Publish 9.0 tags as prereleases (#2524)

* Update tests and bulk helper to stop using body param

* Update compatible-with content-type header for 9.0

.buildkite/pipeline.yml

@@ -1,20 +1,17 @@
 ---
-agents:
-  provider: "gcp"
-  image: family/core-ubuntu-2204
-  memory: "8G"
-  cpu: "2"
-
 steps:
-  - label: ":elasticsearch: :javascript: ES JavaScript ({{ matrix.nodejs }})"
+  - label: ":elasticsearch: :javascript: ES JavaScript ({{ matrix.nodejs }}) Test Suite: {{ matrix.suite }}"
+    agents:
+      provider: "gcp"
     env:
       NODE_VERSION: "{{ matrix.nodejs }}"
-      TEST_SUITE: "platinum"
-      STACK_VERSION: 9.0.0
-      GITHUB_TOKEN_PATH: "secret/ci/elastic-elasticsearch-js/github-token"
-      TEST_ES_STACK: "1"
+      TEST_SUITE: "{{ matrix.suite }}"
+      STACK_VERSION: 8.16.0
     matrix:
       setup:
+        suite:
+          - "free"
+          - "platinum"
         nodejs:
           - "18"
           - "20"
@@ -24,8 +21,11 @@ steps:
   - wait: ~
     continue_on_failure: true
   - label: ":junit: Test results"
+    agents:
+      provider: "gcp"
+      image: family/core-ubuntu-2204
     plugins:
-      - junit-annotate#v2.4.1:
+      - junit-annotate#v2.5.0:
           artifacts: "junit-output/junit-*.xml"
           job-uuid-file-pattern: "junit-(.*).xml"
           fail-build-on-error: true

.buildkite/run-client.sh

@@ -10,29 +10,22 @@ export NODE_VERSION=${NODE_VERSION:-18}
 
 echo "--- :javascript: Building Docker image"
 docker build \
-  --file "$script_path/Dockerfile" \
-  --tag elastic/elasticsearch-js \
-  --build-arg NODE_VERSION="$NODE_VERSION" \
-  .
+       --file "$script_path/Dockerfile" \
+       --tag elastic/elasticsearch-js \
+       --build-arg NODE_VERSION="$NODE_VERSION" \
+       .
 
-GITHUB_TOKEN=$(vault read -field=token "$GITHUB_TOKEN_PATH")
-export GITHUB_TOKEN
-
-echo "--- :javascript: Running tests"
+echo "--- :javascript: Running $TEST_SUITE tests"
 mkdir -p "$repo/junit-output"
 docker run \
-  --network="${network_name}" \
-  --env TEST_ES_STACK \
-  --env STACK_VERSION \
-  --env GITHUB_TOKEN \
-  --env "TEST_ES_SERVER=${elasticsearch_url}" \
-  --env "ELASTIC_PASSWORD=${elastic_password}" \
-  --env "ELASTIC_USER=elastic" \
-  --env "BUILDKITE=true" \
-  --volume "/usr/src/app/node_modules" \
-  --volume "$repo:/usr/src/app" \
-  --volume "$repo/junit-output:/junit-output" \
-  --name elasticsearch-js \
-  --rm \
-  elastic/elasticsearch-js \
-  bash -c "npm run test:integration; [ -f ./report-junit.xml ] && mv ./report-junit.xml /junit-output/junit-$BUILDKITE_JOB_ID.xml || echo 'No JUnit artifact found'"
+       --network="${network_name}" \
+       --env "TEST_ES_SERVER=${elasticsearch_url}" \
+       --env "ELASTIC_PASSWORD=${elastic_password}" \
+       --env "TEST_SUITE=${TEST_SUITE}" \
+       --env "ELASTIC_USER=elastic" \
+       --env "BUILDKITE=true" \
+       --volume "$repo/junit-output:/junit-output" \
+       --name elasticsearch-js \
+       --rm \
+       elastic/elasticsearch-js \
+       bash -c "npm run test:integration; [ -f ./$TEST_SUITE-report-junit.xml ] && mv ./$TEST_SUITE-report-junit.xml /junit-output/junit-$BUILDKITE_JOB_ID.xml || echo 'No JUnit artifact found'"

.dockerignore

@@ -6,6 +6,3 @@ elasticsearch
 lib
 junit-output
 .tap
-rest-api-spec
-yaml-rest-tests
-generated-tests

.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
@@ -176,7 +176,7 @@ 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/stale.yml

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

.github/workflows/npm-publish.yml

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

.github/workflows/serverless-patch.yml

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

.github/workflows/stale.yml

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

.gitignore

@@ -68,7 +68,3 @@ bun.lockb
 test-results
 processinfo
 .tap
-rest-api-spec
-yaml-rest-tests
-generated-tests
-schema

