Auto-generated API code

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/160986f49758f4e8345d183a842f6351.asciidoc → 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/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/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/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/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=",
-  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/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/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/9f16fca9813304e398ee052aa857dbcd.asciidoc → 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/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/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/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/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/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/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/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/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/f4d0ef2e0f76babee83d999fe35127f2.asciidoc → docs/doc_examples/80135e8c644e34cc70ce8a4e7915d1a2.asciidoc

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

docs/doc_examples/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/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/931817b168e055ecf738785c721125dd.asciidoc

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

docs/doc_examples/8593715fcc70315a0816b435551258e0.asciidoc → docs/doc_examples/93c77c65f1e11382f8043d0300e87b89.asciidoc

@@ -9,7 +9,7 @@ const response = await client.indices.create({
     properties: {
       infer_field: {
         type: "semantic_text",
-        inference_id: "my-elser-endpoint",
+        inference_id: ".elser-2-elasticsearch",
       },
       source_field: {
         type: "text",