fixing IT

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);