Add batching for more vector stores

Apply batching when adding Documents to the following vector stores:

- Chroma
- ElasticSearch
- Neo4j
- Qdrant
- Redis
- Typesense
- Weaviate

This improves efficiency by processing multiple Documents at once instead of individually, reducing the overhead for each operation.

Related to #1261

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 @@ import io.micrometer.observation.ObservationRegistry;
 /**
  * @author Christian Tzolov
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ EmbeddingModel.class, RestClient.class, ChromaVectorStore.class, ObjectMapper.class })
@@ -73,14 +77,21 @@ public class ChromaVectorStoreAutoConfiguration {
 		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 @@ import io.micrometer.observation.ObservationRegistry;
  * @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 @@ class ElasticsearchVectorStoreAutoConfiguration {
 
 		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 @@ import io.micrometer.observation.ObservationRegistry;
  * @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 class Neo4jVectorStoreAutoConfiguration {
 
 		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 @@ import org.springframework.context.annotation.Bean;
  * @author Anush Shetty
  * @author Eddú Meléndez
  * @author Christian Tzolov
+ * @author Soby Chacko
  * @since 0.8.1
  */
 @AutoConfiguration
@@ -58,14 +63,21 @@ public class QdrantVectorStoreAutoConfiguration {
 		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;
@@ -35,6 +38,7 @@ import redis.clients.jedis.JedisPooled;
 /**
  * @author Christian Tzolov
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration(after = RedisAutoConfiguration.class)
 @ConditionalOnClass({ JedisPooled.class, JedisConnectionFactory.class, RedisVectorStore.class, EmbeddingModel.class })
@@ -42,11 +46,18 @@ import redis.clients.jedis.JedisPooled;
 @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 class RedisVectorStoreAutoConfiguration {
 		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 @@ import java.util.List;
 /**
  * @author Pablo Sanchidrian Herrera
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ TypesenseVectorStore.class, EmbeddingModel.class })
@@ -51,11 +55,18 @@ public class TypesenseVectorStoreAutoConfiguration {
 		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 class TypesenseVectorStoreAutoConfiguration {
 
 		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

@@ -13,6 +13,7 @@
  * 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;
@@ -20,7 +21,10 @@ 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 class WeaviateVectorStoreAutoConfiguration {
 		}
 	}
 
+	@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 class WeaviateVectorStoreAutoConfiguration {
 
 		return new WeaviateVectorStore(configBuilder.build(), embeddingModel, weaviateClient,
 				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 	static class PropertiesWeaviateConnectionDetails implements WeaviateConnectionDetails {

vector-stores/spring-ai-chroma-store/src/main/java/org/springframework/ai/vectorstore/ChromaVectorStore.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.
@@ -13,6 +13,7 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.vectorstore;
 
 import java.util.ArrayList;
@@ -26,7 +27,10 @@ import org.springframework.ai.chroma.ChromaApi.AddEmbeddingsRequest;
 import org.springframework.ai.chroma.ChromaApi.DeleteEmbeddingsRequest;
 import org.springframework.ai.chroma.ChromaApi.Embedding;
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
 import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
@@ -69,18 +73,21 @@ public class ChromaVectorStore extends AbstractObservationVectorStore implements
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public ChromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi, boolean initializeSchema) {
 		this(embeddingModel, chromaApi, DEFAULT_COLLECTION_NAME, initializeSchema);
 	}
 
