[Backport 8.19] Fix inference examples

docs/add-new-api.md

@@ -173,12 +173,13 @@ Add an `examples` folder and `request` and `xxx_response` subfolders (where `xxx
 
 These examples are for use in the API documentation and must adhere to the [OpenAPI 3.0 Example object specification](https://spec.openapis.org/oas/v3.0.3#example-object). They must have a `value` field that contains the request or response body.
 If there are multiple examples for the endpoint, they must each have a brief `summary` field, which is used as the label for the example. You can also optionaly provide an explanation in a `description` field.
+In order to generate curl and console examples automatically, the request examples must also contain a `method_request`.
 
 For example:
 
 ```yaml
 summary: Sequence query
-# method_request: GET /my-data-stream/_eql/search
+method_request: GET /my-data-stream/_eql/search
 # type: request
 description: >
   Run `GET /my-data-stream/_eql/search` to search for a sequence of events.

specification/inference/put_hugging_face/examples/request/PutHuggingFaceRequestExample2.yaml

@@ -1,6 +1,6 @@
 summary: A rerank task
 description: Run `PUT _inference/rerank/hugging-face-rerank` to create an inference endpoint that performs a `rerank` task type.
-# method_request: "PUT _inference/rerank/hugging-face-rerank"
+method_request: 'PUT _inference/rerank/hugging-face-rerank'
 # type: "request"
 value: |-
   {
@@ -14,3 +14,77 @@ value: |-
           "top_n": 3
       }
   }
+alternatives:
+  - language: Python
+    code: |-
+      resp = client.inference.put(
+          task_type="rerank",
+          inference_id="hugging-face-rerank",
+          inference_config={
+              "service": "hugging_face",
+              "service_settings": {
+                  "api_key": "hugging-face-access-token",
+                  "url": "url-endpoint"
+              },
+              "task_settings": {
+                  "return_documents": True,
+                  "top_n": 3
+              }
+          },
+      )
+  - language: JavaScript
+    code: |-
+      const response = await client.inference.put({
+        task_type: "rerank",
+        inference_id: "hugging-face-rerank",
+        inference_config: {
+          service: "hugging_face",
+          service_settings: {
+            api_key: "hugging-face-access-token",
+            url: "url-endpoint",
+          },
+          task_settings: {
+            return_documents: true,
+            top_n: 3,
+          },
+        },
+      });
+  - language: Ruby
+    code: |-
+      response = client.inference.put(
+        task_type: "rerank",
+        inference_id: "hugging-face-rerank",
+        body: {
+          "service": "hugging_face",
+          "service_settings": {
+            "api_key": "hugging-face-access-token",
+            "url": "url-endpoint"
+          },
+          "task_settings": {
+            "return_documents": true,
+            "top_n": 3
+          }
+        }
+      )
+  - language: PHP
+    code: |-
+      $resp = $client->inference()->put([
+          "task_type" => "rerank",
+          "inference_id" => "hugging-face-rerank",
+          "body" => [
+              "service" => "hugging_face",
+              "service_settings" => [
+                  "api_key" => "hugging-face-access-token",
+                  "url" => "url-endpoint",
+              ],
+              "task_settings" => [
+                  "return_documents" => true,
+                  "top_n" => 3,
+              ],
+          ],
+      ]);
+  - language: curl
+    code:
+      "curl -X PUT -H \"Authorization: ApiKey $ELASTIC_API_KEY\" -H \"Content-Type: application/json\" -d
+      '{\"service\":\"hugging_face\",\"service_settings\":{\"api_key\":\"hugging-face-access-token\",\"url\":\"url-endpoint\"},\"ta\
+      sk_settings\":{\"return_documents\":true,\"top_n\":3}}' \"$ELASTICSEARCH_URL/_inference/rerank/hugging-face-rerank\""

specification/inference/rerank/examples/request/RerankRequestExample2.yaml

@@ -1,6 +1,6 @@
 summary: Rerank task
 description: Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face
-# method_request: "POST _inference/rerank/bge-reranker-base-mkn"
+method_request: 'POST _inference/rerank/bge-reranker-base-mkn'
 # type: "request"
 value: |-
   {
@@ -9,3 +9,73 @@ value: |-
     "return_documents": false,
     "top_n": 2
   }
+alternatives:
+  - language: Python
+    code: |-
+      resp = client.inference.rerank(
