Release notes fo 8.18.1 (#2763) (#2778)

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

.buildkite/pipeline.yml

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

.github/make.sh

@@ -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/stale.yml

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

.github/workflows/npm-publish.yml

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

.github/workflows/serverless-patch.yml

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

.github/workflows/stale.yml

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

docs/basic-config.asciidoc

@@ -167,16 +167,19 @@ const client = new Client({
 ----
 
 |`nodeFilter`
-a|`function` - Filters which node not to use for a request. +
+a|`function` - Takes a `Connection` and returns `true` if it can be sent a request, otherwise `false`. +
 _Default:_
 [source,js]
 ----
-function defaultNodeFilter (node) {
-  // avoid master only nodes
-  if (node.roles.master === true &&
-      node.roles.data === false &&
-      node.roles.ingest === false) {
-    return false
+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
   }
   return true
 }

docs/changelog.asciidoc

@@ -2,15 +2,58 @@
 == Release notes
 
 [discrete]
-=== 9.0.0
+=== 8.18.1
 
 [discrete]
-==== Breaking changes
+==== Fixes
 
 [discrete]
-===== Drop support for deprecated `body` parameter
+===== Fix broken node roles and node filter
 
-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.
+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.
 
 [discrete]
 === 8.16.2
@@ -656,7 +699,6 @@ ac.abort()
 ----
 
 [discrete]
-[[remove-body-key]]
 ===== Remove the body key from the request
 
 *Breaking: Yes* | *Migration effort: Small*

docs/doc_examples/00ad41bde67beac991534ae0e04b1296.asciidoc

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

docs/doc_examples/0722b302b2b3275a988d858044f99d5d.asciidoc

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

docs/doc_examples/074e4602d1ca54412380a40867d078bc.asciidoc

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

docs/doc_examples/082e78c7a2061a7c4a52b494e5ede0e8.asciidoc

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

docs/doc_examples/0c52af573c9401a2a687e86a4beb182b.asciidoc

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

docs/doc_examples/0f028f71f04c1d569fab402869565a84.asciidoc

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

docs/doc_examples/120fcf9f55128d6a81d5e87a9c235bbd.asciidoc

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

docs/doc_examples/12adea5d76f73d94d80d42f53f67563f.asciidoc

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

docs/doc_examples/141ef0ebaa3b0772892b79b9bb85efb0.asciidoc

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

docs/doc_examples/1ead35c954963e83f89872048dabdbe9.asciidoc

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

docs/doc_examples/246763219ec06172f7aa57bba28d344a.asciidoc

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

docs/doc_examples/272e27bf1fcc4fe5dbd4092679dd0342.asciidoc

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

docs/doc_examples/2a21674c40f9b182a8944769d20b2357.asciidoc

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

docs/doc_examples/2a67608dadbf220a2f040f3a79d3677d.asciidoc

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

docs/doc_examples/2afd49985950cbcccf727fa858d00067.asciidoc

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

docs/doc_examples/2f72a63c73dd672ac2dc3997ad15dd41.asciidoc

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

docs/doc_examples/31832bd71c31c46a1ccf8d1c210d89d4.asciidoc

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

docs/doc_examples/32c8c86702ccd68eb70f1573409c2a1f.asciidoc

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

docs/doc_examples/3312c82f81816bf76629db9582991812.asciidoc

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

docs/doc_examples/36792c81c053e0555407d1e83e7e054f.asciidoc

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

docs/doc_examples/3722dad876023e0757138dd5a6d3240e.asciidoc

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

docs/doc_examples/38ba93890494bfa7beece58dffa44f98.asciidoc

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

docs/doc_examples/3a204b57072a104d9b50f3a9e064a8f6.asciidoc

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

docs/doc_examples/3bc4a3681e3ea9cb3de49f72085807d8.asciidoc

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

docs/doc_examples/3ea4c971b3f47735dcc207ee2645fa03.asciidoc

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

docs/doc_examples/3f9dcf2aa42f3ecfb5ebfe48c1774103.asciidoc

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

docs/doc_examples/41d24383d29b2808a65258a0a3256e96.asciidoc