 	public ChromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi, String collectionName,
 			boolean initializeSchema) {
-		this(embeddingModel, chromaApi, collectionName, initializeSchema, ObservationRegistry.NOOP, null);
+		this(embeddingModel, chromaApi, collectionName, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public ChromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi, String collectionName,
 			boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -89,6 +96,7 @@ public class ChromaVectorStore extends AbstractObservationVectorStore implements
 		this.collectionName = collectionName;
 		this.initializeSchema = initializeSchema;
 		this.filterExpressionConverter = new ChromaFilterExpressionConverter();
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	public void setFilterExpressionConverter(FilterExpressionConverter filterExpressionConverter) {
@@ -108,11 +116,13 @@ public class ChromaVectorStore extends AbstractObservationVectorStore implements
 		List<String> contents = new ArrayList<>();
 		List<float[]> embeddings = new ArrayList<>();
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		for (Document document : documents) {
 			ids.add(document.getId());
 			metadatas.add(document.getMetadata());
 			contents.add(document.getContent());
-			document.setEmbedding(this.embeddingModel.embed(document));
+			document.setEmbedding(document.getEmbedding());
 			embeddings.add(document.getEmbedding());
 		}
 

vector-stores/spring-ai-chroma-store/src/test/java/org/springframework/ai/vectorstore/ChromaVectorStoreObservationIT.java

@@ -26,6 +26,7 @@ import org.junit.jupiter.api.Test;
 import org.springframework.ai.chroma.ChromaApi;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.openai.OpenAiEmbeddingModel;
@@ -169,7 +170,8 @@ public class ChromaVectorStoreObservationIT {
 		@Bean
 		public VectorStore chromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi,
 				ObservationRegistry observationRegistry) {
-			return new ChromaVectorStore(embeddingModel, chromaApi, "TestCollection", true, observationRegistry, null);
+			return new ChromaVectorStore(embeddingModel, chromaApi, "TestCollection", true, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-elasticsearch-store/src/main/java/org/springframework/ai/vectorstore/ElasticsearchVectorStore.java

@@ -28,7 +28,10 @@ import org.elasticsearch.client.RestClient;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.model.EmbeddingUtils;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
@@ -85,18 +88,21 @@ public class ElasticsearchVectorStore extends AbstractObservationVectorStore imp
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public ElasticsearchVectorStore(RestClient restClient, EmbeddingModel embeddingModel, boolean initializeSchema) {
 		this(new ElasticsearchVectorStoreOptions(), restClient, embeddingModel, initializeSchema);
 	}
 
 	public ElasticsearchVectorStore(ElasticsearchVectorStoreOptions options, RestClient restClient,
 			EmbeddingModel embeddingModel, boolean initializeSchema) {
-		this(options, restClient, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null);
+		this(options, restClient, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public ElasticsearchVectorStore(ElasticsearchVectorStoreOptions options, RestClient restClient,
 			EmbeddingModel embeddingModel, boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -109,6 +115,7 @@ public class ElasticsearchVectorStore extends AbstractObservationVectorStore imp
 		this.embeddingModel = embeddingModel;
 		this.options = options;
 		this.filterExpressionConverter = new ElasticsearchAiSearchFilterExpressionConverter();
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	@Override
@@ -120,11 +127,9 @@ public class ElasticsearchVectorStore extends AbstractObservationVectorStore imp
 		}
 		BulkRequest.Builder bulkRequestBuilder = new BulkRequest.Builder();
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		for (Document document : documents) {
-			if (Objects.isNull(document.getEmbedding()) || document.getEmbedding().length == 0) {
-				logger.debug("Calling EmbeddingModel for document id = " + document.getId());
-				document.setEmbedding(this.embeddingModel.embed(document));
-			}
 			bulkRequestBuilder.operations(op -> op
 				.index(idx -> idx.index(this.options.getIndexName()).id(document.getId()).document(document)));
 		}

vector-stores/spring-ai-elasticsearch-store/src/test/java/org/springframework/ai/vectorstore/ElasticsearchVectorStoreObservationIT.java

