Bump to 8.16.1 (#2478)

Co-authored-by: Marci W <333176+marciw@users.noreply.github.com>

.dockerignore

@@ -5,4 +5,3 @@ elasticsearch
 .git
 lib
 junit-output
-.tap

.github/make.sh

@@ -65,7 +65,7 @@ codegen)
   if [ -v "$VERSION" ] || [[ -z "$VERSION" ]]; then
     # fall back to branch name or `main` if no VERSION is set
     branch_name=$(git rev-parse --abbrev-ref HEAD)
-    if [[ "$branch_name" =~ ^[0-9]+\.([0-9]+|x) ]]; then
+    if [[ "$branch_name" =~ ^[0-9]+\.[0-9]+ ]]; then
       echo -e "\033[36;1mTARGET: codegen -> No VERSION argument found, using branch name: \`$branch_name\`\033[0m"
       VERSION="$branch_name"
     else
@@ -150,7 +150,7 @@ if [[ -z "${BUILDKITE+x}" ]] && [[ -z "${CI+x}" ]] && [[ -z "${GITHUB_ACTIONS+x}
     -u "$(id -u):$(id -g)" \
     --volume "$repo:/usr/src/elasticsearch-js" \
     --volume /usr/src/elasticsearch-js/node_modules \
-    --volume "$(realpath "$repo/../elastic-client-generator-js"):/usr/src/elastic-client-generator-js" \
+    --volume "$(realpath $repo/../elastic-client-generator-js):/usr/src/elastic-client-generator-js" \
     --env "WORKFLOW=$WORKFLOW" \
     --name make-elasticsearch-js \
     --rm \
@@ -159,14 +159,6 @@ if [[ -z "${BUILDKITE+x}" ]] && [[ -z "${CI+x}" ]] && [[ -z "${GITHUB_ACTIONS+x}
       node .buildkite/make.mjs --task $TASK ${TASK_ARGS[*]}"
 else
   echo -e "\033[34;1mINFO: Running in CI mode"
-
-  # determine branch to clone
-  GENERATOR_BRANCH="main"
-  if [[ "$VERSION" == 8.* ]]; then
-    GENERATOR_BRANCH="8.x"
-  fi
-  echo -e "\033[34;1mINFO: Generator branch: $GENERATOR_BRANCH"
-
   docker run \
     --volume "$repo:/usr/src/elasticsearch-js" \
     --volume /usr/src/elasticsearch-js/node_modules \
@@ -176,7 +168,7 @@ else
     --rm \
     $product \
     /bin/bash -c "cd /usr/src && \
-      git clone --branch $GENERATOR_BRANCH https://$CLIENTS_GITHUB_TOKEN@github.com/elastic/elastic-client-generator-js.git && \
+      git clone 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/workflows/nodejs.yml

@@ -11,10 +11,10 @@ jobs:
     outputs:
       src-only: "${{ steps.changes.outputs.src-only }}"
     steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
-      - uses: dorny/paths-filter/@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3.0.2
+      - uses: dorny/paths-filter/@v3.0.2
         id: changes
         with:
           filters: |
@@ -36,12 +36,12 @@ jobs:
         os: [ubuntu-latest, windows-latest, macOS-latest]
 
     steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
 
       - name: Use Node.js ${{ matrix.node-version }}
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4
+        uses: actions/setup-node@v4
         with:
           node-version: ${{ matrix.node-version }}
 
@@ -66,12 +66,12 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
 
       - name: Use Node.js
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4
+        uses: actions/setup-node@v4
         with:
           node-version: 22.x
 
@@ -96,12 +96,12 @@ jobs:
         os: [ubuntu-latest, windows-latest, macOS-latest]
 
     steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
 
       - name: Use Bun
-        uses: oven-sh/setup-bun@4bc047ad259df6fc24a6c9b0f9a0cb08cf17fbe5 # v2
+        uses: oven-sh/setup-bun@v2
 
       - name: Install
         run: |
@@ -118,3 +118,13 @@ jobs:
       - name: ECMAScript module test
         run: |
           bun run test:esm
+
+  auto-approve:
+    name: Auto-approve
+    needs: [test, license]
+    runs-on: ubuntu-latest
+    permissions:
+      pull-requests: write
+    if: github.actor == 'elasticmachine'
+    steps:
+      - uses: hmarr/auto-approve-action@v4

.github/workflows/npm-publish.yml

@@ -12,11 +12,11 @@ jobs:
       contents: write
       id-token: write
     steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
           ref: ${{ github.event.inputs.branch }}
-      - uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4
+      - uses: actions/setup-node@v4
         with:
           node-version: "22.x"
           registry-url: "https://registry.npmjs.org"

