[ML] Do not create inference endpoint if ID is used in existing mappings

docs/changelog/137055.yaml

@@ -0,0 +1,6 @@
+pr: 137055
+summary: Do not create inference endpoint if ID is used in existing mappings
+area: Machine Learning
+type: bug
+issues:
+ - 124272

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/utils/InferenceProcessorInfoExtractor.java

@@ -116,13 +116,12 @@ public static Map<String, Set<String>> pipelineIdsByResource(ClusterState state,
     }
 
     /**
-     * @param state Current {@link ClusterState}
+     * @param metadata Current cluster state {@link Metadata}
      * @return a map from Model or Deployment IDs or Aliases to each pipeline referencing them.
      */
-    public static Set<String> pipelineIdsForResource(ClusterState state, Set<String> ids) {
+    public static Set<String> pipelineIdsForResource(Metadata metadata, Set<String> ids) {
         assert Transports.assertNotTransportThread("non-trivial nested loops over cluster state structures");
         Set<String> pipelineIds = new HashSet<>();
-        Metadata metadata = state.metadata();
         if (metadata == null) {
             return pipelineIds;
         }

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

@@ -171,6 +171,22 @@ static String mockDenseServiceModelConfig() {
             """;
     }
 
+    static String mockDenseServiceModelConfig(int dimensions) {
+        return Strings.format("""
+            {
+              "task_type": "text_embedding",
+              "service": "text_embedding_test_service",
+              "service_settings": {
+                "model": "my_dense_vector_model",
+                "api_key": "abc64",
+                "dimensions": %s
+              },
+              "task_settings": {
+              }
+            }
+            """, dimensions);
+    }
+
     static String mockRerankServiceModelConfig() {
         return """
             {

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

@@ -10,6 +10,7 @@
 package org.elasticsearch.xpack.inference;
 
 import org.apache.http.util.EntityUtils;
+import org.elasticsearch.client.Request;
 import org.elasticsearch.client.Response;
 import org.elasticsearch.client.ResponseException;
 import org.elasticsearch.common.Strings;
@@ -211,7 +212,7 @@ public void testDeleteEndpointWhileReferencedBySemanticText() throws IOException
         final String endpointId = "endpoint_referenced_by_semantic_text";
         final String searchEndpointId = "search_endpoint_referenced_by_semantic_text";
         final String indexName = randomAlphaOfLength(10).toLowerCase();
-        final Function<String, String> buildErrorString = endpointName -> " Inference endpoint "
+        final Function<String, String> buildErrorString = endpointName -> "Inference endpoint "
             + endpointName
             + " is being used in the mapping for indexes: "
             + Set.of(indexName)
@@ -303,6 +304,74 @@ public void testDeleteEndpointWhileReferencedBySemanticTextAndPipeline() throws
         deleteIndex(indexName);
     }
 
+    public void testCreateEndpoint_withInferenceIdReferencedBySemanticText() throws IOException {
+        final String endpointId = "endpoint_referenced_by_semantic_text";
+        final String otherEndpointId = "other_endpoint_referenced_by_semantic_text";
+        final String indexName1 = randomAlphaOfLength(10).toLowerCase();
+        final String indexName2 = randomValueOtherThan(indexName1, () -> randomAlphaOfLength(10).toLowerCase());
+
+        putModel(endpointId, mockDenseServiceModelConfig(128), TaskType.TEXT_EMBEDDING);
+        putModel(otherEndpointId, mockDenseServiceModelConfig(), TaskType.TEXT_EMBEDDING);
+        // Create two indices, one where the inference ID of the endpoint we'll be deleting and
+        // recreating is used for inference_id and one where it's used for search_inference_id
+        putSemanticText(endpointId, otherEndpointId, indexName1);
+        putSemanticText(otherEndpointId, endpointId, indexName2);
+
+        // Confirm that we can create the endpoint with different settings if there
+        // are documents in the indices which do not use the semantic text field
+        var request = new Request("PUT", indexName1 + "/_create/1");
+        request.setJsonEntity("{\"non_inference_field\": \"value\"}");
+        assertStatusOkOrCreated(client().performRequest(request));
+
+        request = new Request("PUT", indexName2 + "/_create/1");
+        request.setJsonEntity("{\"non_inference_field\": \"value\"}");
+        assertStatusOkOrCreated(client().performRequest(request));
+
+        assertStatusOkOrCreated(client().performRequest(new Request("GET", "_refresh")));
+
+        deleteModel(endpointId, "force=true");
+        putModel(endpointId, mockDenseServiceModelConfig(64), TaskType.TEXT_EMBEDDING);
+
+        // Index a document with the semantic text field into each index
+        request = new Request("PUT", indexName1 + "/_create/2");
+        request.setJsonEntity("{\"inference_field\": \"value\"}");
+        assertStatusOkOrCreated(client().performRequest(request));
+
+        request = new Request("PUT", indexName2 + "/_create/2");
+        request.setJsonEntity("{\"inference_field\": \"value\"}");
+        assertStatusOkOrCreated(client().performRequest(request));
+
+        assertStatusOkOrCreated(client().performRequest(new Request("GET", "_refresh")));
+
+        deleteModel(endpointId, "force=true");
+
+        // Try to create an inference endpoint with the same ID but different dimensions
+        // from when the document with the semantic text field was indexed
+        ResponseException responseException = assertThrows(
+            ResponseException.class,
+            () -> putModel(endpointId, mockDenseServiceModelConfig(128), TaskType.TEXT_EMBEDDING)
+        );
+        assertThat(
+            responseException.getMessage(),
+            containsString(
+                "Inference endpoint ["
+                    + endpointId
+                    + "] could not be created because the inference_id is being used in mappings with incompatible settings for indices: ["
+            )
+        );
+        assertThat(responseException.getMessage(), containsString(indexName1));
+        assertThat(responseException.getMessage(), containsString(indexName2));
+        assertThat(
+            responseException.getMessage(),
+            containsString("Please either use a different inference_id or update the index mappings to refer to a different inference_id.")
+        );
+
+        deleteIndex(indexName1);
+        deleteIndex(indexName2);
+
+        deleteModel(otherEndpointId, "force=true");
+    }
+
     public void testUnsupportedStream() throws Exception {
         String modelId = "streaming";
         putModel(modelId, mockCompletionServiceModelConfig(TaskType.SPARSE_EMBEDDING, "streaming_completion_test_service"));