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

docs/doc_examples/45954b8aaedfed57012be8b6538b0a24.asciidoc

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

docs/doc_examples/48e142e6c69014e0509d4c9251749d77.asciidoc

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

docs/doc_examples/4de4bb55bbc0a76c75d256f245a3ee3f.asciidoc

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

docs/doc_examples/519e46350316a33162740e5d7968aa2c.asciidoc

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

docs/doc_examples/537bce129338d9227bccb6a0283dab45.asciidoc

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

docs/doc_examples/53d9d2ec9cb8d211772d764e76fe6890.asciidoc

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

docs/doc_examples/5836b09198feb1269ed12839b416123d.asciidoc

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

docs/doc_examples/59aa5216630f80c5dc298fc5bba4a819.asciidoc

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

docs/doc_examples/6b67c6121efb86ee100d40c2646f77b5.asciidoc

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

docs/doc_examples/6baf72c04d48cb04c2f8be609ff3b3b5.asciidoc

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

docs/doc_examples/6e498b9dc753b94abf2618c407fa5cd8.asciidoc

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

docs/doc_examples/6fa02c2ad485bbe91f44b321158250f3.asciidoc

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

docs/doc_examples/730045fae3743c39b612813a42c330c3.asciidoc

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

docs/doc_examples/7478ff69113fb53f41ea07cdf911fa67.asciidoc

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

docs/doc_examples/74b229a6e020113e5749099451979c89.asciidoc

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

docs/doc_examples/77cebba946fe648873a1e7375c13df41.asciidoc

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

docs/doc_examples/790684b45bef2bb848ea932f0fd0cfbd.asciidoc

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

docs/doc_examples/7bdc283b96c7a965fae23013647b8578.asciidoc

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

docs/doc_examples/7dd0d9cc6c5982a2c003d301e90feeba.asciidoc

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

docs/doc_examples/80135e8c644e34cc70ce8a4e7915d1a2.asciidoc

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

docs/doc_examples/82bb6c61dab959f4446dc5ecab7ecbdf.asciidoc

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

docs/doc_examples/8621c05cc7cf3880bde751f6670a0c3a.asciidoc

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

docs/doc_examples/89f547649895176c246bb8c41313ff21.asciidoc

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

docs/doc_examples/8c47c80139f40f25db44f5781ca2dfbe.asciidoc

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

docs/doc_examples/8c639d3eef5c2de29e12bd9c6a42d3d4.asciidoc

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

docs/doc_examples/9250ac57ec81d5192e8ad4c462438489.asciidoc

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

docs/doc_examples/931817b168e055ecf738785c721125dd.asciidoc

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

docs/doc_examples/948418e0ef1b7e7cfee2f11be715d7d2.asciidoc

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

docs/doc_examples/9cc952d4a03264b700136cbc45abc8c6.asciidoc

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

docs/doc_examples/a46f566ca031375658c22f89b87dc6d2.asciidoc

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

docs/doc_examples/a675fafa7c688cb3ea1be09bf887ebf0.asciidoc

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

docs/doc_examples/b590241c4296299b836fbb5a95bdd2dc.asciidoc

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

docs/doc_examples/b6d278737d27973e498ac61cda9e5126.asciidoc

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

docs/doc_examples/ba0e7e0b18fc9ec6c623d40186d1f61b.asciidoc

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

docs/doc_examples/bccd4eb26b1a325d103b12e198a13c08.asciidoc

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

docs/doc_examples/bcd1afb793240b1dddd9fa5d3f21192b.asciidoc

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

docs/doc_examples/bdc55256fa5f701680631a149dbb75a9.asciidoc

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

docs/doc_examples/bdd28276618235487ac96bd6679bc206.asciidoc

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

docs/doc_examples/bf3c3bc41c593a80faebef1df353e483.asciidoc

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

docs/doc_examples/c3b77e11b16e37e9e37e28dec922432e.asciidoc

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

docs/doc_examples/cdb7613b445e6ed6e8b473f9cae1af90.asciidoc

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