.github/workflows/serverless-patch.yml

@@ -26,14 +26,14 @@ jobs:
         )
       )
     steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
           repository: elastic/elasticsearch-js
           ref: main
           path: stack
           fetch-depth: 0
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
+      - uses: actions/checkout@v4
         with:
           persist-credentials: false
           repository: elastic/elasticsearch-serverless-js
@@ -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@c5a7806660adbe173f04e3e038b0ccdcd758773c # v6
+      - uses: peter-evans/create-pull-request@v6
         with:
           token: ${{ secrets.GH_TOKEN }}
           path: serverless

.github/workflows/stale.yml

@@ -8,7 +8,7 @@ jobs:
   stale:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@1160a2240286f5da8ec72b1c0816ce2481aabf84 # v8
+      - uses: actions/stale@v8
         with:
           stale-issue-label: stale
           stale-pr-label: stale

.gitignore

@@ -67,4 +67,3 @@ junit-output
 bun.lockb
 test-results
 processinfo
-.tap

.npmignore

@@ -73,4 +73,3 @@ CONTRIBUTING.md
 
 src
 bun.lockb
-.tap

catalog-info.yaml

@@ -42,9 +42,6 @@ spec:
         main:
           branch: "main"
           cronline: "@daily"
-        8_x:
-          branch: "8.x"
-          cronline: "@daily"
         8_14:
-          branch: "8.16"
+          branch: "8.14"
           cronline: "@daily"

docs/basic-config.asciidoc

@@ -167,11 +167,19 @@ const client = new Client({
 ----
 
 |`nodeFilter`
-a|`function` - Takes a `Connection` and returns `true` if it can be sent a request, otherwise `false`. +
+a|`function` - Filters which node not to use for a request. +
 _Default:_
 [source,js]
 ----
-() => true
+function defaultNodeFilter (node) {
+  // avoid master only nodes
+  if (node.roles.master === true &&
+      node.roles.data === false &&
+      node.roles.ingest === false) {
+    return false
+  }
+  return true
+}
 ----
 
 |`nodeSelector`

docs/changelog.asciidoc

@@ -1,64 +1,6 @@
 [[changelog-client]]
 == Release notes
 
-=== 8.18.0
-
-[discrete]
-==== Features
-
-[discrete]
-===== Support for Elasticsearch `v8.18`
-
-You can find all the API changes
-https://www.elastic.co/guide/en/elasticsearch/reference/8.18/release-notes-8.18.0.html[here].
-
-[discrete]
-==== Fixes
-
-[discrete]
-===== Improved Cloud ID parsing
-
-When using a Cloud ID as the `cloud` parameter to instantiate the client, that ID was assumed to be in the correct format. New assertions have been added to verify that format and throw a `ConfigurationError` if it is invalid. See https://github.com/elastic/elasticsearch-js/issues/2694[#2694].
-
-[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]
-=== 8.16.3
-
-[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
-
-[discrete]
-==== Fixes
-
-[discrete]
-===== Improved support for Elasticsearch `v8.16`
-
-Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
-
-[discrete]
-===== Drop testing artifacts from npm package
-
-Tap, the unit testing tool used by this project, was recently upgraded and started writing to a `.tap` directory. Since tests are run prior to an `npm publish` in CI, this directory was being included in the published package and bloating its size.
-
 [discrete]
 === 8.16.1
 
@@ -95,27 +37,11 @@ The ES|QL helper can now return results as an Apache Arrow `Table` or `RecordBat
 
 The client's `disablePrototypePoisoningProtection` option was set to `true` by default, but when it was set to any other value it was ignored, making it impossible to enable prototype poisoning protection without providing a custom serializer implementation.
 
-[discrete]
-=== 8.15.3
-
-[discrete]
-==== Fixes
-
-[discrete]
-===== Improved support for Elasticsearch `v8.15`
-
-Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
-
-[discrete]
-===== Drop testing artifacts from npm package
-
-Tap, the unit testing tool, was recently upgraded and started writing to a `.tap` directory. Since tests are run prior to an `npm publish` in CI, this directory was being included in the published package and bloating its size.
-
 [discrete]
 === 8.15.2
 
 [discrete]
-==== Fixes
+==== Features
 
 [discrete]
 ===== Improved support for Elasticsearch `v8.15`
@@ -126,7 +52,7 @@ Updated TypeScript types based on fixes and improvements to the Elasticsearch sp
 === 8.15.1
 