x-pack/plugin/inference/qa/test-service-plugin/src/main/java/org/elasticsearch/xpack/inference/mock/TestCompletionServiceExtension.java

@@ -49,7 +49,7 @@ public List<Factory> getInferenceServiceFactories() {
     }
 
     public static class TestInferenceService extends AbstractTestInferenceService {
-        private static final String NAME = "completion_test_service";
+        public static final String NAME = "completion_test_service";
         private static final EnumSet<TaskType> SUPPORTED_TASK_TYPES = EnumSet.of(TaskType.COMPLETION);
 
         public TestInferenceService(InferenceServiceFactoryContext context) {}

x-pack/plugin/inference/qa/test-service-plugin/src/main/java/org/elasticsearch/xpack/inference/mock/TestDenseInferenceServiceExtension.java

@@ -170,7 +170,12 @@ public void chunkedInfer(
         private DenseEmbeddingFloatResults makeResults(List<String> input, ServiceSettings serviceSettings) {
             List<DenseEmbeddingFloatResults.Embedding> embeddings = new ArrayList<>();
             for (String inputString : input) {
-                List<Float> floatEmbeddings = generateEmbedding(inputString, serviceSettings.dimensions(), serviceSettings.elementType());
+                List<Float> floatEmbeddings = generateEmbedding(
+                    inputString,
+                    serviceSettings.dimensions(),
+                    serviceSettings.elementType(),
+                    serviceSettings.similarity()
+                );
                 embeddings.add(DenseEmbeddingFloatResults.Embedding.of(floatEmbeddings));
             }
             return new DenseEmbeddingFloatResults(embeddings);
@@ -206,7 +211,7 @@ protected ServiceSettings getServiceSettingsFromMap(Map<String, Object> serviceS
          * <ul>
          *     <li>Unique to the input</li>
          *     <li>Reproducible (i.e given the same input, the same embedding should be generated)</li>
-         *     <li>Valid for the provided element type</li>
+         *     <li>Valid for the provided element type and similarity measure</li>
          * </ul>
          * <p>
          * The embedding is generated by:
@@ -216,6 +221,7 @@ protected ServiceSettings getServiceSettingsFromMap(Map<String, Object> serviceS
          *     <li>converting the hash code value to a string</li>
          *     <li>converting the string to a UTF-8 encoded byte array</li>
          *     <li>repeatedly appending the byte array to the embedding until the desired number of dimensions are populated</li>
+         *     <li>converting the embedding to a unit vector if the similarity measure requires that</li>
          * </ul>
          * <p>
          * Since the hash code value, when interpreted as a string, is guaranteed to only contain digits and the "-" character, the UTF-8
@@ -226,11 +232,17 @@ protected ServiceSettings getServiceSettingsFromMap(Map<String, Object> serviceS
          * embedding byte.
          * </p>
          *
-         * @param input The input string
-         * @param dimensions The embedding dimension count
+         * @param input             The input string
+         * @param dimensions        The embedding dimension count
+         * @param similarityMeasure The similarity measure
          * @return An embedding
          */
-        private static List<Float> generateEmbedding(String input, int dimensions, DenseVectorFieldMapper.ElementType elementType) {
+        private static List<Float> generateEmbedding(
+            String input,
+            int dimensions,
+            DenseVectorFieldMapper.ElementType elementType,
+            SimilarityMeasure similarityMeasure
+        ) {
             int embeddingLength = getEmbeddingLength(elementType, dimensions);
             List<Float> embedding = new ArrayList<>(embeddingLength);
 
