Batching strategy for more vector stores

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/chroma/ChromaVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2023 - 2024 the original author or authors.
+ * Copyright 2023-2024 the original author or authors.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -13,10 +13,13 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.chroma;
 
 import org.springframework.ai.chroma.ChromaApi;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.ChromaVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -36,6 +39,7 @@
 /**
  * @author Christian Tzolov
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ EmbeddingModel.class, RestClient.class, ChromaVectorStore.class, ObjectMapper.class })
@@ -73,14 +77,21 @@ else if (StringUtils.hasText(apiProperties.getUsername()) && StringUtils.hasText
 		return chromaApi;
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy chromaBatchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public ChromaVectorStore vectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi,
 			ChromaVectorStoreProperties storeProperties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy chromaBatchingStrategy) {
 		return new ChromaVectorStore(embeddingModel, chromaApi, storeProperties.getCollectionName(),
 				storeProperties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), chromaBatchingStrategy);
 	}
 
 	static class PropertiesChromaConnectionDetails implements ChromaConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/elasticsearch/ElasticsearchVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2023 - 2024 the original author or authors.
+ * Copyright 2023-2024 the original author or authors.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -13,11 +13,14 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.elasticsearch;
 
 import org.elasticsearch.client.RestClient;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.ElasticsearchVectorStore;
 import org.springframework.ai.vectorstore.ElasticsearchVectorStoreOptions;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
@@ -37,19 +40,26 @@
  * @author Wei Jiang
  * @author Josh Long
  * @author Christian Tzolov
+ * @author Soby Chacko
  * @since 1.0.0
  */
-
 @AutoConfiguration(after = ElasticsearchRestClientAutoConfiguration.class)
 @ConditionalOnClass({ ElasticsearchVectorStore.class, EmbeddingModel.class, RestClient.class })
 @EnableConfigurationProperties(ElasticsearchVectorStoreProperties.class)
 class ElasticsearchVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	ElasticsearchVectorStore vectorStore(ElasticsearchVectorStoreProperties properties, RestClient restClient,
 			EmbeddingModel embeddingModel, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		ElasticsearchVectorStoreOptions elasticsearchVectorStoreOptions = new ElasticsearchVectorStoreOptions();
 
 		if (StringUtils.hasText(properties.getIndexName())) {
@@ -64,7 +74,7 @@ ElasticsearchVectorStore vectorStore(ElasticsearchVectorStoreProperties properti
 
 		return new ElasticsearchVectorStore(elasticsearchVectorStoreOptions, restClient, embeddingModel,
 				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/neo4j/Neo4jVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2023 - 2024 the original author or authors.
+ * Copyright 2023-2024 the original author or authors.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -13,11 +13,14 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.neo4j;
 
 import org.neo4j.driver.Driver;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.Neo4jVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -34,17 +37,25 @@
  * @author Jingzhou Ou
  * @author Josh Long
  * @author Christian Tzolov
+ * @author Soby Chacko
  */
 @AutoConfiguration(after = Neo4jAutoConfiguration.class)
 @ConditionalOnClass({ Neo4jVectorStore.class, EmbeddingModel.class, Driver.class })
 @EnableConfigurationProperties({ Neo4jVectorStoreProperties.class })
 public class Neo4jVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public Neo4jVectorStore vectorStore(Driver driver, EmbeddingModel embeddingModel,
 			Neo4jVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		Neo4jVectorStore.Neo4jVectorStoreConfig config = Neo4jVectorStore.Neo4jVectorStoreConfig.builder()
 			.withDatabaseName(properties.getDatabaseName())
 			.withEmbeddingDimension(properties.getEmbeddingDimension())
@@ -58,7 +69,7 @@ public Neo4jVectorStore vectorStore(Driver driver, EmbeddingModel embeddingModel
 
 		return new Neo4jVectorStore(driver, embeddingModel, config, properties.isInitializeSchema(),
 				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/qdrant/QdrantVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2023 - 2024 the original author or authors.
+ * Copyright 2023-2024 the original author or authors.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -13,12 +13,16 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.qdrant;
 