.npmignore

@@ -74,6 +74,3 @@ CONTRIBUTING.md
 src
 bun.lockb
 .tap
-rest-api-spec
-yaml-rest-tests
-generated-tests

docs/basic-config.asciidoc

@@ -167,19 +167,16 @@ 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]
 ----
-function defaultNodeFilter (conn) {
-  if (conn.roles != null) {
-    if (
-      // avoid master-only nodes
-      conn.roles.master &&
-      !conn.roles.data &&
-      !conn.roles.ingest &&
-      !conn.roles.ml
-    ) return false
+function defaultNodeFilter (node) {
+  // avoid master only nodes
+  if (node.roles.master === true &&
+      node.roles.data === false &&
+      node.roles.ingest === false) {
+    return false
   }
   return true
 }

docs/changelog.asciidoc

@@ -2,69 +2,15 @@
 == Release notes
 
 [discrete]
-=== 8.18.2
+=== 9.0.0
 
 [discrete]
-==== Fixes
+==== Breaking changes
 
 [discrete]
-===== Ensure Apache Arrow ES|QL helper uses async iterator
+===== Drop support for deprecated `body` parameter
 
-The `esql.toArrowReader()` helper function was trying to return `RecordBatchStreamReader`, a synchronous iterator, despite the fact that the `apache-arrow` package was, in most cases, automatically coercing it to `AsyncRecordBatchStreamReader`, its asynchronous counterpart. It now is always returned as an async iterator.
-
-[discrete]
-=== 8.18.1
-
-[discrete]
-==== Fixes
-
-[discrete]
-===== Fix broken node roles and node filter
-
-The docs note a `nodeFilter` option on the client that will, by default, filter the nodes based on any `roles` values that are set at instantition. At some point, this functionality was partially disabled. This brings the feature back, ensuring that it matches what the documentation has said it does all along.
-
-[discrete]
-=== 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.
+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]
 === 8.16.2
@@ -710,6 +656,7 @@ ac.abort()
 ----
 
 [discrete]
+[[remove-body-key]]
 ===== Remove the body key from the request
 
 *Breaking: Yes* | *Migration effort: Small*

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/0722b302b2b3275a988d858044f99d5d.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.getMapping({
-  index: "kibana_sample_data_ecommerce",
-});
-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/0e83f140237d75469a428ff403564bb5.asciidoc

@@ -5,8 +5,10 @@
 ----
 const response = await client.cluster.putSettings({
   persistent: {
-    "cluster.routing.allocation.disk.watermark.low": "90%",
-    "cluster.routing.allocation.disk.watermark.high": "95%",
+    "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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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.getAlias({
-  index: ".ml-anomalies-custom-example",
+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

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

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/9ad0864bcd665b63551e944653d32423.asciidoc

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

docs/doc_examples/9cc952d4a03264b700136cbc45abc8c6.asciidoc

@@ -1,30 +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-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/9d47f02a063444da9f098858a1830d28.asciidoc

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

docs/doc_examples/9f16fca9813304e398ee052aa857dbcd.asciidoc

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

docs/doc_examples/a225fc8c134cb21a85bc6025dac9368b.asciidoc

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

docs/doc_examples/a46f566ca031375658c22f89b87dc6d2.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.cat.indices({
-  index: ".ml-anomalies-custom-example",
-  v: "true",
-  h: "index,store.size",
-});
-console.log(response);
-----

docs/doc_examples/a675fafa7c688cb3ea1be09bf887ebf0.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.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/b26b5574438e4eaf146b2428bf537c51.asciidoc

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

docs/doc_examples/b590241c4296299b836fbb5a95bdd2dc.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: {
-    avg_order_value: {
-      avg: {
-        field: "taxful_total_price",
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/b6d278737d27973e498ac61cda9e5126.asciidoc

@@ -1,21 +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_orders: {
-      date_histogram: {
-        field: "order_date",
-        calendar_interval: "day",
-        format: "yyyy-MM-dd",
-        min_doc_count: 0,
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/bb5a1319c496acc862c670cc7224e59a.asciidoc

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

docs/doc_examples/bccd4eb26b1a325d103b12e198a13c08.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.indices.getSettings({
-  index: "_all",
-  expand_wildcards: "all",
-  filter_path: "*.settings.index.*.slowlog",
-});
-console.log(response);
-----

docs/doc_examples/bdc55256fa5f701680631a149dbb75a9.asciidoc

@@ -1,22 +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: {
-    sales_by_category: {
-      terms: {
-        field: "category.keyword",
-        size: 5,
-        order: {
-          _count: "desc",
-        },
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/bdd28276618235487ac96bd6679bc206.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.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/bee3fda7bb07086243424b62e5b16ca7.asciidoc