@@ -33,6 +33,7 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.openai.OpenAiEmbeddingModel;
@@ -202,7 +203,7 @@ public class ElasticsearchVectorStoreObservationIT {
 		public ElasticsearchVectorStore vectorStoreDefault(EmbeddingModel embeddingModel, RestClient restClient,
 				ObservationRegistry observationRegistry) {
 			return new ElasticsearchVectorStore(new ElasticsearchVectorStoreOptions(), restClient, embeddingModel, true,
-					observationRegistry, null);
+					observationRegistry, null, new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-neo4j-store/src/main/java/org/springframework/ai/vectorstore/Neo4jVectorStore.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.
@@ -13,6 +13,7 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.vectorstore;
 
 import java.util.HashMap;
@@ -26,7 +27,10 @@ import org.neo4j.driver.Driver;
 import org.neo4j.driver.SessionConfig;
 import org.neo4j.driver.Values;
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.Neo4jVectorFilterExpressionConverter;
@@ -43,6 +47,7 @@ import io.micrometer.observation.ObservationRegistry;
  * @author Michael Simons
  * @author Christian Tzolov
  * @author Thomas Vitale
+ * @author Soby Chacko
  */
 public class Neo4jVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
@@ -284,31 +289,33 @@ public class Neo4jVectorStore extends AbstractObservationVectorStore implements
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public Neo4jVectorStore(Driver driver, EmbeddingModel embeddingModel, Neo4jVectorStoreConfig config,
 			boolean initializeSchema) {
-		this(driver, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+		this(driver, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public Neo4jVectorStore(Driver driver, EmbeddingModel embeddingModel, Neo4jVectorStoreConfig config,
 			boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
-
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 		super(observationRegistry, customObservationConvention);
 
 		this.initializeSchema = initializeSchema;
-
 		Assert.notNull(driver, "Neo4j driver must not be null");
 		Assert.notNull(embeddingModel, "Embedding model must not be null");
-
 		this.driver = driver;
 		this.embeddingModel = embeddingModel;
-
 		this.config = config;
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	@Override
 	public void doAdd(List<Document> documents) {
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		var rows = documents.stream().map(this::documentToRecord).toList();
 
 		try (var session = this.driver.session()) {
@@ -398,8 +405,7 @@ public class Neo4jVectorStore extends AbstractObservationVectorStore implements
 	}
 
 	private Map<String, Object> documentToRecord(Document document) {
-		var embedding = this.embeddingModel.embed(document);
-		document.setEmbedding(embedding);
+		document.setEmbedding(document.getEmbedding());
 
 		var row = new HashMap<String, Object>();
 
@@ -411,7 +417,7 @@ public class Neo4jVectorStore extends AbstractObservationVectorStore implements
 		document.getMetadata().forEach((k, v) -> properties.put("metadata." + k, Values.value(v)));
 		row.put("properties", properties);
 
-		row.put(this.config.embeddingProperty, Values.value(embedding));
+		row.put(this.config.embeddingProperty, Values.value(document.getEmbedding()));
 		return row;
 	}
 

vector-stores/spring-ai-neo4j-store/src/test/java/org/springframework/ai/vectorstore/Neo4jVectorStoreObservationIT.java

@@ -31,6 +31,7 @@ import org.neo4j.driver.Driver;
 import org.neo4j.driver.GraphDatabase;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.openai.OpenAiEmbeddingModel;
@@ -174,7 +175,7 @@ public class Neo4jVectorStoreObservationIT {
 				ObservationRegistry observationRegistry) {
 
 			return new Neo4jVectorStore(driver, embeddingModel, Neo4jVectorStore.Neo4jVectorStoreConfig.defaultConfig(),
-					true, observationRegistry, null);
+					true, observationRegistry, null, new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-qdrant-store/src/main/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStore.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.
@@ -13,6 +13,7 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.vectorstore.qdrant;
 
 import static io.qdrant.client.PointIdFactory.id;
@@ -27,7 +28,10 @@ import java.util.UUID;
 import java.util.concurrent.ExecutionException;
 
