[EIS] Dense Text Embedding task type integration (#129847)

server/src/main/java/org/elasticsearch/TransportVersions.java

@@ -206,6 +206,7 @@ public class TransportVersions {
     public static final TransportVersion RANDOM_SAMPLER_QUERY_BUILDER_8_19 = def(8_841_0_56);
     public static final TransportVersion ML_INFERENCE_SAGEMAKER_ELASTIC_8_19 = def(8_841_0_57);
     public static final TransportVersion SPARSE_VECTOR_FIELD_PRUNING_OPTIONS_8_19 = def(8_841_0_58);
+    public static final TransportVersion ML_INFERENCE_ELASTIC_DENSE_TEXT_EMBEDDINGS_ADDED_8_19 = def(8_841_0_59);
     public static final TransportVersion V_9_0_0 = def(9_000_0_09);
     public static final TransportVersion INITIAL_ELASTICSEARCH_9_0_1 = def(9_000_0_10);
     public static final TransportVersion INITIAL_ELASTICSEARCH_9_0_2 = def(9_000_0_11);
@@ -318,6 +319,7 @@ public class TransportVersions {
     public static final TransportVersion ML_INFERENCE_SAGEMAKER_ELASTIC = def(9_106_0_00);
     public static final TransportVersion SPARSE_VECTOR_FIELD_PRUNING_OPTIONS = def(9_107_0_00);
     public static final TransportVersion CLUSTER_STATE_PROJECTS_SETTINGS = def(9_108_0_00);
+    public static final TransportVersion ML_INFERENCE_ELASTIC_DENSE_TEXT_EMBEDDINGS_ADDED = def(9_109_00_0);
 
     /*
      * STOP! READ THIS FIRST! No, really,

x-pack/plugin/inference/qa/inference-service-tests/src/javaRestTest/java/org/elasticsearch/xpack/inference/InferenceGetModelsWithElasticInferenceServiceIT.java

@@ -33,7 +33,7 @@ public class InferenceGetModelsWithElasticInferenceServiceIT extends BaseMockEIS
         var allModels = getAllModels();
         var chatCompletionModels = getModels("_all", TaskType.CHAT_COMPLETION);
 
-        assertThat(allModels, hasSize(6));
+        assertThat(allModels, hasSize(7));
         assertThat(chatCompletionModels, hasSize(1));
 
         for (var model : chatCompletionModels) {
@@ -42,6 +42,7 @@ public class InferenceGetModelsWithElasticInferenceServiceIT extends BaseMockEIS
 
         assertInferenceIdTaskType(allModels, ".rainbow-sprinkles-elastic", TaskType.CHAT_COMPLETION);
         assertInferenceIdTaskType(allModels, ".elser-v2-elastic", TaskType.SPARSE_EMBEDDING);
+        assertInferenceIdTaskType(allModels, ".multilingual-embed-v1-elastic", TaskType.TEXT_EMBEDDING);
         assertInferenceIdTaskType(allModels, ".rerank-v1-elastic", TaskType.RERANK);
     }
 

x-pack/plugin/inference/qa/inference-service-tests/src/javaRestTest/java/org/elasticsearch/xpack/inference/InferenceGetServicesIT.java

@@ -20,6 +20,7 @@ import java.util.Map;
 
 import static org.elasticsearch.xpack.inference.InferenceBaseRestTest.assertStatusOkOrCreated;
 import static org.hamcrest.Matchers.containsInAnyOrder;
+import static org.hamcrest.Matchers.equalTo;
 
 public class InferenceGetServicesIT extends BaseMockEISAuthServerTest {
 
@@ -76,16 +77,21 @@ public class InferenceGetServicesIT extends BaseMockEISAuthServerTest {
     }
 
     public void testGetServicesWithTextEmbeddingTaskType() throws IOException {
+        List<Object> services = getServices(TaskType.TEXT_EMBEDDING);
+        assertThat(services.size(), equalTo(18));
+
         assertThat(
             providersFor(TaskType.TEXT_EMBEDDING),
             containsInAnyOrder(
                 List.of(
                     "alibabacloud-ai-search",
                     "amazonbedrock",
+                    "amazon_sagemaker",
                     "azureaistudio",
                     "azureopenai",
                     "cohere",
                     "custom",
+                    "elastic",
                     "elasticsearch",
                     "googleaistudio",
                     "googlevertexai",
@@ -95,8 +101,7 @@ public class InferenceGetServicesIT extends BaseMockEISAuthServerTest {
                     "openai",
                     "text_embedding_test_service",
                     "voyageai",
-                    "watsonxai",
-                    "amazon_sagemaker"
+                    "watsonxai"
                 ).toArray()
             )
         );

x-pack/plugin/inference/qa/inference-service-tests/src/javaRestTest/java/org/elasticsearch/xpack/inference/MockElasticInferenceServiceAuthorizationServer.java

@@ -43,6 +43,10 @@ public class MockElasticInferenceServiceAuthorizationServer implements TestRule
                       "task_types": ["embed/text/sparse"]
                     },
                     {
+                      "model_name": "multilingual-embed-v1",
+                      "task_types": ["embed/text/dense"]
+                    },
+                  {
                       "model_name": "rerank-v1",
                       "task_types": ["rerank/text/text-similarity"]
                     }

x-pack/plugin/inference/src/internalClusterTest/java/org/elasticsearch/xpack/inference/integration/InferenceRevokeDefaultEndpointsIT.java

@@ -11,6 +11,7 @@ import org.elasticsearch.ResourceNotFoundException;
 import org.elasticsearch.action.support.PlainActionFuture;
 import org.elasticsearch.common.settings.Settings;
 import org.elasticsearch.core.TimeValue;
+import org.elasticsearch.index.mapper.vectors.DenseVectorFieldMapper;
 import org.elasticsearch.inference.InferenceService;
 import org.elasticsearch.inference.MinimalServiceSettings;
 import org.elasticsearch.inference.Model;
@@ -43,6 +44,7 @@ import static org.elasticsearch.xpack.inference.Utils.mockClusterServiceEmpty;
 import static org.elasticsearch.xpack.inference.external.http.Utils.getUrl;
 import static org.elasticsearch.xpack.inference.services.ServiceComponentsTests.createWithEmptySettings;
 import static org.hamcrest.CoreMatchers.is;
+import static org.hamcrest.Matchers.containsInAnyOrder;
 import static org.mockito.Mockito.mock;
 
 public class InferenceRevokeDefaultEndpointsIT extends ESSingleNodeTestCase {
@@ -190,13 +192,17 @@ public class InferenceRevokeDefaultEndpointsIT extends ESSingleNodeTestCase {
             String responseJson = """
                 {
                     "models": [
+                        {
+                          "model_name": "elser-v2",
+                          "task_types": ["embed/text/sparse"]
+                        },
                         {
                           "model_name": "rainbow-sprinkles",
                           "task_types": ["chat"]
                         },
                         {
-                          "model_name": "elser-v2",
-                          "task_types": ["embed/text/sparse"]
+                          "model_name": "multilingual-embed-v1",
+                          "task_types": ["embed/text/dense"]
                         },
                         {
                           "model_name": "rerank-v1",
@@ -214,36 +220,48 @@ public class InferenceRevokeDefaultEndpointsIT extends ESSingleNodeTestCase {
                 assertThat(service.supportedStreamingTasks(), is(EnumSet.of(TaskType.CHAT_COMPLETION)));
                 assertThat(
                     service.defaultConfigIds(),
-                    is(
-                        List.of(
-                            new InferenceService.DefaultConfigId(
-                                ".elser-v2-elastic",
-                                MinimalServiceSettings.sparseEmbedding(ElasticInferenceService.NAME),
-                                service
-                            ),
-                            new InferenceService.DefaultConfigId(
-                                ".rainbow-sprinkles-elastic",
-                                MinimalServiceSettings.chatCompletion(ElasticInferenceService.NAME),
-                                service
+                    containsInAnyOrder(
+                        new InferenceService.DefaultConfigId(
+                            ".elser-v2-elastic",
+                            MinimalServiceSettings.sparseEmbedding(ElasticInferenceService.NAME),
+                            service
+                        ),
+                        new InferenceService.DefaultConfigId(
+                            ".rainbow-sprinkles-elastic",
+                            MinimalServiceSettings.chatCompletion(ElasticInferenceService.NAME),
+                            service
+                        ),
+                        new InferenceService.DefaultConfigId(
+                            ".multilingual-embed-v1-elastic",
+                            MinimalServiceSettings.textEmbedding(
+                                ElasticInferenceService.NAME,
+                                ElasticInferenceService.DENSE_TEXT_EMBEDDINGS_DIMENSIONS,
+                                ElasticInferenceService.defaultDenseTextEmbeddingsSimilarity(),
+                                DenseVectorFieldMapper.ElementType.FLOAT
                             ),
-                            new InferenceService.DefaultConfigId(
-                                ".rerank-v1-elastic",
-                                MinimalServiceSettings.rerank(ElasticInferenceService.NAME),
-                                service
-                            )
+                            service
+                        ),
+                        new InferenceService.DefaultConfigId(
+                            ".rerank-v1-elastic",
+                            MinimalServiceSettings.rerank(ElasticInferenceService.NAME),
+                            service
                         )
                     )
                 );
                 assertThat(
                     service.supportedTaskTypes(),
-                    is(EnumSet.of(TaskType.CHAT_COMPLETION, TaskType.SPARSE_EMBEDDING, TaskType.RERANK))
+                    is(EnumSet.of(TaskType.CHAT_COMPLETION, TaskType.SPARSE_EMBEDDING, TaskType.RERANK, TaskType.TEXT_EMBEDDING))
                 );
 
                 PlainActionFuture<List<Model>> listener = new PlainActionFuture<>();
                 service.defaultConfigs(listener);
                 assertThat(listener.actionGet(TIMEOUT).get(0).getConfigurations().getInferenceEntityId(), is(".elser-v2-elastic"));
-                assertThat(listener.actionGet(TIMEOUT).get(1).getConfigurations().getInferenceEntityId(), is(".rainbow-sprinkles-elastic"));
-                assertThat(listener.actionGet(TIMEOUT).get(2).getConfigurations().getInferenceEntityId(), is(".rerank-v1-elastic"));
+                assertThat(
+                    listener.actionGet(TIMEOUT).get(1).getConfigurations().getInferenceEntityId(),
+                    is(".multilingual-embed-v1-elastic")
+                );
+                assertThat(listener.actionGet(TIMEOUT).get(2).getConfigurations().getInferenceEntityId(), is(".rainbow-sprinkles-elastic"));
+                assertThat(listener.actionGet(TIMEOUT).get(3).getConfigurations().getInferenceEntityId(), is(".rerank-v1-elastic"));
 
                 var getModelListener = new PlainActionFuture<UnparsedModel>();
                 // persists the default endpoints
@@ -265,6 +283,10 @@ public class InferenceRevokeDefaultEndpointsIT extends ESSingleNodeTestCase {
                         {
                           "model_name": "rerank-v1",
                           "task_types": ["rerank/text/text-similarity"]
+                        },
+                        {
+                          "model_name": "multilingual-embed-v1",
+                          "task_types": ["embed/text/dense"]
                         }
                     ]
                 }
@@ -278,22 +300,33 @@ public class InferenceRevokeDefaultEndpointsIT extends ESSingleNodeTestCase {
                 assertThat(service.supportedStreamingTasks(), is(EnumSet.noneOf(TaskType.class)));
                 assertThat(
                     service.defaultConfigIds(),
-                    is(
-                        List.of(
-                            new InferenceService.DefaultConfigId(
-                                ".elser-v2-elastic",
-                                MinimalServiceSettings.sparseEmbedding(ElasticInferenceService.NAME),
-                                service
+                    containsInAnyOrder(
+                        new InferenceService.DefaultConfigId(
+                            ".elser-v2-elastic",
+                            MinimalServiceSettings.sparseEmbedding(ElasticInferenceService.NAME),
+                            service
+                        ),
+                        new InferenceService.DefaultConfigId(
+                            ".multilingual-embed-v1-elastic",
+                            MinimalServiceSettings.textEmbedding(
+                                ElasticInferenceService.NAME,
+                                ElasticInferenceService.DENSE_TEXT_EMBEDDINGS_DIMENSIONS,
+                                ElasticInferenceService.defaultDenseTextEmbeddingsSimilarity(),
+                                DenseVectorFieldMapper.ElementType.FLOAT
                             ),
-                            new InferenceService.DefaultConfigId(
-                                ".rerank-v1-elastic",
-                                MinimalServiceSettings.rerank(ElasticInferenceService.NAME),
-                                service
-                            )
+                            service
+                        ),
+                        new InferenceService.DefaultConfigId(
+                            ".rerank-v1-elastic",
+                            MinimalServiceSettings.rerank(ElasticInferenceService.NAME),
+                            service
                         )
                     )
                 );
-                assertThat(service.supportedTaskTypes(), is(EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.RERANK)));
+                assertThat(
+                    service.supportedTaskTypes(),
+                    is(EnumSet.of(TaskType.TEXT_EMBEDDING, TaskType.SPARSE_EMBEDDING, TaskType.RERANK))
+                );
 
                 var getModelListener = new PlainActionFuture<UnparsedModel>();
                 modelRegistry.getModel(".rainbow-sprinkles-elastic", getModelListener);

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/external/response/elastic/ElasticInferenceServiceDenseTextEmbeddingsResponseEntity.java