 [discrete]
-==== Fixes
+==== Features
 
 [discrete]
 ===== Improved support for Elasticsearch `v8.15`

docs/doc_examples/00ad41bde67beac991534ae0e04b1296.asciidoc

@@ -1,11 +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.indices.getDataStream({
-  name: "my-data-stream",
-  filter_path: "data_streams.indices.index_name",
-});
-console.log(response);
-----

docs/doc_examples/015e6e6132b6d6d44bddb06bc3b316ed.asciidoc

@@ -1,46 +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: "retrievers_example",
-  retriever: {
-    rrf: {
-      retrievers: [
-        {
-          standard: {
-            query: {
-              range: {
-                year: {
-                  gt: 2023,
-                },
-              },
-            },
-          },
-        },
-        {
-          standard: {
-            query: {
-              term: {
-                topic: "elastic",
-              },
-            },
-          },
-        },
-      ],
-      rank_window_size: 10,
-      rank_constant: 1,
-    },
-  },
-  _source: false,
-  aggs: {
-    topics: {
-      terms: {
-        field: "topic",
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/0165d22da5f2fc7678392b31d8eb5566.asciidoc

@@ -1,18 +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.inference.put({
-  task_type: "rerank",
-  inference_id: "my-rerank-model",
-  inference_config: {
-    service: "cohere",
-    service_settings: {
-      model_id: "rerank-english-v3.0",
-      api_key: "{{COHERE_API_KEY}}",
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/082e78c7a2061a7c4a52b494e5ede0e8.asciidoc

@@ -1,42 +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.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/0bc6155e0c88062a4d8490da49db3aa8.asciidoc

@@ -1,49 +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: "retrievers_example_nested",
-  retriever: {
-    rrf: {
-      retrievers: [
-        {
-          standard: {
-            query: {
-              nested: {
-                path: "nested_field",
-                inner_hits: {
-                  name: "nested_vector",
-                  _source: false,
-                  fields: ["nested_field.paragraph_id"],
-                },
-                query: {
-                  knn: {
-                    field: "nested_field.nested_vector",
-                    query_vector: [1, 0, 0.5],
-                    k: 10,
-                  },
-                },
-              },
-            },
-          },
-        },
-        {
-          standard: {
-            query: {
-              term: {
-                topic: "ai",
-              },
-            },
-          },
-        },
-      ],
-      rank_window_size: 10,
-      rank_constant: 1,
-    },
-  },
-  _source: ["topic"],
-});
-console.log(response);
-----

docs/doc_examples/0bee07a581c5776e068f6f4efad5a399.asciidoc

@@ -3,12 +3,8 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_query/async",
-  querystring: {
-    format: "json",
-  },
+const response = await client.esql.asyncQuery({
+  format: "json",
   body: {
     query:
       "\n    FROM my-index-000001,cluster_one:my-index-000001,cluster_two:my-index*\n    | STATS COUNT(http.response.status_code) BY user.id\n    | LIMIT 2\n  ",

docs/doc_examples/0d689ac6e78be5d438f9b5d441be2b44.asciidoc

@@ -1,57 +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: "retrievers_example",
-  retriever: {
-    rrf: {
-      retrievers: [
-        {
-          standard: {
-            query: {
-              term: {
-                topic: "elastic",
-              },
-            },
-          },
-        },
-        {
-          rrf: {
-            retrievers: [
-              {
-                standard: {
-                  query: {
-                    query_string: {
-                      query:
-                        "(information retrieval) OR (artificial intelligence)",
-                      default_field: "text",
-                    },
-                  },
-                },
-              },
-              {
-                knn: {
-                  field: "vector",
-                  query_vector: [0.23, 0.67, 0.89],
-                  k: 3,
-                  num_candidates: 5,
-                },
-              },
-            ],
-            rank_window_size: 10,
-            rank_constant: 1,
-          },
-        },
-      ],
-      rank_window_size: 10,
-      rank_constant: 1,
-    },
-  },
-  _source: false,
-  size: 1,
-  explain: true,
-});
-console.log(response);
-----

docs/doc_examples/0dfde6a9d953822fd4b3aa0121ddd8fb.asciidoc

@@ -3,9 +3,8 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_application/search_application/my-app/_render_query",
+const response = await client.searchApplication.renderQuery({
+  name: "my-app",
   body: {
     params: {
       query_string: "my first query",

docs/doc_examples/0e83f140237d75469a428ff403564bb5.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.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",
+  },
+});
+console.log(response);
+----

docs/doc_examples/120fcf9f55128d6a81d5e87a9c235bbd.asciidoc

@@ -1,20 +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.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

