, for example in order to reindex the contents of one index
+Scrolling is not intended for real time user requests, but rather for processing 
+large amounts of data, for example in order to reindex the contents of one index 
 into a new index with a different configuration.
 
-NOTE: The results that are returned from a scroll request reflect the state of
-the index at the time that the initial search request was made, like a snapshot
-in time. Subsequent changes to documents (index, update or delete) will only
+NOTE: The results that are returned from a scroll request reflect the state of 
+the index at the time that the initial search request was made, like a snapshot 
+in time. Subsequent changes to documents (index, update or delete) will only 
 affect later search requests.
 
-In order to use scrolling, the initial search request should specify the scroll
-parameter in the query string, which tells {es} how long it should keep the
+In order to use scrolling, the initial search request should specify the scroll 
+parameter in the query string, which tells {es} how long it should keep the 
 “search context” alive.
 
-NOTE: Did you know that we provide an helper for sending scroll requests? You can find it <<scroll-search-helper,here>>.
+NOTE: Did you know that we provide an helper for sending scroll requests? You can find it {jsclient}/client-helpers.html[here].
 
 [source,js]
 ----
@@ -113,7 +113,7 @@ async function run () {
 run().catch(console.log)
 ----
 
-Another cool usage of the `scroll` API can be done with Node.js ≥ 10, by using
+Another cool usage of the `scroll` API can be done with Node.js ≥ 10, by using 
 async iteration!
 
 [source,js]

docs/helpers.asciidoc

@@ -338,7 +338,6 @@ console.log(result)
 ----
 
 [discrete]
-[[bulk-modify-doc]]
 ==== Modifying a document before operation
 
 ~Added~ ~in~ ~`v8.8.2`~

docs/index.asciidoc

@@ -1,5 +1,8 @@
 = Elasticsearch JavaScript Client
 
+include::{asciidoc-dir}/../../shared/versions/stack/{source_branch}.asciidoc[]
+include::{asciidoc-dir}/../../shared/attributes.asciidoc[]
+
 include::introduction.asciidoc[]
 include::getting-started.asciidoc[]
 include::changelog.asciidoc[]
@@ -14,7 +17,8 @@ include::integrations.asciidoc[]
 include::observability.asciidoc[]
 include::transport.asciidoc[]
 include::typescript.asciidoc[]
-include::reference/main.asciidoc[]
+include::reference.asciidoc[]
 include::examples/index.asciidoc[]
 include::helpers.asciidoc[]
+include::redirects.asciidoc[]
 include::timeout-best-practices.asciidoc[]

docs/observability.asciidoc

@@ -16,7 +16,6 @@ features.
 All of these observability features are documented below.
 
 [discrete]
-[[o11y-otel]]
 ==== OpenTelemetry
 
 The client supports OpenTelemetry's https://opentelemetry.io/docs/zero-code/js/[zero-code