@@ -0,0 +1,103 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.external.response.elastic;
+
+import org.elasticsearch.common.xcontent.XContentParserUtils;
+import org.elasticsearch.xcontent.ConstructingObjectParser;
+import org.elasticsearch.xcontent.ParseField;
+import org.elasticsearch.xcontent.XContentFactory;
+import org.elasticsearch.xcontent.XContentParserConfiguration;
+import org.elasticsearch.xcontent.XContentType;
+import org.elasticsearch.xpack.core.inference.results.TextEmbeddingFloatResults;
+import org.elasticsearch.xpack.inference.external.http.HttpResult;
+import org.elasticsearch.xpack.inference.external.request.Request;
+
+import java.io.IOException;
+import java.util.List;
+
+import static org.elasticsearch.xcontent.ConstructingObjectParser.constructorArg;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsResponseEntity {
+
+    /**
+     * Parses the Elastic Inference Service Dense Text Embeddings response.
+     *
+     * For a request like:
+     *
+     * <pre>
+     *     <code>
+     *         {
+     *             "inputs": ["Embed this text", "Embed this text, too"]
+     *         }
+     *     </code>
+     * </pre>
+     *
+     * The response would look like:
+     *
+     * <pre>
+     *     <code>
+     *         {
+     *             "data": [
+     *                  [
+     *                      2.1259406,
+     *                      1.7073475,
+     *                      0.9020516
+     *                  ],
+     *                  (...)
+     *             ],
+     *             "meta": {
+     *                  "usage": {...}
+     *             }
+     *         }
+     *     </code>
+     * </pre>
+     */
+    public static TextEmbeddingFloatResults fromResponse(Request request, HttpResult response) throws IOException {
+        try (var p = XContentFactory.xContent(XContentType.JSON).createParser(XContentParserConfiguration.EMPTY, response.body())) {
+            return EmbeddingFloatResult.PARSER.apply(p, null).toTextEmbeddingFloatResults();
+        }
+    }
+
+    public record EmbeddingFloatResult(List<EmbeddingFloatResultEntry> embeddingResults) {
+        @SuppressWarnings("unchecked")
+        public static final ConstructingObjectParser<EmbeddingFloatResult, Void> PARSER = new ConstructingObjectParser<>(
+            EmbeddingFloatResult.class.getSimpleName(),
+            true,
+            args -> new EmbeddingFloatResult((List<EmbeddingFloatResultEntry>) args[0])
+        );
+
+        static {
+            // Custom field declaration to handle array of arrays format
+            PARSER.declareField(constructorArg(), (parser, context) -> {
+                return XContentParserUtils.parseList(parser, (p, index) -> {
+                    List<Float> embedding = XContentParserUtils.parseList(p, (innerParser, innerIndex) -> innerParser.floatValue());
+                    return EmbeddingFloatResultEntry.fromFloatArray(embedding);
+                });
+            }, new ParseField("data"), org.elasticsearch.xcontent.ObjectParser.ValueType.OBJECT_ARRAY);
+        }
+
+        public TextEmbeddingFloatResults toTextEmbeddingFloatResults() {
+            return new TextEmbeddingFloatResults(
+                embeddingResults.stream().map(entry -> TextEmbeddingFloatResults.Embedding.of(entry.embedding)).toList()
+            );
+        }
+    }
+
+    /**
+     * Represents a single embedding entry in the response.
+     * For the Elastic Inference Service, each entry is just an array of floats (no wrapper object).
+     * This is a simpler wrapper that just holds the float array.
+     */
+    public record EmbeddingFloatResultEntry(List<Float> embedding) {
+        public static EmbeddingFloatResultEntry fromFloatArray(List<Float> floats) {
+            return new EmbeddingFloatResultEntry(floats);
+        }
+    }
+
+    private ElasticInferenceServiceDenseTextEmbeddingsResponseEntity() {}
+}

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/ElasticInferenceService.java

@@ -16,6 +16,7 @@ import org.elasticsearch.common.ValidationException;
 import org.elasticsearch.common.util.LazyInitializable;
 import org.elasticsearch.core.Nullable;
 import org.elasticsearch.core.TimeValue;
+import org.elasticsearch.index.mapper.vectors.DenseVectorFieldMapper;
 import org.elasticsearch.inference.ChunkedInference;
 import org.elasticsearch.inference.ChunkingSettings;
 import org.elasticsearch.inference.EmptySecretSettings;
@@ -28,6 +29,7 @@ import org.elasticsearch.inference.Model;
 import org.elasticsearch.inference.ModelConfigurations;
 import org.elasticsearch.inference.ModelSecrets;
 import org.elasticsearch.inference.SettingsConfiguration;
+import org.elasticsearch.inference.SimilarityMeasure;
 import org.elasticsearch.inference.TaskType;
 import org.elasticsearch.inference.configuration.SettingsConfigurationFieldType;
 import org.elasticsearch.rest.RestStatus;
@@ -54,6 +56,8 @@ import org.elasticsearch.xpack.inference.services.elastic.authorization.ElasticI
 import org.elasticsearch.xpack.inference.services.elastic.authorization.ElasticInferenceServiceAuthorizationRequestHandler;
 import org.elasticsearch.xpack.inference.services.elastic.completion.ElasticInferenceServiceCompletionModel;
 import org.elasticsearch.xpack.inference.services.elastic.completion.ElasticInferenceServiceCompletionServiceSettings;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModel;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsServiceSettings;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModel;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankServiceSettings;
 import org.elasticsearch.xpack.inference.services.elastic.sparseembeddings.ElasticInferenceServiceSparseEmbeddingsModel;
@@ -84,15 +88,20 @@ public class ElasticInferenceService extends SenderService {
 
     public static final String NAME = "elastic";
     public static final String ELASTIC_INFERENCE_SERVICE_IDENTIFIER = "Elastic Inference Service";
-    public static final int SPARSE_TEXT_EMBEDDING_MAX_BATCH_SIZE = 512;
+    public static final Integer DENSE_TEXT_EMBEDDINGS_DIMENSIONS = 1024;
+    public static final Integer SPARSE_TEXT_EMBEDDING_MAX_BATCH_SIZE = 512;
 
     private static final EnumSet<TaskType> IMPLEMENTED_TASK_TYPES = EnumSet.of(
         TaskType.SPARSE_EMBEDDING,
         TaskType.CHAT_COMPLETION,
-        TaskType.RERANK
+        TaskType.RERANK,
+        TaskType.TEXT_EMBEDDING
     );
     private static final String SERVICE_NAME = "Elastic";
 
+    // TODO: check with team, what makes the most sense
+    private static final Integer DENSE_TEXT_EMBEDDINGS_MAX_BATCH_SIZE = 32;
+
     // rainbow-sprinkles
     static final String DEFAULT_CHAT_COMPLETION_MODEL_ID_V1 = "rainbow-sprinkles";
     static final String DEFAULT_CHAT_COMPLETION_ENDPOINT_ID_V1 = defaultEndpointId(DEFAULT_CHAT_COMPLETION_MODEL_ID_V1);
@@ -101,6 +110,10 @@ public class ElasticInferenceService extends SenderService {
     static final String DEFAULT_ELSER_MODEL_ID_V2 = "elser-v2";
     static final String DEFAULT_ELSER_ENDPOINT_ID_V2 = defaultEndpointId(DEFAULT_ELSER_MODEL_ID_V2);
 
+    // multilingual-text-embed
+    static final String DEFAULT_MULTILINGUAL_EMBED_MODEL_ID = "multilingual-embed-v1";
+    static final String DEFAULT_MULTILINGUAL_EMBED_ENDPOINT_ID = defaultEndpointId(DEFAULT_MULTILINGUAL_EMBED_MODEL_ID);
+
     // rerank-v1
     static final String DEFAULT_RERANK_MODEL_ID_V1 = "rerank-v1";
     static final String DEFAULT_RERANK_ENDPOINT_ID_V1 = defaultEndpointId(DEFAULT_RERANK_MODEL_ID_V1);
@@ -108,7 +121,11 @@ public class ElasticInferenceService extends SenderService {
     /**
      * The task types that the {@link InferenceAction.Request} can accept.
      */
-    private static final EnumSet<TaskType> SUPPORTED_INFERENCE_ACTION_TASK_TYPES = EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.RERANK);
+    private static final EnumSet<TaskType> SUPPORTED_INFERENCE_ACTION_TASK_TYPES = EnumSet.of(
+        TaskType.SPARSE_EMBEDDING,
+        TaskType.RERANK,
+        TaskType.TEXT_EMBEDDING
+    );
 
     public static String defaultEndpointId(String modelId) {
         return Strings.format(".%s-elastic", modelId);
@@ -171,6 +188,32 @@ public class ElasticInferenceService extends SenderService {
                 ),
                 MinimalServiceSettings.sparseEmbedding(NAME)
             ),
+            DEFAULT_MULTILINGUAL_EMBED_MODEL_ID,
+            new DefaultModelConfig(
+                new ElasticInferenceServiceDenseTextEmbeddingsModel(
+                    DEFAULT_MULTILINGUAL_EMBED_ENDPOINT_ID,
+                    TaskType.TEXT_EMBEDDING,
+                    NAME,
+                    new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+                        DEFAULT_MULTILINGUAL_EMBED_MODEL_ID,
+                        defaultDenseTextEmbeddingsSimilarity(),
+                        null,
+                        null,
+                        ElasticInferenceServiceDenseTextEmbeddingsServiceSettings.DEFAULT_RATE_LIMIT_SETTINGS
+                    ),
+                    EmptyTaskSettings.INSTANCE,
+                    EmptySecretSettings.INSTANCE,
+                    elasticInferenceServiceComponents,
+                    ChunkingSettingsBuilder.DEFAULT_SETTINGS
+                ),
+                MinimalServiceSettings.textEmbedding(
+                    NAME,
+                    DENSE_TEXT_EMBEDDINGS_DIMENSIONS,
+                    defaultDenseTextEmbeddingsSimilarity(),
+                    DenseVectorFieldMapper.ElementType.FLOAT
+                )
+            ),
+
             DEFAULT_RERANK_MODEL_ID_V1,
             new DefaultModelConfig(
                 new ElasticInferenceServiceRerankModel(
@@ -310,6 +353,23 @@ public class ElasticInferenceService extends SenderService {
         TimeValue timeout,
         ActionListener<List<ChunkedInference>> listener
     ) {
+        if (model instanceof ElasticInferenceServiceDenseTextEmbeddingsModel denseTextEmbeddingsModel) {
+            var actionCreator = new ElasticInferenceServiceActionCreator(getSender(), getServiceComponents(), getCurrentTraceInfo());
+
+            List<EmbeddingRequestChunker.BatchRequestAndListener> batchedRequests = new EmbeddingRequestChunker<>(
+                inputs.getInputs(),
+                DENSE_TEXT_EMBEDDINGS_MAX_BATCH_SIZE,
+                denseTextEmbeddingsModel.getConfigurations().getChunkingSettings()
+            ).batchRequestsWithListeners(listener);
+
+            for (var request : batchedRequests) {
+                var action = denseTextEmbeddingsModel.accept(actionCreator, taskSettings);
+                action.execute(EmbeddingsInput.fromStrings(request.batch().inputs().get(), inputType), timeout, request.listener());
+            }
+
+            return;
+        }
+
         if (model instanceof ElasticInferenceServiceSparseEmbeddingsModel sparseTextEmbeddingsModel) {
             var actionCreator = new ElasticInferenceServiceActionCreator(getSender(), getServiceComponents(), getCurrentTraceInfo());
 
@@ -348,7 +408,7 @@ public class ElasticInferenceService extends SenderService {
             Map<String, Object> taskSettingsMap = removeFromMapOrDefaultEmpty(config, ModelConfigurations.TASK_SETTINGS);
 
             ChunkingSettings chunkingSettings = null;
-            if (TaskType.SPARSE_EMBEDDING.equals(taskType)) {
+            if (TaskType.SPARSE_EMBEDDING.equals(taskType) || TaskType.TEXT_EMBEDDING.equals(taskType)) {
                 chunkingSettings = ChunkingSettingsBuilder.fromMap(
                     removeFromMapOrDefaultEmpty(config, ModelConfigurations.CHUNKING_SETTINGS)
                 );
@@ -359,11 +419,11 @@ public class ElasticInferenceService extends SenderService {
                 taskType,
                 serviceSettingsMap,
                 taskSettingsMap,
+                chunkingSettings,
                 serviceSettingsMap,
                 elasticInferenceServiceComponents,
                 TaskType.unsupportedTaskTypeErrorMsg(taskType, NAME),
-                ConfigurationParseContext.REQUEST,
-                chunkingSettings
+                ConfigurationParseContext.REQUEST
             );
 
             throwIfNotEmptyMap(config, NAME);
@@ -396,11 +456,11 @@ public class ElasticInferenceService extends SenderService {
         TaskType taskType,
         Map<String, Object> serviceSettings,
         Map<String, Object> taskSettings,
+        ChunkingSettings chunkingSettings,
         @Nullable Map<String, Object> secretSettings,
         ElasticInferenceServiceComponents elasticInferenceServiceComponents,
         String failureMessage,
-        ConfigurationParseContext context,
-        ChunkingSettings chunkingSettings
+        ConfigurationParseContext context
     ) {
         return switch (taskType) {
             case SPARSE_EMBEDDING -> new ElasticInferenceServiceSparseEmbeddingsModel(
@@ -434,6 +494,17 @@ public class ElasticInferenceService extends SenderService {
                 elasticInferenceServiceComponents,
                 context
             );
+            case TEXT_EMBEDDING -> new ElasticInferenceServiceDenseTextEmbeddingsModel(
+                inferenceEntityId,
+                taskType,
+                NAME,
+                serviceSettings,
+                taskSettings,
+                secretSettings,
+                elasticInferenceServiceComponents,
+                context,
+                chunkingSettings
+            );
             default -> throw new ElasticsearchStatusException(failureMessage, RestStatus.BAD_REQUEST);
         };
     }
@@ -450,7 +521,7 @@ public class ElasticInferenceService extends SenderService {
         Map<String, Object> secretSettingsMap = removeFromMapOrDefaultEmpty(secrets, ModelSecrets.SECRET_SETTINGS);
 
         ChunkingSettings chunkingSettings = null;
-        if (TaskType.SPARSE_EMBEDDING.equals(taskType)) {
+        if (TaskType.SPARSE_EMBEDDING.equals(taskType) || TaskType.TEXT_EMBEDDING.equals(taskType)) {
             chunkingSettings = ChunkingSettingsBuilder.fromMap(removeFromMap(config, ModelConfigurations.CHUNKING_SETTINGS));
         }
 
@@ -459,9 +530,9 @@ public class ElasticInferenceService extends SenderService {
             taskType,
             serviceSettingsMap,
             taskSettingsMap,
+            chunkingSettings,
             secretSettingsMap,
-            parsePersistedConfigErrorMsg(inferenceEntityId, NAME),
-            chunkingSettings
+            parsePersistedConfigErrorMsg(inferenceEntityId, NAME)
         );
     }
 
@@ -471,7 +542,7 @@ public class ElasticInferenceService extends SenderService {
         Map<String, Object> taskSettingsMap = removeFromMapOrDefaultEmpty(config, ModelConfigurations.TASK_SETTINGS);
 
