Auto-generated code for 8.15 (#2363)

docs/doc_examples/01b23f09d2b7f140faf649eadbbf3ac3.asciidoc

@@ -26,7 +26,7 @@ const response1 = await client.cluster.putComponentTemplate({
           type: "keyword",
           script: {
             source:
-              "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))",
+              "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ENGLISH))",
           },
         },
       },

docs/doc_examples/01cd0ea360282a2c591a366679d7187d.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.tasks.list({
+  human: "true",
+  detailed: "true",
+  actions: "indices:data/write/bulk",
+});
+console.log(response);
+----

docs/doc_examples/05e637284bc3bedd46e0b7c26ad983c4.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "alibabacloud_ai_search_embeddings",
+  id: "alibabacloud_ai_search_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/0b4e50f1b5a0537cbb1a41276bb51c54.asciidoc

@@ -10,7 +10,7 @@ const response = await client.search({
       type: "keyword",
       script: {
         source:
-          "emit(doc['@timestamp'].value.dayOfWeekEnum\n        .getDisplayName(TextStyle.FULL, Locale.ROOT))",
+          "emit(doc['@timestamp'].value.dayOfWeekEnum\n        .getDisplayName(TextStyle.FULL, Locale.ENGLISH))",
       },
     },
   },

docs/doc_examples/1c330f0fc9eac19d0edeb8c4017b9b93.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "hugging_face_embeddings",
+  id: "hugging_face_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/1cbecd19be22979aefb45b4f160e77ea.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "google_vertex_ai_embeddings",
+  id: "google_vertex_ai_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/24a037008e0fc2550ecb6a5d36c04a93.asciidoc

@@ -10,7 +10,7 @@ const response = await client.search({
     "date.day_of_week": {
       type: "keyword",
       script:
-        "emit(doc['date'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))",
+        "emit(doc['date'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ENGLISH))",
     },
   },
   aggs: {

docs/doc_examples/2968ffb8135f77ba3a9b876dd4918119.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "azure-ai-studio-embeddings",
-    pipeline: "azure_ai_studio_embeddings",
+    pipeline: "azure_ai_studio_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/310bdfb0d0d75bac7bff036a3fe51d4d.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "azure_ai_studio_embeddings",
+  id: "azure_ai_studio_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/36ac0ef9ea63efc431580f7ade8ad53c.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "openai-embeddings",
-    pipeline: "openai_embeddings",
+    pipeline: "openai_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/3a489743e49902df38e3368cae00717a.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.nodes.hotThreads();
+console.log(response);
+----

docs/doc_examples/3a4953663a5a3809b692c27446e16b7f.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "amazon-bedrock-embeddings",
-    pipeline: "amazon_bedrock_embeddings",
+    pipeline: "amazon_bedrock_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/4a72c68b96f44e80463084dfc0449d51.asciidoc

@@ -10,7 +10,7 @@ const response = await client.search({
       type: "keyword",
       script: {
         source:
-          "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))",
+          "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ENGLISH))",
       },
     },
   },

docs/doc_examples/4dc151eebefd484a28aed1a175743364.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "openai_embeddings",
+  id: "openai_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/4eeded40f30949e359714a5bb6c88612.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "elser-embeddings",
-    pipeline: "elser_embeddings",
+    pipeline: "elser_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/4f6694ef147a73b1163bde3c13779d26.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.nodes.stats({
+  human: "true",
+  filter_path: "nodes.*.indexing_pressure",
+});
+console.log(response);
+----

docs/doc_examples/548a9b6f447bb820380c1c23e57c18c3.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "cohere_embeddings",
+  id: "cohere_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/551467688d8c701315d0a371850a4056.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "hugging-face-embeddings",
-    pipeline: "hugging_face_embeddings",
+    pipeline: "hugging_face_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/60d3f9a99cc91b43aaa7524a9a74dba0.asciidoc

@@ -3,8 +3,8 @@
 
 [source, js]
 ----
-const response = await client.nodes.hotThreads({
-  node_id: "my-node,my-other-node",
+const response = await client.nodes.stats({
+  metric: "breaker",
 });
 console.log(response);
 ----

docs/doc_examples/6b6e275efe3d2aafe0fc3443f2c96868.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "google-vertex-ai-embeddings",
-    pipeline: "google_vertex_ai_embeddings",
+    pipeline: "google_vertex_ai_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/7888c509774a2abfe82ca370c43d8789.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "cohere-embeddings",
-    pipeline: "cohere_embeddings",
+    pipeline: "cohere_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/84237aa9da49ab4b4c4e2b21d2548df2.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.snapshot.create({
+  repository: "my_repository",
+  snapshot: "_verify_integrity",
+});
+console.log(response);
+----

docs/doc_examples/894fce12d8f0d01e4c4083885a0c0077.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "mistral-embeddings",
-    pipeline: "mistral_embeddings",
+    pipeline: "mistral_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/968fb5b92aa65af09544f7c002b0953e.asciidoc

