Auto-generated API code (#2578)

(cherry picked from commit ed3cace127)

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

.dockerignore

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

.github/make.sh

@@ -150,7 +150,7 @@ if [[ -z "${BUILDKITE+x}" ]] && [[ -z "${CI+x}" ]] && [[ -z "${GITHUB_ACTIONS+x}
     -u "$(id -u):$(id -g)" \
     --volume "$repo:/usr/src/elasticsearch-js" \
     --volume /usr/src/elasticsearch-js/node_modules \
-    --volume "$(realpath $repo/../elastic-client-generator-js):/usr/src/elastic-client-generator-js" \
+    --volume "$(realpath "$repo/../elastic-client-generator-js"):/usr/src/elastic-client-generator-js" \
     --env "WORKFLOW=$WORKFLOW" \
     --name make-elasticsearch-js \
     --rm \
@@ -159,6 +159,14 @@ if [[ -z "${BUILDKITE+x}" ]] && [[ -z "${CI+x}" ]] && [[ -z "${GITHUB_ACTIONS+x}
       node .buildkite/make.mjs --task $TASK ${TASK_ARGS[*]}"
 else
   echo -e "\033[34;1mINFO: Running in CI mode"
+
+  # determine branch to clone
+  GENERATOR_BRANCH="main"
+  if [[ "$VERSION" == 8.* ]]; then
+    GENERATOR_BRANCH="8.x"
+  fi
+  echo -e "\033[34;1mINFO: Generator branch: $GENERATOR_BRANCH"
+
   docker run \
     --volume "$repo:/usr/src/elasticsearch-js" \
     --volume /usr/src/elasticsearch-js/node_modules \
@@ -168,7 +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[*]}"

.gitignore

@@ -64,3 +64,7 @@ test/bundlers/parcel-test/.parcel-cache
 
 lib
 junit-output
+bun.lockb
+test-results
+processinfo
+.tap

.npmignore

@@ -72,3 +72,5 @@ CODE_OF_CONDUCT.md
 CONTRIBUTING.md
 
 src
+bun.lockb
+.tap

docs/changelog.asciidoc

@@ -1,6 +1,44 @@
 [[changelog-client]]
 == Release notes
 
+[discrete]
+=== 8.15.3
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.15`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
+[discrete]
+===== Drop testing artifacts from npm package
+
+Tap, the unit testing tool, was recently upgraded and started writing to a `.tap` directory. Since tests are run prior to an `npm publish` in CI, this directory was being included in the published package and bloating its size.
+
+[discrete]
+=== 8.15.2
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.15`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
+[discrete]
+=== 8.15.1
+
+[discrete]
+==== Fixes
+
+[discrete]
+===== Improved support for Elasticsearch `v8.15`
+
+Updated TypeScript types based on fixes and improvements to the Elasticsearch specification.
+
 [discrete]
 === 8.15.0
 

docs/configuration.asciidoc

@@ -7,5 +7,6 @@ section, you can see the possible options that you can use to configure it.
 
 * <<basic-config>>
 * <<advanced-config>>
+* <<timeout-best-practices>>
 * <<child>>
 * <<client-testing>>

docs/doc_examples/015e6e6132b6d6d44bddb06bc3b316ed.asciidoc

@@ -0,0 +1,46 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "retrievers_example",
+  retriever: {
+    rrf: {
+      retrievers: [
+        {
+          standard: {
+            query: {
+              range: {
+                year: {
+                  gt: 2023,
+                },
+              },
+            },
+          },
+        },
+        {
+          standard: {
+            query: {
+              term: {
+                topic: "elastic",
+              },
+            },
+          },
+        },
+      ],
+      rank_window_size: 10,
+      rank_constant: 1,
+    },
+  },
+  _source: false,
+  aggs: {
+    topics: {
+      terms: {
+        field: "topic",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/0165d22da5f2fc7678392b31d8eb5566.asciidoc