docs/reference/async_search.asciidoc

@@ -1,250 +0,0 @@
-[[reference-async_search]]
-== client.asyncSearch
-
-////////
-===========================================================================================================================
-||                                                                                                                       ||
-||                                                                                                                       ||
-||                                                                                                                       ||
-||        ██████╗ ███████╗ █████╗ ██████╗ ███╗   ███╗███████╗                                                            ||
-||        ██╔══██╗██╔════╝██╔══██╗██╔══██╗████╗ ████║██╔════╝                                                            ||
-||        ██████╔╝█████╗  ███████║██║  ██║██╔████╔██║█████╗                                                              ||
-||        ██╔══██╗██╔══╝  ██╔══██║██║  ██║██║╚██╔╝██║██╔══╝                                                              ||
-||        ██║  ██║███████╗██║  ██║██████╔╝██║ ╚═╝ ██║███████╗                                                            ||
-||        ╚═╝  ╚═╝╚══════╝╚═╝  ╚═╝╚═════╝ ╚═╝     ╚═╝╚══════╝                                                            ||
-||                                                                                                                       ||
-||                                                                                                                       ||
-||    This file is autogenerated, DO NOT send pull requests that changes this file directly.                             ||
-||    You should update the script that does the generation, which can be found in:                                      ||
-||    https://github.com/elastic/elastic-client-generator-js                                                             ||
-||                                                                                                                       ||
-||    You can run the script with the following command:                                                                 ||
-||       npm run elasticsearch -- --version <version>                                                                    ||
-||                                                                                                                       ||
-||                                                                                                                       ||
-||                                                                                                                       ||
-===========================================================================================================================
-////////
-++++
-<style>
-.lang-ts a.xref {
-  text-decoration: underline !important;
-}
-</style>
-++++
-
-
-[discrete]
-[[client.asyncSearch.delete]]
-== `client.asyncSearch.delete()`
-
-Delete an async search. If the asynchronous search is still running, it is cancelled. Otherwise, the saved search results are deleted. If the Elasticsearch security features are enabled, the deletion of a specific async search is restricted to: the authenticated user that submitted the original search request; users that have the `cancel_task` cluster privilege.
-
-{ref}/async-search.html[{es} documentation]
-[discrete]
-=== Function signature
-
-[source,ts]
-----
-(request: AsyncSearchDeleteRequest, options?: TransportRequestOptions) => Promise<AsyncSearchDeleteResponse>
-----
-
-[discrete]
-=== Request
-
-[source,ts,subs=+macros]
-----
-interface AsyncSearchDeleteRequest extends <<RequestBase>> {
-  id: <<Id>>
-}
-
-----
-
-
-[discrete]
-=== Response
-
-[source,ts,subs=+macros]
-----
-type AsyncSearchDeleteResponse = <<AcknowledgedResponseBase>>
-
-----
-
-
-[discrete]
-[[client.asyncSearch.get]]
-== `client.asyncSearch.get()`
-
-Get async search results. Retrieve the results of a previously submitted asynchronous search request. If the Elasticsearch security features are enabled, access to the results of a specific async search is restricted to the user or API key that submitted it.
-
-{ref}/async-search.html[{es} documentation]
-[discrete]
-=== Function signature
-
-[source,ts]
-----
-(request: AsyncSearchGetRequest, options?: TransportRequestOptions) => Promise<AsyncSearchGetResponse>
-----
-
-[discrete]
-=== Request
-
-[source,ts,subs=+macros]
-----
-interface AsyncSearchGetRequest extends <<RequestBase>> {
-  id: <<Id>>
-  keep_alive?: <<Duration>>
-  typed_keys?: boolean