@@ -1,11 +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.indices.addBlock({
-  index: ".ml-anomalies-custom-example",
-  block: "read_only",
-});
-console.log(response);
-----

docs/doc_examples/1420a22aa817c7a996baaed0ad366d6f.asciidoc

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

docs/doc_examples/160986f49758f4e8345d183a842f6351.asciidoc

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

docs/doc_examples/16634cfa7916cf4e8048a1d70e6240f2.asciidoc

@@ -11,7 +11,7 @@ const response = await client.searchApplication.put({
       script: {
         lang: "mustache",
         source:
-          '\n        {\n          "query": {\n            "bool": {\n              "must": [\n              {{#query}}\n              {{/query}}\n            ],\n            "filter": {{#toJson}}_es_filters{{/toJson}}\n            }\n          },\n          "_source": {\n            "includes": ["title", "plot"]\n            },\n            "highlight": {\n              "fields": {\n                "title": { "fragment_size": 0 },\n                "plot": { "fragment_size": 200 }\n                }\n                },\n                "aggs": {{#toJson}}_es_aggs{{/toJson}},\n                "from": {{from}},\n                "size": {{size}},\n                "sort": {{#toJson}}_es_sort_fields{{/toJson}}\n                }\n                ',
+          '\n        {\n          "query": {\n            "bool": {\n              "must": [\n              {{#query}}\n                \n              {{/query}}\n            ],\n            "filter": {{#toJson}}_es_filters{{/toJson}}\n            }\n          },\n          "_source": {\n            "includes": ["title", "plot"]\n            },\n            "highlight": {\n              "fields": {\n                "title": { "fragment_size": 0 },\n                "plot": { "fragment_size": 200 }\n                }\n                },\n                "aggs": {{#toJson}}_es_aggs{{/toJson}},\n                "from": {{from}},\n                "size": {{size}},\n                "sort": {{#toJson}}_es_sort_fields{{/toJson}}\n                }\n                ',
         params: {
           query: "",
           _es_filters: {},

docs/doc_examples/17b1647c8509543f2388c886f2584a20.asciidoc

@@ -1,27 +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({
-  retriever: {
-    text_similarity_reranker: {
-      retriever: {
-        standard: {
-          query: {
-            match: {
-              text: "How often does the moon hide the sun?",
-            },
-          },
-        },
-      },
-      field: "text",
-      inference_id: "elastic-rerank",
-      inference_text: "How often does the moon hide the sun?",
-      rank_window_size: 100,
-      min_score: 0.5,
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/191074b2eebd5f74e628c2ada4b6d2e4.asciidoc

@@ -8,6 +8,11 @@ const response = await client.search({
   query: {
     bool: {
       must: [
+        {
+          term: {
+            "category.keyword": "Main Course",
+          },
+        },
         {
           term: {
             tags: "vegetarian",
@@ -22,11 +27,6 @@ const response = await client.search({
         },
       ],
       should: [
-        {
-          term: {
-            category: "Main Course",
-          },
-        },
         {
           multi_match: {
             query: "curry spicy",

docs/doc_examples/19c00c6b29bc7dbc5e92b3668da2da93.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_ingest/_simulate",
+const response = await client.simulate.ingest({
   body: {
     docs: [
       {

docs/doc_examples/19f1f9f25933f8e7aba59a10881c648b.asciidoc

@@ -9,6 +9,7 @@ const response = await client.indices.create({
     properties: {
       inference_field: {
         type: "semantic_text",
+        inference_id: "my-elser-endpoint",
       },
     },
   },

docs/doc_examples/1ead35c954963e83f89872048dabdbe9.asciidoc

@@ -1,19 +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.security.queryRole({
-  query: {
-    bool: {
-      must_not: {
-        term: {
-          "metadata._reserved": true,
-        },
-      },
-    },
-  },
-  sort: ["name"],
-});
-console.log(response);
-----

docs/doc_examples/23af230e824f48b9cd56a4cf973d788c.asciidoc

@@ -14,7 +14,6 @@ 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/246763219ec06172f7aa57bba28d344a.asciidoc

@@ -1,67 +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.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/2577acb462b95bd4394523cf2f8a661f.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.esql.query({
+  format: "txt",
+  query:
+    "\n      FROM library\n    | SORT page_count DESC\n    | KEEP name, author\n    | LOOKUP era ON author\n    | LIMIT 5\n  ",
+  tables: {
+    era: {
+      author: {
+        keyword: [
+          "Frank Herbert",
+          "Peter F. Hamilton",
+          "Vernor Vinge",
+          "Alastair Reynolds",
+          "James S.A. Corey",
+        ],
+      },
+      era: {
+        keyword: ["The New Wave", "Diamond", "Diamond", "Diamond", "Hadron"],
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/272e27bf1fcc4fe5dbd4092679dd0342.asciidoc