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

docs/doc_examples/01ae196538fac197eedbbf458a4ef31b.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       kwd: {
         type: "keyword",

docs/doc_examples/0709a38613d2de90d418ce12b36af30e.asciidoc

@@ -0,0 +1,8 @@
+// This 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.reroute();
+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/0bc6155e0c88062a4d8490da49db3aa8.asciidoc

@@ -0,0 +1,49 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.search({
+  index: "retrievers_example_nested",
+  retriever: {
+    rrf: {
+      retrievers: [
+        {
+          standard: {
+            query: {
+              nested: {
+                path: "nested_field",
+                inner_hits: {
+                  name: "nested_vector",
+                  _source: false,
+                  fields: ["nested_field.paragraph_id"],
+                },
+                query: {
+                  knn: {
+                    field: "nested_field.nested_vector",
+                    query_vector: [1, 0, 0.5],
+                    k: 10,
+                  },
+                },
+              },
+            },
+          },
+        },
+        {
+          standard: {
+            query: {
+              term: {
+                topic: "ai",
+              },
+            },
+          },
+        },
+      ],
+      rank_window_size: 10,
+      rank_constant: 1,
+    },
+  },
+  _source: ["topic"],
+});
+console.log(response);
+----

docs/doc_examples/0bee07a581c5776e068f6f4efad5a399.asciidoc

@@ -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.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  ",
+    include_ccs_metadata: true,
+  },
+});
+console.log(response);
+----

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/0c8be7aec84ea86b243904f5d4162f5a.asciidoc

@@ -4,14 +4,12 @@
 [source, js]
 ----
 const response = await client.search({
-  index: "my-index",
+  index: "cooking_blog",
   query: {
-    semantic: {
-      field: "inference_field",
-      query: "mountain lake",
-      inner_hits: {
-        from: 1,
-        size: 1,
+    match: {
+      title: {
+        query: "fluffy pancakes breakfast",
+        minimum_should_match: 2,
       },
     },
   },

docs/doc_examples/0d30077cd34e93377a3a86f2ebd69415.asciidoc

@@ -9,7 +9,7 @@ const response = await client.connector.put({
   name: "My Connector",
   description: "My Connector to sync data to Elastic index from Google Drive",
   service_type: "google_drive",
-  language: "english",
+  language: "en",
 });
 console.log(response);
 ----

docs/doc_examples/0d689ac6e78be5d438f9b5d441be2b44.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.search({
+  index: "retrievers_example",
+  retriever: {
+    rrf: {
+      retrievers: [
+        {
+          standard: {
+            query: {
+              term: {
+                topic: "elastic",
+              },
+            },
+          },
+        },
+        {
+          rrf: {
+            retrievers: [
+              {
+                standard: {
+                  query: {
+                    query_string: {
+                      query:
+                        "(information retrieval) OR (artificial intelligence)",
+                      default_field: "text",
+                    },
+                  },
+                },
+              },
+              {
+                knn: {
+                  field: "vector",
+                  query_vector: [0.23, 0.67, 0.89],
+                  k: 3,
+                  num_candidates: 5,
+                },
+              },
+            ],
+            rank_window_size: 10,
+            rank_constant: 1,
+          },
+        },
+      ],
+      rank_window_size: 10,
+      rank_constant: 1,
+    },
+  },
+  _source: false,
+  size: 1,
+  explain: true,
+});
+console.log(response);
+----

docs/doc_examples/0dfde6a9d953822fd4b3aa0121ddd8fb.asciidoc

@@ -3,8 +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/0e31b8ad176b31028becf9500989bcbd.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.inference.put({
+  task_type: "text_embedding",
+  inference_id: "watsonx-embeddings",
+  inference_config: {
+    service: "watsonxai",
+    service_settings: {
+      api_key: "<api_key>",
+      url: "<url>",
+      model_id: "ibm/slate-30m-english-rtrvr",
+      project_id: "<project_id>",
+      api_version: "2024-03-14",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/0e83f140237d75469a428ff403564bb5.asciidoc

