Neo4j module: Determine default embedding dimension from model.

In cases where no custom size is set, derive the size by the given
embedding model.

Had to migrate the embeddingDimension Spring Boot property from int to Integer
to introduce the null check for the fluent config. Everything else would
have been just noisy.

Auto-cherry-pick to 1.0.x

Fixes spring-projects#977

Signed-off-by: Gerrit Meier <[email protected]>
Signed-off-by: minsoo.nam <[email protected]>

Author: meistermeier

auto-configurations/vector-stores/spring-ai-autoconfigure-vector-store-neo4j/src/main/java/org/springframework/ai/vectorstore/neo4j/autoconfigure/Neo4jVectorStoreAutoConfiguration.java

@@ -68,7 +68,8 @@ public Neo4jVectorStore vectorStore(Driver driver, EmbeddingModel embeddingModel
 			.customObservationConvention(customObservationConvention.getIfAvailable(() -> null))
 			.batchingStrategy(batchingStrategy)
 			.databaseName(properties.getDatabaseName())
-			.embeddingDimension(properties.getEmbeddingDimension())
+			.embeddingDimension(properties.getEmbeddingDimension() != null ? properties.getEmbeddingDimension()
+					: embeddingModel.dimensions())
 			.distanceType(properties.getDistanceType())
 			.label(properties.getLabel())
 			.embeddingProperty(properties.getEmbeddingProperty())

auto-configurations/vector-stores/spring-ai-autoconfigure-vector-store-neo4j/src/main/java/org/springframework/ai/vectorstore/neo4j/autoconfigure/Neo4jVectorStoreProperties.java

@@ -33,7 +33,7 @@ public class Neo4jVectorStoreProperties extends CommonVectorStoreProperties {
 
 	private String databaseName;
 
-	private int embeddingDimension = Neo4jVectorStore.DEFAULT_EMBEDDING_DIMENSION;
+	private Integer embeddingDimension;
 
 	private Neo4jVectorStore.Neo4jDistanceType distanceType = Neo4jVectorStore.Neo4jDistanceType.COSINE;
 
@@ -57,7 +57,7 @@ public void setDatabaseName(String databaseName) {
 		this.databaseName = databaseName;
 	}
 
-	public int getEmbeddingDimension() {
+	public Integer getEmbeddingDimension() {
 		return this.embeddingDimension;
 	}
 

vector-stores/spring-ai-neo4j-store/src/main/java/org/springframework/ai/vectorstore/neo4j/Neo4jVectorStore.java

@@ -136,6 +136,7 @@ public class Neo4jVectorStore extends AbstractObservationVectorStore implements
 
 	private static final Logger logger = LoggerFactory.getLogger(Neo4jVectorStore.class);
 
+	@Deprecated(forRemoval = true)
 	public static final int DEFAULT_EMBEDDING_DIMENSION = 1536;
 
 	public static final int DEFAULT_TRANSACTION_SIZE = 10_000;
@@ -189,7 +190,7 @@ protected Neo4jVectorStore(Builder builder) {
 
 		this.driver = builder.driver;
 		this.sessionConfig = builder.sessionConfig;
-		this.embeddingDimension = builder.embeddingDimension;
+		this.embeddingDimension = builder.embeddingDimension.orElseGet(() -> builder.getEmbeddingModel().dimensions());
 		this.distanceType = builder.distanceType;
 		this.embeddingProperty = SchemaNames.sanitize(builder.embeddingProperty).orElseThrow();
 		this.label = SchemaNames.sanitize(builder.label).orElseThrow();
@@ -404,7 +405,7 @@ public static class Builder extends AbstractVectorStoreBuilder<Builder> {
 
 		private SessionConfig sessionConfig = SessionConfig.defaultConfig();
 
-		private int embeddingDimension = DEFAULT_EMBEDDING_DIMENSION;
+		private Optional<Integer> embeddingDimension = Optional.empty();
 
 		private Neo4jDistanceType distanceType = Neo4jDistanceType.COSINE;
 
@@ -459,7 +460,7 @@ public Builder sessionConfig(SessionConfig sessionConfig) {
 		 */
 		public Builder embeddingDimension(int dimension) {
 			Assert.isTrue(dimension >= 1, "Dimension has to be positive");
-			this.embeddingDimension = dimension;
+			this.embeddingDimension = Optional.of(dimension);
 			return this;
 		}
 

vector-stores/spring-ai-neo4j-store/src/test/java/org/springframework/ai/vectorstore/neo4j/Neo4jVectorStoreIT.java

@@ -31,6 +31,7 @@
 import org.neo4j.driver.AuthTokens;
 import org.neo4j.driver.Driver;
 import org.neo4j.driver.GraphDatabase;
+import org.springframework.context.annotation.Primary;
 import org.testcontainers.containers.Neo4jContainer;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
@@ -356,16 +357,43 @@ void getNativeClientTest() {
 		});
 	}
 
+	@Test
+	void vectorIndexDimensionsDefaultAndOverwriteWorks() {
+		this.contextRunner.run(context -> {
+			var result = context.getBean(Driver.class)
+				.executableQuery(
+						"SHOW VECTOR INDEXES yield name, options return name, options['indexConfig']['vector.dimensions'] as dimensions")
+				.execute()
+				.records()
+				.stream()
+				.map(r -> r.get("name").asString() + r.get("dimensions").asInt())
+				.toList();
+			assertThat(result).containsExactlyInAnyOrder("secondIndex123", "spring-ai-document-index1536");
+		});
+	}
+
 	@SpringBootConfiguration
 	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
 	public static class TestApplication {
 
 		@Bean
+		@Primary
 		public VectorStore vectorStore(Driver driver, EmbeddingModel embeddingModel) {
 
 			return Neo4jVectorStore.builder(driver, embeddingModel).initializeSchema(true).build();
 		}
 
+		@Bean
+		public VectorStore vectorStoreWithCustomDimension(Driver driver, EmbeddingModel embeddingModel) {
+
+			return Neo4jVectorStore.builder(driver, embeddingModel)
+				.initializeSchema(true)
+				.indexName("secondIndex")
+				.embeddingProperty("somethingElse")
+				.embeddingDimension(123)
+				.build();
+		}
+
 		@Bean
 		public Driver driver() {
 			return GraphDatabase.driver(neo4jContainer.getBoltUrl(),