 import io.micrometer.observation.ObservationRegistry;
 import io.qdrant.client.QdrantClient;
 import io.qdrant.client.QdrantGrpcClient;
+
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.ai.vectorstore.qdrant.QdrantVectorStore;
 import org.springframework.beans.factory.ObjectProvider;
@@ -32,6 +36,7 @@
  * @author Anush Shetty
  * @author Eddú Meléndez
  * @author Christian Tzolov
+ * @author Soby Chacko
  * @since 0.8.1
  */
 @AutoConfiguration
@@ -58,14 +63,21 @@ public QdrantClient qdrantClient(QdrantVectorStoreProperties properties,
 		return new QdrantClient(grpcClientBuilder.build());
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public QdrantVectorStore vectorStore(EmbeddingModel embeddingModel, QdrantVectorStoreProperties properties,
 			QdrantClient qdrantClient, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		return new QdrantVectorStore(qdrantClient, properties.getCollectionName(), embeddingModel,
 				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 	static class PropertiesQdrantConnectionDetails implements QdrantConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/redis/RedisVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2023 - 2024 the original author or authors.
+ * Copyright 2023-2024 the original author or authors.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -13,9 +13,12 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.redis;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.RedisVectorStore;
 import org.springframework.ai.vectorstore.RedisVectorStore.RedisVectorStoreConfig;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
@@ -35,18 +38,26 @@
 /**
  * @author Christian Tzolov
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration(after = RedisAutoConfiguration.class)
 @ConditionalOnClass({ JedisPooled.class, JedisConnectionFactory.class, RedisVectorStore.class, EmbeddingModel.class })
 @ConditionalOnBean(JedisConnectionFactory.class)
 @EnableConfigurationProperties(RedisVectorStoreProperties.class)
 public class RedisVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public RedisVectorStore vectorStore(EmbeddingModel embeddingModel, RedisVectorStoreProperties properties,
 			JedisConnectionFactory jedisConnectionFactory, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		var config = RedisVectorStoreConfig.builder()
 			.withIndexName(properties.getIndex())
@@ -56,7 +67,7 @@ public RedisVectorStore vectorStore(EmbeddingModel embeddingModel, RedisVectorSt
 		return new RedisVectorStore(config, embeddingModel,
 				new JedisPooled(jedisConnectionFactory.getHostName(), jedisConnectionFactory.getPort()),
 				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/typesense/TypesenseVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2023 - 2024 the original author or authors.
+ * Copyright 2023-2024 the original author or authors.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -13,9 +13,12 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.typesense;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.TypesenseVectorStore;
 import org.springframework.ai.vectorstore.TypesenseVectorStore.TypesenseVectorStoreConfig;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
@@ -38,6 +41,7 @@
 /**
  * @author Pablo Sanchidrian Herrera
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ TypesenseVectorStore.class, EmbeddingModel.class })
@@ -51,11 +55,18 @@ TypesenseVectorStoreAutoConfiguration.PropertiesTypesenseConnectionDetails types
 		return new TypesenseVectorStoreAutoConfiguration.PropertiesTypesenseConnectionDetails(properties);
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public TypesenseVectorStore vectorStore(Client typesenseClient, EmbeddingModel embeddingModel,
 			TypesenseVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		TypesenseVectorStoreConfig config = TypesenseVectorStoreConfig.builder()
 			.withCollectionName(properties.getCollectionName())
@@ -64,7 +75,7 @@ public TypesenseVectorStore vectorStore(Client typesenseClient, EmbeddingModel e
 
 		return new TypesenseVectorStore(typesenseClient, embeddingModel, config, properties.isInitializeSchema(),
 				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 	@Bean

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/weaviate/WeaviateVectorStoreAutoConfiguration.java

@@ -13,14 +13,18 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.weaviate;
 
 import io.micrometer.observation.ObservationRegistry;
 import io.weaviate.client.Config;
 import io.weaviate.client.WeaviateAuthClient;
 import io.weaviate.client.WeaviateClient;
 import io.weaviate.client.v1.auth.exception.AuthException;
+
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.WeaviateVectorStore;
 import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig;
 import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.MetadataField;
@@ -62,11 +66,18 @@ public WeaviateClient weaviateClient(WeaviateVectorStoreProperties properties,
 		}
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public WeaviateVectorStore vectorStore(EmbeddingModel embeddingModel, WeaviateClient weaviateClient,
 			WeaviateVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		WeaviateVectorStoreConfig.Builder configBuilder = WeaviateVectorStore.WeaviateVectorStoreConfig.builder()
 			.withObjectClass(properties.getObjectClass())
@@ -79,7 +90,7 @@ public WeaviateVectorStore vectorStore(EmbeddingModel embeddingModel, WeaviateCl
 
 		return new WeaviateVectorStore(configBuilder.build(), embeddingModel, weaviateClient,
 				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 	static class PropertiesWeaviateConnectionDetails implements WeaviateConnectionDetails {