@@ -1,15 +0,0 @@
-// This file is autogenerated, DO NOT EDIT
-// Use `node scripts/generate-docs-examples.js` to generate the docs examples
-
-[source, js]
-----
-const response = await client.cluster.putSettings({
-  persistent: {
-    "cluster.routing.allocation.disk.watermark.low": "100gb",
-    "cluster.routing.allocation.disk.watermark.high": "50gb",
-    "cluster.routing.allocation.disk.watermark.flood_stage": "10gb",
-    "cluster.info.update.interval": "1m",
-  },
-});
-console.log(response);
-----

docs/doc_examples/11be807bdeaeecc8174dec88e0851ea7.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: "GET",
+  path: "/_connector/_sync_job",
+  querystring: {
+    connector_id: "my-connector-id",
+    size: "1",
+  },
+});
+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/12e9e758f7f18a6cbf27e9d0aea57a19.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.update({
+  index: ".elastic-connectors",
+  id: "connector_id",
+  doc: {
+    features: {
+      native_connector_api_keys: {
+        enabled: true,
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/141ef0ebaa3b0772892b79b9bb85efb0.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.inference.put({
+  task_type: "my-inference-endpoint",
+  inference_id: "_update",
+  inference_config: {
+    service_settings: {
+      api_key: "<API_KEY>",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/1522a9297151d7046e6345b9b27539ca.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.connector.updateConfiguration({
+  connector_id: "my-connector-id",
+  values: {
+    host: "127.0.0.1",
+    port: 5432,
+    username: "myuser",
+    password: "mypassword",
+    database: "chinook",
+    schema: "public",
+    tables: "album,artist",
+  },
+});
+console.log(response);
+----

docs/doc_examples/15f769bbd7b5fddeb3353ae726b71b14.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-bit-vectors",
+  query: {
+    script_score: {
+      query: {
+        match_all: {},
+      },
+      script: {
+        source: "dotProduct(params.query_vector, 'my_dense_vector')",
+        params: {
+          query_vector: [
+            0.23, 1.45, 3.67, 4.89, -0.56, 2.34, 3.21, 1.78, -2.45, 0.98, -0.12,
+            3.45, 4.56, 2.78, 1.23, 0.67, 3.89, 4.12, -2.34, 1.56, 0.78, 3.21,
+            4.12, 2.45, -1.67, 0.34, -3.45, 4.56, -2.78, 1.23, -0.67, 3.89,
+            -4.34, 2.12, -1.56, 0.78, -3.21, 4.45, 2.12, 1.67,
+          ],
+        },
+      },
+    },
+  },
+});
+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/16a7ce08b4a6b3af269f27eecc71d664.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.delete({
+  index: "books",
+});
+console.log(response);
+
+const response1 = await client.indices.delete({
+  index: "my-explicit-mappings-books",
+});
+console.log(response1);
+----

docs/doc_examples/17316a81c9dbdd120b7754116bf0461c.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.security.createApiKey({
+  name: "my-connector-api-key",
+  role_descriptors: {
+    "my-connector-connector-role": {
+      cluster: ["monitor", "manage_connector"],
+      indices: [
+        {
+          names: [
+            "my-index_name",
+            ".search-acl-filter-my-index_name",
+            ".elastic-connectors*",
+          ],
+          privileges: ["all"],
+          allow_restricted_indices: false,
+        },
+      ],
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/17b1647c8509543f2388c886f2584a20.asciidoc

@@ -16,7 +16,7 @@ const response = await client.search({
         },
       },
       field: "text",
-      inference_id: "my-cohere-rerank-model",
+      inference_id: "elastic-rerank",
       inference_text: "How often does the moon hide the sun?",
       rank_window_size: 100,
       min_score: 0.5,

docs/doc_examples/193704020a19714dec390452a4e75e8d.asciidoc

@@ -4,12 +4,7 @@
 [source, js]
 ----
 const response = await client.indices.create({
-  index: "idx",
-  mappings: {
-    _source: {
-      mode: "synthetic",
-    },
-  },
+  index: "books",
 });
 console.log(response);
 ----