docs/doc_examples/cecfaa659af6646b3b67d7b311586fa0.asciidoc

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

docs/doc_examples/d2e7dead222cfbebbd2c21a7cc1893b4.asciidoc

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

docs/doc_examples/d3672a87a857ddb87519788236e57497.asciidoc

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

docs/doc_examples/d3a0f648d0fd50b54a4e9ebe363c5047.asciidoc

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

docs/doc_examples/d5242b1ab0213f25e5e0742032274ce6.asciidoc

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

docs/doc_examples/d6a4548b29e939fb197189c20c7c016f.asciidoc

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

docs/doc_examples/dd16c9c981551c9da47ebb5ef5105fa0.asciidoc

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

docs/doc_examples/df81b88a2192dd6f9912e0c948a44487.asciidoc

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

docs/doc_examples/e375c7da666276c4df6664c6821cd5f4.asciidoc

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

docs/doc_examples/e715fb8c792bf09ac98f0ceca99beb84.asciidoc

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

docs/doc_examples/e77c2f41a7eca765b0c5f734a66d919f.asciidoc

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

docs/doc_examples/ea8c4229afa6dd4f1321355542be9912.asciidoc

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

docs/doc_examples/ec4b43c3ebd8816799fa004596b2f0cb.asciidoc

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

docs/doc_examples/f994498dd6576be657dedce2822d2b9e.asciidoc

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

docs/doc_examples/ffda10edaa7ce087703193c3cb95a426.asciidoc

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

docs/doc_examples/fff86117c47f974074284644e8a97a99.asciidoc

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

docs/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)_.
+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`.
 [source,js]
 ----
 client.diagnostic.on('deserialization', (err, result) => {

package.json

@@ -1,7 +1,7 @@
 {
   "name": "@elastic/elasticsearch",
-  "version": "9.0.0-alpha.1",
-  "versionCanary": "9.0.0-canary.0",
+  "version": "8.18.1",
+  "versionCanary": "8.18.1-canary.0",
   "description": "The official Elasticsearch client for Node.js",
   "main": "./index.js",
   "types": "index.d.ts",
@@ -56,15 +56,14 @@
     "node": ">=18"
   },
   "devDependencies": {
-    "@elastic/request-converter": "8.16.2",
-    "@sinonjs/fake-timers": "github:sinonjs/fake-timers#0bfffc1",
+    "@elastic/request-converter": "8.17.0",
+    "@sinonjs/fake-timers": "github:sinonjs/fake-timers#48f089f",
     "@types/debug": "4.1.12",
     "@types/ms": "0.7.34",
-    "@types/node": "22.10.1",
+    "@types/node": "22.10.7",
     "@types/sinonjs__fake-timers": "8.1.5",
     "@types/split2": "4.2.3",
     "@types/stoppable": "1.1.3",
-    "@types/tap": "15.0.12",
     "chai": "5.1.2",
     "cross-zip": "4.0.1",
     "desm": "1.3.1",
@@ -84,13 +83,13 @@
     "tap": "21.0.1",
     "ts-node": "10.9.2",
     "ts-standard": "12.0.2",
-    "typescript": "5.7.2",
+    "typescript": "5.7.3",
     "workq": "3.0.0",
     "xmlbuilder2": "3.1.1",
     "zx": "7.2.3"
   },
   "dependencies": {
-    "@elastic/transport": "^8.9.1",
+    "@elastic/transport": "^8.9.6",
     "apache-arrow": "^18.0.0",
     "tslib": "^2.4.0"
   },

renovate.json

@@ -1,29 +0,0 @@
-{
-  "$schema": "https://docs.renovatebot.com/renovate-schema.json",
-  "extends": [
-    "local>elastic/renovate-config"
-  ],
-  "schedule": [
-    "* * * * 0"
-  ],
-  "packageRules": [
-    {
-      "matchDepTypes": [
-        "devDependencies"
-      ],
-      "automerge": true,
-      "labels": [
-        "backport 8.x"
-      ]
-    },
-    {
-      "matchPackageNames": [
-        "node"
-      ],
-      "matchManagers": [
-        "dockerfile"
-      ],
-      "enabled": false
-    }
-  ]
-}

scripts/generate-docs-examples.js

@@ -91,6 +91,7 @@ ${source.trim()}
 }
 
 const options = minimist(process.argv.slice(2), {
+  boolean: ['debug'],
   string: ['version'],
   default: {
     version: 'master'
@@ -102,7 +103,7 @@ generate(options.version)
   .catch(err => log.fail(err.message))
   .finally(() => {
     const keys = Object.keys(failures)
-    if (keys.length > 0) {
+    if (keys.length > 0 && options.debug) {
       let message = 'Some examples failed to generate:\n\n'
       for (const key of keys) {
         message += `${key}: ${failures[key]}\n`

src/api/api/async_search.ts

@@ -35,6 +35,7 @@ import {
   TransportResult
 } from '@elastic/transport'
 import * as T from '../types'
+import * as TB from '../typesWithBodyKey'
 interface That { transport: Transport }
 
 export default class AsyncSearch {
@@ -45,12 +46,12 @@ export default class AsyncSearch {
 