         ChunkingSettings chunkingSettings = null;
-        if (TaskType.SPARSE_EMBEDDING.equals(taskType)) {
+        if (TaskType.SPARSE_EMBEDDING.equals(taskType) || TaskType.TEXT_EMBEDDING.equals(taskType)) {
             chunkingSettings = ChunkingSettingsBuilder.fromMap(removeFromMap(config, ModelConfigurations.CHUNKING_SETTINGS));
         }
 
@@ -480,9 +551,9 @@ public class ElasticInferenceService extends SenderService {
             taskType,
             serviceSettingsMap,
             taskSettingsMap,
+            chunkingSettings,
             null,
-            parsePersistedConfigErrorMsg(inferenceEntityId, NAME),
-            chunkingSettings
+            parsePersistedConfigErrorMsg(inferenceEntityId, NAME)
         );
     }
 
@@ -496,23 +567,51 @@ public class ElasticInferenceService extends SenderService {
         TaskType taskType,
         Map<String, Object> serviceSettings,
         Map<String, Object> taskSettings,
+        ChunkingSettings chunkingSettings,
         @Nullable Map<String, Object> secretSettings,
-        String failureMessage,
-        ChunkingSettings chunkingSettings
+        String failureMessage
     ) {
         return createModel(
             inferenceEntityId,
             taskType,
             serviceSettings,
             taskSettings,
+            chunkingSettings,
             secretSettings,
             elasticInferenceServiceComponents,
             failureMessage,
-            ConfigurationParseContext.PERSISTENT,
-            chunkingSettings
+            ConfigurationParseContext.PERSISTENT
         );
     }
 
+    @Override
+    public Model updateModelWithEmbeddingDetails(Model model, int embeddingSize) {
+        if (model instanceof ElasticInferenceServiceDenseTextEmbeddingsModel embeddingsModel) {
+            var serviceSettings = embeddingsModel.getServiceSettings();
+            var modelId = serviceSettings.modelId();
+            var similarityFromModel = serviceSettings.similarity();
+            var similarityToUse = similarityFromModel == null ? defaultDenseTextEmbeddingsSimilarity() : similarityFromModel;
+            var maxInputTokens = serviceSettings.maxInputTokens();
+
+            var updateServiceSettings = new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+                modelId,
+                similarityToUse,
+                embeddingSize,
+                maxInputTokens,
+                serviceSettings.rateLimitSettings()
+            );
+
+            return new ElasticInferenceServiceDenseTextEmbeddingsModel(embeddingsModel, updateServiceSettings);
+        } else {
+            throw ServiceUtils.invalidModelTypeForUpdateModelWithEmbeddingDetails(model.getClass());
+        }
+    }
+
+    public static SimilarityMeasure defaultDenseTextEmbeddingsSimilarity() {
+        // TODO: double-check
+        return SimilarityMeasure.COSINE;
+    }
+
     private static List<ChunkedInference> translateToChunkedResults(InferenceInputs inputs, InferenceServiceResults inferenceResults) {
         if (inferenceResults instanceof SparseEmbeddingResults sparseEmbeddingResults) {
             var inputsAsList = EmbeddingsInput.of(inputs).getStringInputs();
@@ -550,8 +649,9 @@ public class ElasticInferenceService extends SenderService {
 
                 configurationMap.put(
                     MODEL_ID,
-                    new SettingsConfiguration.Builder(EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.CHAT_COMPLETION, TaskType.RERANK))
-                        .setDescription("The name of the model to use for the inference task.")
+                    new SettingsConfiguration.Builder(
+                        EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.CHAT_COMPLETION, TaskType.RERANK, TaskType.TEXT_EMBEDDING)
+                    ).setDescription("The name of the model to use for the inference task.")
                         .setLabel("Model ID")
                         .setRequired(true)
                         .setSensitive(false)
@@ -562,7 +662,7 @@ public class ElasticInferenceService extends SenderService {
 
                 configurationMap.put(
                     MAX_INPUT_TOKENS,
-                    new SettingsConfiguration.Builder(EnumSet.of(TaskType.SPARSE_EMBEDDING)).setDescription(
+                    new SettingsConfiguration.Builder(EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.TEXT_EMBEDDING)).setDescription(
                         "Allows you to specify the maximum number of tokens per input."
                     )
                         .setLabel("Maximum Input Tokens")
@@ -575,7 +675,7 @@ public class ElasticInferenceService extends SenderService {
 
                 configurationMap.putAll(
                     RateLimitSettings.toSettingsConfiguration(
-                        EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.CHAT_COMPLETION, TaskType.RERANK)
+                        EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.CHAT_COMPLETION, TaskType.RERANK, TaskType.TEXT_EMBEDDING)
                     )
                 );
 

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/action/ElasticInferenceServiceActionCreator.java

@@ -11,14 +11,18 @@ import org.elasticsearch.common.Strings;
 import org.elasticsearch.xpack.inference.external.action.ExecutableAction;
 import org.elasticsearch.xpack.inference.external.action.SenderExecutableAction;
 import org.elasticsearch.xpack.inference.external.http.retry.ResponseHandler;
+import org.elasticsearch.xpack.inference.external.http.sender.EmbeddingsInput;
 import org.elasticsearch.xpack.inference.external.http.sender.GenericRequestManager;
 import org.elasticsearch.xpack.inference.external.http.sender.QueryAndDocsInputs;
 import org.elasticsearch.xpack.inference.external.http.sender.Sender;
-import org.elasticsearch.xpack.inference.external.request.elastic.rerank.ElasticInferenceServiceRerankRequest;
+import org.elasticsearch.xpack.inference.external.response.elastic.ElasticInferenceServiceDenseTextEmbeddingsResponseEntity;
 import org.elasticsearch.xpack.inference.external.response.elastic.ElasticInferenceServiceRerankResponseEntity;
 import org.elasticsearch.xpack.inference.services.ServiceComponents;
 import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceResponseHandler;
 import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceSparseEmbeddingsRequestManager;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModel;
+import org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceDenseTextEmbeddingsRequest;
+import org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceRerankRequest;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModel;
 import org.elasticsearch.xpack.inference.services.elastic.sparseembeddings.ElasticInferenceServiceSparseEmbeddingsModel;
 import org.elasticsearch.xpack.inference.telemetry.TraceContext;
@@ -31,17 +35,22 @@ import static org.elasticsearch.xpack.inference.services.elastic.request.Elastic
 
 public class ElasticInferenceServiceActionCreator implements ElasticInferenceServiceActionVisitor {
 
-    private final Sender sender;
-
-    private final ServiceComponents serviceComponents;
-
-    private final TraceContext traceContext;
+    static final ResponseHandler DENSE_TEXT_EMBEDDINGS_HANDLER = new ElasticInferenceServiceResponseHandler(
+        "elastic dense text embedding",
+        ElasticInferenceServiceDenseTextEmbeddingsResponseEntity::fromResponse
+    );
 
     static final ResponseHandler RERANK_HANDLER = new ElasticInferenceServiceResponseHandler(
         "elastic rerank",
         (request, response) -> ElasticInferenceServiceRerankResponseEntity.fromResponse(response)
     );
 
+    private final Sender sender;
+
+    private final ServiceComponents serviceComponents;
+
+    private final TraceContext traceContext;
+
     public ElasticInferenceServiceActionCreator(Sender sender, ServiceComponents serviceComponents, TraceContext traceContext) {
         this.sender = Objects.requireNonNull(sender);
         this.serviceComponents = Objects.requireNonNull(serviceComponents);
@@ -77,4 +86,26 @@ public class ElasticInferenceServiceActionCreator implements ElasticInferenceSer
         var errorMessage = constructFailedToSendRequestMessage(Strings.format("%s rerank", ELASTIC_INFERENCE_SERVICE_IDENTIFIER));
         return new SenderExecutableAction(sender, requestManager, errorMessage);
     }
+
+    @Override
+    public ExecutableAction create(ElasticInferenceServiceDenseTextEmbeddingsModel model) {
+        var threadPool = serviceComponents.threadPool();
+
+        var manager = new GenericRequestManager<>(
+            threadPool,
+            model,
+            DENSE_TEXT_EMBEDDINGS_HANDLER,
+            (embeddingsInput) -> new ElasticInferenceServiceDenseTextEmbeddingsRequest(
+                model,
+                embeddingsInput.getStringInputs(),
+                traceContext,
+                extractRequestMetadataFromThreadContext(threadPool.getThreadContext()),
+                embeddingsInput.getInputType()
+            ),
+            EmbeddingsInput.class
+        );
+
+        var failedToSendRequestErrorMessage = constructFailedToSendRequestMessage("Elastic dense text embeddings");
+        return new SenderExecutableAction(sender, manager, failedToSendRequestErrorMessage);
+    }
 }

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/action/ElasticInferenceServiceActionVisitor.java

@@ -8,6 +8,7 @@
 package org.elasticsearch.xpack.inference.services.elastic.action;
 
 import org.elasticsearch.xpack.inference.external.action.ExecutableAction;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModel;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModel;
 import org.elasticsearch.xpack.inference.services.elastic.sparseembeddings.ElasticInferenceServiceSparseEmbeddingsModel;
 
@@ -17,4 +18,5 @@ public interface ElasticInferenceServiceActionVisitor {
 
     ExecutableAction create(ElasticInferenceServiceRerankModel model);
 
+    ExecutableAction create(ElasticInferenceServiceDenseTextEmbeddingsModel model);
 }

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/densetextembeddings/ElasticInferenceServiceDenseTextEmbeddingsModel.java

@@ -0,0 +1,116 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.densetextembeddings;
+
+import org.elasticsearch.ElasticsearchStatusException;
+import org.elasticsearch.core.Nullable;
+import org.elasticsearch.inference.ChunkingSettings;
+import org.elasticsearch.inference.EmptySecretSettings;
+import org.elasticsearch.inference.EmptyTaskSettings;
+import org.elasticsearch.inference.ModelConfigurations;
+import org.elasticsearch.inference.ModelSecrets;
+import org.elasticsearch.inference.SecretSettings;
+import org.elasticsearch.inference.TaskSettings;
+import org.elasticsearch.inference.TaskType;
+import org.elasticsearch.rest.RestStatus;
+import org.elasticsearch.xpack.inference.external.action.ExecutableAction;
+import org.elasticsearch.xpack.inference.services.ConfigurationParseContext;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceComponents;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceExecutableActionModel;
+import org.elasticsearch.xpack.inference.services.elastic.action.ElasticInferenceServiceActionVisitor;
+
+import java.net.URI;
+import java.net.URISyntaxException;
+import java.util.Map;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsModel extends ElasticInferenceServiceExecutableActionModel {
+
+    private final URI uri;
+
+    public ElasticInferenceServiceDenseTextEmbeddingsModel(
+        String inferenceEntityId,
+        TaskType taskType,
+        String service,
+        Map<String, Object> serviceSettings,
+        Map<String, Object> taskSettings,
+        Map<String, Object> secrets,
+        ElasticInferenceServiceComponents elasticInferenceServiceComponents,
+        ConfigurationParseContext context,
+        ChunkingSettings chunkingSettings
+    ) {
+        this(
+            inferenceEntityId,
+            taskType,
+            service,
+            ElasticInferenceServiceDenseTextEmbeddingsServiceSettings.fromMap(serviceSettings, context),
+            EmptyTaskSettings.INSTANCE,
+            EmptySecretSettings.INSTANCE,
+            elasticInferenceServiceComponents,
+            chunkingSettings
+        );
+    }
+
+    public ElasticInferenceServiceDenseTextEmbeddingsModel(
+        String inferenceEntityId,
+        TaskType taskType,
+        String service,
+        ElasticInferenceServiceDenseTextEmbeddingsServiceSettings serviceSettings,
+        @Nullable TaskSettings taskSettings,
+        @Nullable SecretSettings secretSettings,
+        ElasticInferenceServiceComponents elasticInferenceServiceComponents,
+        ChunkingSettings chunkingSettings
+    ) {
+        super(
+            new ModelConfigurations(inferenceEntityId, taskType, service, serviceSettings, taskSettings, chunkingSettings),
+            new ModelSecrets(secretSettings),
+            serviceSettings,
+            elasticInferenceServiceComponents
+        );
+        this.uri = createUri();
+    }
+
+    public ElasticInferenceServiceDenseTextEmbeddingsModel(
+        ElasticInferenceServiceDenseTextEmbeddingsModel model,
+        ElasticInferenceServiceDenseTextEmbeddingsServiceSettings serviceSettings
+    ) {
+        super(model, serviceSettings);
+        this.uri = createUri();
+    }
+
+    @Override
+    public ExecutableAction accept(ElasticInferenceServiceActionVisitor visitor, Map<String, Object> taskSettings) {
+        return visitor.create(this);
+    }
+
+    @Override
+    public ElasticInferenceServiceDenseTextEmbeddingsServiceSettings getServiceSettings() {
+        return (ElasticInferenceServiceDenseTextEmbeddingsServiceSettings) super.getServiceSettings();
+    }
+
+    public URI uri() {
+        return uri;
+    }
+
+    private URI createUri() throws ElasticsearchStatusException {
+        try {
+            // TODO, consider transforming the base URL into a URI for better error handling.
+            return new URI(elasticInferenceServiceComponents().elasticInferenceServiceUrl() + "/api/v1/embed/text/dense");
+        } catch (URISyntaxException e) {
+            throw new ElasticsearchStatusException(
+                "Failed to create URI for service ["
+                    + this.getConfigurations().getService()
+                    + "] with taskType ["
+                    + this.getTaskType()
+                    + "]: "
+                    + e.getMessage(),
+                RestStatus.BAD_REQUEST,
+                e
+            );
+        }
+    }
+}

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/densetextembeddings/ElasticInferenceServiceDenseTextEmbeddingsServiceSettings.java