-  wait_for_completion_timeout?: <<Duration>>
-}
-
-----
-
-
-[discrete]
-=== Response
-
-[source,ts,subs=+macros]
-----
-type AsyncSearchGetResponse<TDocument = unknown, TAggregations = Record<<<AggregateName>>, <<AggregationsAggregate>>>> = <<AsyncSearchAsyncSearchDocumentResponseBase>><TDocument, TAggregations>
-
-----
-
-
-[discrete]
-[[client.asyncSearch.status]]
-== `client.asyncSearch.status()`
-
-Get the async search status. Get the status of a previously submitted async search request given its identifier, without retrieving search results. If the Elasticsearch security features are enabled, use of this API is restricted to the `monitoring_user` role.
-
-{ref}/async-search.html[{es} documentation]
-[discrete]
-=== Function signature
-
-[source,ts]
-----
-(request: AsyncSearchStatusRequest, options?: TransportRequestOptions) => Promise<AsyncSearchStatusResponse>
-----
-
-[discrete]
-=== Request
-
-[source,ts,subs=+macros]
-----
-interface AsyncSearchStatusRequest extends <<RequestBase>> {
-  id: <<Id>>
-  keep_alive?: <<Duration>>
-}
-
-----
-
-
-[discrete]
-=== Response
-
-[source,ts,subs=+macros]
-----
-type AsyncSearchStatusResponse = AsyncSearchStatusStatusResponseBase
-
-----
-
-
-[discrete]
-[[client.asyncSearch.submit]]
-== `client.asyncSearch.submit()`
-
-Run an async search. When the primary sort of the results is an indexed field, shards get sorted based on minimum and maximum value that they hold for that field. Partial results become available following the sort criteria that was requested. Warning: Asynchronous search does not support scroll or search requests that include only the suggest section. By default, Elasticsearch does not allow you to store an async search response larger than 10Mb and an attempt to do this results in an error. The maximum allowed size for a stored async search response can be set by changing the `search.max_async_search_response_size` cluster level setting.
-
-{ref}/async-search.html[{es} documentation]
-[discrete]
-=== Function signature
-
-[source,ts]
-----
-(request: AsyncSearchSubmitRequest, options?: TransportRequestOptions) => Promise<AsyncSearchSubmitResponse>
-----
-
-[discrete]
-=== Request
-
-[source,ts,subs=+macros]
-----
-interface AsyncSearchSubmitRequest extends <<RequestBase>> {
-  index?: <<Indices>>
-  wait_for_completion_timeout?: <<Duration>>
-  keep_on_completion?: boolean
-  allow_no_indices?: boolean
-  allow_partial_search_results?: boolean
-  analyzer?: string
-  analyze_wildcard?: boolean
-  batched_reduce_size?: <<long>>
-  ccs_minimize_roundtrips?: boolean
-  default_operator?: <<QueryDslOperator>>
-  df?: string
-  expand_wildcards?: <<ExpandWildcards>>
-  ignore_throttled?: boolean
-  ignore_unavailable?: boolean
-  lenient?: boolean
-  max_concurrent_shard_requests?: <<long>>
-  preference?: string
-  request_cache?: boolean
-  routing?: <<Routing>>
-  search_type?: <<SearchType>>
-  suggest_field?: <<Field>>
-  suggest_mode?: <<SuggestMode>>
-  suggest_size?: <<long>>
-  suggest_text?: string
-  typed_keys?: boolean
-  rest_total_hits_as_int?: boolean
-  _source_excludes?: <<Fields>>
-  _source_includes?: <<Fields>>
-  q?: string
-  aggregations?: Record<string, <<AggregationsAggregationContainer>>>
-  pass:[/**] @alias aggregations */
-  aggs?: Record<string, <<AggregationsAggregationContainer>>>
-  collapse?: <<SearchFieldCollapse>>
-  explain?: boolean
-  ext?: Record<string, any>
-  from?: <<integer>>
-  highlight?: <<SearchHighlight>>
-  track_total_hits?: <<SearchTrackHits>>
-  indices_boost?: Record<<<IndexName>>, <<double>>>[]
-  docvalue_fields?: (<<QueryDslFieldAndFormat>> | <<Field>>)[]
-  knn?: <<KnnSearch>> | <<KnnSearch>>[]
-  min_score?: <<double>>
-  post_filter?: <<QueryDslQueryContainer>>
-  profile?: boolean
-  query?: <<QueryDslQueryContainer>>
-  rescore?: <<SearchRescore>> | <<SearchRescore>>[]
-  script_fields?: Record<string, <<ScriptField>>>
-  search_after?: <<SortResults>>
-  size?: <<integer>>
-  slice?: <<SlicedScroll>>
-  sort?: <<Sort>>
-  _source?: <<SearchSourceConfig>>
-  fields?: (<<QueryDslFieldAndFormat>> | <<Field>>)[]
-  suggest?: <<SearchSuggester>>
-  terminate_after?: <<long>>
-  timeout?: string
-  track_scores?: boolean
-  version?: boolean
-  seq_no_primary_term?: boolean
-  stored_fields?: <<Fields>>
-  pit?: <<SearchPointInTimeReference>>
-  runtime_mappings?: <<MappingRuntimeFields>>
-  stats?: string[]
-}
-
-----
-
-
-[discrete]
-=== Response
-
-[source,ts,subs=+macros]
-----
-type AsyncSearchSubmitResponse<TDocument = unknown, TAggregations = Record<<<AggregateName>>, <<AggregationsAggregate>>>> = <<AsyncSearchAsyncSearchDocumentResponseBase>><TDocument, TAggregations>
-
-----
-
-