Auto-generated API code (#2852)

Fixes #2324

(cherry picked from commit 172180cb21)

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

docs/changelog.asciidoc

@@ -1,6 +1,22 @@
 [[changelog-client]]
 == Release notes
 
+[discrete]
+=== 8.17.1
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.17`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
+[discrete]
+===== Report correct transport connection type in telemetry
+
+The client's telemetry reporting mechanism was incorrectly reporting all traffic as using `HttpConnection` when the default is `UndiciConnection`. https://github.com/elastic/elasticsearch-js/issues/2324[#2324]
+
 [discrete]
 === 8.17.0
 
@@ -13,6 +29,22 @@
 You can find all the API changes
 https://www.elastic.co/guide/en/elasticsearch/reference/8.17/release-notes-8.17.0.html[here].
 
+[discrete]
+=== 8.16.4
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.16`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
+[discrete]
+===== Report correct transport connection type in telemetry
+
+The client's telemetry reporting mechanism was incorrectly reporting all traffic as using `HttpConnection` when the default is `UndiciConnection`. https://github.com/elastic/elasticsearch-js/issues/2324[#2324]
+
 [discrete]
 === 8.16.3
 

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/0bee07a581c5776e068f6f4efad5a399.asciidoc

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

docs/doc_examples/0dfde6a9d953822fd4b3aa0121ddd8fb.asciidoc

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

docs/doc_examples/0f028f71f04c1d569fab402869565a84.asciidoc

@@ -0,0 +1,15 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.indices.putSettings({
+  index: ".reindexed-v9-ml-anomalies-custom-example",
+  settings: {
+    index: {
+      number_of_replicas: "<original_number_of_replicas>",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/120fcf9f55128d6a81d5e87a9c235bbd.asciidoc

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

docs/doc_examples/12adea5d76f73d94d80d42f53f67563f.asciidoc

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

docs/doc_examples/141ef0ebaa3b0772892b79b9bb85efb0.asciidoc

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

docs/doc_examples/16634cfa7916cf4e8048a1d70e6240f2.asciidoc

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

docs/doc_examples/19c00c6b29bc7dbc5e92b3668da2da93.asciidoc

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

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/2a1eece9a59ac1773edcf0a932c26de0.asciidoc

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

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/2afd49985950cbcccf727fa858d00067.asciidoc

@@ -6,13 +6,13 @@
 const response = await client.indices.create({
   index: "test-index",
   query: {
-    semantic: {
-      field: "my_semantic_field",
+    match: {
+      my_field: "Which country is Paris in?",
     },
   },
   highlight: {
     fields: {
-      my_semantic_field: {
+      my_field: {
         type: "semantic",
         number_of_fragments: 2,
         order: "score",

docs/doc_examples/2afdf0d83724953aa2875b5fb37d60cc.asciidoc

@@ -3,10 +3,12 @@
 
 [source, js]
 ----
-const response = await client.esql.asyncQueryGet({
-  id: "FmNJRUZ1YWZCU3dHY1BIOUhaenVSRkEaaXFlZ3h4c1RTWFNocDdnY2FSaERnUTozNDE=",
-  wait_for_completion_timeout: "30s",
-  body: null,
+const response = await client.transport.request({
+  method: "GET",
+  path: "/_query/async/FmNJRUZ1YWZCU3dHY1BIOUhaenVSRkEaaXFlZ3h4c1RTWFNocDdnY2FSaERnUTozNDE=",
+  querystring: {
+    wait_for_completion_timeout: "30s",
+  },
 });
 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/3f1fe5f5f99b98d0891f38003e10b636.asciidoc

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

docs/doc_examples/3f9dcf2aa42f3ecfb5ebfe48c1774103.asciidoc

@@ -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/405511f7c1f12cc0a227b4563fe7b2e2.asciidoc

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

docs/doc_examples/41d24383d29b2808a65258a0a3256e96.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.indices.create({
+  index: "jinaai-index",
+  mappings: {
+    properties: {
+      content: {
+        type: "semantic_text",
+        inference_id: "jinaai-embeddings",
+      },
+    },
+  },
+});
+console.log(response);
+----

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/4b91ad7c9b44e07db4a4e81390f19ad3.asciidoc

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

docs/doc_examples/4de4bb55bbc0a76c75d256f245a3ee3f.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: "sparse_embedding",
+  inference_id: "elser-model-eis",
+  inference_config: {
+    service: "elastic",
+    service_settings: {
+      model_name: "elser",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/519e46350316a33162740e5d7968aa2c.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.search({
+  index: "image-index",
+  knn: {
+    field: "image-vector",
+    query_vector: [-5, 9, -12],
+    k: 10,
+    num_candidates: 100,
+    rescore_vector: {
+      oversample: 2,
+    },
+  },
+  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/57dc15e5ad663c342fd5c1d86fcd1b29.asciidoc

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

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/5bba213a7f543190139d1a69ab2ed076.asciidoc