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/1a7483796087053ba55029d0dc2ab356.asciidoc

@@ -4,14 +4,16 @@
 [source, js]
 ----
 const response = await client.index({
-  index: "my-index",
-  id: "lake_tahoe",
+  index: "mv",
+  refresh: "true",
   document: {
-    inference_field: [
-      "Lake Tahoe is the largest alpine lake in North America",
-      "When hiking in the area, please be on alert for bears",
-    ],
+    a: [2, null, 1],
   },
 });
 console.log(response);
+
+const response1 = await client.esql.query({
+  query: "FROM mv | LIMIT 1",
+});
+console.log(response1);
 ----

docs/doc_examples/1aa96eeaf63fc967e166d1a2fcdccccc.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.indices.create({
-  index: "my-index-000003",
+  index: "my-index-000002",
   mappings: {
     properties: {
       metrics: {
@@ -29,7 +29,7 @@ const response = await client.indices.create({
 console.log(response);
 
 const response1 = await client.indices.getMapping({
-  index: "my-index-000003",
+  index: "my-index-000002",
 });
 console.log(response1);
 ----

docs/doc_examples/1c9dac4183a3532c91dbd1a46907729b.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.cluster.reroute({
-  metric: "none",
+const response = await client.indices.delete({
+  index: "music",
 });
 console.log(response);
 ----

docs/doc_examples/1fb2c77c0988bc6545040b20e3afa7e9.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.security.createApiKey({
+  name: "john-api-key",
+  expiration: "1d",
+  role_descriptors: {
+    "sharepoint-online-role": {
+      index: [
+        {
+          names: ["sharepoint-search-application"],
+          privileges: ["read"],
+          query: {
+            template: {
+              params: {
+                access_control: ["john@example.co", "Engineering Members"],
+              },
+              source:
+                '\n              {\n                "bool": {\n                  "should": [\n                    {\n                      "bool": {\n                        "must_not": {\n                          "exists": {\n                            "field": "_allow_access_control"\n                          }\n                        }\n                      }\n                    },\n                    {\n                      "terms": {\n                        "_allow_access_control.enum": {{#toJson}}access_control{{/toJson}}\n                      }\n                    }\n                  ]\n                }\n              }\n              ',
+            },
+          },
+        },
+      ],
+      restriction: {
+        workflows: ["search_application_query"],
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/216e24f05cbb82c1718713fbab8623d2.asciidoc

@@ -5,7 +5,7 @@
 ----
 const response = await client.ingest.putPipeline({
   id: "geoip",
-  description: "Add geoip info",
+  description: "Add ip geolocation info",
   processors: [
     {
       geoip: {

docs/doc_examples/21d41e8cbd107fbdf0901f885834dafc.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       card: {
         type: "wildcard",

docs/doc_examples/22b176a184517cf1b5801f5eb4f17f97.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.indices.unfreeze({
-  index: "my-index-000001",
+const response = await client.indices.rollover({
+  alias: "datastream",
 });
 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/2577acb462b95bd4394523cf2f8a661f.asciidoc

@@ -1,28 +0,0 @@
-// This file is autogenerated, DO NOT EDIT
-// Use `node scripts/generate-docs-examples.js` to generate the docs examples
-
-[source, js]
-----
-const response = await client.esql.query({
-  format: "txt",
-  query:
-    "\n      FROM library\n    | SORT page_count DESC\n    | KEEP name, author\n    | LOOKUP era ON author\n    | LIMIT 5\n  ",
-  tables: {
-    era: {
-      author: {
-        keyword: [
-          "Frank Herbert",
-          "Peter F. Hamilton",
-          "Vernor Vinge",
-          "Alastair Reynolds",
-          "James S.A. Corey",
-        ],
-      },
-      era: {
-        keyword: ["The New Wave", "Diamond", "Diamond", "Diamond", "Hadron"],
-      },
-    },
-  },
-});
-console.log(response);
-----

docs/doc_examples/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/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/2afdf0d83724953aa2875b5fb37d60cc.asciidoc