   /**
     * Delete an async search. If the asynchronous search is still running, it is cancelled. Otherwise, the saved search results are deleted. If the Elasticsearch security features are enabled, the deletion of a specific async search is restricted to: the authenticated user that submitted the original search request; users that have the `cancel_task` cluster privilege.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/async-search.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/async-search.html | Elasticsearch API documentation}
     */
-  async delete (this: That, params: T.AsyncSearchDeleteRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchDeleteResponse>
-  async delete (this: That, params: T.AsyncSearchDeleteRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchDeleteResponse, unknown>>
-  async delete (this: That, params: T.AsyncSearchDeleteRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchDeleteResponse>
-  async delete (this: That, params: T.AsyncSearchDeleteRequest, options?: TransportRequestOptions): Promise<any> {
+  async delete (this: That, params: T.AsyncSearchDeleteRequest | TB.AsyncSearchDeleteRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchDeleteResponse>
+  async delete (this: That, params: T.AsyncSearchDeleteRequest | TB.AsyncSearchDeleteRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchDeleteResponse, unknown>>
+  async delete (this: That, params: T.AsyncSearchDeleteRequest | TB.AsyncSearchDeleteRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchDeleteResponse>
+  async delete (this: That, params: T.AsyncSearchDeleteRequest | TB.AsyncSearchDeleteRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['id']
     const querystring: Record<string, any> = {}
     const body = undefined
@@ -58,7 +59,7 @@ export default class AsyncSearch {
     for (const key in params) {
       if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }
@@ -77,12 +78,12 @@ export default class AsyncSearch {
 
   /**
     * Get async search results. Retrieve the results of a previously submitted asynchronous search request. If the Elasticsearch security features are enabled, access to the results of a specific async search is restricted to the user or API key that submitted it.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/async-search.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/async-search.html | Elasticsearch API documentation}
     */
-  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchGetResponse<TDocument, TAggregations>>
-  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchGetResponse<TDocument, TAggregations>, unknown>>
-  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchGetResponse<TDocument, TAggregations>>
-  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest, options?: TransportRequestOptions): Promise<any> {
+  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest | TB.AsyncSearchGetRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchGetResponse<TDocument, TAggregations>>
+  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest | TB.AsyncSearchGetRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchGetResponse<TDocument, TAggregations>, unknown>>
+  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest | TB.AsyncSearchGetRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchGetResponse<TDocument, TAggregations>>
+  async get<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params: T.AsyncSearchGetRequest | TB.AsyncSearchGetRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['id']
     const querystring: Record<string, any> = {}
     const body = undefined
@@ -90,7 +91,7 @@ export default class AsyncSearch {
     for (const key in params) {
       if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }
@@ -108,13 +109,13 @@ export default class AsyncSearch {
   }
 
   /**
-    * Get the async search status. Get the status of a previously submitted async search request given its identifier, without retrieving search results. If the Elasticsearch security features are enabled, use of this API is restricted to the `monitoring_user` role.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/async-search.html | Elasticsearch API documentation}
+    * Get the async search status. Get the status of a previously submitted async search request given its identifier, without retrieving search results. If the Elasticsearch security features are enabled, the access to the status of a specific async search is restricted to: * The user or API key that submitted the original async search request. * Users that have the `monitor` cluster privilege or greater privileges.
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/async-search.html | Elasticsearch API documentation}
     */
-  async status (this: That, params: T.AsyncSearchStatusRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchStatusResponse>
-  async status (this: That, params: T.AsyncSearchStatusRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchStatusResponse, unknown>>
-  async status (this: That, params: T.AsyncSearchStatusRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchStatusResponse>
-  async status (this: That, params: T.AsyncSearchStatusRequest, options?: TransportRequestOptions): Promise<any> {
+  async status (this: That, params: T.AsyncSearchStatusRequest | TB.AsyncSearchStatusRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchStatusResponse>
+  async status (this: That, params: T.AsyncSearchStatusRequest | TB.AsyncSearchStatusRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchStatusResponse, unknown>>
+  async status (this: That, params: T.AsyncSearchStatusRequest | TB.AsyncSearchStatusRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchStatusResponse>
+  async status (this: That, params: T.AsyncSearchStatusRequest | TB.AsyncSearchStatusRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['id']
     const querystring: Record<string, any> = {}
     const body = undefined
@@ -122,7 +123,7 @@ export default class AsyncSearch {
     for (const key in params) {
       if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }
@@ -141,21 +142,31 @@ export default class AsyncSearch {
 
