Convert Qdrant vector store IT use OpenAI embedding model (#3671)

- Move Qdrant vector store test dependency from OpenAI model module
  - Convert existing Qdrant vector store ITs to use OpenAI embedding model for better unification along with other vector stores

Fixes #3671

Signed-off-by: Ilayaperumal Gopinathan <[email protected]>
(cherry picked from commit 5316073)

Author: ilayaperumalg

models/spring-ai-openai/pom.xml

@@ -87,31 +87,12 @@
 			<scope>test</scope>
 		</dependency>
 
-		<dependency>
-			<groupId>org.springframework.ai</groupId>
-			<artifactId>spring-ai-qdrant-store</artifactId>
-			<version>${project.version}</version>
-			<exclusions>
-				<exclusion>
-					<groupId>org.springframework.ai</groupId>
-					<artifactId>spring-ai-openai</artifactId>
-				</exclusion>
-			</exclusions>
-			<scope>test</scope>
-		</dependency>
-
 		<dependency>
 			<groupId>io.micrometer</groupId>
 			<artifactId>micrometer-observation-test</artifactId>
 			<scope>test</scope>
 		</dependency>
 
-		<dependency>
-			<groupId>org.testcontainers</groupId>
-			<artifactId>qdrant</artifactId>
-			<scope>test</scope>
-		</dependency>
-
 		<dependency>
 			<groupId>org.testcontainers</groupId>
 			<artifactId>testcontainers</artifactId>

vector-stores/spring-ai-qdrant-store/pom.xml

@@ -68,7 +68,7 @@
         <!-- TESTING -->
 		<dependency>
 			<groupId>org.springframework.ai</groupId>
-			<artifactId>spring-ai-mistral-ai</artifactId>
+			<artifactId>spring-ai-openai</artifactId>
 			<version>${project.parent.version}</version>
 			<scope>test</scope>
 		</dependency>

vector-stores/spring-ai-qdrant-store/src/test/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStoreIT.java

@@ -32,16 +32,15 @@
 import org.junit.jupiter.api.BeforeAll;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
-import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariables;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 import org.testcontainers.qdrant.QdrantContainer;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.DocumentMetadata;
 import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.mistralai.MistralAiEmbeddingModel;
-import org.springframework.ai.mistralai.api.MistralAiApi;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.test.vectorstore.BaseVectorStoreTests;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
@@ -62,12 +61,12 @@
  * @since 0.8.1
  */
 @Testcontainers
-@EnabledIfEnvironmentVariable(named = "MISTRAL_AI_API_KEY", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
 public class QdrantVectorStoreIT extends BaseVectorStoreTests {
 
 	private static final String COLLECTION_NAME = "test_collection";
 
-	private static final int EMBEDDING_DIMENSION = 1024;
+	private static final int EMBEDDING_DIMENSION = 1536;
 
 	@Container
 	static QdrantContainer qdrantContainer = new QdrantContainer(QdrantImage.DEFAULT_IMAGE);
@@ -355,7 +354,7 @@ public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel, QdrantClient
 
 		@Bean
 		public EmbeddingModel embeddingModel() {
-			return new MistralAiEmbeddingModel(new MistralAiApi(System.getenv("MISTRAL_AI_API_KEY")));
+			return new OpenAiEmbeddingModel(OpenAiApi.builder().apiKey(System.getenv("OPENAI_API_KEY")).build());
 		}
 
 	}

vector-stores/spring-ai-qdrant-store/src/test/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStoreObservationIT.java

@@ -39,10 +39,10 @@
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.embedding.TokenCountBatchingStrategy;
-import org.springframework.ai.mistralai.MistralAiEmbeddingModel;
-import org.springframework.ai.mistralai.api.MistralAiApi;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
 import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
@@ -61,12 +61,12 @@
  * @author Thomas Vitale
  */
 @Testcontainers
-@EnabledIfEnvironmentVariable(named = "MISTRAL_AI_API_KEY", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
 public class QdrantVectorStoreObservationIT {
 
 	private static final String COLLECTION_NAME = "test_collection";
 
-	private static final int EMBEDDING_DIMENSION = 1024;
+	private static final int EMBEDDING_DIMENSION = 1536;
 
 	@Container
 	static QdrantContainer qdrantContainer = new QdrantContainer(QdrantImage.DEFAULT_IMAGE);
@@ -126,7 +126,7 @@ void observationVectorStoreAddAndQueryOperations() {
 				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(),
 						SpringAiKind.VECTOR_STORE.value())
 				.doesNotHaveHighCardinalityKeyValueWithKey(HighCardinalityKeyNames.DB_VECTOR_QUERY_CONTENT.asString())
-				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_DIMENSION_COUNT.asString(), "1024")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_DIMENSION_COUNT.asString(), "1536")
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_COLLECTION_NAME.asString(), COLLECTION_NAME)
 				.doesNotHaveHighCardinalityKeyValueWithKey(HighCardinalityKeyNames.DB_NAMESPACE.asString())
 				.doesNotHaveHighCardinalityKeyValueWithKey(HighCardinalityKeyNames.DB_VECTOR_FIELD_NAME.asString())
@@ -159,7 +159,7 @@ void observationVectorStoreAddAndQueryOperations() {
 
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_CONTENT.asString(),
 						"What is Great Depression")
-				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_DIMENSION_COUNT.asString(), "1024")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_DIMENSION_COUNT.asString(), "1536")
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_COLLECTION_NAME.asString(), COLLECTION_NAME)
 				.doesNotHaveHighCardinalityKeyValueWithKey(HighCardinalityKeyNames.DB_NAMESPACE.asString())
 				.doesNotHaveHighCardinalityKeyValueWithKey(HighCardinalityKeyNames.DB_VECTOR_FIELD_NAME.asString())
@@ -206,7 +206,7 @@ public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel, QdrantClient
 
 		@Bean
 		public EmbeddingModel embeddingModel() {
-			return new MistralAiEmbeddingModel(new MistralAiApi(System.getenv("MISTRAL_AI_API_KEY")));
+			return new OpenAiEmbeddingModel(OpenAiApi.builder().apiKey(System.getenv("OPENAI_API_KEY")).build());
 		}
 
 	}