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

docs/doc_examples/2bb41b0b4876ce98cd0cd8fb6d337f18.asciidoc

@@ -1,16 +0,0 @@
-// This file is autogenerated, DO NOT EDIT
-// Use `node scripts/generate-docs-examples.js` to generate the docs examples
-
-[source, js]
-----
-const response = await client.cluster.putSettings({
-  persistent: {
-    "cluster.indices.close.enable": false,
-    "indices.recovery.max_bytes_per_sec": "50mb",
-  },
-  transient: {
-    "*": null,
-  },
-});
-console.log(response);
-----

docs/doc_examples/2c079d1ae4819a0c206b9e1aa5623523.asciidoc

@@ -0,0 +1,77 @@
+// This 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-000001",
+  mappings: {
+    properties: {
+      attributes: {
+        type: "passthrough",
+        priority: 10,
+        properties: {
+          id: {
+            type: "keyword",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+
+const response1 = await client.index({
+  index: "my-index-000001",
+  id: 1,
+  document: {
+    attributes: {
+      id: "foo",
+      zone: 10,
+    },
+  },
+});
+console.log(response1);
+
+const response2 = await client.search({
+  index: "my-index-000001",
+  query: {
+    bool: {
+      must: [
+        {
+          match: {
+            id: "foo",
+          },
+        },
+        {
+          match: {
+            zone: 10,
+          },
+        },
+      ],
+    },
+  },
+});
+console.log(response2);
+
+const response3 = await client.search({
+  index: "my-index-000001",
+  query: {
+    bool: {
+      must: [
+        {
+          match: {
+            "attributes.id": "foo",
+          },
+        },
+        {
+          match: {
+            "attributes.zone": 10,
+          },
+        },
+      ],
+    },
+  },
+});
+console.log(response3);
+----

docs/doc_examples/2c86840a46242a38cf82024a9321be46.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.indices.create({
+  index: "my-explicit-mappings-books",
+  mappings: {
+    dynamic: false,
+    properties: {
+      name: {
+        type: "text",
+      },
+      author: {
+        type: "text",
+      },
+      release_date: {
+        type: "date",
+        format: "yyyy-MM-dd",
+      },
+      page_count: {
+        type: "integer",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/2d0244c020075595acb625aa5ba8f455.asciidoc

@@ -0,0 +1,25 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.index({
+  index: "idx_keep",
+  id: 1,
+  document: {
+    path: {
+      to: [
+        {
+          foo: [3, 2, 1],
+        },
+        {
+          foo: [30, 20, 10],
+        },
+      ],
+      bar: "baz",
+    },
+    ids: [200, 100, 300, 100],
+  },
+});
+console.log(response);
+----

docs/doc_examples/2e7844477b41fcfa9efefee4ec0e7101.asciidoc

@@ -0,0 +1,43 @@
+// This 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",
+  retriever: {
+    rule: {
+      match_criteria: {
+        query_string: "puggles",
+        user_country: "us",
+      },
+      ruleset_ids: ["my-ruleset"],
+      retriever: {
+        rrf: {
+          retrievers: [
+            {
+              standard: {
+                query: {
+                  query_string: {
+                    query: "pugs",
+                  },
+                },
+              },
+            },
+            {
+              standard: {
+                query: {
+                  query_string: {
+                    query: "puggles",
+                  },
+                },
+              },
+            },
+          ],
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

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

docs/doc_examples/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/334811cfceb6858aeec5b3461717dd63.asciidoc