@@ -1,11 +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.indices.addBlock({
-  index: ".ml-anomalies-custom-example",
-  block: "write",
-});
-console.log(response);
-----

docs/doc_examples/2a1eece9a59ac1773edcf0a932c26de0.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_security/oidc/logout",
+const response = await client.security.oidcLogout({
   body: {
     token:
       "dGhpcyBpcyBub3QgYSByZWFsIHRva2VuIGJ1dCBpdCBpcyBvbmx5IHRlc3QgZGF0YS4gZG8gbm90IHRyeSB0byByZWFkIHRva2VuIQ==",

docs/doc_examples/2a21674c40f9b182a8944769d20b2357.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: "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

@@ -1,35 +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.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

@@ -1,24 +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.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/2afdf0d83724953aa2875b5fb37d60cc.asciidoc

@@ -3,12 +3,10 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "GET",
-  path: "/_query/async/FmNJRUZ1YWZCU3dHY1BIOUhaenVSRkEaaXFlZ3h4c1RTWFNocDdnY2FSaERnUTozNDE=",
-  querystring: {
-    wait_for_completion_timeout: "30s",
-  },
+const response = await client.esql.asyncQueryGet({
+  id: "FmNJRUZ1YWZCU3dHY1BIOUhaenVSRkEaaXFlZ3h4c1RTWFNocDdnY2FSaERnUTozNDE=",
+  wait_for_completion_timeout: "30s",
+  body: null,
 });
 console.log(response);
 ----

docs/doc_examples/2bb41b0b4876ce98cd0cd8fb6d337f18.asciidoc

@@ -5,8 +5,11 @@
 ----
 const response = await client.cluster.putSettings({
   persistent: {
-    "cluster.routing.allocation.disk.watermark.low": "90%",
-    "cluster.routing.allocation.disk.watermark.high": "95%",
+    "cluster.indices.close.enable": false,
+    "indices.recovery.max_bytes_per_sec": "50mb",
+  },
+  transient: {
+    "*": null,
   },
 });
 console.log(response);

docs/doc_examples/2f07b81fd47ec3b074242a760f0c4e9e.asciidoc

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

docs/doc_examples/2f72a63c73dd672ac2dc3997ad15dd41.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.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/2fd458d37aab509fe2d970c0b6e2a10f.asciidoc

@@ -45,7 +45,7 @@ console.log(response);
 
 const response1 = await client.indices.putIndexTemplate({
   name: 2,
-  index_patterns: ["k9s*"],
+  index_patterns: ["k8s*"],
   composed_of: ["destination_template"],
   data_stream: {},
 });

docs/doc_examples/30d051f534aeb884176eedb2c11dac85.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.inference.put({
-  task_type: "rerank",
-  inference_id: "my-elastic-rerank",
-  inference_config: {
-    service: "elasticsearch",
-    service_settings: {
-      model_id: ".rerank-v1",
-      num_threads: 1,
-      adaptive_allocations: {
-        enabled: true,
-        min_number_of_allocations: 1,
-        max_number_of_allocations: 4,
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/31832bd71c31c46a1ccf8d1c210d89d4.asciidoc

@@ -1,28 +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: "my-index-*",
-  query: {
-    bool: {
-      must: [
-        {
-          match: {
-            "user.id": "kimchy",
-          },
-        },
-      ],
-      must_not: [
-        {
-          terms: {
-            _index: ["my-index-01"],
-          },
-        },
-      ],
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/31bc93e429ad0de11dd2dd231e8f2c5e.asciidoc

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

docs/doc_examples/32c8c86702ccd68eb70f1573409c2a1f.asciidoc

@@ -1,31 +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.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/34cdeefb09bbbe5206957a8bc1bd513d.asciidoc

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

docs/doc_examples/357edc9d10e98ed776401c7a439a1a55.asciidoc

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

docs/doc_examples/35fd9549350926f8d57dc1765e2f40d3.asciidoc

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

docs/doc_examples/36792c81c053e0555407d1e83e7e054f.asciidoc

@@ -1,70 +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: "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

@@ -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.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

@@ -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.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

@@ -1,19 +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: ".ml-anomalies-custom-example",
-  size: 0,
-  aggs: {
-    job_ids: {
-      terms: {
-        field: "job_id",
-        size: 100,
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/3bc4a3681e3ea9cb3de49f72085807d8.asciidoc

@@ -1,61 +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: "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