@@ -248,6 +260,9 @@ private static List<Float> generateEmbedding(String input, int dimensions, Dense
             if (remainingLength > 0) {
                 embedding.addAll(embeddingValues.subList(0, remainingLength));
             }
+            if (similarityMeasure == SimilarityMeasure.DOT_PRODUCT) {
+                embedding = toUnitVector(embedding);
+            }
 
             return embedding;
         }
@@ -263,6 +278,11 @@ private static int getEmbeddingLength(DenseVectorFieldMapper.ElementType element
             };
         }
 
+        private static List<Float> toUnitVector(List<Float> embedding) {
+            var magnitude = (float) Math.sqrt(embedding.stream().reduce(0f, (a, b) -> a + (b * b)));
+            return embedding.stream().map(v -> v / magnitude).toList();
+        }
+
         public static class Configuration {
             public static InferenceServiceConfiguration get() {
                 return configuration.getOrCompute();
@@ -304,9 +324,13 @@ public record TestServiceSettings(
         public static TestServiceSettings fromMap(Map<String, Object> map) {
             ValidationException validationException = new ValidationException();
 
-            String model = (String) map.remove("model");
+            String model = (String) map.remove("model_id");
+
             if (model == null) {
-                validationException.addValidationError("missing model");
+                model = (String) map.remove("model");
+                if (model == null) {
+                    validationException.addValidationError("missing model");
+                }
             }
 
             Integer dimensions = (Integer) map.remove("dimensions");

x-pack/plugin/inference/qa/test-service-plugin/src/main/java/org/elasticsearch/xpack/inference/mock/TestRerankingServiceExtension.java

@@ -318,7 +318,10 @@ public static TestServiceSettings fromMap(Map<String, Object> map) {
             String model = (String) map.remove("model_id");
 
             if (model == null) {
-                validationException.addValidationError("missing model");
+                model = (String) map.remove("model");
+                if (model == null) {
+                    validationException.addValidationError("missing model");
+                }
             }
 
             if (validationException.validationErrors().isEmpty() == false) {

x-pack/plugin/inference/qa/test-service-plugin/src/main/java/org/elasticsearch/xpack/inference/mock/TestSparseInferenceServiceExtension.java

@@ -268,10 +268,13 @@ public record TestServiceSettings(String model, String hiddenField, boolean shou
         public static TestServiceSettings fromMap(Map<String, Object> map) {
             ValidationException validationException = new ValidationException();
 
-            String model = (String) map.remove("model");
+            String model = (String) map.remove("model_id");
 
             if (model == null) {
-                validationException.addValidationError("missing model");
+                model = (String) map.remove("model");
+                if (model == null) {
+                    validationException.addValidationError("missing model");
+                }
             }
 
             String hiddenField = (String) map.remove("hidden_field");

x-pack/plugin/inference/qa/test-service-plugin/src/main/java/org/elasticsearch/xpack/inference/mock/TestStreamingCompletionServiceExtension.java

@@ -59,7 +59,7 @@ public List<Factory> getInferenceServiceFactories() {
     }
 
     public static class TestInferenceService extends AbstractTestInferenceService {
-        private static final String NAME = "streaming_completion_test_service";
+        public static final String NAME = "streaming_completion_test_service";
         private static final String ALIAS = "streaming_completion_test_service_alias";
         private static final Set<TaskType> supportedStreamingTasks = Set.of(TaskType.COMPLETION, TaskType.CHAT_COMPLETION);
 
@@ -343,12 +343,15 @@ public TestServiceSettings(StreamInput in) throws IOException {
         }
 
         public static TestServiceSettings fromMap(Map<String, Object> map) {
-            var modelId = map.remove("model").toString();
+            String modelId = (String) map.remove("model_id");
 
             if (modelId == null) {
-                ValidationException validationException = new ValidationException();
-                validationException.addValidationError("missing model id");
-                throw validationException;
+                modelId = (String) map.remove("model");
+                if (modelId == null) {
+                    ValidationException validationException = new ValidationException();
+                    validationException.addValidationError("missing model id");
+                    throw validationException;
+                }
             }
 
             return new TestServiceSettings(modelId);