@@ -0,0 +1,236 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.densetextembeddings;
+
+import org.elasticsearch.TransportVersion;
+import org.elasticsearch.TransportVersions;
+import org.elasticsearch.common.ValidationException;
+import org.elasticsearch.common.io.stream.StreamInput;
+import org.elasticsearch.common.io.stream.StreamOutput;
+import org.elasticsearch.core.Nullable;
+import org.elasticsearch.index.mapper.vectors.DenseVectorFieldMapper;
+import org.elasticsearch.inference.ModelConfigurations;
+import org.elasticsearch.inference.ServiceSettings;
+import org.elasticsearch.inference.SimilarityMeasure;
+import org.elasticsearch.xcontent.XContentBuilder;
+import org.elasticsearch.xpack.inference.services.ConfigurationParseContext;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceService;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceRateLimitServiceSettings;
+import org.elasticsearch.xpack.inference.services.settings.FilteredXContentObject;
+import org.elasticsearch.xpack.inference.services.settings.RateLimitSettings;
+
+import java.io.IOException;
+import java.util.Map;
+import java.util.Objects;
+
+import static org.elasticsearch.xpack.inference.services.ServiceFields.DIMENSIONS;
+import static org.elasticsearch.xpack.inference.services.ServiceFields.MAX_INPUT_TOKENS;
+import static org.elasticsearch.xpack.inference.services.ServiceFields.MODEL_ID;
+import static org.elasticsearch.xpack.inference.services.ServiceFields.SIMILARITY;
+import static org.elasticsearch.xpack.inference.services.ServiceUtils.extractRequiredString;
+import static org.elasticsearch.xpack.inference.services.ServiceUtils.extractSimilarity;
+import static org.elasticsearch.xpack.inference.services.ServiceUtils.removeAsType;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsServiceSettings extends FilteredXContentObject
+    implements
+        ServiceSettings,
+        ElasticInferenceServiceRateLimitServiceSettings {
+
+    public static final String NAME = "elastic_inference_service_dense_embeddings_service_settings";
+
+    public static final RateLimitSettings DEFAULT_RATE_LIMIT_SETTINGS = new RateLimitSettings(10_000);
+
+    private final String modelId;
+    private final SimilarityMeasure similarity;
+    private final Integer dimensions;
+    private final Integer maxInputTokens;
+    private final RateLimitSettings rateLimitSettings;
+
+    public static ElasticInferenceServiceDenseTextEmbeddingsServiceSettings fromMap(
+        Map<String, Object> map,
+        ConfigurationParseContext context
+    ) {
+        return switch (context) {
+            case REQUEST -> fromRequestMap(map, context);
+            case PERSISTENT -> fromPersistentMap(map, context);
+        };
+    }
+
+    private static ElasticInferenceServiceDenseTextEmbeddingsServiceSettings fromRequestMap(
+        Map<String, Object> map,
+        ConfigurationParseContext context
+    ) {
+        ValidationException validationException = new ValidationException();
+
+        String modelId = extractRequiredString(map, MODEL_ID, ModelConfigurations.SERVICE_SETTINGS, validationException);
+        RateLimitSettings rateLimitSettings = RateLimitSettings.of(
+            map,
+            DEFAULT_RATE_LIMIT_SETTINGS,
+            validationException,
+            ElasticInferenceService.NAME,
+            context
+        );
+
+        SimilarityMeasure similarity = extractSimilarity(map, ModelConfigurations.SERVICE_SETTINGS, validationException);
+        Integer dims = removeAsType(map, DIMENSIONS, Integer.class);
+        Integer maxInputTokens = removeAsType(map, MAX_INPUT_TOKENS, Integer.class);
+
+        if (validationException.validationErrors().isEmpty() == false) {
+            throw validationException;
+        }
+
+        return new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(modelId, similarity, dims, maxInputTokens, rateLimitSettings);
+    }
+
+    private static ElasticInferenceServiceDenseTextEmbeddingsServiceSettings fromPersistentMap(
+        Map<String, Object> map,
+        ConfigurationParseContext context
+    ) {
+        ValidationException validationException = new ValidationException();
+
+        String modelId = extractRequiredString(map, MODEL_ID, ModelConfigurations.SERVICE_SETTINGS, validationException);
+        RateLimitSettings rateLimitSettings = RateLimitSettings.of(
+            map,
+            DEFAULT_RATE_LIMIT_SETTINGS,
+            validationException,
+            ElasticInferenceService.NAME,
+            context
+        );
+
+        SimilarityMeasure similarity = extractSimilarity(map, ModelConfigurations.SERVICE_SETTINGS, validationException);
+        Integer dims = removeAsType(map, DIMENSIONS, Integer.class);
+        Integer maxInputTokens = removeAsType(map, MAX_INPUT_TOKENS, Integer.class);
+
+        if (validationException.validationErrors().isEmpty() == false) {
+            throw validationException;
+        }
+
+        return new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(modelId, similarity, dims, maxInputTokens, rateLimitSettings);
+    }
+
+    public ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+        String modelId,
+        @Nullable SimilarityMeasure similarity,
+        @Nullable Integer dimensions,
+        @Nullable Integer maxInputTokens,
+        RateLimitSettings rateLimitSettings
+    ) {
+        this.modelId = modelId;
+        this.similarity = similarity;
+        this.dimensions = dimensions;
+        this.maxInputTokens = maxInputTokens;
+        this.rateLimitSettings = Objects.requireNonNullElse(rateLimitSettings, DEFAULT_RATE_LIMIT_SETTINGS);
+    }
+
+    public ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(StreamInput in) throws IOException {
+        this.modelId = in.readString();
+        this.similarity = in.readOptionalEnum(SimilarityMeasure.class);
+        this.dimensions = in.readOptionalVInt();
+        this.maxInputTokens = in.readOptionalVInt();
+        this.rateLimitSettings = new RateLimitSettings(in);
+    }
+
+    @Override
+    public SimilarityMeasure similarity() {
+        return similarity;
+    }
+
+    @Override
+    public Integer dimensions() {
+        return dimensions;
+    }
+
+    public Integer maxInputTokens() {
+        return maxInputTokens;
+    }
+
+    @Override
+    public String modelId() {
+        return modelId;
+    }
+
+    @Override
+    public RateLimitSettings rateLimitSettings() {
+        return rateLimitSettings;
+    }
+
+    @Override
+    public DenseVectorFieldMapper.ElementType elementType() {
+        return DenseVectorFieldMapper.ElementType.FLOAT;
+    }
+
+    public RateLimitSettings getRateLimitSettings() {
+        return rateLimitSettings;
+    }
+
+    @Override
+    public String getWriteableName() {
+        return NAME;
+    }
+
+    @Override
+    public XContentBuilder toXContentFragmentOfExposedFields(XContentBuilder builder, Params params) throws IOException {
+        builder.field(MODEL_ID, modelId);
+        rateLimitSettings.toXContent(builder, params);
+
+        return builder;
+    }
+
+    @Override
+    public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
+        builder.startObject();
+
+        if (similarity != null) {
+            builder.field(SIMILARITY, similarity);
+        }
+
+        if (dimensions != null) {
+            builder.field(DIMENSIONS, dimensions);
+        }
+
+        if (maxInputTokens != null) {
+            builder.field(MAX_INPUT_TOKENS, maxInputTokens);
+        }
+
+        toXContentFragmentOfExposedFields(builder, params);
+
+        builder.endObject();
+        return builder;
+    }
+
+    @Override
+    public TransportVersion getMinimalSupportedVersion() {
+        return TransportVersions.ML_INFERENCE_ELASTIC_DENSE_TEXT_EMBEDDINGS_ADDED;
+    }
+
+    @Override
+    public void writeTo(StreamOutput out) throws IOException {
+        out.writeString(modelId);
+        out.writeOptionalEnum(SimilarityMeasure.translateSimilarity(similarity, out.getTransportVersion()));
+        out.writeOptionalVInt(dimensions);
+        out.writeOptionalVInt(maxInputTokens);
+        rateLimitSettings.writeTo(out);
+    }
+
+    @Override
+    public boolean equals(Object o) {
+        if (this == o) return true;
+        if (o == null || getClass() != o.getClass()) return false;
+        ElasticInferenceServiceDenseTextEmbeddingsServiceSettings that = (ElasticInferenceServiceDenseTextEmbeddingsServiceSettings) o;
+        return Objects.equals(modelId, that.modelId)
+            && similarity == that.similarity
+            && Objects.equals(dimensions, that.dimensions)
+            && Objects.equals(maxInputTokens, that.maxInputTokens)
+            && Objects.equals(rateLimitSettings, that.rateLimitSettings);
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hash(modelId, similarity, dimensions, maxInputTokens, rateLimitSettings);
+    }
+}

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/request/ElasticInferenceServiceDenseTextEmbeddingsRequest.java

@@ -0,0 +1,93 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.request;
+
+import org.apache.http.HttpHeaders;
+import org.apache.http.client.methods.HttpPost;
+import org.apache.http.client.methods.HttpRequestBase;
+import org.apache.http.entity.ByteArrayEntity;
+import org.apache.http.message.BasicHeader;
+import org.elasticsearch.common.Strings;
+import org.elasticsearch.inference.InputType;
+import org.elasticsearch.xcontent.XContentType;
+import org.elasticsearch.xpack.inference.external.request.Request;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModel;
+import org.elasticsearch.xpack.inference.telemetry.TraceContext;
+import org.elasticsearch.xpack.inference.telemetry.TraceContextHandler;
+
+import java.net.URI;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Objects;
+
+import static org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceSparseEmbeddingsRequest.inputTypeToUsageContext;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsRequest extends ElasticInferenceServiceRequest {
+
+    private final URI uri;
+    private final ElasticInferenceServiceDenseTextEmbeddingsModel model;
+    private final List<String> inputs;
+    private final TraceContextHandler traceContextHandler;
+    private final InputType inputType;
+
+    public ElasticInferenceServiceDenseTextEmbeddingsRequest(
+        ElasticInferenceServiceDenseTextEmbeddingsModel model,
+        List<String> inputs,
+        TraceContext traceContext,
+        ElasticInferenceServiceRequestMetadata metadata,
+        InputType inputType
+    ) {
+        super(metadata);
+        this.inputs = inputs;
+        this.model = Objects.requireNonNull(model);
+        this.uri = model.uri();
+        this.traceContextHandler = new TraceContextHandler(traceContext);
+        this.inputType = inputType;
+    }
+
+    @Override
+    public HttpRequestBase createHttpRequestBase() {
+        var httpPost = new HttpPost(uri);
+        var usageContext = inputTypeToUsageContext(inputType);
+        var requestEntity = Strings.toString(
+            new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(inputs, model.getServiceSettings().modelId(), usageContext)
+        );
+
+        ByteArrayEntity byteEntity = new ByteArrayEntity(requestEntity.getBytes(StandardCharsets.UTF_8));
+        httpPost.setEntity(byteEntity);
+
+        traceContextHandler.propagateTraceContext(httpPost);
+        httpPost.setHeader(new BasicHeader(HttpHeaders.CONTENT_TYPE, XContentType.JSON.mediaType()));
+
+        return httpPost;
+    }
+
+    public TraceContext getTraceContext() {
+        return traceContextHandler.traceContext();
+    }
+
+    @Override
+    public String getInferenceEntityId() {
+        return model.getInferenceEntityId();
+    }
+
+    @Override
+    public URI getURI() {
+        return this.uri;
+    }
+
+    @Override
+    public Request truncate() {
+        return this;
+    }
+
+    @Override
+    public boolean[] getTruncationInfo() {
+        return null;
+    }
+}

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/request/ElasticInferenceServiceDenseTextEmbeddingsRequestEntity.java

@@ -0,0 +1,57 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.request;
+
+import org.elasticsearch.core.Nullable;
+import org.elasticsearch.xcontent.ToXContentObject;
+import org.elasticsearch.xcontent.XContentBuilder;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceUsageContext;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Objects;
+
+public record ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+    List<String> inputs,
+    String modelId,
+    @Nullable ElasticInferenceServiceUsageContext usageContext
+) implements ToXContentObject {
+
+    private static final String INPUT_FIELD = "input";
+    private static final String MODEL_FIELD = "model";
+    private static final String USAGE_CONTEXT = "usage_context";
+
+    public ElasticInferenceServiceDenseTextEmbeddingsRequestEntity {
+        Objects.requireNonNull(inputs);
+        Objects.requireNonNull(modelId);
+    }
+
+    @Override
+    public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
+        builder.startObject();
+        builder.startArray(INPUT_FIELD);
+
+        for (String input : inputs) {
+            builder.value(input);
+        }
+
+        builder.endArray();
+
+        builder.field(MODEL_FIELD, modelId);
+
+        // optional field
+        if (Objects.nonNull(usageContext) && usageContext != ElasticInferenceServiceUsageContext.UNSPECIFIED) {
+            builder.field(USAGE_CONTEXT, usageContext);
+        }
+
+        builder.endObject();
+
+        return builder;
+    }
+
+}

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/external/request/elastic/rerank/ElasticInferenceServiceRerankRequest.java → x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/request/ElasticInferenceServiceRerankRequest.java

@@ -5,7 +5,7 @@
  * 2.0.
  */
 
-package org.elasticsearch.xpack.inference.external.request.elastic.rerank;
+package org.elasticsearch.xpack.inference.services.elastic.request;
 
 import org.apache.http.HttpHeaders;
 import org.apache.http.client.methods.HttpPost;
@@ -15,8 +15,6 @@ import org.apache.http.message.BasicHeader;
 import org.elasticsearch.common.Strings;
 import org.elasticsearch.xcontent.XContentType;
 import org.elasticsearch.xpack.inference.external.request.Request;
-import org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceRequest;
-import org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceRequestMetadata;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModel;
 import org.elasticsearch.xpack.inference.telemetry.TraceContext;
 import org.elasticsearch.xpack.inference.telemetry.TraceContextHandler;

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/external/request/elastic/rerank/ElasticInferenceServiceRerankRequestEntity.java → x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/request/ElasticInferenceServiceRerankRequestEntity.java

@@ -5,7 +5,7 @@
  * 2.0.
  */
 
-package org.elasticsearch.xpack.inference.external.request.elastic.rerank;
+package org.elasticsearch.xpack.inference.services.elastic.request;
 
 import org.elasticsearch.core.Nullable;
 import org.elasticsearch.xcontent.ToXContentObject;

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/response/ElasticInferenceServiceAuthorizationResponseEntity.java

@@ -44,6 +44,8 @@ public class ElasticInferenceServiceAuthorizationResponseEntity implements Infer
         TaskType.SPARSE_EMBEDDING,
         "chat",
         TaskType.CHAT_COMPLETION,
+        "embed/text/dense",
+        TaskType.TEXT_EMBEDDING,
         "rerank/text/text-similarity",
         TaskType.RERANK
     );

x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/services/elastic/response/ElasticInferenceServiceSparseEmbeddingsResponseEntity.java