@@ -1,16 +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.indices.updateAliases({
-  actions: [
-    {
-      remove_index: {
-        index: "my-index-2099.05.06-000001",
-      },
-    },
-  ],
-});
-console.log(response);
-----

docs/doc_examples/3f1fe5f5f99b98d0891f38003e10b636.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_query/async",
+const response = await client.esql.asyncQuery({
   body: {
     query:
       "\n    FROM library\n    | EVAL year = DATE_TRUNC(1 YEARS, release_date)\n    | STATS MAX(page_count) BY year\n    | SORT year\n    | LIMIT 5\n  ",

docs/doc_examples/3f9dcf2aa42f3ecfb5ebfe48c1774103.asciidoc

@@ -1,18 +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: "kibana_sample_data_ecommerce",
-  size: 0,
-  aggs: {
-    order_stats: {
-      stats: {
-        field: "taxful_total_price",
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/405511f7c1f12cc0a227b4563fe7b2e2.asciidoc

@@ -3,9 +3,9 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "GET",
-  path: "/_query/async/FkpMRkJGS1gzVDRlM3g4ZzMyRGlLbkEaTXlJZHdNT09TU2VTZVBoNDM3cFZMUToxMDM=",
+const response = await client.esql.asyncQueryGet({
+  id: "FkpMRkJGS1gzVDRlM3g4ZzMyRGlLbkEaTXlJZHdNT09TU2VTZVBoNDM3cFZMUToxMDM=",
+  body: null,
 });
 console.log(response);
 ----

docs/doc_examples/436d50b85fc8f0977d02059eec00719b.asciidoc

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

docs/doc_examples/45954b8aaedfed57012be8b6538b0a24.asciidoc

@@ -1,47 +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.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/49b31e23f8b9667b6a7b2734d55fb6ed.asciidoc

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

docs/doc_examples/4b91ad7c9b44e07db4a4e81390f19ad3.asciidoc

@@ -3,9 +3,9 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_inference/completion/openai-completion/_stream",
+const response = await client.inference.streamInference({
+  task_type: "completion",
+  inference_id: "openai-completion",
   body: {
     input: "What is Elastic?",
   },

docs/doc_examples/4dab4c5168047ba596af1beb0e55b845.asciidoc

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

docs/doc_examples/4de4bb55bbc0a76c75d256f245a3ee3f.asciidoc

@@ -1,17 +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.inference.put({
-  task_type: "sparse_embedding",
-  inference_id: "elser-model-eis",
-  inference_config: {
-    service: "elastic",
-    service_settings: {
-      model_name: "elser",
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/53d9d2ec9cb8d211772d764e76fe6890.asciidoc

@@ -1,18 +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.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/57dc15e5ad663c342fd5c1d86fcd1b29.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_security/oidc/prepare",
+const response = await client.security.oidcPrepareAuthentication({
   body: {
     realm: "oidc1",
     state: "lGYK0EcSLjqH6pkT5EVZjC6eIW5YCGgywj2sxROO",

docs/doc_examples/5836b09198feb1269ed12839b416123d.asciidoc

@@ -1,16 +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: "jinaai-index",
-  query: {
-    semantic: {
-      field: "content",
-      query: "who inspired taking care of the sea?",
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/58f6b72009512851843c7b7a20e9504a.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.indices.create({
-  index: "my-index-000003",
+  index: "my-index-000002",
   mappings: {
     properties: {
       inference_field: {

docs/doc_examples/59aa5216630f80c5dc298fc5bba4a819.asciidoc

@@ -1,10 +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.indices.getSettings({
-  index: ".reindexed-v9-ml-anomalies-custom-example",
-});
-console.log(response);
-----

docs/doc_examples/5a70db31f587b7ffed5e9bc1445430cb.asciidoc

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

docs/doc_examples/5ba32ebaa7ee28a339c7693696d305ca.asciidoc

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

docs/doc_examples/5bba213a7f543190139d1a69ab2ed076.asciidoc

@@ -3,12 +3,8 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_query/async",
-  querystring: {
-    format: "json",
-  },
+const response = await client.esql.asyncQuery({
+  format: "json",
   body: {
     query:
       "\n    FROM cluster_one:my-index*,cluster_two:logs*\n    | STATS COUNT(http.response.status_code) BY user.id\n    | LIMIT 2\n  ",

docs/doc_examples/6b67c6121efb86ee100d40c2646f77b5.asciidoc

@@ -1,15 +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.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/6b6fd0a5942dfb9762ad2790cf421a80.asciidoc