@@ -5,7 +5,7 @@
 ----
 const response = await client.ingest.putPipeline({
   id: "geoip",
-  description: "Add geoip info",
+  description: "Add ip geolocation info",
   processors: [
     {
       geoip: {

docs/doc_examples/339c4e5af9f9069ad9912aa574488b59.asciidoc

@@ -0,0 +1,52 @@
+// This 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-bit-vectors",
+  mappings: {
+    properties: {
+      my_dense_vector: {
+        type: "dense_vector",
+        index: false,
+        element_type: "bit",
+        dims: 40,
+      },
+    },
+  },
+});
+console.log(response);
+
+const response1 = await client.index({
+  index: "my-index-bit-vectors",
+  id: 1,
+  document: {
+    my_dense_vector: [8, 5, -15, 1, -7],
+  },
+});
+console.log(response1);
+
+const response2 = await client.index({
+  index: "my-index-bit-vectors",
+  id: 2,
+  document: {
+    my_dense_vector: [-1, 115, -3, 4, -128],
+  },
+});
+console.log(response2);
+
+const response3 = await client.index({
+  index: "my-index-bit-vectors",
+  id: 3,
+  document: {
+    my_dense_vector: [2, 18, -5, 0, -124],
+  },
+});
+console.log(response3);
+
+const response4 = await client.indices.refresh({
+  index: "my-index-bit-vectors",
+});
+console.log(response4);
+----

docs/doc_examples/37f367ca81a16d3aef4ef7126ec33a2e.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.search({
+  index: "movies",
+  size: 10,
+  retriever: {
+    rescorer: {
+      rescore: {
+        query: {
+          window_size: 50,
+          rescore_query: {
+            script_score: {
+              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/3ab8f65fcb55a0e3664c55749ec41efd.asciidoc

@@ -29,6 +29,7 @@ const response = await client.indices.create({
             "arabic_normalization",
             "persian_normalization",
             "persian_stop",
+            "persian_stem",
           ],
         },
       },

docs/doc_examples/3ea4c971b3f47735dcc207ee2645fa03.asciidoc

@@ -6,15 +6,8 @@
 const response = await client.indices.updateAliases({
   actions: [
     {
-      remove: {
-        index: "my-index-000001",
-        alias: "my-index",
-      },
-    },
-    {
-      add: {
-        index: "my-index-000002",
-        alias: "my-index",
+      remove_index: {
+        index: "my-index-2099.05.06-000001",
       },
     },
   ],

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/40f287bf733420bbab134b74c7d0ea5d.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.index({
+  index: "amazon-reviews",
+  id: 1,
+  document: {
+    review_text:
+      "This product is lifechanging! I'm telling all my friends about it.",
+    review_vector: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
+  },
+});
+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/44198781d164a15be633d4469485a544.asciidoc

@@ -4,15 +4,16 @@
 [source, js]
 ----
 const response = await client.search({
-  index: "test-index",
+  index: "my-index-bit-vectors",
   query: {
-    nested: {
-      path: "inference_field.inference.chunks",
+    script_score: {
       query: {
-        sparse_vector: {
-          field: "inference_field.inference.chunks.embeddings",
-          inference_id: "my-inference-id",
-          query: "mountain lake",
+        match_all: {},
+      },
+      script: {
+        source: "dotProduct(params.query_vector, 'my_dense_vector')",
+        params: {
+          query_vector: [8, 5, -15, 1, -7],
         },
       },
     },

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/49a19615ebe2c013b8321152163478ab.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.index({
+  index: "my-index-000001",
+  id: 1,
+  refresh: "true",
+  document: {
+    text: "quick brown fox",
+  },
+});
+console.log(response);
+
+const response1 = await client.index({
+  index: "my-index-000001",
+  id: 2,
+  refresh: "true",
+  document: {
+    text: "quick fox",
+  },
+});
+console.log(response1);
+
+const response2 = await client.search({
+  index: "my-index-000001",
+  query: {
+    script_score: {
+      query: {
+        match: {
+          text: "quick brown fox",
+        },
+      },
+      script: {
+        source: "_termStats.termFreq().getAverage()",
+      },
+    },
+  },
+});
+console.log(response2);
+----

