diff --git a/langchain4j-azure-ai-search-spring-boot-starter/src/test/java/dev/langchain4j/azure/aisearch/spring/AutoConfigIT.java b/langchain4j-azure-ai-search-spring-boot-starter/src/test/java/dev/langchain4j/azure/aisearch/spring/AutoConfigIT.java
index a394f241..839101dc 100644
--- a/langchain4j-azure-ai-search-spring-boot-starter/src/test/java/dev/langchain4j/azure/aisearch/spring/AutoConfigIT.java
+++ b/langchain4j-azure-ai-search-spring-boot-starter/src/test/java/dev/langchain4j/azure/aisearch/spring/AutoConfigIT.java
@@ -6,6 +6,7 @@
 import com.azure.search.documents.indexes.models.SearchIndex;
 import dev.langchain4j.data.embedding.Embedding;
 import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.internal.Utils;
 import dev.langchain4j.model.embedding.AllMiniLmL6V2EmbeddingModel;
 import dev.langchain4j.model.embedding.EmbeddingModel;
 import dev.langchain4j.rag.content.Content;
@@ -26,7 +27,6 @@
 
 import java.util.List;
 
-import static dev.langchain4j.store.embedding.azure.search.AbstractAzureAiSearchEmbeddingStore.DEFAULT_INDEX_NAME;
 import static java.util.Arrays.asList;
 import static org.assertj.core.api.Assertions.assertThat;
 
@@ -44,26 +44,21 @@ class AutoConfigIT {
             .endpoint(System.getenv("AZURE_SEARCH_ENDPOINT"))
             .credential(new AzureKeyCredential(System.getenv("AZURE_SEARCH_KEY")))
             .buildClient();
-    private final SearchIndex index = new SearchIndex(DEFAULT_INDEX_NAME);
+
+    private final String indexName = Utils.randomUUID();
+    private final SearchIndex index = new SearchIndex(indexName);
 
     private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
             .withConfiguration(AutoConfigurations.of(AutoConfig.class));
 
     @AfterEach
     void afterEach() {
-        searchIndexClient.deleteIndex(DEFAULT_INDEX_NAME);
-        try {
-            Thread.sleep(10_000);
-        } catch (InterruptedException e) {
-            throw new RuntimeException(e);
-        }
+        searchIndexClient.deleteIndex(indexName);
     }
 
     @Test
     void should_provide_ai_search_retriever() {
 
-        // TODO extract in separate tests
-
         contextRunner
                 .withPropertyValues(
                         Properties.PREFIX + ".content-retriever.api-key=" + AZURE_SEARCH_KEY,
@@ -159,6 +154,34 @@ void should_provide_ai_search_retriever() {
     @EnabledIfEnvironmentVariable(named = "AZURE_SEARCH_RERANKER_AVAILABLE", matches = "true")
     void should_provide_ai_search_retriever_with_reranking() {
 
+        contextRunner
+                .withPropertyValues(
+                        Properties.PREFIX + ".content-retriever.api-key=" + AZURE_SEARCH_KEY,
+                        Properties.PREFIX + ".content-retriever.endpoint=" + AZURE_SEARCH_ENDPOINT,
+                        Properties.PREFIX + ".content-retriever.dimensions=" + dimensions,
+                        Properties.PREFIX + ".content-retriever.create-or-update-index=" + "true",
+                        Properties.PREFIX + ".content-retriever.query-type=" + "VECTOR"
+                ).withBean(EmbeddingModel.class, () -> embeddingModel)
+                .run(context -> {
+                    ContentRetriever contentRetriever = context.getBean(ContentRetriever.class);
+                    assertThat(contentRetriever).isInstanceOf(AzureAiSearchContentRetriever.class);
+                    AzureAiSearchContentRetriever azureAiSearchContentRetriever = (AzureAiSearchContentRetriever) contentRetriever;
+
+                    String content1 = "This book is about politics";
+                    String content2 = "Cats sleeps a lot.";
+                    String content3 = "Sandwiches taste good.";
+                    String content4 = "The house is open";
+                    List<String> contents = asList(content1, content2, content3, content4);
+
+                    for (String content : contents) {
+                        TextSegment textSegment = TextSegment.from(content);
+                        Embedding embedding = embeddingModel.embed(content).content();
+                        azureAiSearchContentRetriever.add(embedding, textSegment);
+                    }
+
+                    awaitUntilPersisted();
+                });
+
         String content = "house";
         Query query = Query.from(content);