@@ -51,11 +51,11 @@ public class ElasticInferenceServiceSparseEmbeddingsResponseEntity {
      *     <code>
      *         {
      *           "data": [
-     *                     {
-     *                       "Embed": 2.1259406,
-     *                       "this": 1.7073475,
-     *                       "text": 0.9020516
-     *                     },
+     *                     [
+     *                       2.1259406,
+     *                       1.7073475,
+     *                       0.9020516
+     *                     ],
      *                    (...)
      *                  ],
      *           "meta": {

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/external/request/elastic/ElasticInferenceServiceRerankRequestEntityTests.java

@@ -12,7 +12,7 @@ import org.elasticsearch.test.ESTestCase;
 import org.elasticsearch.xcontent.XContentBuilder;
 import org.elasticsearch.xcontent.XContentFactory;
 import org.elasticsearch.xcontent.XContentType;
-import org.elasticsearch.xpack.inference.external.request.elastic.rerank.ElasticInferenceServiceRerankRequestEntity;
+import org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceRerankRequestEntity;
 
 import java.io.IOException;
 import java.util.List;

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/external/request/elastic/ElasticInferenceServiceRerankRequestTests.java

@@ -10,7 +10,7 @@ package org.elasticsearch.xpack.inference.external.request.elastic;
 import org.apache.http.client.methods.HttpPost;
 import org.elasticsearch.tasks.Task;
 import org.elasticsearch.test.ESTestCase;
-import org.elasticsearch.xpack.inference.external.request.elastic.rerank.ElasticInferenceServiceRerankRequest;
+import org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceRerankRequest;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModelTests;
 import org.elasticsearch.xpack.inference.telemetry.TraceContext;
 

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/ElasticInferenceServiceTests.java

@@ -17,6 +17,7 @@ import org.elasticsearch.common.bytes.BytesReference;
 import org.elasticsearch.common.settings.Settings;
 import org.elasticsearch.common.xcontent.XContentHelper;
 import org.elasticsearch.core.TimeValue;
+import org.elasticsearch.index.mapper.vectors.DenseVectorFieldMapper;
 import org.elasticsearch.inference.ChunkInferenceInput;
 import org.elasticsearch.inference.ChunkedInference;
 import org.elasticsearch.inference.EmptySecretSettings;
@@ -29,7 +30,6 @@ import org.elasticsearch.inference.MinimalServiceSettings;
 import org.elasticsearch.inference.Model;
 import org.elasticsearch.inference.TaskType;
 import org.elasticsearch.inference.UnifiedCompletionRequest;
-import org.elasticsearch.inference.WeightedToken;
 import org.elasticsearch.plugins.Plugin;
 import org.elasticsearch.test.ESSingleNodeTestCase;
 import org.elasticsearch.test.http.MockResponse;
@@ -40,9 +40,8 @@ import org.elasticsearch.xcontent.XContentFactory;
 import org.elasticsearch.xcontent.XContentType;
 import org.elasticsearch.xpack.core.inference.action.InferenceAction;
 import org.elasticsearch.xpack.core.inference.results.ChunkedInferenceEmbedding;
-import org.elasticsearch.xpack.core.inference.results.EmbeddingResults;
-import org.elasticsearch.xpack.core.inference.results.SparseEmbeddingResults;
 import org.elasticsearch.xpack.core.inference.results.SparseEmbeddingResultsTests;
+import org.elasticsearch.xpack.core.inference.results.TextEmbeddingFloatResults;
 import org.elasticsearch.xpack.core.inference.results.UnifiedChatCompletionException;
 import org.elasticsearch.xpack.inference.InferencePlugin;
 import org.elasticsearch.xpack.inference.LocalStateInferencePlugin;
@@ -59,6 +58,7 @@ import org.elasticsearch.xpack.inference.services.elastic.authorization.ElasticI
 import org.elasticsearch.xpack.inference.services.elastic.authorization.ElasticInferenceServiceAuthorizationRequestHandler;
 import org.elasticsearch.xpack.inference.services.elastic.completion.ElasticInferenceServiceCompletionModel;
 import org.elasticsearch.xpack.inference.services.elastic.completion.ElasticInferenceServiceCompletionServiceSettings;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModelTests;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModel;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModelTests;
 import org.elasticsearch.xpack.inference.services.elastic.response.ElasticInferenceServiceAuthorizationResponseEntity;
@@ -421,47 +421,6 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
         }
     }
 
-    public void testInfer_ThrowsErrorWhenTaskTypeIsNotValid() throws IOException {
-        var sender = mock(Sender.class);
-
-        var factory = mock(HttpRequestSender.Factory.class);
-        when(factory.createSender()).thenReturn(sender);
-
-        var mockModel = getInvalidModel("model_id", "service_name", TaskType.TEXT_EMBEDDING);
-
-        try (var service = createService(factory)) {
-            PlainActionFuture<InferenceServiceResults> listener = new PlainActionFuture<>();
-            service.infer(
-                mockModel,
-                null,
-                null,
-                null,
-                List.of(""),
-                false,
-                new HashMap<>(),
-                InputType.INGEST,
-                InferenceAction.Request.DEFAULT_TIMEOUT,
-                listener
-            );
-
-            var thrownException = expectThrows(ElasticsearchStatusException.class, () -> listener.actionGet(TIMEOUT));
-            MatcherAssert.assertThat(
-                thrownException.getMessage(),
-                is(
-                    "Inference entity [model_id] does not support task type [text_embedding] "
-                        + "for inference, the task type must be one of [sparse_embedding, rerank]."
-                )
-            );
-
-            verify(factory, times(1)).createSender();
-            verify(sender, times(1)).start();
-        }
-
-        verify(sender, times(1)).close();
-        verifyNoMoreInteractions(factory);
-        verifyNoMoreInteractions(sender);
-    }
-
     public void testInfer_ThrowsErrorWhenTaskTypeIsNotValid_ChatCompletion() throws IOException {
         var sender = mock(Sender.class);
 
@@ -490,7 +449,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                 thrownException.getMessage(),
                 is(
                     "Inference entity [model_id] does not support task type [chat_completion] "
-                        + "for inference, the task type must be one of [sparse_embedding, rerank]. "
+                        + "for inference, the task type must be one of [text_embedding, sparse_embedding, rerank]. "
                         + "The task type for the inference entity is chat_completion, "
                         + "please use the _inference/chat_completion/model_id/_stream URL."
                 )
@@ -701,82 +660,6 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
         }
     }
 
-    public void testChunkedInfer_PropagatesProductUseCaseHeader() throws IOException {
-        var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
-        var elasticInferenceServiceURL = getUrl(webServer);
-
-        try (var service = createService(senderFactory, elasticInferenceServiceURL)) {
-            String responseJson = """
-                {
-                    "data": [
-                        {
-                            "hello": 2.1259406,
-                            "greet": 1.7073475
-                        }
-                    ]
-                }
-                """;
-
-            webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
-
-            // Set up the product use case in the thread context
-            String productUseCase = "test-product-use-case";
-            threadPool.getThreadContext().putHeader(InferencePlugin.X_ELASTIC_PRODUCT_USE_CASE_HTTP_HEADER, productUseCase);
-
-            var model = ElasticInferenceServiceSparseEmbeddingsModelTests.createModel(elasticInferenceServiceURL, "my-model-id");
-            PlainActionFuture<List<ChunkedInference>> listener = new PlainActionFuture<>();
-
-            try {
-                service.chunkedInfer(
-                    model,
-                    null,
-                    List.of(new ChunkInferenceInput("input text")),
-                    new HashMap<>(),
-                    InputType.INGEST,
-                    InferenceAction.Request.DEFAULT_TIMEOUT,
-                    listener
-                );
-
-                var results = listener.actionGet(TIMEOUT);
-
-                // Verify the response was processed correctly
-                ChunkedInference inferenceResult = results.getFirst();
-                assertThat(inferenceResult, instanceOf(ChunkedInferenceEmbedding.class));
-                var sparseResult = (ChunkedInferenceEmbedding) inferenceResult;
-                assertThat(
-                    sparseResult.chunks(),
-                    is(
-                        List.of(
-                            new EmbeddingResults.Chunk(
-                                new SparseEmbeddingResults.Embedding(
-                                    List.of(new WeightedToken("hello", 2.1259406f), new WeightedToken("greet", 1.7073475f)),
-                                    false
-                                ),
-                                new ChunkedInference.TextOffset(0, "input text".length())
-                            )
-                        )
-                    )
-                );
-
-                // Verify the request was sent and contains expected headers
-                MatcherAssert.assertThat(webServer.requests(), hasSize(1));
-                var request = webServer.requests().getFirst();
-                assertNull(request.getUri().getQuery());
-                MatcherAssert.assertThat(request.getHeader(HttpHeaders.CONTENT_TYPE), equalTo(XContentType.JSON.mediaType()));
-
-                // Check that the product use case header was set correctly
-                assertThat(request.getHeader(InferencePlugin.X_ELASTIC_PRODUCT_USE_CASE_HTTP_HEADER), is(productUseCase));
-
-                // Verify request body
-                var requestMap = entityAsMap(request.getBody());
-                assertThat(requestMap, is(Map.of("input", List.of("input text"), "model", "my-model-id", "usage_context", "ingest")));
-            } finally {
-                // Clean up the thread context
-                threadPool.getThreadContext().stashContext();
-            }
-        }
-    }
-
     public void testUnifiedCompletionInfer_PropagatesProductUseCaseHeader() throws IOException {
         var elasticInferenceServiceURL = getUrl(webServer);
         var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
@@ -835,30 +718,45 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
         }
     }
 
-    public void testChunkedInfer() throws IOException {
+    public void testChunkedInfer_PropagatesProductUseCaseHeader() throws IOException {
         var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
-        var elasticInferenceServiceURL = getUrl(webServer);
 
-        try (var service = createService(senderFactory, elasticInferenceServiceURL)) {
+        try (var service = createService(senderFactory, getUrl(webServer))) {
+
+            // Batching will call the service with 2 inputs
             String responseJson = """
                 {
                     "data": [
-                        {
-                            "hello": 2.1259406,
-                            "greet": 1.7073475
+                        [
+                            0.123,
+                            -0.456,
+                            0.789
+                        ],
+                        [
+                            0.987,
+                            -0.654,
+                            0.321
+                        ]
+                    ],
+                    "meta": {
+                        "usage": {
+                            "total_tokens": 10
                         }
-                    ]
+                    }
                 }
                 """;
-
             webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
+            var model = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(getUrl(webServer), "my-dense-model-id");
+
+            String productUseCase = "test-product-use-case";
+            threadPool.getThreadContext().putHeader(InferencePlugin.X_ELASTIC_PRODUCT_USE_CASE_HTTP_HEADER, productUseCase);
 
-            var model = ElasticInferenceServiceSparseEmbeddingsModelTests.createModel(elasticInferenceServiceURL, "my-model-id");
             PlainActionFuture<List<ChunkedInference>> listener = new PlainActionFuture<>();
+            // 2 inputs
             service.chunkedInfer(
                 model,
                 null,
-                List.of(new ChunkInferenceInput("input text")),
+                List.of(new ChunkInferenceInput("hello world"), new ChunkInferenceInput("dense embedding")),
                 new HashMap<>(),
                 InputType.INGEST,
                 InferenceAction.Request.DEFAULT_TIMEOUT,
@@ -866,58 +764,111 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
             );
 
             var results = listener.actionGet(TIMEOUT);
-            assertThat(results.get(0), instanceOf(ChunkedInferenceEmbedding.class));
-            var sparseResult = (ChunkedInferenceEmbedding) results.get(0);
-            assertThat(
-                sparseResult.chunks(),
-                is(
-                    List.of(
-                        new EmbeddingResults.Chunk(
-                            new SparseEmbeddingResults.Embedding(
-                                List.of(new WeightedToken("hello", 2.1259406f), new WeightedToken("greet", 1.7073475f)),
-                                false
-                            ),
-                            new ChunkedInference.TextOffset(0, "input text".length())
-                        )
-                    )
-                )
-            );
+            assertThat(results, hasSize(2));
 
-            MatcherAssert.assertThat(webServer.requests(), hasSize(1));
-            assertNull(webServer.requests().get(0).getUri().getQuery());
-            MatcherAssert.assertThat(
-                webServer.requests().get(0).getHeader(HttpHeaders.CONTENT_TYPE),
-                equalTo(XContentType.JSON.mediaType())
-            );
+            // Verify the response was processed correctly
+            ChunkedInference inferenceResult = results.getFirst();
+            assertThat(inferenceResult, instanceOf(ChunkedInferenceEmbedding.class));
+
+            // Verify the request was sent and contains expected headers
+            assertThat(webServer.requests(), hasSize(1));
+            var request = webServer.requests().getFirst();
+            assertNull(request.getUri().getQuery());
+            assertThat(request.getHeader(HttpHeaders.CONTENT_TYPE), equalTo(XContentType.JSON.mediaType()));
 
-            var requestMap = entityAsMap(webServer.requests().get(0).getBody());
-            assertThat(requestMap, is(Map.of("input", List.of("input text"), "model", "my-model-id", "usage_context", "ingest")));
+            // Check that the product use case header was set correctly
+            assertThat(request.getHeader(InferencePlugin.X_ELASTIC_PRODUCT_USE_CASE_HTTP_HEADER), is(productUseCase));
+
+        } finally {
+            // Clean up the thread context
+            threadPool.getThreadContext().stashContext();
         }
     }
 
-    public void testHideFromConfigurationApi_ReturnsTrue_WithNoAvailableModels() throws Exception {
-        try (var service = createServiceWithMockSender(ElasticInferenceServiceAuthorizationModel.newDisabledService())) {
-            ensureAuthorizationCallFinished(service);
+    public void testChunkedInfer_BatchesCallsChunkingSettingsSet() throws IOException {
+        var model = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(getUrl(webServer), "my-dense-model-id");
 
