Added YAML test

Author: Mikep86

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/InferenceFeatures.java

@@ -49,7 +49,8 @@ public Set<NodeFeature> getTestFeatures() {
             SemanticInferenceMetadataFieldsMapper.INFERENCE_METADATA_FIELDS_ENABLED_BY_DEFAULT,
             SEMANTIC_TEXT_HIGHLIGHTER_DEFAULT,
             SEMANTIC_KNN_FILTER_FIX,
-            TEST_RERANKING_SERVICE_PARSE_TEXT_AS_SCORE
+            TEST_RERANKING_SERVICE_PARSE_TEXT_AS_SCORE,
+            SemanticTextFieldMapper.SEMANTIC_TEXT_BIT_VECTOR_SUPPORT
         );
     }
 }

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/mapper/SemanticTextFieldMapper.java

@@ -118,6 +118,7 @@ public class SemanticTextFieldMapper extends FieldMapper implements InferenceFie
         "semantic_text.always_emit_inference_id_fix"
     );
     public static final NodeFeature SEMANTIC_TEXT_SKIP_INFERENCE_FIELDS = new NodeFeature("semantic_text.skip_inference_fields");
+    public static final NodeFeature SEMANTIC_TEXT_BIT_VECTOR_SUPPORT = new NodeFeature("semantic_text.bit_vector_support");
 
     public static final String CONTENT_TYPE = "semantic_text";
     public static final String DEFAULT_ELSER_2_INFERENCE_ID = DEFAULT_ELSER_ID;

x-pack/plugin/inference/src/yamlRestTest/resources/rest-api-spec/test/inference/40_semantic_text_query.yml

@@ -351,6 +351,70 @@ setup:
   - match: { hits.hits.0._id: "doc_1" }
   - close_to: { hits.hits.0._score: { value: 1.0, error: 0.0001 } }
 
+---
+"Query using a dense embedding model that uses bit embeddings":
+  - requires:
+      cluster_features: "semantic_text.bit_vector_support"
+      reason: Bit vector support
+
+  - skip:
+      features: [ "headers", "close_to" ]
+
+  - do:
+      inference.put:
+        task_type: text_embedding
+        inference_id: dense-inference-bit-id
+        body: >
+          {
+            "service": "text_embedding_test_service",
+            "service_settings": {
+              "model": "my_model",
+              "dimensions": 16,
+              "api_key": "abc64",
+              "similarity": "L2_NORM",
+              "element_type": "bit"
+            },
+            "task_settings": {
+            }
+          }
+
+  - do:
+      indices.create:
+        index: test-dense-bit-index
+        body:
+          mappings:
+            properties:
+              inference_field:
+                type: semantic_text
+                inference_id: dense-inference-bit-id
+              non_inference_field:
+                type: text
+
+  - do:
+      index:
+        index: test-dense-bit-index
+        id: doc_1
+        body:
+          inference_field: [ "inference test", "another inference test" ]
+          non_inference_field: "non inference test"
+        refresh: true
+
+  - do:
+      headers:
+        # Force JSON content type so that we use a parser that interprets the floating-point score as a double
+        Content-Type: application/json
+      search:
+        index: test-dense-bit-index
+        body:
+          query:
+            semantic:
+              field: "inference_field"
+              query: "inference test"
+
+  - match: { hits.total.value: 1 }
+  - match: { hits.hits.0._id: "doc_1" }
+  - close_to: { hits.hits.0._score: { value: 1.0, error: 0.0001 } }
+
 ---
 "Query using a dense embedding model via a search inference ID":
   - skip: