Improve npm publish version parsing (#2638)

Co-authored-by: elastic-renovate-prod[bot] <174716857+elastic-renovate-prod[bot]@users.noreply.github.com>
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#v2.6.0:
           artifacts: "junit-output/junit-*.xml"
           job-uuid-file-pattern: "junit-(.*).xml"
           fail-build-on-error: true

.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]+ ]]; then
+    if [[ "$branch_name" =~ ^[0-9]+\.([0-9]+|x) ]]; then
       echo -e "\033[36;1mTARGET: codegen -> No VERSION argument found, using branch name: \`$branch_name\`\033[0m"
       VERSION="$branch_name"
     else
@@ -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/workflows/docs-build.yml

@@ -0,0 +1,19 @@
+name: docs-build
+
+on:
+  push:
+    branches:
+      - main
+  pull_request_target: ~
+  merge_group: ~
+
+jobs:
+  docs-preview:
+    uses: elastic/docs-builder/.github/workflows/preview-build.yml@main
+    with:
+      path-pattern: docs/**
+    permissions:
+      deployments: write
+      id-token: write
+      contents: read
+      pull-requests: read

.github/workflows/docs-cleanup.yml

@@ -0,0 +1,14 @@
+name: docs-cleanup
+
+on:
+  pull_request_target:
+    types:
+      - closed
+
+jobs:
+  docs-preview:
+    uses: elastic/docs-builder/.github/workflows/preview-cleanup.yml@main
+    permissions:
+      contents: none
+      id-token: write
+      deployments: write

.github/workflows/nodejs.yml

@@ -41,7 +41,7 @@ jobs:
           persist-credentials: false
 
       - name: Use Node.js ${{ matrix.node-version }}
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4
+        uses: actions/setup-node@1d0ff469b7ec7b3cb9d8673fde0c81c44821de2a # v4
         with:
           node-version: ${{ matrix.node-version }}
 
@@ -71,7 +71,7 @@ jobs:
           persist-credentials: false
 
       - name: Use Node.js
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4
+        uses: actions/setup-node@1d0ff469b7ec7b3cb9d8673fde0c81c44821de2a # v4
         with:
           node-version: 22.x
 

.github/workflows/npm-publish.yml

@@ -16,26 +16,45 @@ jobs:
         with:
           persist-credentials: false
           ref: ${{ github.event.inputs.branch }}
-      - uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4
+      - uses: actions/setup-node@1d0ff469b7ec7b3cb9d8673fde0c81c44821de2a # v4
         with:
           node-version: "22.x"
           registry-url: "https://registry.npmjs.org"
       - run: npm install -g npm
       - run: npm install
       - run: npm test
-      - run: npm publish --provenance --access public --tag alpha
+      - name: npm publish
+        run: |
+          version=$(jq -r .version package.json)
+          tag_meta=$(echo "$version" | cut -s -d '-' -f2)
+          if [[ -z "$tag_meta" ]]; then
+            npm publish --provenance --access public
+          else
+            tag=$(echo "$tag_meta" | cut -d '.' -f1)
+            npm publish --provenance --access public --tag "$tag"
+          fi
         env:
           NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
       - name: Publish version on GitHub
         run: |
           version=$(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 \
-            --target "$BRANCH_NAME" \
-            --title "v$version" \
-            "v$version"
+          tag_meta=$(echo "$version" | cut -s -d '-' -f2)
+          if [[ -z "$tag_meta" ]]; then
+            gh release create \
+              -n "[Changelog](https://www.elastic.co/guide/en/elasticsearch/client/javascript-api/$BRANCH_NAME/changelog-client.html)"
+              --target "$BRANCH_NAME" \
+              --title "v$version" \
+              "v$version"
+          else
+            tag_main=$(echo "$version" | cut -d '-' -f1)
+            gh release create \
+              -n "This is a $tag_main pre-release. Changes may not be stable." \
+              --latest=false \
+              --prerelease \
+              --target "$BRANCH_NAME" \
+              --title "v$version" \
+              "v$version"
+          fi
         env:
           BRANCH_NAME: ${{ github.event.inputs.branch }}
           GH_TOKEN: ${{ github.token }}

