fix: include index name in OpenSearchVectorStore for similarity search

- Resolved issue where index name was not being sent during similaritySearch.
- Updated similaritySearch method to include index in the SearchRequest.
- Implemented a test to verify that documents can be added and retrieved from two different indices using separate OpenSearchVectorStore instances. Ensured that similarity search results are correctly returned for the respective indices.

vector-stores/spring-ai-opensearch-store/src/main/java/org/springframework/ai/vectorstore/OpenSearchVectorStore.java

@@ -60,6 +60,7 @@
  * @author Soby Chacko
  * @author Christian Tzolov
  * @author Thomas Vitale
+ * @author inpink
  * @since 1.0.0
  */
 public class OpenSearchVectorStore extends AbstractObservationVectorStore implements InitializingBean {
@@ -178,6 +179,7 @@ public List<Document> similaritySearch(float[] embedding, int topK, double simil
 			Filter.Expression filterExpression) {
 		return similaritySearch(new org.opensearch.client.opensearch.core.SearchRequest.Builder()
 			.query(getOpenSearchSimilarityQuery(embedding, filterExpression))
+			.index(this.index)
 			.sort(sortOptionsBuilder -> sortOptionsBuilder
 				.score(scoreSortBuilder -> scoreSortBuilder.order(SortOrder.Desc)))
 			.size(topK)

vector-stores/spring-ai-opensearch-store/src/test/java/org/springframework/ai/vectorstore/OpenSearchVectorStoreIT.java

@@ -20,6 +20,7 @@
 import org.awaitility.Awaitility;
 import org.junit.jupiter.api.BeforeAll;
 import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 import org.junit.jupiter.params.ParameterizedTest;
 import org.junit.jupiter.params.provider.ValueSource;
@@ -30,6 +31,7 @@
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.beans.factory.annotation.Qualifier;
 import org.springframework.boot.SpringBootConfiguration;
 import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
 import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
@@ -58,6 +60,7 @@
 /**
  * @author Jemin Huh
  * @author Soby Chacko
+ * @author inpink
  * @since 1.0.0
  */
 @Testcontainers
@@ -99,8 +102,11 @@ private ApplicationContextRunner getContextRunner() {
 	@BeforeEach
 	void cleanDatabase() {
 		getContextRunner().run(context -> {
-			VectorStore vectorStore = context.getBean(VectorStore.class);
+			VectorStore vectorStore = context.getBean("vectorStore", OpenSearchVectorStore.class);
 			vectorStore.delete(List.of("_all"));
+
+			VectorStore anotherVectorStore = context.getBean("anotherVectorStore", OpenSearchVectorStore.class);
+			anotherVectorStore.delete(List.of("_all"));
 		});
 	}
 
@@ -109,7 +115,7 @@ void cleanDatabase() {
 	public void addAndSearchTest(String similarityFunction) {
 
 		getContextRunner().run(context -> {
-			OpenSearchVectorStore vectorStore = context.getBean(OpenSearchVectorStore.class);
+			OpenSearchVectorStore vectorStore = context.getBean("vectorStore", OpenSearchVectorStore.class);
 
 			if (!DEFAULT.equals(similarityFunction)) {
 				vectorStore.withSimilarityFunction(similarityFunction);
@@ -148,7 +154,7 @@ public void addAndSearchTest(String similarityFunction) {
 	public void searchWithFilters(String similarityFunction) {
 
 		getContextRunner().run(context -> {
-			OpenSearchVectorStore vectorStore = context.getBean(OpenSearchVectorStore.class);
+			OpenSearchVectorStore vectorStore = context.getBean("vectorStore", OpenSearchVectorStore.class);
 
 			if (!DEFAULT.equals(similarityFunction)) {
 				vectorStore.withSimilarityFunction(similarityFunction);
@@ -246,7 +252,7 @@ public void searchWithFilters(String similarityFunction) {
 	public void documentUpdateTest(String similarityFunction) {
 
 		getContextRunner().run(context -> {
-			OpenSearchVectorStore vectorStore = context.getBean(OpenSearchVectorStore.class);
+			OpenSearchVectorStore vectorStore = context.getBean("vectorStore", OpenSearchVectorStore.class);
 			if (!DEFAULT.equals(similarityFunction)) {
 				vectorStore.withSimilarityFunction(similarityFunction);
 			}
@@ -302,7 +308,7 @@ public void documentUpdateTest(String similarityFunction) {
 	public void searchThresholdTest(String similarityFunction) {
 
 		getContextRunner().run(context -> {
-			OpenSearchVectorStore vectorStore = context.getBean(OpenSearchVectorStore.class);
+			OpenSearchVectorStore vectorStore = context.getBean("vectorStore", OpenSearchVectorStore.class);
 			if (!DEFAULT.equals(similarityFunction)) {
 				vectorStore.withSimilarityFunction(similarityFunction);
 			}
@@ -343,11 +349,41 @@ public void searchThresholdTest(String similarityFunction) {
 		});
 	}
 
+	@Test
+	public void searchDocumentsInTwoIndicesTest() {
+		getContextRunner().run(context -> {
+			// given
+			OpenSearchVectorStore vectorStore1 = context.getBean("vectorStore", OpenSearchVectorStore.class);
+			OpenSearchVectorStore vectorStore2 = context.getBean("anotherVectorStore", OpenSearchVectorStore.class);
+
+			Document docInIndex1 = new Document("1", "Document in index 1", Map.of("meta", "index1"));
+			Document docInIndex2 = new Document("2", "Document in index 2", Map.of("meta", "index2"));
+
+			// when
+			vectorStore1.add(List.of(docInIndex1));
+			vectorStore2.add(List.of(docInIndex2));
+
+			List<Document> resultInIndex1 = vectorStore1
+				.similaritySearch(SearchRequest.query("Document in index 1").withTopK(1).withSimilarityThreshold(0));
+
+			List<Document> resultInIndex2 = vectorStore2
+				.similaritySearch(SearchRequest.query("Document in index 2").withTopK(1).withSimilarityThreshold(0));
+
+			// then
+			assertThat(resultInIndex1).hasSize(1);
+			assertThat(resultInIndex1.get(0).getId()).isEqualTo(docInIndex1.getId());
+
+			assertThat(resultInIndex2).hasSize(1);
+			assertThat(resultInIndex2.get(0).getId()).isEqualTo(docInIndex2.getId());
+		});
+	}
+
 	@SpringBootConfiguration
 	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
 	public static class TestApplication {
 
 		@Bean
+		@Qualifier("vectorStore")
 		public OpenSearchVectorStore vectorStore(EmbeddingModel embeddingModel) {
 			try {
 				return new OpenSearchVectorStore(new OpenSearchClient(ApacheHttpClient5TransportBuilder
@@ -359,6 +395,22 @@ public OpenSearchVectorStore vectorStore(EmbeddingModel embeddingModel) {
 			}
 		}
 
+		@Bean
+		@Qualifier("anotherVectorStore")
+		public OpenSearchVectorStore anotherVectorStore(EmbeddingModel embeddingModel) {
+			try {
+				return new OpenSearchVectorStore("another_index",
+						new OpenSearchClient(ApacheHttpClient5TransportBuilder
+							.builder(HttpHost.create(opensearchContainer.getHttpHostAddress()))
+							.build()),
+						embeddingModel, OpenSearchVectorStore.DEFAULT_MAPPING_EMBEDDING_TYPE_KNN_VECTOR_DIMENSION_1536,
+						true);
+			}
+			catch (URISyntaxException e) {
+				throw new RuntimeException(e);
+			}
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));