@@ -11,7 +11,7 @@ const response = await client.searchApplication.put({
       script: {
         lang: "mustache",
         source:
-          '\n        {\n          "query": {\n            "bool": {\n              "must": [\n              {{#query}}\n              {{/query}}\n            ],\n            "filter": {{#toJson}}_es_filters{{/toJson}}\n            }\n          },\n          "_source": {\n            "includes": ["title", "plot"]\n          },\n          "aggs": {{#toJson}}_es_aggs{{/toJson}},\n          "from": {{from}},\n          "size": {{size}},\n          "sort": {{#toJson}}_es_sort_fields{{/toJson}}\n        }\n      ',
+          '\n        {\n          "query": {\n            "bool": {\n              "must": [\n              {{#query}}\n                \n              {{/query}}\n            ],\n            "filter": {{#toJson}}_es_filters{{/toJson}}\n            }\n          },\n          "_source": {\n            "includes": ["title", "plot"]\n          },\n          "aggs": {{#toJson}}_es_aggs{{/toJson}},\n          "from": {{from}},\n          "size": {{size}},\n          "sort": {{#toJson}}_es_sort_fields{{/toJson}}\n        }\n      ',
         params: {
           query: "",
           _es_filters: {},

docs/doc_examples/6e498b9dc753b94abf2618c407fa5cd8.asciidoc

@@ -1,16 +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.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/6f3b723bf6179b96c3413597ed7f49e1.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_security/api_key/_bulk_update",
+const response = await client.security.bulkUpdateApiKeys({
   body: {
     ids: ["VuaCfGcBCdbkQm-e5aOx", "H3_AhoIBA9hmeQJdg7ij"],
   },

docs/doc_examples/730045fae3743c39b612813a42c330c3.asciidoc

@@ -1,24 +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: "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

@@ -1,33 +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: "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

@@ -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: "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/76e02434835630cb830724beb92df354.asciidoc

@@ -1,44 +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: "retrievers_example",
-  retriever: {
-    rrf: {
-      retrievers: [
-        {
-          knn: {
-            field: "vector",
-            query_vector: [0.23, 0.67, 0.89],
-            k: 3,
-            num_candidates: 5,
-          },
-        },
-        {
-          text_similarity_reranker: {
-            retriever: {
-              standard: {
-                query: {
-                  term: {
-                    topic: "ai",
-                  },
-                },
-              },
-            },
-            field: "text",
-            inference_id: "my-rerank-model",
-            inference_text:
-              "Can I use generative AI to identify user intent and improve search relevance?",
-          },
-        },
-      ],
-      rank_window_size: 10,
-      rank_constant: 1,
-    },
-  },
-  _source: false,
-});
-console.log(response);
-----

docs/doc_examples/77518e8c6198acfe77c0934fd2fe65cb.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_text_structure/find_message_structure",
+const response = await client.textStructure.findMessageStructure({
   body: {
     messages: [
       "[2024-03-05T10:52:36,256][INFO ][o.a.l.u.VectorUtilPanamaProvider] [laptop] Java vector incubator API enabled; uses preferredBitSize=128",

docs/doc_examples/78043831fd32004a82930c8ac8a1d809.asciidoc

@@ -1,46 +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: "retrievers_example",
-  retriever: {
-    text_similarity_reranker: {
-      retriever: {
-        rrf: {
-          retrievers: [
-            {
-              standard: {
-                query: {
-                  query_string: {
-                    query:
-                      "(information retrieval) OR (artificial intelligence)",
-                    default_field: "text",
-                  },
-                },
-              },
-            },
-            {
-              knn: {
-                field: "vector",
-                query_vector: [0.23, 0.67, 0.89],
-                k: 3,
-                num_candidates: 5,
-              },
-            },
-          ],
-          rank_window_size: 10,
-          rank_constant: 1,
-        },
-      },
-      field: "text",
-      inference_id: "my-rerank-model",
-      inference_text:
-        "What are the state of the art applications of AI in information retrieval?",
-    },
-  },
-  _source: false,
-});
-console.log(response);
-----

docs/doc_examples/790684b45bef2bb848ea932f0fd0cfbd.asciidoc

@@ -1,35 +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({
-  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/7b9691bd34a02dd859562eb927f175e0.asciidoc

@@ -12,7 +12,7 @@ const response = await client.inference.put({
       adaptive_allocations: {
         enabled: true,
         min_number_of_allocations: 1,
-        max_number_of_allocations: 4,
+        max_number_of_allocations: 10,
       },
       num_threads: 1,
       model_id: ".elser_model_2",

docs/doc_examples/7ba29f0be2297b54a640b0a17d7ef5ca.asciidoc

@@ -1,11 +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.transport.request({
-  method: "DELETE",
-  path: "/_ingest/ip_location/database/my-database-id",
-});
-console.log(response);
-----

docs/doc_examples/7dd0d9cc6c5982a2c003d301e90feeba.asciidoc

@@ -1,37 +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: "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/80dd7f5882c59b9c1c90e8351937441f.asciidoc

