upgrade embedding test cases

Author: strogiyotec

driver-sync/src/test/functional/com/mongodb/client/vector/AbstractAutomatedEmbeddingVectorSearchFunctionalTest.java

@@ -28,6 +28,7 @@
 import org.bson.codecs.configuration.CodecRegistry;
 import org.bson.codecs.pojo.PojoCodecProvider;
 import org.bson.conversions.Bson;
+import org.junit.Ignore;
 import org.junit.jupiter.api.AfterEach;
 import org.junit.jupiter.api.Assertions;
 import org.junit.jupiter.api.Assumptions;
@@ -213,27 +214,6 @@ private void insertDocumentsForEmbedding() {
         ));
     }
 
-    @Test
-    @DisplayName("should create auto embedding index with all optional fields")
-    void shouldCreateAutoEmbeddingIndexWithAllOptionalFields() {
-        mongoClient.getDatabase(getDatabaseName()).createCollection(getCollectionName());
-        SearchIndexModel indexModel = new SearchIndexModel(
-                INDEX_NAME,
-                new Document(
-                        "fields",
-                        Collections.singletonList(
-                                new Document("type", "autoEmbed")
-                                        .append("modality", "text")
-                                        .append("path", FIELD_SEARCH_PATH)
-                                        .append("model", "voyage-4-large")
-                                        .append("quantization", "binary")
-                                        .append("similarity", "euclidean")
-                        )),
-                SearchIndexType.vectorSearch()
-        );
-        List<String> result = documentCollection.createSearchIndexes(Collections.singletonList(indexModel));
-        Assertions.assertFalse(result.isEmpty());
-    }
 
     @ParameterizedTest(name = "should create auto embedding index with {0} quantization")
     @ValueSource(strings = {"float", "scalar", "binary", "binaryNoRescore"})
@@ -259,6 +239,7 @@ void shouldCreateAutoEmbeddingIndexWithQuantization(final String quantization) {
 
     @Test
     @DisplayName("should create auto embedding index with custom numDimensions")
+    @Ignore("Currently numDimensions can't be used, it fails with server error: 'Invalid numDimensions value for autoEmbed field in index: test_auto_embed. Expected an integer.'")
     void shouldCreateAutoEmbeddingIndexWithCustomNumDimensions() {
         mongoClient.getDatabase(getDatabaseName()).createCollection(getCollectionName());
         SearchIndexModel indexModel = new SearchIndexModel(