   /**
     * Run an async search. When the primary sort of the results is an indexed field, shards get sorted based on minimum and maximum value that they hold for that field. Partial results become available following the sort criteria that was requested. Warning: Asynchronous search does not support scroll or search requests that include only the suggest section. By default, Elasticsearch does not allow you to store an async search response larger than 10Mb and an attempt to do this results in an error. The maximum allowed size for a stored async search response can be set by changing the `search.max_async_search_response_size` cluster level setting.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/async-search.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/async-search.html | Elasticsearch API documentation}
     */
-  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchSubmitResponse<TDocument, TAggregations>>
-  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchSubmitResponse<TDocument, TAggregations>, unknown>>
-  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchSubmitResponse<TDocument, TAggregations>>
-  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest, options?: TransportRequestOptions): Promise<any> {
+  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest | TB.AsyncSearchSubmitRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AsyncSearchSubmitResponse<TDocument, TAggregations>>
+  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest | TB.AsyncSearchSubmitRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AsyncSearchSubmitResponse<TDocument, TAggregations>, unknown>>
+  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest | TB.AsyncSearchSubmitRequest, options?: TransportRequestOptions): Promise<T.AsyncSearchSubmitResponse<TDocument, TAggregations>>
+  async submit<TDocument = unknown, TAggregations = Record<T.AggregateName, T.AggregationsAggregate>> (this: That, params?: T.AsyncSearchSubmitRequest | TB.AsyncSearchSubmitRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['index']
     const acceptedBody: string[] = ['aggregations', 'aggs', 'collapse', 'explain', 'ext', 'from', 'highlight', 'track_total_hits', 'indices_boost', 'docvalue_fields', 'knn', 'min_score', 'post_filter', 'profile', 'query', 'rescore', 'script_fields', 'search_after', 'size', 'slice', 'sort', '_source', 'fields', 'suggest', 'terminate_after', 'timeout', 'track_scores', 'version', 'seq_no_primary_term', 'stored_fields', 'pit', 'runtime_mappings', 'stats']
     const querystring: Record<string, any> = {}
-    const body: Record<string, any> = {}
+    // @ts-expect-error
+    const userBody: any = params?.body
+    let body: Record<string, any> | string
+    if (typeof userBody === 'string') {
+      body = userBody
+    } else {
+      body = userBody != null ? { ...userBody } : undefined
+    }
 
     params = params ?? {}
     for (const key in params) {
       if (acceptedBody.includes(key)) {
+        body = body ?? {}
+        // @ts-expect-error
         if (key === 'sort' && typeof params[key] === 'string' && params[key].includes(':')) { // eslint-disable-line
+          // @ts-expect-error
           querystring[key] = params[key]
         } else {
           // @ts-expect-error
@@ -163,7 +174,7 @@ export default class AsyncSearch {
         }
       } else if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }

src/api/api/autoscaling.ts

@@ -35,6 +35,7 @@ import {
   TransportResult
 } from '@elastic/transport'
 import * as T from '../types'
+import * as TB from '../typesWithBodyKey'
 interface That { transport: Transport }
 
 export default class Autoscaling {
@@ -45,12 +46,12 @@ export default class Autoscaling {
 
   /**
     * Delete an autoscaling policy. NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/autoscaling-delete-autoscaling-policy.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/autoscaling-delete-autoscaling-policy.html | Elasticsearch API documentation}
     */
-  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingDeleteAutoscalingPolicyResponse>
-  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingDeleteAutoscalingPolicyResponse, unknown>>
-  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<T.AutoscalingDeleteAutoscalingPolicyResponse>
-  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<any> {
+  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest | TB.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingDeleteAutoscalingPolicyResponse>
+  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest | TB.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingDeleteAutoscalingPolicyResponse, unknown>>
+  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest | TB.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<T.AutoscalingDeleteAutoscalingPolicyResponse>
+  async deleteAutoscalingPolicy (this: That, params: T.AutoscalingDeleteAutoscalingPolicyRequest | TB.AutoscalingDeleteAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['name']
     const querystring: Record<string, any> = {}
     const body = undefined
@@ -58,7 +59,7 @@ export default class Autoscaling {
     for (const key in params) {
       if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }
@@ -77,12 +78,12 @@ export default class Autoscaling {
 