@@ -3,9 +3,7 @@
 
 [source, js]
 ----
-const response = await client.transport.request({
-  method: "POST",
-  path: "/_security/api_key/_bulk_update",
+const response = await client.security.bulkUpdateApiKeys({
   body: {
     ids: ["VuaCfGcBCdbkQm-e5aOx", "H3_AhoIBA9hmeQJdg7ij"],
     role_descriptors: {

docs/doc_examples/82bb6c61dab959f4446dc5ecab7ecbdf.asciidoc

@@ -1,34 +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.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/844928da2ff9a1394af5347a5e2e4f78.asciidoc

@@ -11,8 +11,6 @@ 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/8593715fcc70315a0816b435551258e0.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/89f547649895176c246bb8c41313ff21.asciidoc

@@ -1,12 +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.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/8b144b3eb20872595fd7cbc6c245c7c8.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.indices.rollover({
-  alias: "datastream",
+const response = await client.security.queryRole({
+  sort: ["name"],
 });
 console.log(response);
 ----

docs/doc_examples/8c639d3eef5c2de29e12bd9c6a42d3d4.asciidoc

@@ -1,39 +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: "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/8cad5d95a0e7c103f08be53d0b172558.asciidoc

@@ -4,18 +4,17 @@
 [source, js]
 ----
 const response = await client.inference.put({
-  task_type: "rerank",
-  inference_id: "my-elastic-rerank",
+  task_type: "sparse_embedding",
+  inference_id: "my-elser-endpoint",
   inference_config: {
-    service: "elasticsearch",
+    service: "elser",
     service_settings: {
-      model_id: ".rerank-v1",
-      num_threads: 1,
       adaptive_allocations: {
         enabled: true,
-        min_number_of_allocations: 1,
+        min_number_of_allocations: 3,
         max_number_of_allocations: 10,
       },
+      num_threads: 1,
     },
   },
 });

docs/doc_examples/91e106a2affbc8df32cd940684a779ed.asciidoc

@@ -1,17 +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.transport.request({
-  method: "PUT",
-  path: "/_ingest/ip_location/database/my-database-1",
-  body: {
-    name: "GeoIP2-Domain",
-    maxmind: {
-      account_id: "1234567",
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/9250ac57ec81d5192e8ad4c462438489.asciidoc

@@ -1,42 +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: "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

@@ -1,32 +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.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

@@ -1,89 +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.indices.create({
-  index: "retrievers_example_nested",
-  settings: {
-    number_of_shards: 1,
-  },
-  mappings: {
-    properties: {
-      nested_field: {
-        type: "nested",
-        properties: {
-          paragraph_id: {
-            type: "keyword",
-          },
-          nested_vector: {
-            type: "dense_vector",
-            dims: 3,
-            similarity: "l2_norm",
-            index: true,
-            index_options: {
-              type: "flat",
-            },
-          },
-        },
-      },
-      topic: {
-        type: "keyword",
-      },
-    },
-  },
-});
-console.log(response);
-
-const response1 = await client.index({
-  index: "retrievers_example_nested",
-  id: 1,
-  document: {
-    nested_field: [
-      {
-        paragraph_id: "1a",
-        nested_vector: [-1.12, -0.59, 0.78],
-      },
-      {
-        paragraph_id: "1b",
-        nested_vector: [-0.12, 1.56, 0.42],
-      },
-      {
-        paragraph_id: "1c",
-        nested_vector: [1, -1, 0],
-      },
-    ],
-    topic: ["ai"],
-  },
-});
-console.log(response1);
-
-const response2 = await client.index({
-  index: "retrievers_example_nested",
-  id: 2,
-  document: {
-    nested_field: [
-      {
-        paragraph_id: "2a",
-        nested_vector: [0.23, 1.24, 0.65],
-      },
-    ],
-    topic: ["information_retrieval"],
-  },
-});
-console.log(response2);
-
-const response3 = await client.index({
-  index: "retrievers_example_nested",
-  id: 3,
-  document: {
-    topic: ["ai"],
-  },
-});
-console.log(response3);
-
-const response4 = await client.indices.refresh({
-  index: "retrievers_example_nested",
-});
-console.log(response4);
-----

docs/doc_examples/96e88611f99e6834bd64b58dc8a282c1.asciidoc

@@ -1,18 +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.indices.create({
-  index: "my-index-000002",
-  mappings: {
-    properties: {
-      inference_field: {
-        type: "semantic_text",
-        inference_id: "my-openai-endpoint",
-      },
-    },
-  },
-});
-console.log(response);
-----