-            assertTrue(service.hideFromConfigurationApi());
+        var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
+
+        try (var service = createService(senderFactory, getUrl(webServer))) {
+
+            // Batching will call the service with 2 inputs
+            String responseJson = """
+                {
+                    "data": [
+                        [
+                            0.123,
+                            -0.456,
+                            0.789
+                        ],
+                        [
+                            0.987,
+                            -0.654,
+                            0.321
+                        ]
+                    ],
+                    "meta": {
+                        "usage": {
+                            "total_tokens": 10
+                        }
+                    }
+                }
+                """;
+            webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
+
+            PlainActionFuture<List<ChunkedInference>> listener = new PlainActionFuture<>();
+            // 2 inputs
+            service.chunkedInfer(
+                model,
+                null,
+                List.of(new ChunkInferenceInput("hello world"), new ChunkInferenceInput("dense embedding")),
+                new HashMap<>(),
+                InputType.INGEST,
+                InferenceAction.Request.DEFAULT_TIMEOUT,
+                listener
+            );
+
+            var results = listener.actionGet(TIMEOUT);
+            assertThat(results, hasSize(2));
+
+            // First result
+            {
+                assertThat(results.getFirst(), instanceOf(ChunkedInferenceEmbedding.class));
+                var denseResult = (ChunkedInferenceEmbedding) results.getFirst();
+                assertThat(denseResult.chunks(), hasSize(1));
+                assertEquals(new ChunkedInference.TextOffset(0, "hello world".length()), denseResult.chunks().getFirst().offset());
+                assertThat(denseResult.chunks().get(0).embedding(), instanceOf(TextEmbeddingFloatResults.Embedding.class));
+
+                var embedding = (TextEmbeddingFloatResults.Embedding) denseResult.chunks().get(0).embedding();
+                assertArrayEquals(new float[] { 0.123f, -0.456f, 0.789f }, embedding.values(), 0.0f);
+            }
+
+            // Second result
+            {
+                assertThat(results.get(1), instanceOf(ChunkedInferenceEmbedding.class));
+                var denseResult = (ChunkedInferenceEmbedding) results.get(1);
+                assertThat(denseResult.chunks(), hasSize(1));
+                assertEquals(new ChunkedInference.TextOffset(0, "dense embedding".length()), denseResult.chunks().getFirst().offset());
+                assertThat(denseResult.chunks().getFirst().embedding(), instanceOf(TextEmbeddingFloatResults.Embedding.class));
+
+                var embedding = (TextEmbeddingFloatResults.Embedding) denseResult.chunks().get(0).embedding();
+                assertArrayEquals(new float[] { 0.987f, -0.654f, 0.321f }, embedding.values(), 0.0f);
+            }
+
+            assertThat(webServer.requests(), hasSize(1));
+            assertNull(webServer.requests().getFirst().getUri().getQuery());
+            assertThat(webServer.requests().getFirst().getHeader(HttpHeaders.CONTENT_TYPE), equalTo(XContentType.JSON.mediaType()));
+
+            var requestMap = entityAsMap(webServer.requests().getFirst().getBody());
+            MatcherAssert.assertThat(
+                requestMap,
+                is(Map.of("input", List.of("hello world", "dense embedding"), "model", "my-dense-model-id", "usage_context", "ingest"))
+            );
         }
     }
 
-    public void testHideFromConfigurationApi_ReturnsTrue_WithModelTaskTypesThatAreNotImplemented() throws Exception {
-        try (
-            var service = createServiceWithMockSender(
-                ElasticInferenceServiceAuthorizationModel.of(
-                    new ElasticInferenceServiceAuthorizationResponseEntity(
-                        List.of(
-                            new ElasticInferenceServiceAuthorizationResponseEntity.AuthorizedModel(
-                                "model-1",
-                                EnumSet.of(TaskType.TEXT_EMBEDDING)
-                            )
-                        )
-                    )
-                )
-            )
-        ) {
+    public void testHideFromConfigurationApi_ReturnsTrue_WithNoAvailableModels() throws Exception {
+        try (var service = createServiceWithMockSender(ElasticInferenceServiceAuthorizationModel.newDisabledService())) {
             ensureAuthorizationCallFinished(service);
 
             assertTrue(service.hideFromConfigurationApi());
@@ -953,7 +904,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                         List.of(
                             new ElasticInferenceServiceAuthorizationResponseEntity.AuthorizedModel(
                                 "model-1",
-                                EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.CHAT_COMPLETION)
+                                EnumSet.of(TaskType.SPARSE_EMBEDDING, TaskType.CHAT_COMPLETION, TaskType.TEXT_EMBEDDING)
                             )
                         )
                     )
@@ -966,7 +917,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                 {
                        "service": "elastic",
                        "name": "Elastic",
-                       "task_types": ["sparse_embedding", "chat_completion"],
+                       "task_types": ["sparse_embedding", "chat_completion", "text_embedding"],
                        "configurations": {
                            "rate_limit.requests_per_minute": {
                                "description": "Minimize the number of rate limit errors.",
@@ -975,7 +926,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "int",
-                               "supported_task_types": ["sparse_embedding" , "rerank", "chat_completion"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding" , "rerank", "chat_completion"]
                            },
                            "model_id": {
                                "description": "The name of the model to use for the inference task.",
@@ -984,7 +935,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "str",
-                               "supported_task_types": ["sparse_embedding" , "rerank", "chat_completion"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding" , "rerank", "chat_completion"]
                            },
                            "max_input_tokens": {
                                "description": "Allows you to specify the maximum number of tokens per input.",
@@ -993,7 +944,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "int",
-                               "supported_task_types": ["sparse_embedding"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding"]
                            }
                        }
                    }
@@ -1030,7 +981,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "int",
-                               "supported_task_types": ["sparse_embedding" , "rerank", "chat_completion"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding" , "rerank", "chat_completion"]
                            },
                            "model_id": {
                                "description": "The name of the model to use for the inference task.",
@@ -1039,7 +990,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "str",
-                               "supported_task_types": ["sparse_embedding" , "rerank", "chat_completion"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding" , "rerank", "chat_completion"]
                            },
                            "max_input_tokens": {
                                "description": "Allows you to specify the maximum number of tokens per input.",
@@ -1048,7 +999,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "int",
-                               "supported_task_types": ["sparse_embedding"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding"]
                            }
                        }
                    }
@@ -1090,7 +1041,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                 {
                        "service": "elastic",
                        "name": "Elastic",
-                       "task_types": [],
+                       "task_types": ["text_embedding"],
                        "configurations": {
                            "rate_limit.requests_per_minute": {
                                "description": "Minimize the number of rate limit errors.",
@@ -1099,7 +1050,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "int",
-                               "supported_task_types": ["sparse_embedding" , "rerank", "chat_completion"]
+                               "supported_task_types": ["text_embedding" , "sparse_embedding", "rerank", "chat_completion"]
                            },
                            "model_id": {
                                "description": "The name of the model to use for the inference task.",
@@ -1108,7 +1059,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "str",
-                               "supported_task_types": ["sparse_embedding" , "rerank", "chat_completion"]
+                               "supported_task_types": ["text_embedding" , "sparse_embedding", "rerank", "chat_completion"]
                            },
                            "max_input_tokens": {
                                "description": "Allows you to specify the maximum number of tokens per input.",
@@ -1117,7 +1068,7 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                                "sensitive": false,
                                "updatable": false,
                                "type": "int",
-                               "supported_task_types": ["sparse_embedding"]
+                               "supported_task_types": ["text_embedding", "sparse_embedding"]
                            }
                        }
                    }
@@ -1296,6 +1247,10 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                       "task_types": ["embed/text/sparse"]
                     },
                     {
+                      "model_name": "multilingual-embed-v1",
+                      "task_types": ["embed/text/dense"]
+                    },
+                  {
                       "model_name": "rerank-v1",
                       "task_types": ["rerank/text/text-similarity"]
                     }
@@ -1319,6 +1274,16 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                             MinimalServiceSettings.sparseEmbedding(ElasticInferenceService.NAME),
                             service
                         ),
+                        new InferenceService.DefaultConfigId(
+                            ".multilingual-embed-v1-elastic",
+                            MinimalServiceSettings.textEmbedding(
+                                ElasticInferenceService.NAME,
+                                ElasticInferenceService.DENSE_TEXT_EMBEDDINGS_DIMENSIONS,
+                                ElasticInferenceService.defaultDenseTextEmbeddingsSimilarity(),
+                                DenseVectorFieldMapper.ElementType.FLOAT
+                            ),
+                            service
+                        ),
                         new InferenceService.DefaultConfigId(
                             ".rainbow-sprinkles-elastic",
                             MinimalServiceSettings.chatCompletion(ElasticInferenceService.NAME),
@@ -1332,16 +1297,19 @@ public class ElasticInferenceServiceTests extends ESSingleNodeTestCase {
                     )
                 )
             );
-            assertThat(service.supportedTaskTypes(), is(EnumSet.of(TaskType.CHAT_COMPLETION, TaskType.SPARSE_EMBEDDING, TaskType.RERANK)));
+            assertThat(
+                service.supportedTaskTypes(),
+                is(EnumSet.of(TaskType.CHAT_COMPLETION, TaskType.SPARSE_EMBEDDING, TaskType.RERANK, TaskType.TEXT_EMBEDDING))
+            );
 
             PlainActionFuture<List<Model>> listener = new PlainActionFuture<>();
             service.defaultConfigs(listener);
             var models = listener.actionGet(TIMEOUT);
-            assertThat(models.size(), is(3));
+            assertThat(models.size(), is(4));
             assertThat(models.get(0).getConfigurations().getInferenceEntityId(), is(".elser-v2-elastic"));
-            assertThat(models.get(1).getConfigurations().getInferenceEntityId(), is(".rainbow-sprinkles-elastic"));
-            assertThat(models.get(2).getConfigurations().getInferenceEntityId(), is(".rerank-v1-elastic"));
-
+            assertThat(models.get(1).getConfigurations().getInferenceEntityId(), is(".multilingual-embed-v1-elastic"));
+            assertThat(models.get(2).getConfigurations().getInferenceEntityId(), is(".rainbow-sprinkles-elastic"));
+            assertThat(models.get(3).getConfigurations().getInferenceEntityId(), is(".rerank-v1-elastic"));
         }
     }
 

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/action/ElasticInferenceServiceActionCreatorTests.java

@@ -22,12 +22,14 @@ import org.elasticsearch.xcontent.XContentType;
 import org.elasticsearch.xpack.core.inference.action.InferenceAction;
 import org.elasticsearch.xpack.core.inference.results.RankedDocsResultsTests;
 import org.elasticsearch.xpack.core.inference.results.SparseEmbeddingResultsTests;
+import org.elasticsearch.xpack.core.inference.results.TextEmbeddingFloatResults;
 import org.elasticsearch.xpack.inference.external.http.HttpClientManager;
 import org.elasticsearch.xpack.inference.external.http.sender.EmbeddingsInput;
 import org.elasticsearch.xpack.inference.external.http.sender.HttpRequestSenderTests;
 import org.elasticsearch.xpack.inference.external.http.sender.QueryAndDocsInputs;
 import org.elasticsearch.xpack.inference.logging.ThrottlerManager;
 import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceSparseEmbeddingsModelTests;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModelTests;
 import org.elasticsearch.xpack.inference.services.elastic.rerank.ElasticInferenceServiceRerankModelTests;
 import org.elasticsearch.xpack.inference.telemetry.TraceContext;
 import org.junit.After;
@@ -46,6 +48,7 @@ import static org.elasticsearch.xpack.inference.external.http.retry.RetrySetting
 import static org.elasticsearch.xpack.inference.external.http.sender.HttpRequestSenderTests.createSender;
 import static org.elasticsearch.xpack.inference.services.ServiceComponentsTests.createWithEmptySettings;
 import static org.hamcrest.Matchers.contains;
+import static org.hamcrest.Matchers.containsString;
 import static org.hamcrest.Matchers.equalTo;
 import static org.hamcrest.Matchers.hasSize;
 import static org.hamcrest.Matchers.instanceOf;
@@ -256,6 +259,206 @@ public class ElasticInferenceServiceActionCreatorTests extends ESTestCase {
         }
     }
 