.github/workflows/serverless-patch.sh

@@ -1,43 +0,0 @@
-#!/usr/bin/env bash
-
-set -exuo pipefail
-
-merge_commit_sha=$(jq -r '.pull_request.merge_commit_sha' "$GITHUB_EVENT_PATH")
-pull_request_id=$(jq -r '.pull_request.number' "$GITHUB_EVENT_PATH")
-pr_shortcode="elastic/elasticsearch-js#$pull_request_id"
-
-# generate patch file
-cd "$GITHUB_WORKSPACE/stack"
-git format-patch -1 --stdout "$merge_commit_sha" > /tmp/patch.diff
-
-# set committer info
-git config --global user.email "elasticmachine@users.noreply.github.com"
-git config --global user.name "Elastic Machine"
-
-# apply patch file
-cd "$GITHUB_WORKSPACE/serverless"
-git am -C1 --reject /tmp/patch.diff || git am --quit
-
-# generate PR body comment
-comment="Patch applied from $pr_shortcode"
-
-# enumerate rejected patches in PR comment
-has_rejects='false'
-for f in ./**/*.rej; do
-  has_rejects='true'
-  comment="$comment
-
-## Rejected patch \`$f\` must be resolved:
-
-\`\`\`diff
-$(cat "$f")
-\`\`\`
-"
-done
-
-# delete .rej files
-rm -fv ./**/*.rej
-
-# send data to output parameters
-echo "$comment" > /tmp/pr_body
-echo "PR_DRAFT=$has_rejects" >> "$GITHUB_OUTPUT"

.github/workflows/serverless-patch.yml

@@ -1,53 +0,0 @@
----
-name: Apply PR changes to serverless
-on:
-  pull_request_target:
-    types:
-      - closed
-      - labeled
-
-jobs:
-  apply-patch:
-    name: Apply patch
-    runs-on: ubuntu-latest
-    # Only react to merged PRs for security reasons.
-    # See https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows#pull_request_target.
-    if: >
-      github.event.pull_request.merged
-      && (
-        (
-          github.event.action == 'closed'
-          && contains(github.event.pull_request.labels.*.name, 'apply-to-serverless')
-        )
-        ||
-        (
-          github.event.action == 'labeled'
-          && github.event.label.name == 'apply-to-serverless'
-        )
-      )
-    steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
-        with:
-          persist-credentials: false
-          repository: elastic/elasticsearch-js
-          ref: main
-          path: stack
-          fetch-depth: 0
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
-        with:
-          persist-credentials: false
-          repository: elastic/elasticsearch-serverless-js
-          ref: main
-          path: serverless
-      - 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
-        with:
-          token: ${{ secrets.GH_TOKEN }}
-          path: serverless
-          title: "Apply patch from elastic/elasticsearch-js#${{ github.event.pull_request.number }}"
-          commit-message: "Apply patch from elastic/elasticsearch-js#${{ github.event.pull_request.number }}"
-          body-path: /tmp/pr_body
-          draft: "${{ steps.apply-patch.outputs.PR_DRAFT }}"
-          add-paths: ":!*.rej"

.github/workflows/stale.yml

@@ -8,7 +8,7 @@ jobs:
   stale:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@28ca1036281a5e5922ead5184a1bbf96e5fc984e # v9
+      - uses: actions/stale@5bef64f19d7facfb25b37b414482c7164d639639 # v9
         with:
           stale-issue-label: stale
           stale-pr-label: stale

catalog-info.yaml

@@ -28,6 +28,9 @@ spec:
     spec:
       repository: elastic/elasticsearch-js
       pipeline_file: .buildkite/pipeline.yml
+      env:
+        ELASTIC_SLACK_NOTIFICATIONS_ENABLED: "true"
+        SLACK_NOTIFICATIONS_CHANNEL: "#devtools-notify-javascript"
       teams:
         devtools-team:
           access_level: MANAGE_BUILD_AND_READ
@@ -45,6 +48,9 @@ spec:
         8_x:
           branch: "8.x"
           cronline: "@daily"
-        8_14:
-          branch: "8.16"
+        8_17:
+          branch: "8.17"
+          cronline: "@daily"
+        8_18:
+          branch: "8.18"
           cronline: "@daily"

docs/basic-config.asciidoc

@@ -13,7 +13,6 @@ const client = new Client({
   cloud: { id: '<cloud-id>' },
   auth: { apiKey: 'base64EncodedKey' },
   maxRetries: 5,
-  requestTimeout: 60000,
   sniffOnStart: true
 })
 ----
@@ -82,7 +81,7 @@ _Default:_ `3`
 
 |`requestTimeout`
 |`number` - Max request timeout in milliseconds for each request. +
-_Default:_ `30000`
+_Default:_ No value
 
 |`pingTimeout`
 |`number` - Max ping request timeout in milliseconds for each request. +

docs/changelog.asciidoc

@@ -12,6 +12,66 @@
 
 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.
 
+[discrete]
+===== Remove the default 30-second timeout on all requests sent to Elasticsearch
+
+Setting HTTP timeouts on Elasticsearch requests goes against Elastic's recommendations. See <<timeout-best-practices>> for more information.
+
+[discrete]
+=== 8.17.1
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.17`
+
+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
 

docs/child.asciidoc

@@ -1,22 +1,22 @@
 [[child]]
 === Creating a child client
 
-There are some use cases where you may need multiple instances of the client. 
-You can easily do that by calling `new Client()` as many times as you need, but 
-you will lose all the benefits of using one single client, such as the long 
-living connections and the connection pool handling. To avoid this problem, the 
-client offers a `child` API, which returns a new client instance that shares the 
+There are some use cases where you may need multiple instances of the client.
+You can easily do that by calling `new Client()` as many times as you need, but
+you will lose all the benefits of using one single client, such as the long
+living connections and the connection pool handling. To avoid this problem, the
+client offers a `child` API, which returns a new client instance that shares the
 connection pool with the parent client.
 
-NOTE: The event emitter is shared between the parent and the child(ren). If you 
-extend the parent client, the child client will have the same extensions, while 
+NOTE: The event emitter is shared between the parent and the child(ren). If you
+extend the parent client, the child client will have the same extensions, while
 if the child client adds an extension, the parent client will not be extended.
 
-You can pass to the `child` every client option you would pass to a normal 
-client, but the connection pool specific options (`ssl`, `agent`, `pingTimeout`, 
+You can pass to the `child` every client option you would pass to a normal
+client, but the connection pool specific options (`ssl`, `agent`, `pingTimeout`,
 `Connection`, and `resurrectStrategy`).
 
-CAUTION: If you call `close` in any of the parent/child clients, every client 
+CAUTION: If you call `close` in any of the parent/child clients, every client
 will be closed.
 
 [source,js]
@@ -28,9 +28,8 @@ const client = new Client({
 })
 const child = client.child({
   headers: { 'x-foo': 'bar' },
-  requestTimeout: 1000
 })
 
 client.info().then(console.log, console.log)
 child.info().then(console.log, console.log)
-----
+----

docs/connecting.asciidoc

@@ -414,8 +414,8 @@ The supported request specific options are:
 _Default:_ `null`
 
 |`requestTimeout`
-|`number | string` - Max request timeout for the request in milliseconds, it overrides the client default. +
-_Default:_ `30000`
+|`number | string | null` - Max request timeout for the request in milliseconds. This overrides the client default, which is to not time out at all. See https://www.elastic.co/guide/en/elasticsearch/reference/current/modules-network.html#_http_client_configuration[Elasticsearch best practices for HTML clients] for more info. +
+_Default:_ No timeout
 
 |`retryOnTimeout`
 |`boolean` - Retry requests that have timed out.

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

@@ -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: ".reindexed-v9-ml-anomalies-custom-example",
+  settings: {
+    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

@@ -4,9 +4,11 @@
 [source, js]
 ----
 const response = await client.indices.putSettings({
-  index: "my-index-000001",
+  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.blocks.read_only_allow_delete": null,
+    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 {jsclient}/api-reference.html#_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 {jsclient}/client-helpers.html[bulk helper].
+NOTE: You can also use the <<bulk-helper,bulk helper>>.
 
 [source,js]
 ----

docs/examples/exists.asciidoc

@@ -6,7 +6,7 @@ Check that the document `/game-of-thrones/1` exists.
 NOTE: Since this API uses the `HEAD` method, the body value will be boolean.
 
 [source,js]
----------
+----
 'use strict'
 
 const { Client } = require('@elastic/elasticsearch')
@@ -34,4 +34,4 @@ async function run () {
 }
 
 run().catch(console.log)
----------
+----