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

docs/doc_examples/6b67c6121efb86ee100d40c2646f77b5.asciidoc

@@ -4,9 +4,11 @@
 [source, js]
 ----
 const response = await client.indices.putSettings({
-  index: "my-index-000001",
+  index: "*",
   settings: {
     "index.search.slowlog.include.user": true,
+    "index.search.slowlog.threshold.fetch.warn": "30s",
+    "index.search.slowlog.threshold.query.warn": "30s",
   },
 });
 console.log(response);

docs/doc_examples/6b6fd0a5942dfb9762ad2790cf421a80.asciidoc

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

docs/doc_examples/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/6f3b723bf6179b96c3413597ed7f49e1.asciidoc

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

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/77518e8c6198acfe77c0934fd2fe65cb.asciidoc

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

docs/doc_examples/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/7ba29f0be2297b54a640b0a17d7ef5ca.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.transport.request({
+  method: "DELETE",
+  path: "/_ingest/ip_location/database/my-database-id",
+});
+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: ".elser-2-elasticsearch",
-      },
       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/80dd7f5882c59b9c1c90e8351937441f.asciidoc

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

docs/doc_examples/82bb6c61dab959f4446dc5ecab7ecbdf.asciidoc

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

docs/doc_examples/8621c05cc7cf3880bde751f6670a0c3a.asciidoc

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

docs/doc_examples/89f547649895176c246bb8c41313ff21.asciidoc

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

docs/doc_examples/8c47c80139f40f25db44f5781ca2dfbe.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.security.queryRole({
-  sort: ["name"],
+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/91e106a2affbc8df32cd940684a779ed.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.transport.request({
+  method: "PUT",
+  path: "/_ingest/ip_location/database/my-database-1",
+  body: {
+    name: "GeoIP2-Domain",
+    maxmind: {
+      account_id: "1234567",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/9250ac57ec81d5192e8ad4c462438489.asciidoc

@@ -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/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/99fb82d49ac477e6a9dfdd71f9465374.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.transport.request({
+  method: "DELETE",
+  path: "/_ingest/ip_location/database/example-database-id",
+});
+console.log(response);
+----

docs/doc_examples/9afa0844883b7471883aa378a8dd10b4.asciidoc

@@ -3,9 +3,9 @@
 
 [source, js]
 ----
-const response = await client.searchApplication.postBehavioralAnalyticsEvent({
-  collection_name: "my_analytics_collection",
-  event_type: "search_click",
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_application/analytics/my_analytics_collection/event/search_click",
   body: {
     session: {
       id: "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9",

docs/doc_examples/9c01db07c9ac395b6370e3b33965c21f.asciidoc

@@ -3,7 +3,9 @@
 
 [source, js]
 ----
-const response = await client.security.oidcAuthenticate({
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_security/oidc/authenticate",
   body: {
     redirect_uri:
       "https://oidc-kibana.elastic.co:5603/api/security/oidc/callback?code=jtI3Ntt8v3_XvcLzCFGq&state=4dbrihtIAt3wBTwo6DxK-vdk-sSyDBV8Yf0AjdkdT5I",

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/a162eb50853331c80596f5994e9d1c38.asciidoc

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

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/b0bddf2ffaa83049b195829c06b875cd.asciidoc

@@ -3,9 +3,9 @@
 
 [source, js]
 ----
-const response = await client.searchApplication.renderQuery({
-  name: "my_search_application",
-  body: null,
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_application/search_application/my_search_application/_render_query",
 });
 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/b62eaa20c4e0e48134a6d1d1b3c30b26.asciidoc

@@ -208,10 +208,13 @@ const response = await client.bulk({
 });
 console.log(response);
 
-const response1 = await client.textStructure.findFieldStructure({
-  index: "test-logs",
-  field: "message",
-  body: null,
+const response1 = await client.transport.request({
+  method: "GET",
+  path: "/_text_structure/find_field_structure",
+  querystring: {
+    index: "test-logs",
+    field: "message",
+  },
 });
 console.log(response1);
 ----

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/bcdfaa4487747249699a86a0dcd22f5e.asciidoc

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

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/c580990a70028bb49cca8a6bde86bbf6.asciidoc

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

docs/doc_examples/ccc613951c61f0b17e1ed8a2d3ae54a2.asciidoc

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

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/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/d35c8cf7a98b3f112e1de8797ec6689d.asciidoc

@@ -3,7 +3,9 @@
 
 [source, js]
 ----
-const response = await client.security.oidcPrepareAuthentication({
+const response = await client.transport.request({
+  method: "POST",
+  path: "/_security/oidc/prepare",
   body: {
     iss: "http://127.0.0.1:8080",
     login_hint: "this_is_an_opaque_string",

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/d4df39f72d3a3b80cd4042f6a21c3f19.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.transport.request({
+  method: "PUT",
+  path: "/_ingest/ip_location/database/my-database-2",
+  body: {
+    name: "standard_location",
+    ipinfo: {},
+  },
+});
+console.log(response);
+----

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/d8c053ee26c1533ce936ec81101d8e1b.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.transport.request({
+  method: "GET",
+  path: "/_ingest/ip_location/database/my-database-id",
+});
+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/dd71b0c9f9197684ff29c61062c55660.asciidoc

@@ -3,6 +3,9 @@
 
 [source, js]
 ----
-const response = await client.security.getSettings();
+const response = await client.transport.request({
+  method: "GET",
+  path: "/_security/settings",
+});
 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/e3019fd5f23458ae49ad9854c97d321c.asciidoc

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