+    @SuppressWarnings("unchecked")
+    public void testExecute_ReturnsSuccessfulResponse_ForDenseTextEmbeddingsAction() throws IOException {
+        var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
+
+        try (var sender = createSender(senderFactory)) {
+            sender.start();
+
+            String responseJson = """
+                {
+                    "data": [
+                        [
+                            2.1259406,
+                            1.7073475,
+                            0.9020516
+                        ],
+                        [
+                            1.8342123,
+                            2.3456789,
+                            0.7654321
+                        ]
+                    ]
+                }
+                """;
+
+            webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
+
+            var model = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(getUrl(webServer), "my-dense-model-id");
+            var actionCreator = new ElasticInferenceServiceActionCreator(sender, createWithEmptySettings(threadPool), createTraceContext());
+            var action = actionCreator.create(model);
+
+            PlainActionFuture<InferenceServiceResults> listener = new PlainActionFuture<>();
+            action.execute(
+                new EmbeddingsInput(List.of("hello world", "second text"), null, InputType.UNSPECIFIED),
+                InferenceAction.Request.DEFAULT_TIMEOUT,
+                listener
+            );
+
+            var result = listener.actionGet(TIMEOUT);
+
+            assertThat(result, instanceOf(TextEmbeddingFloatResults.class));
+            var textEmbeddingResults = (TextEmbeddingFloatResults) result;
+            assertThat(textEmbeddingResults.embeddings(), hasSize(2));
+
+            var firstEmbedding = textEmbeddingResults.embeddings().get(0);
+            assertThat(firstEmbedding.values(), is(new float[] { 2.1259406f, 1.7073475f, 0.9020516f }));
+
+            var secondEmbedding = textEmbeddingResults.embeddings().get(1);
+            assertThat(secondEmbedding.values(), is(new float[] { 1.8342123f, 2.3456789f, 0.7654321f }));
+
+            assertThat(webServer.requests(), hasSize(1));
+            assertNull(webServer.requests().get(0).getUri().getQuery());
+            assertThat(webServer.requests().get(0).getHeader(HttpHeaders.CONTENT_TYPE), equalTo(XContentType.JSON.mediaType()));
+
+            var requestMap = entityAsMap(webServer.requests().get(0).getBody());
+            assertThat(requestMap.size(), is(2));
+            assertThat(requestMap.get("input"), instanceOf(List.class));
+            var inputList = (List<String>) requestMap.get("input");
+            assertThat(inputList, contains("hello world", "second text"));
+            assertThat(requestMap.get("model"), is("my-dense-model-id"));
+        }
+    }
+
+    @SuppressWarnings("unchecked")
+    public void testExecute_ReturnsSuccessfulResponse_ForDenseTextEmbeddingsAction_WithUsageContext() throws IOException {
+        var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
+
+        try (var sender = createSender(senderFactory)) {
+            sender.start();
+
+            String responseJson = """
+                {
+                    "data": [
+                        [
+                            0.1234567,
+                            0.9876543
+                        ]
+                    ]
+                }
+                """;
+
+            webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
+
+            var model = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(getUrl(webServer), "my-dense-model-id");
+            var actionCreator = new ElasticInferenceServiceActionCreator(sender, createWithEmptySettings(threadPool), createTraceContext());
+            var action = actionCreator.create(model);
+
+            PlainActionFuture<InferenceServiceResults> listener = new PlainActionFuture<>();
+            action.execute(
+                new EmbeddingsInput(List.of("search query"), null, InputType.SEARCH),
+                InferenceAction.Request.DEFAULT_TIMEOUT,
+                listener
+            );
+
+            var result = listener.actionGet(TIMEOUT);
+
+            assertThat(result, instanceOf(TextEmbeddingFloatResults.class));
+            var textEmbeddingResults = (TextEmbeddingFloatResults) result;
+            assertThat(textEmbeddingResults.embeddings(), hasSize(1));
+
+            var embedding = textEmbeddingResults.embeddings().get(0);
+            assertThat(embedding.values(), is(new float[] { 0.1234567f, 0.9876543f }));
+
+            assertThat(webServer.requests(), hasSize(1));
+            var requestMap = entityAsMap(webServer.requests().get(0).getBody());
+            assertThat(requestMap.size(), is(3));
+            assertThat(requestMap.get("input"), instanceOf(List.class));
+            var inputList = (List<String>) requestMap.get("input");
+            assertThat(inputList, contains("search query"));
+            assertThat(requestMap.get("model"), is("my-dense-model-id"));
+            assertThat(requestMap.get("usage_context"), is("search"));
+        }
+    }
+
+    @SuppressWarnings("unchecked")
+    public void testSend_FailsFromInvalidResponseFormat_ForDenseTextEmbeddingsAction() throws IOException {
+        // timeout as zero for no retries
+        var settings = buildSettingsWithRetryFields(
+            TimeValue.timeValueMillis(1),
+            TimeValue.timeValueMinutes(1),
+            TimeValue.timeValueSeconds(0)
+        );
+        var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager, settings);
+
+        try (var sender = createSender(senderFactory)) {
+            sender.start();
+
+            // This will fail because the expected output is {"data": [[...]]}
+            String responseJson = """
+                {
+                    "data": {
+                        "embedding": [2.1259406, 1.7073475]
+                    }
+                }
+                """;
+
+            webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
+
+            var model = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(getUrl(webServer), "my-dense-model-id");
+            var actionCreator = new ElasticInferenceServiceActionCreator(sender, createWithEmptySettings(threadPool), createTraceContext());
+            var action = actionCreator.create(model);
+
+            PlainActionFuture<InferenceServiceResults> listener = new PlainActionFuture<>();
+            action.execute(
+                new EmbeddingsInput(List.of("hello world"), null, InputType.UNSPECIFIED),
+                InferenceAction.Request.DEFAULT_TIMEOUT,
+                listener
+            );
+
+            var thrownException = expectThrows(ElasticsearchException.class, () -> listener.actionGet(TIMEOUT));
+            assertThat(thrownException.getMessage(), containsString("[EmbeddingFloatResult] failed to parse field [data]"));
+
+            assertThat(webServer.requests(), hasSize(1));
+            assertNull(webServer.requests().get(0).getUri().getQuery());
+            assertThat(webServer.requests().get(0).getHeader(HttpHeaders.CONTENT_TYPE), equalTo(XContentType.JSON.mediaType()));
+
+            var requestMap = entityAsMap(webServer.requests().get(0).getBody());
+            assertThat(requestMap.size(), is(2));
+            assertThat(requestMap.get("input"), instanceOf(List.class));
+            var inputList = (List<String>) requestMap.get("input");
+            assertThat(inputList, contains("hello world"));
+            assertThat(requestMap.get("model"), is("my-dense-model-id"));
+        }
+    }
+
+    @SuppressWarnings("unchecked")
+    public void testExecute_ReturnsSuccessfulResponse_ForDenseTextEmbeddingsAction_EmptyEmbeddings() throws IOException {
+        var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
+
+        try (var sender = createSender(senderFactory)) {
+            sender.start();
+
+            String responseJson = """
+                {
+                    "data": []
+                }
+                """;
+
+            webServer.enqueue(new MockResponse().setResponseCode(200).setBody(responseJson));
+
+            var model = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(getUrl(webServer), "my-dense-model-id");
+            var actionCreator = new ElasticInferenceServiceActionCreator(sender, createWithEmptySettings(threadPool), createTraceContext());
+            var action = actionCreator.create(model);
+
+            PlainActionFuture<InferenceServiceResults> listener = new PlainActionFuture<>();
+            action.execute(new EmbeddingsInput(List.of(), null, InputType.UNSPECIFIED), InferenceAction.Request.DEFAULT_TIMEOUT, listener);
+
+            var result = listener.actionGet(TIMEOUT);
+
+            assertThat(result, instanceOf(TextEmbeddingFloatResults.class));
+            var textEmbeddingResults = (TextEmbeddingFloatResults) result;
+            assertThat(textEmbeddingResults.embeddings(), hasSize(0));
+
+            assertThat(webServer.requests(), hasSize(1));
+            var requestMap = entityAsMap(webServer.requests().get(0).getBody());
+            assertThat(requestMap.get("input"), instanceOf(List.class));
+            var inputList = (List<String>) requestMap.get("input");
+            assertThat(inputList, hasSize(0));
+        }
+    }
+
     public void testExecute_ReturnsSuccessfulResponse_AfterTruncating() throws IOException {
         var senderFactory = HttpRequestSenderTests.createSenderFactory(threadPool, clientManager);
 

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/densetextembeddings/ElasticInferenceServiceDenseTextEmbeddingsModelTests.java

@@ -0,0 +1,39 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.densetextembeddings;
+
+import org.elasticsearch.inference.EmptySecretSettings;
+import org.elasticsearch.inference.EmptyTaskSettings;
+import org.elasticsearch.inference.SimilarityMeasure;
+import org.elasticsearch.inference.TaskType;
+import org.elasticsearch.xpack.inference.chunking.ChunkingSettingsBuilder;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceComponents;
+import org.elasticsearch.xpack.inference.services.settings.RateLimitSettings;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsModelTests {
+
+    public static ElasticInferenceServiceDenseTextEmbeddingsModel createModel(String url, String modelId) {
+        return new ElasticInferenceServiceDenseTextEmbeddingsModel(
+            "id",
+            TaskType.TEXT_EMBEDDING,
+            "elastic",
+            new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+                modelId,
+                SimilarityMeasure.COSINE,
+                null,
+                null,
+                new RateLimitSettings(1000L)
+            ),
+            EmptyTaskSettings.INSTANCE,
+            EmptySecretSettings.INSTANCE,
+            ElasticInferenceServiceComponents.of(url),
+            ChunkingSettingsBuilder.DEFAULT_SETTINGS
+        );
+    }
+
+}

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/densetextembeddings/ElasticInferenceServiceDenseTextEmbeddingsServiceSettingsTests.java

@@ -0,0 +1,165 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.densetextembeddings;
+
+import org.elasticsearch.common.Strings;
+import org.elasticsearch.common.io.stream.Writeable;
+import org.elasticsearch.inference.SimilarityMeasure;
+import org.elasticsearch.test.AbstractWireSerializingTestCase;
+import org.elasticsearch.xcontent.XContentBuilder;
+import org.elasticsearch.xcontent.XContentFactory;
+import org.elasticsearch.xcontent.XContentType;
+import org.elasticsearch.xpack.inference.services.ConfigurationParseContext;
+import org.elasticsearch.xpack.inference.services.ServiceFields;
+import org.elasticsearch.xpack.inference.services.settings.RateLimitSettings;
+
+import java.io.IOException;
+import java.util.HashMap;
+import java.util.Map;
+
+import static org.hamcrest.Matchers.is;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsServiceSettingsTests extends AbstractWireSerializingTestCase<
+    ElasticInferenceServiceDenseTextEmbeddingsServiceSettings> {
+
+    @Override
+    protected Writeable.Reader<ElasticInferenceServiceDenseTextEmbeddingsServiceSettings> instanceReader() {
+        return ElasticInferenceServiceDenseTextEmbeddingsServiceSettings::new;
+    }
+
+    @Override
+    protected ElasticInferenceServiceDenseTextEmbeddingsServiceSettings createTestInstance() {
+        return createRandom();
+    }
+
+    @Override
+    protected ElasticInferenceServiceDenseTextEmbeddingsServiceSettings mutateInstance(
+        ElasticInferenceServiceDenseTextEmbeddingsServiceSettings instance
+    ) throws IOException {
+        return randomValueOtherThan(instance, ElasticInferenceServiceDenseTextEmbeddingsServiceSettingsTests::createRandom);
+    }
+
+    public void testFromMap_Request_WithAllSettings() {
+        var modelId = "my-dense-model-id";
+        var similarity = SimilarityMeasure.COSINE;
+        var dimensions = 384;
+        var maxInputTokens = 512;
+
+        var serviceSettings = ElasticInferenceServiceDenseTextEmbeddingsServiceSettings.fromMap(
+            new HashMap<>(
+                Map.of(
+                    ServiceFields.MODEL_ID,
+                    modelId,
+                    ServiceFields.SIMILARITY,
+                    similarity.toString(),
+                    ServiceFields.DIMENSIONS,
+                    dimensions,
+                    ServiceFields.MAX_INPUT_TOKENS,
+                    maxInputTokens
+                )
+            ),
+            ConfigurationParseContext.REQUEST
+        );
+
+        assertThat(serviceSettings.modelId(), is(modelId));
+        assertThat(serviceSettings.similarity(), is(similarity));
+        assertThat(serviceSettings.dimensions(), is(dimensions));
+        assertThat(serviceSettings.maxInputTokens(), is(maxInputTokens));
+    }
+
+    public void testToXContent_WritesAllFields() throws IOException {
+        var modelId = "my-dense-model";
+        var similarity = SimilarityMeasure.DOT_PRODUCT;
+        var dimensions = 1024;
+        var maxInputTokens = 256;
+        var rateLimitSettings = new RateLimitSettings(5000);
+
+        var serviceSettings = new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+            modelId,
+            similarity,
+            dimensions,
+            maxInputTokens,
+            rateLimitSettings
+        );
+
+        XContentBuilder builder = XContentFactory.contentBuilder(XContentType.JSON);
+        serviceSettings.toXContent(builder, null);
+        String xContentResult = Strings.toString(builder);
+
+        String expectedResult = Strings.format(
+            """
+                {"similarity":"%s","dimensions":%d,"max_input_tokens":%d,"model_id":"%s","rate_limit":{"requests_per_minute":%d}}""",
+            similarity,
+            dimensions,
+            maxInputTokens,
+            modelId,
+            rateLimitSettings.requestsPerTimeUnit()
+        );
+
+        assertThat(xContentResult, is(expectedResult));
+    }
+
+    public void testToXContent_WritesOnlyNonNullFields() throws IOException {
+        var modelId = "my-dense-model";
+        var rateLimitSettings = new RateLimitSettings(2000);
+
+        var serviceSettings = new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+            modelId,
+            null, // similarity
+            null, // dimensions
+            null, // maxInputTokens
+            rateLimitSettings
+        );
+
+        XContentBuilder builder = XContentFactory.contentBuilder(XContentType.JSON);
+        serviceSettings.toXContent(builder, null);
+        String xContentResult = Strings.toString(builder);
+
+        assertThat(xContentResult, is(Strings.format("""
+            {"model_id":"%s","rate_limit":{"requests_per_minute":%d}}""", modelId, rateLimitSettings.requestsPerTimeUnit())));
+    }
+
+    public void testToXContentFragmentOfExposedFields() throws IOException {
+        var modelId = "my-dense-model";
+        var rateLimitSettings = new RateLimitSettings(1500);
+
+        var serviceSettings = new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+            modelId,
+            SimilarityMeasure.COSINE,
+            512,
+            128,
+            rateLimitSettings
+        );
+
+        XContentBuilder builder = XContentFactory.contentBuilder(XContentType.JSON);
+        builder.startObject();
+        serviceSettings.toXContentFragmentOfExposedFields(builder, null);
+        builder.endObject();
+        String xContentResult = Strings.toString(builder);
+
+        // Only model_id and rate_limit should be in exposed fields
+        assertThat(xContentResult, is(Strings.format("""
+            {"model_id":"%s","rate_limit":{"requests_per_minute":%d}}""", modelId, rateLimitSettings.requestsPerTimeUnit())));
+    }
+
+    public static ElasticInferenceServiceDenseTextEmbeddingsServiceSettings createRandom() {
+        var modelId = randomAlphaOfLength(10);
+        var similarity = SimilarityMeasure.COSINE;
+        var dimensions = randomBoolean() ? randomIntBetween(1, 1024) : null;
+        var maxInputTokens = randomBoolean() ? randomIntBetween(128, 256) : null;
+        var rateLimitSettings = randomBoolean() ? new RateLimitSettings(randomIntBetween(1, 10000)) : null;
+
+        return new ElasticInferenceServiceDenseTextEmbeddingsServiceSettings(
+            modelId,
+            similarity,
+            dimensions,
+            maxInputTokens,
+            rateLimitSettings
+        );
+    }
+}

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/request/ElasticInferenceServiceDenseTextEmbeddingsRequestEntityTests.java