@@ -7,7 +7,7 @@ const response = await client.search({
   index: "semantic-embeddings",
   query: {
     semantic: {
-      field: "semantic_text",
+      field: "content",
       query: "How to avoid muscle soreness while running?",
     },
   },

docs/doc_examples/9d66cb59711f24e6b4ff85608c9b5a1b.asciidoc

@@ -4,7 +4,9 @@
 [source, js]
 ----
 const response = await client.tasks.list({
-  filter_path: "nodes.*.tasks",
+  pretty: "true",
+  human: "true",
+  detailed: "true",
 });
 console.log(response);
 ----

docs/doc_examples/a769d696bf12f5e9de4b3250646d250c.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "alibabacloud-ai-search-embeddings",
-    pipeline: "alibabacloud_ai_search_embeddings",
+    pipeline: "alibabacloud_ai_search_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/a95ae76fca7c3e273e4bd10323b3caa6.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "azure_openai_embeddings",
+  id: "azure_openai_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/aa814309ad5f1630886ba75255b444f5.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.pendingTasks();
+console.log(response);
+----

docs/doc_examples/b09f155602f9b2a6c40fe7c4a5436b7a.asciidoc

@@ -8,7 +8,7 @@ const response = await client.search({
     day_of_week: {
       type: "keyword",
       script:
-        "\n        emit(doc['timestamp'].value.dayOfWeekEnum\n          .getDisplayName(TextStyle.FULL, Locale.ROOT))\n      ",
+        "\n        emit(doc['timestamp'].value.dayOfWeekEnum\n          .getDisplayName(TextStyle.FULL, Locale.ENGLISH))\n      ",
     },
   },
   size: 0,

docs/doc_examples/c8fa8d7e029792d539464fede18ce258.asciidoc

@@ -7,14 +7,10 @@ const response = await client.indices.create({
   index: "semantic-embeddings",
   mappings: {
     properties: {
-      semantic_text: {
+      content: {
         type: "semantic_text",
         inference_id: "my-elser-endpoint",
       },
-      content: {
-        type: "text",
-        copy_to: "semantic_text",
-      },
     },
   },
 });

docs/doc_examples/d3440ec81dde5f1a01c0206cb35e539c.asciidoc

@@ -11,7 +11,7 @@ const response = await client.reindex({
   },
   dest: {
     index: "azure-openai-embeddings",
-    pipeline: "azure_openai_embeddings",
+    pipeline: "azure_openai_embeddings_pipeline",
   },
 });
 console.log(response);

docs/doc_examples/dd7814258121d3c2e576a7f00469d7e3.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "mistral_embeddings",
+  id: "mistral_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/e3fe842951dc873d7d00c8f6a010c53f.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.tasks.list({
+  human: "true",
+  detailed: "true",
+  actions: "indices:data/write/search",
+});
+console.log(response);
+----

docs/doc_examples/e9625da419bff6470ffd9927c59ca159.asciidoc

@@ -5,7 +5,7 @@
 ----
 const response = await client.cat.threadPool({
   v: "true",
-  h: "id,name,active,rejected,completed",
+  h: "id,name,queue,active,rejected,completed",
 });
 console.log(response);
 ----

docs/doc_examples/ef46c42d473b2acc151a6a41272e0f14.asciidoc

@@ -12,7 +12,7 @@ const response = await client.indices.create({
         type: "keyword",
         script: {
           source:
-            "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))",
+            "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ENGLISH))",
         },
       },
     },

docs/doc_examples/efbd4936cca1a752493d8fa2ba6ad1a3.asciidoc

@@ -11,7 +11,7 @@ const response = await client.indices.create({
         type: "keyword",
         script: {
           source:
-            "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))",
+            "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ENGLISH))",
         },
       },
     },

docs/doc_examples/f03352bb1129938a89f97e4b650038dd.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "amazon_bedrock_embeddings",
+  id: "amazon_bedrock_embeddings_pipeline",
   processors: [
     {
       inference: {

docs/doc_examples/f86337e13526c968848cfe29a52d658f.asciidoc

@@ -4,7 +4,7 @@
 [source, js]
 ----
 const response = await client.ingest.putPipeline({
-  id: "elser_embeddings",
+  id: "elser_embeddings_pipeline",
   processors: [
     {
       inference: {