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

docs/doc_examples/bf3c3bc41c593a80faebef1df353e483.asciidoc

@@ -1,22 +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: "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

@@ -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.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

@@ -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: 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/d2e7dead222cfbebbd2c21a7cc1893b4.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.cluster.state({
-  metric: "metadata",
-  filter_path: "metadata.indices.*.system",
-});
-console.log(response);
-----

docs/doc_examples/d3672a87a857ddb87519788236e57497.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: "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

@@ -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: {
-    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/d6a4548b29e939fb197189c20c7c016f.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: "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

@@ -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.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/ddaadd91b7743a1c7e946ce1b593cd1b.asciidoc

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

docs/doc_examples/e20037f66bf54bcac7d10f536f031f34.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: "<original_number_of_replicas>",
-    },
+    "index.blocks.read_only_allow_delete": null,
   },
 });
 console.log(response);

docs/doc_examples/e375c7da666276c4df6664c6821cd5f4.asciidoc

@@ -1,29 +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-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/ee05714a83d75fb6858e3b9fcbeb8f8b.asciidoc

@@ -5,9 +5,6 @@
 ----
 const response = await client.indices.create({
   index: "retrievers_example",
-  settings: {
-    number_of_shards: 1,
-  },
   mappings: {
     properties: {
       vector: {
@@ -15,9 +12,6 @@ const response = await client.indices.create({
         dims: 3,
         similarity: "l2_norm",
         index: true,
-        index_options: {
-          type: "flat",
-        },
       },
       text: {
         type: "text",
@@ -28,9 +22,6 @@ const response = await client.indices.create({
       topic: {
         type: "keyword",
       },
-      timestamp: {
-        type: "date",
-      },
     },
   },
 });
@@ -44,7 +35,6 @@ 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);
@@ -57,7 +47,6 @@ 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);
@@ -70,7 +59,6 @@ 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);
@@ -83,7 +71,6 @@ 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);
@@ -96,7 +83,6 @@ 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/f4d0ef2e0f76babee83d999fe35127f2.asciidoc

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

docs/doc_examples/f9ee5d55a73f4c1fe7d507609047aefd.asciidoc

@@ -12,13 +12,6 @@ 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/fff86117c47f974074284644e8a97a99.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: "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/helpers.asciidoc

@@ -715,7 +715,7 @@ const result = await client.helpers
 
 ES|QL can return results in multiple binary formats, including https://arrow.apache.org/[Apache Arrow]'s streaming format. Because it is a very efficient format to read, it can be valuable for performing high-performance in-memory analytics. And, because the response is streamed as batches of records, it can be used to produce aggregations and other calculations on larger-than-memory data sets.
 
-`toArrowReader` returns a https://github.com/apache/arrow/blob/520ae44272d491bbb52eb3c9b84864ed7088f11a/js/src/ipc/reader.ts#L216[`AsyncRecordBatchStreamReader`].
+`toArrowReader` returns a https://arrow.apache.org/docs/js/classes/Arrow_dom.RecordBatchReader.html[`RecordBatchStreamReader`].
 
 [source,ts]
 ----
@@ -724,7 +724,7 @@ const reader = await client.helpers
   .toArrowReader()
 
 // print each record as JSON
-for await (const recordBatch of reader) {
+for (const recordBatch of reader) {
   for (const record of recordBatch) {
     console.log(record.toJSON())
   }

docs/observability.asciidoc

@@ -97,7 +97,7 @@ client.diagnostic.on('request', (err, result) => {
 ----
 
 |`deserialization`
-a|Emitted before starting deserialization and decompression. If you want to measure this phase duration, you should measure the time elapsed between this event and `response`. This event might not be emitted in certain situations, like: when `asStream` is set to true; a response is terminated early due to content length being too large; or a response is terminated early by an `AbortController`.
+a|Emitted before starting deserialization and decompression. If you want to measure this phase duration, you should measure the time elapsed between this event and `response`. _(This event might not be emitted in certain situations)_.
 [source,js]
 ----
 client.diagnostic.on('deserialization', (err, result) => {

index.d.ts

@@ -25,4 +25,3 @@ export * as estypes from './lib/api/types'
 export * as estypesWithBody from './lib/api/typesWithBodyKey'
 export { Client, SniffingTransport }
 export type { ClientOptions, NodeOptions } from './lib/client'
-export * as helpers from './lib/helpers'