@@ -0,0 +1,147 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.request;
+
+import org.elasticsearch.common.Strings;
+import org.elasticsearch.test.ESTestCase;
+import org.elasticsearch.xcontent.XContentBuilder;
+import org.elasticsearch.xcontent.XContentFactory;
+import org.elasticsearch.xcontent.XContentType;
+import org.elasticsearch.xpack.inference.services.elastic.ElasticInferenceServiceUsageContext;
+
+import java.io.IOException;
+import java.util.List;
+
+import static org.elasticsearch.xpack.inference.MatchersUtils.equalToIgnoringWhitespaceInJsonString;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsRequestEntityTests extends ESTestCase {
+
+    public void testToXContent_SingleInput_UnspecifiedUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of("abc"),
+            "my-model-id",
+            ElasticInferenceServiceUsageContext.UNSPECIFIED
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": ["abc"],
+                "model": "my-model-id"
+            }"""));
+    }
+
+    public void testToXContent_MultipleInputs_UnspecifiedUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of("abc", "def"),
+            "my-model-id",
+            ElasticInferenceServiceUsageContext.UNSPECIFIED
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": [
+                    "abc",
+                    "def"
+                ],
+                "model": "my-model-id"
+            }
+            """));
+    }
+
+    public void testToXContent_SingleInput_SearchUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of("abc"),
+            "my-model-id",
+            ElasticInferenceServiceUsageContext.SEARCH
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": ["abc"],
+                "model": "my-model-id",
+                "usage_context": "search"
+            }
+            """));
+    }
+
+    public void testToXContent_SingleInput_IngestUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of("abc"),
+            "my-model-id",
+            ElasticInferenceServiceUsageContext.INGEST
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": ["abc"],
+                "model": "my-model-id",
+                "usage_context": "ingest"
+            }
+            """));
+    }
+
+    public void testToXContent_MultipleInputs_SearchUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of("first input", "second input", "third input"),
+            "my-dense-model",
+            ElasticInferenceServiceUsageContext.SEARCH
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": [
+                    "first input",
+                    "second input",
+                    "third input"
+                ],
+                "model": "my-dense-model",
+                "usage_context": "search"
+            }
+            """));
+    }
+
+    public void testToXContent_MultipleInputs_IngestUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of("document one", "document two"),
+            "embedding-model-v2",
+            ElasticInferenceServiceUsageContext.INGEST
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": [
+                    "document one",
+                    "document two"
+                ],
+                "model": "embedding-model-v2",
+                "usage_context": "ingest"
+            }
+            """));
+    }
+
+    public void testToXContent_EmptyInput_UnspecifiedUsageContext() throws IOException {
+        var entity = new ElasticInferenceServiceDenseTextEmbeddingsRequestEntity(
+            List.of(""),
+            "my-model-id",
+            ElasticInferenceServiceUsageContext.UNSPECIFIED
+        );
+        String xContentString = xContentEntityToString(entity);
+        assertThat(xContentString, equalToIgnoringWhitespaceInJsonString("""
+            {
+                "input": [""],
+                "model": "my-model-id"
+            }
+            """));
+    }
+
+    private String xContentEntityToString(ElasticInferenceServiceDenseTextEmbeddingsRequestEntity entity) throws IOException {
+        XContentBuilder builder = XContentFactory.contentBuilder(XContentType.JSON);
+        entity.toXContent(builder, null);
+        return Strings.toString(builder);
+    }
+}

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/request/ElasticInferenceServiceDenseTextEmbeddingsRequestTests.java

@@ -0,0 +1,165 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.request;
+
+import org.apache.http.HttpHeaders;
+import org.apache.http.client.methods.HttpPost;
+import org.elasticsearch.inference.InputType;
+import org.elasticsearch.tasks.Task;
+import org.elasticsearch.test.ESTestCase;
+import org.elasticsearch.xcontent.XContentType;
+import org.elasticsearch.xpack.inference.services.elastic.densetextembeddings.ElasticInferenceServiceDenseTextEmbeddingsModelTests;
+import org.elasticsearch.xpack.inference.telemetry.TraceContext;
+
+import java.io.IOException;
+import java.util.List;
+
+import static org.elasticsearch.xpack.inference.external.http.Utils.entityAsMap;
+import static org.elasticsearch.xpack.inference.services.elastic.request.ElasticInferenceServiceRequestTests.randomElasticInferenceServiceRequestMetadata;
+import static org.hamcrest.Matchers.aMapWithSize;
+import static org.hamcrest.Matchers.equalTo;
+import static org.hamcrest.Matchers.instanceOf;
+import static org.hamcrest.Matchers.is;
+import static org.hamcrest.Matchers.nullValue;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsRequestTests extends ESTestCase {
+
+    public void testCreateHttpRequest_UsageContextSearch() throws IOException {
+        var url = "http://eis-gateway.com";
+        var input = List.of("input text");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, input, InputType.SEARCH);
+        var httpRequest = request.createHttpRequest();
+
+        assertThat(httpRequest.httpRequestBase(), instanceOf(HttpPost.class));
+        var httpPost = (HttpPost) httpRequest.httpRequestBase();
+
+        assertThat(httpPost.getLastHeader(HttpHeaders.CONTENT_TYPE).getValue(), is(XContentType.JSON.mediaType()));
+        var requestMap = entityAsMap(httpPost.getEntity().getContent());
+        assertThat(requestMap.size(), equalTo(3));
+        assertThat(requestMap.get("input"), is(input));
+        assertThat(requestMap.get("model"), is(modelId));
+        assertThat(requestMap.get("usage_context"), equalTo("search"));
+    }
+
+    public void testCreateHttpRequest_UsageContextIngest() throws IOException {
+        var url = "http://eis-gateway.com";
+        var input = List.of("ingest text");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, input, InputType.INGEST);
+        var httpRequest = request.createHttpRequest();
+
+        assertThat(httpRequest.httpRequestBase(), instanceOf(HttpPost.class));
+        var httpPost = (HttpPost) httpRequest.httpRequestBase();
+
+        assertThat(httpPost.getLastHeader(HttpHeaders.CONTENT_TYPE).getValue(), is(XContentType.JSON.mediaType()));
+        var requestMap = entityAsMap(httpPost.getEntity().getContent());
+        assertThat(requestMap.size(), equalTo(3));
+        assertThat(requestMap.get("input"), is(input));
+        assertThat(requestMap.get("model"), is(modelId));
+        assertThat(requestMap.get("usage_context"), equalTo("ingest"));
+    }
+
+    public void testCreateHttpRequest_UsageContextUnspecified() throws IOException {
+        var url = "http://eis-gateway.com";
+        var input = List.of("unspecified text");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, input, InputType.UNSPECIFIED);
+        var httpRequest = request.createHttpRequest();
+
+        assertThat(httpRequest.httpRequestBase(), instanceOf(HttpPost.class));
+        var httpPost = (HttpPost) httpRequest.httpRequestBase();
+
+        assertThat(httpPost.getLastHeader(HttpHeaders.CONTENT_TYPE).getValue(), is(XContentType.JSON.mediaType()));
+        var requestMap = entityAsMap(httpPost.getEntity().getContent());
+        assertThat(requestMap, aMapWithSize(2));
+        assertThat(requestMap.get("input"), is(input));
+        assertThat(requestMap.get("model"), is(modelId));
+        // usage_context should not be present for UNSPECIFIED
+    }
+
+    public void testCreateHttpRequest_MultipleInputs() throws IOException {
+        var url = "http://eis-gateway.com";
+        var inputs = List.of("first input", "second input", "third input");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, inputs, InputType.SEARCH);
+        var httpRequest = request.createHttpRequest();
+
+        assertThat(httpRequest.httpRequestBase(), instanceOf(HttpPost.class));
+        var httpPost = (HttpPost) httpRequest.httpRequestBase();
+
+        assertThat(httpPost.getLastHeader(HttpHeaders.CONTENT_TYPE).getValue(), is(XContentType.JSON.mediaType()));
+        var requestMap = entityAsMap(httpPost.getEntity().getContent());
+        assertThat(requestMap.size(), equalTo(3));
+        assertThat(requestMap.get("input"), is(inputs));
+        assertThat(requestMap.get("model"), is(modelId));
+        assertThat(requestMap.get("usage_context"), equalTo("search"));
+    }
+
+    public void testTraceContextPropagatedThroughHTTPHeaders() {
+        var url = "http://eis-gateway.com";
+        var input = List.of("input text");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, input, InputType.UNSPECIFIED);
+        var httpRequest = request.createHttpRequest();
+
+        assertThat(httpRequest.httpRequestBase(), instanceOf(HttpPost.class));
+        var httpPost = (HttpPost) httpRequest.httpRequestBase();
+
+        var traceParent = request.getTraceContext().traceParent();
+        var traceState = request.getTraceContext().traceState();
+
+        assertThat(httpPost.getLastHeader(Task.TRACE_PARENT_HTTP_HEADER).getValue(), is(traceParent));
+        assertThat(httpPost.getLastHeader(Task.TRACE_STATE).getValue(), is(traceState));
+    }
+
+    public void testTruncate_ReturnsSameInstance() {
+        var url = "http://eis-gateway.com";
+        var input = List.of("input text");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, input, InputType.UNSPECIFIED);
+        var truncatedRequest = request.truncate();
+
+        // Dense text embeddings request doesn't support truncation, should return same instance
+        assertThat(truncatedRequest, is(request));
+    }
+
+    public void testGetTruncationInfo_ReturnsNull() {
+        var url = "http://eis-gateway.com";
+        var input = List.of("input text");
+        var modelId = "my-dense-model-id";
+
+        var request = createRequest(url, modelId, input, InputType.UNSPECIFIED);
+
+        // Dense text embeddings request doesn't support truncation info
+        assertThat(request.getTruncationInfo(), is(nullValue()));
+    }
+
+    private ElasticInferenceServiceDenseTextEmbeddingsRequest createRequest(
+        String url,
+        String modelId,
+        List<String> inputs,
+        InputType inputType
+    ) {
+        var embeddingsModel = ElasticInferenceServiceDenseTextEmbeddingsModelTests.createModel(url, modelId);
+
+        return new ElasticInferenceServiceDenseTextEmbeddingsRequest(
+            embeddingsModel,
+            inputs,
+            new TraceContext(randomAlphaOfLength(10), randomAlphaOfLength(10)),
+            randomElasticInferenceServiceRequestMetadata(),
+            inputType
+        );
+    }
+}

x-pack/plugin/inference/src/test/java/org/elasticsearch/xpack/inference/services/elastic/response/ElasticInferenceServiceDenseTextEmbeddingsResponseEntityTests.java

@@ -0,0 +1,124 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+package org.elasticsearch.xpack.inference.services.elastic.response;
+
+import org.apache.http.HttpResponse;
+import org.elasticsearch.test.ESTestCase;
+import org.elasticsearch.xpack.core.inference.results.TextEmbeddingFloatResults;
+import org.elasticsearch.xpack.inference.external.http.HttpResult;
+import org.elasticsearch.xpack.inference.external.request.Request;
+import org.elasticsearch.xpack.inference.external.response.elastic.ElasticInferenceServiceDenseTextEmbeddingsResponseEntity;
+
+import java.nio.charset.StandardCharsets;
+
+import static org.hamcrest.CoreMatchers.is;
+import static org.hamcrest.Matchers.hasSize;
+import static org.mockito.Mockito.mock;
+
+public class ElasticInferenceServiceDenseTextEmbeddingsResponseEntityTests extends ESTestCase {
+
+    public void testDenseTextEmbeddingsResponse_SingleEmbeddingInData_NoMeta() throws Exception {
+        String responseJson = """
+            {
+                "data": [
+                    [
+                        1.23,
+                        4.56,
+                        7.89
+                    ]
+                ]
+            }
+            """;
+
+        TextEmbeddingFloatResults parsedResults = ElasticInferenceServiceDenseTextEmbeddingsResponseEntity.fromResponse(
+            mock(Request.class),
+            new HttpResult(mock(HttpResponse.class), responseJson.getBytes(StandardCharsets.UTF_8))
+        );
+
+        assertThat(parsedResults.embeddings(), hasSize(1));
+
+        var embedding = parsedResults.embeddings().get(0);
+        assertThat(embedding.values(), is(new float[] { 1.23f, 4.56f, 7.89f }));
+    }
+
+    public void testDenseTextEmbeddingsResponse_MultipleEmbeddingsInData_NoMeta() throws Exception {
+        String responseJson = """
+            {
+                "data": [
+                    [
+                        1.23,
+                        4.56,
+                        7.89
+                    ],
+                    [
+                        0.12,
+                        0.34,
+                        0.56
+                    ]
+                ]
+            }
+            """;
+
+        TextEmbeddingFloatResults parsedResults = ElasticInferenceServiceDenseTextEmbeddingsResponseEntity.fromResponse(
+            mock(Request.class),
+            new HttpResult(mock(HttpResponse.class), responseJson.getBytes(StandardCharsets.UTF_8))
+        );
+
+        assertThat(parsedResults.embeddings(), hasSize(2));
+
+        var firstEmbedding = parsedResults.embeddings().get(0);
+        assertThat(firstEmbedding.values(), is(new float[] { 1.23f, 4.56f, 7.89f }));
+
+        var secondEmbedding = parsedResults.embeddings().get(1);
+        assertThat(secondEmbedding.values(), is(new float[] { 0.12f, 0.34f, 0.56f }));
+    }
+
+    public void testDenseTextEmbeddingsResponse_EmptyData() throws Exception {
+        String responseJson = """
+            {
+                "data": []
+            }
+            """;
+
+        TextEmbeddingFloatResults parsedResults = ElasticInferenceServiceDenseTextEmbeddingsResponseEntity.fromResponse(
+            mock(Request.class),
+            new HttpResult(mock(HttpResponse.class), responseJson.getBytes(StandardCharsets.UTF_8))
+        );
+
+        assertThat(parsedResults.embeddings(), hasSize(0));
+    }
+
+    public void testDenseTextEmbeddingsResponse_SingleEmbeddingInData_IgnoresMeta() throws Exception {
+        String responseJson = """
+            {
+                "data": [
+                    [
+                        -1.0,
+                        0.0,
+                        1.0
+                    ]
+                ],
+                "meta": {
+                    "usage": {
+                        "total_tokens": 5
+                    }
+                }
+            }
+            """;
+
+        TextEmbeddingFloatResults parsedResults = ElasticInferenceServiceDenseTextEmbeddingsResponseEntity.fromResponse(
+            mock(Request.class),
+            new HttpResult(mock(HttpResponse.class), responseJson.getBytes(StandardCharsets.UTF_8))
+        );
+
+        assertThat(parsedResults.embeddings(), hasSize(1));
+
+        var embedding = parsedResults.embeddings().get(0);
+        assertThat(embedding.values(), is(new float[] { -1.0f, 0.0f, 1.0f }));
+    }
+}