   /**
     * Get the autoscaling capacity. NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported. This API gets the current autoscaling capacity based on the configured autoscaling policy. It will return information to size the cluster appropriately to the current workload. The `required_capacity` is calculated as the maximum of the `required_capacity` result of all individual deciders that are enabled for the policy. The operator should verify that the `current_nodes` match the operator’s knowledge of the cluster to avoid making autoscaling decisions based on stale or incomplete information. The response contains decider-specific information you can use to diagnose how and why autoscaling determined a certain capacity was required. This information is provided for diagnosis only. Do not use this information to make autoscaling decisions.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/autoscaling-get-autoscaling-capacity.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/autoscaling-get-autoscaling-capacity.html | Elasticsearch API documentation}
     */
-  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingGetAutoscalingCapacityResponse>
-  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingGetAutoscalingCapacityResponse, unknown>>
-  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptions): Promise<T.AutoscalingGetAutoscalingCapacityResponse>
-  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptions): Promise<any> {
+  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest | TB.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingGetAutoscalingCapacityResponse>
+  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest | TB.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingGetAutoscalingCapacityResponse, unknown>>
+  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest | TB.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptions): Promise<T.AutoscalingGetAutoscalingCapacityResponse>
+  async getAutoscalingCapacity (this: That, params?: T.AutoscalingGetAutoscalingCapacityRequest | TB.AutoscalingGetAutoscalingCapacityRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = []
     const querystring: Record<string, any> = {}
     const body = undefined
@@ -91,7 +92,7 @@ export default class Autoscaling {
     for (const key in params) {
       if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }
@@ -107,12 +108,12 @@ export default class Autoscaling {
 
   /**
     * Get an autoscaling policy. NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/autoscaling-get-autoscaling-capacity.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/autoscaling-get-autoscaling-capacity.html | Elasticsearch API documentation}
     */
-  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingGetAutoscalingPolicyResponse>
-  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingGetAutoscalingPolicyResponse, unknown>>
-  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<T.AutoscalingGetAutoscalingPolicyResponse>
-  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<any> {
+  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest | TB.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingGetAutoscalingPolicyResponse>
+  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest | TB.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingGetAutoscalingPolicyResponse, unknown>>
+  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest | TB.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<T.AutoscalingGetAutoscalingPolicyResponse>
+  async getAutoscalingPolicy (this: That, params: T.AutoscalingGetAutoscalingPolicyRequest | TB.AutoscalingGetAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['name']
     const querystring: Record<string, any> = {}
     const body = undefined
@@ -120,7 +121,7 @@ export default class Autoscaling {
     for (const key in params) {
       if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }
@@ -139,16 +140,17 @@ export default class Autoscaling {
 
   /**
     * Create or update an autoscaling policy. NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
-    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/master/autoscaling-put-autoscaling-policy.html | Elasticsearch API documentation}
+    * @see {@link https://www.elastic.co/guide/en/elasticsearch/reference/8.18/autoscaling-put-autoscaling-policy.html | Elasticsearch API documentation}
     */
-  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingPutAutoscalingPolicyResponse>
-  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingPutAutoscalingPolicyResponse, unknown>>
-  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<T.AutoscalingPutAutoscalingPolicyResponse>
-  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<any> {
+  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest | TB.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptionsWithOutMeta): Promise<T.AutoscalingPutAutoscalingPolicyResponse>
+  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest | TB.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptionsWithMeta): Promise<TransportResult<T.AutoscalingPutAutoscalingPolicyResponse, unknown>>
+  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest | TB.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<T.AutoscalingPutAutoscalingPolicyResponse>
+  async putAutoscalingPolicy (this: That, params: T.AutoscalingPutAutoscalingPolicyRequest | TB.AutoscalingPutAutoscalingPolicyRequest, options?: TransportRequestOptions): Promise<any> {
     const acceptedPath: string[] = ['name']
     const acceptedBody: string[] = ['policy']
     const querystring: Record<string, any> = {}
-    let body: any
+    // @ts-expect-error
+    let body: any = params.body ?? undefined
 
     for (const key in params) {
       if (acceptedBody.includes(key)) {
@@ -156,7 +158,7 @@ export default class Autoscaling {
         body = params[key]
       } else if (acceptedPath.includes(key)) {
         continue
-      } else {
+      } else if (key !== 'body') {
         // @ts-expect-error
         querystring[key] = params[key]
       }