+          inference_id="bge-reranker-base-mkn",
+          input=[
+              "luke",
+              "like",
+              "leia",
+              "chewy",
+              "r2d2",
+              "star",
+              "wars"
+          ],
+          query="star wars main character",
+          return_documents=False,
+          top_n=2,
+      )
+  - language: JavaScript
+    code: |-
+      const response = await client.inference.rerank({
+        inference_id: "bge-reranker-base-mkn",
+        input: ["luke", "like", "leia", "chewy", "r2d2", "star", "wars"],
+        query: "star wars main character",
+        return_documents: false,
+        top_n: 2,
+      });
+  - language: Ruby
+    code: |-
+      response = client.inference.rerank(
+        inference_id: "bge-reranker-base-mkn",
+        body: {
+          "input": [
+            "luke",
+            "like",
+            "leia",
+            "chewy",
+            "r2d2",
+            "star",
+            "wars"
+          ],
+          "query": "star wars main character",
+          "return_documents": false,
+          "top_n": 2
+        }
+      )
+  - language: PHP
+    code: |-
+      $resp = $client->inference()->rerank([
+          "inference_id" => "bge-reranker-base-mkn",
+          "body" => [
+              "input" => array(
+                  "luke",
+                  "like",
+                  "leia",
+                  "chewy",
+                  "r2d2",
+                  "star",
+                  "wars",
+              ),
+              "query" => "star wars main character",
+              "return_documents" => false,
+              "top_n" => 2,
+          ],
+      ]);
+  - language: curl
+    code:
+      'curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d
+      ''{"input":["luke","like","leia","chewy","r2d2","star","wars"],"query":"star wars main
+      character","return_documents":false,"top_n":2}'' "$ELASTICSEARCH_URL/_inference/rerank/bge-reranker-base-mkn"'

specification/inference/rerank/examples/request/RerankRequestExample3.yaml

@@ -1,6 +1,6 @@
 summary: Rerank task
 description: Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face
-# method_request: "POST _inference/rerank/bge-reranker-base-mkn"
+method_request: 'POST _inference/rerank/bge-reranker-base-mkn'
 # type: "request"
 value: |-
   {
@@ -9,3 +9,73 @@ value: |-
     "return_documents": true,
     "top_n": 3
   }
+alternatives:
+  - language: Python
+    code: |-
+      resp = client.inference.rerank(
+          inference_id="bge-reranker-base-mkn",
+          input=[
+              "luke",
+              "like",
+              "leia",
+              "chewy",
+              "r2d2",
+              "star",
+              "wars"
+          ],
+          query="star wars main character",
+          return_documents=True,
+          top_n=3,
+      )
+  - language: JavaScript
+    code: |-
+      const response = await client.inference.rerank({
+        inference_id: "bge-reranker-base-mkn",
+        input: ["luke", "like", "leia", "chewy", "r2d2", "star", "wars"],
+        query: "star wars main character",
+        return_documents: true,
+        top_n: 3,
+      });
+  - language: Ruby
+    code: |-
+      response = client.inference.rerank(
+        inference_id: "bge-reranker-base-mkn",
+        body: {
+          "input": [
+            "luke",
+            "like",
+            "leia",
+            "chewy",
+            "r2d2",
+            "star",
+            "wars"
+          ],
+          "query": "star wars main character",
+          "return_documents": true,
+          "top_n": 3
+        }
+      )
+  - language: PHP
+    code: |-
+      $resp = $client->inference()->rerank([
+          "inference_id" => "bge-reranker-base-mkn",
+          "body" => [
+              "input" => array(
+                  "luke",
+                  "like",
+                  "leia",
+                  "chewy",
+                  "r2d2",
+                  "star",
+                  "wars",
+              ),
+              "query" => "star wars main character",
+              "return_documents" => true,
+              "top_n" => 3,
+          ],
+      ]);
+  - language: curl
+    code:
+      'curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d
+      ''{"input":["luke","like","leia","chewy","r2d2","star","wars"],"query":"star wars main
+      character","return_documents":true,"top_n":3}'' "$ELASTICSEARCH_URL/_inference/rerank/bge-reranker-base-mkn"'