docs/doc_examples/4b91ad7c9b44e07db4a4e81390f19ad3.asciidoc

@@ -0,0 +1,14 @@
+// This 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/completion/openai-completion/_stream",
+  body: {
+    input: "What is Elastic?",
+  },
+});
+console.log(response);
+----

docs/doc_examples/4da0cb8693e9ceceee2ba3b558014bbf.asciidoc

@@ -0,0 +1,38 @@
+// This file is autogenerated, DO NOT EDIT
+// Use `node scripts/generate-docs-examples.js` to generate the docs examples
+
+[source, js]
+----
+const response = await client.updateByQuery({
+  index: "INDEX_NAME",
+  conflicts: "proceed",
+  query: {
+    bool: {
+      filter: [
+        {
+          match: {
+            object_type: "drive_item",
+          },
+        },
+        {
+          exists: {
+            field: "file",
+          },
+        },
+        {
+          range: {
+            lastModifiedDateTime: {
+              lte: "now-180d",
+            },
+          },
+        },
+      ],
+    },
+  },
+  script: {
+    source: "ctx._source.body = ''",
+    lang: "painless",
+  },
+});
+console.log(response);
+----

docs/doc_examples/4edfb5934d14ad7655bd7e19a112b5c0.asciidoc

@@ -0,0 +1,55 @@
+// This 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: "cooking_blog",
+  query: {
+    bool: {
+      must: [
+        {
+          term: {
+            tags: "vegetarian",
+          },
+        },
+        {
+          range: {
+            rating: {
+              gte: 4.5,
+            },
+          },
+        },
+      ],
+      should: [
+        {
+          term: {
+            category: "Main Course",
+          },
+        },
+        {
+          multi_match: {
+            query: "curry spicy",
+            fields: ["title^2", "description"],
+          },
+        },
+        {
+          range: {
+            date: {
+              gte: "now-1M/d",
+            },
+          },
+        },
+      ],
+      must_not: [
+        {
+          term: {
+            "category.keyword": "Dessert",
+          },
+        },
+      ],
+    },
+  },
+});
+console.log(response);
+----

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/529671ffaf7cc75fe83a81d729788be4.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.update({
+  index: ".elastic-connectors",
+  id: "connector_id",
+  doc: {
+    configuration: {
+      field_a: {
+        type: "str",
+        value: "",
+      },
+      field_b: {
+        type: "bool",
+        value: false,
+      },
+      field_c: {
+        type: "int",
+        value: 1,
+      },
+      field_d: {
+        type: "list",
+        value: "a,b",
+      },
+    },
+  },
+});
+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/54a47b5d07e7bfbea75c77f35eaae18d.asciidoc

@@ -3,10 +3,12 @@
 
 [source, js]
 ----
-const response = await client.indices.putSettings({
-  index: "my-index-000001",
-  settings: {
-    "index.merge.policy.max_merge_at_once_explicit": null,
+const response = await client.indices.putMapping({
+  index: ".elastic-connectors-sync-jobs-v1",
+  properties: {
+    job_type: {
+      type: "keyword",
+    },
   },
 });
 console.log(response);

docs/doc_examples/55085e6a2891040b6ac696561d0787c8.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.indices.create({
+  index: "my-index-000002",
+  mappings: {
+    properties: {
+      attributes: {
+        type: "passthrough",
+        priority: 10,
+        properties: {
+          id: {
+            type: "keyword",
+          },
+        },
+      },
+      "resource.attributes": {
+        type: "passthrough",
+        priority: 20,
+        properties: {
+          id: {
+            type: "keyword",
+          },
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/551799fef2f86e393db83a967e4a30d1.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       agg_metric: {
         type: "aggregate_metric_double",

docs/doc_examples/56da252798b8e7b006738428aa1a7f4c.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       my_range: {
         type: "long_range",

