Auto-generated API code (#2577)

Co-authored-by: Josh Mock <[email protected]>

Author: elasticmachine

Diff for: 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);
+----

Diff for: docs/doc_examples/ddaadd91b7743a1c7e946ce1b593cd1b.asciidoc renamed to 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);

Diff for: 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);
+----

Diff for: docs/doc_examples/31bc93e429ad0de11dd2dd231e8f2c5e.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);
+----

Diff for: docs/doc_examples/38ba93890494bfa7beece58dffa44f98.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);
+----

Diff for: docs/doc_examples/45954b8aaedfed57012be8b6538b0a24.asciidoc

@@ -5,13 +5,19 @@
 ----
 const response = await client.indices.create({
   index: "retrievers_example",
+  settings: {
+    number_of_shards: 1,
+  },
   mappings: {
     properties: {
       vector: {
         type: "dense_vector",
         dims: 3,
         similarity: "l2_norm",
         index: true,
+        index_options: {
+          type: "flat",
+        },
       },
       text: {
         type: "text",

Diff for: docs/doc_examples/519e46350316a33162740e5d7968aa2c.asciidoc

@@ -5,7 +5,8 @@
 ----
 const response = await client.cluster.putSettings({
   persistent: {
-    "cluster.routing.allocation.disk.watermark.low": "30gb",
+    "cluster.routing.allocation.disk.watermark.low": "90%",
+    "cluster.routing.allocation.disk.watermark.high": "95%",
   },
 });
 console.log(response);

Diff for: docs/doc_examples/ee05714a83d75fb6858e3b9fcbeb8f8b.asciidoc renamed to docs/doc_examples/681d24c2633f598fc43d6afff8996dbb.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",
+      },
     },
   },
 });

Diff for: docs/doc_examples/9d47f02a063444da9f098858a1830d28.asciidoc renamed to docs/doc_examples/77cebba946fe648873a1e7375c13df41.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);
+----

Diff for: docs/doc_examples/93c77c65f1e11382f8043d0300e87b89.asciidoc renamed to docs/doc_examples/7bdc283b96c7a965fae23013647b8578.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",
+            },
           },
         },
       },