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

@@ -4,12 +4,11 @@
 [source, js]
 ----
 const response = await client.search({
-  index: "my-index",
+  index: "jinaai-index",
   query: {
     semantic: {
-      field: "inference_field",
-      query: "mountain lake",
-      inner_hits: {},
+      field: "content",
+      query: "who inspired taking care of the sea?",
     },
   },
 });

docs/doc_examples/58dd26afc919722e21358c91e112b27a.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: "cooking_blog",
+  query: {
+    range: {
+      date: {
+        gte: "2023-05-01",
+        lte: "2023-05-31",
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/5bba213a7f543190139d1a69ab2ed076.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.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  ",
+    include_ccs_metadata: true,
+  },
+});
+console.log(response);
+----

docs/doc_examples/5ceb734e3affe00e2cdc29af748d95bf.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.inference.put({
+  task_type: "sparse_embedding",
+  inference_id: "small_chunk_size",
+  inference_config: {
+    service: "elasticsearch",
+    service_settings: {
+      num_allocations: 1,
+      num_threads: 1,
+    },
+    chunking_settings: {
+      strategy: "sentence",
+      max_chunk_size: 100,
+      sentence_overlap: 0,
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/5cf12cc4f98d98dc79bead7e6556679c.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.indices.create({
+  index: "idx",
+  settings: {
+    index: {
+      mapping: {
+        source: {
+          mode: "synthetic",
+        },
+      },
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/5daf8ede198be9b118da5bee9896cb00.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       flattened: {
         type: "flattened",

docs/doc_examples/5e021307d331a4483a5aa2198168451b.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.security.putRole({
-  name: "role_with_remote_indices",
+  name: "only_remote_access_role",
   remote_indices: [
     {
       clusters: ["my_remote"],
@@ -12,6 +12,12 @@ const response = await client.security.putRole({
       privileges: ["read", "read_cross_cluster", "view_index_metadata"],
     },
   ],
+  remote_cluster: [
+    {
+      clusters: ["my_remote"],
+      privileges: ["monitor_stats"],
+    },
+  ],
 });
 console.log(response);
 ----

docs/doc_examples/5f16358ebb5d14b86f57612d5f92d923.asciidoc

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

docs/doc_examples/6329fb2840a4373ff6d342f2653247cb.asciidoc

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

docs/doc_examples/63a53fcb0717ae9033a679cbfc932851.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.inference.put({
+  task_type: "completion",
+  inference_id: "alibabacloud_ai_search_completion",
+  inference_config: {
+    service: "alibabacloud-ai-search",
+    service_settings: {
+      host: "default-j01.platform-cn-shanghai.opensearch.aliyuncs.com",
+      api_key: "{{API_KEY}}",
+      service_id: "ops-qwen-turbo",
+      workspace: "default",
+    },
+  },
+});
+console.log(response);
+----

docs/doc_examples/640dbeecb736bd25f6f2b392b76a7531.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.cluster.stats({
+  include_remotes: "true",
+});
+console.log(response);
+----

docs/doc_examples/68d7f7d4d268ee98caead5aef19933d6.asciidoc

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

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/6cb1dae368c945ecf7c9ec332a5743a2.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       text: {
         type: "text",

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/6f8bdca97e43aac75e32de655aa4314a.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.connector.delete({
+  connector_id: "my-connector-id&delete_sync_jobs=true",
+});
+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/7163346755400594d1dd7e445aa19ff0.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.search({
+  index: "music",
+});
+console.log(response);
+----

docs/doc_examples/71998bb300ac2a58419b0772cdc1c586.asciidoc

@@ -5,10 +5,16 @@
 ----
 const response = await client.indices.create({
   index: "idx",
-  mappings: {
-    _source: {
+  settings: {
+    index: {
+      mapping: {
+        source: {
           mode: "synthetic",
         },
+      },
+    },
+  },
+  mappings: {
     properties: {
       versions: {
         type: "version",

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);
+----