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.model.EmbeddingUtils;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
@@ -58,6 +62,7 @@ import io.qdrant.client.grpc.Points.UpdateStatus;
  * @author Christian Tzolov
  * @author Eddú Meléndez
  * @author Josh Long
+ * @author Soby Chacko
  * @since 0.8.1
  */
 public class QdrantVectorStore extends AbstractObservationVectorStore implements InitializingBean {
@@ -78,6 +83,8 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	/**
 	 * Configuration class for the QdrantVectorStore.
 	 *
@@ -161,7 +168,8 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
 	 */
 	public QdrantVectorStore(QdrantClient qdrantClient, String collectionName, EmbeddingModel embeddingModel,
 			boolean initializeSchema) {
-		this(qdrantClient, collectionName, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null);
+		this(qdrantClient, collectionName, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	/**
@@ -175,7 +183,7 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
 	 */
 	public QdrantVectorStore(QdrantClient qdrantClient, String collectionName, EmbeddingModel embeddingModel,
 			boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -187,6 +195,7 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
 		this.embeddingModel = embeddingModel;
 		this.collectionName = collectionName;
 		this.qdrantClient = qdrantClient;
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	/**
@@ -196,16 +205,17 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
 	@Override
 	public void doAdd(List<Document> documents) {
 		try {
-			List<PointStruct> points = documents.stream().map(document -> {
-				// Compute and assign an embedding to the document.
-				document.setEmbedding(this.embeddingModel.embed(document));
 
-				return PointStruct.newBuilder()
+			// Compute and assign an embedding to the document.
+			this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
+			List<PointStruct> points = documents.stream()
+				.map(document -> PointStruct.newBuilder()
 					.setId(id(UUID.fromString(document.getId())))
 					.setVectors(vectors(document.getEmbedding()))
 					.putAllPayload(toPayload(document))
-					.build();
-			}).toList();
+					.build())
+				.toList();
 
 			this.qdrantClient.upsertAsync(this.collectionName, points).get();
 		}

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

@@ -28,6 +28,7 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 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;
@@ -191,8 +192,8 @@ public class QdrantVectorStoreObservationIT {
 		@Bean
 		public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel, QdrantClient qdrantClient,
 				ObservationRegistry observationRegistry) {
-			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingModel, true, observationRegistry,
-					null);
+			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingModel, true, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-redis-store/src/main/java/org/springframework/ai/vectorstore/RedisVectorStore.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.
@@ -13,6 +13,7 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.vectorstore;
 
 import java.text.MessageFormat;
@@ -29,7 +30,10 @@ import java.util.stream.Collectors;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
 import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
@@ -75,6 +79,7 @@ import redis.clients.jedis.search.schemafields.VectorField.VectorAlgorithm;
  * @author Christian Tzolov
  * @author Eddú Meléndez
  * @author Thomas Vitale
+ * @author Soby Chacko
  * @see VectorStore
  * @see RedisVectorStoreConfig
  * @see EmbeddingModel
@@ -278,15 +283,18 @@ public class RedisVectorStore extends AbstractObservationVectorStore implements
 
 	private FilterExpressionConverter filterExpressionConverter;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public RedisVectorStore(RedisVectorStoreConfig config, EmbeddingModel embeddingModel, JedisPooled jedis,
 			boolean initializeSchema) {
 
-		this(config, embeddingModel, jedis, initializeSchema, ObservationRegistry.NOOP, null);
+		this(config, embeddingModel, jedis, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public RedisVectorStore(RedisVectorStoreConfig config, EmbeddingModel embeddingModel, JedisPooled jedis,
 			boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -298,6 +306,7 @@ public class RedisVectorStore extends AbstractObservationVectorStore implements
 		this.embeddingModel = embeddingModel;
 		this.config = config;
 		this.filterExpressionConverter = new RedisFilterExpressionConverter(this.config.metadataFields);
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	public JedisPooled getJedis() {
@@ -307,12 +316,13 @@ public class RedisVectorStore extends AbstractObservationVectorStore implements
 	@Override
 	public void doAdd(List<Document> documents) {
 		try (Pipeline pipeline = this.jedis.pipelined()) {
-			for (Document document : documents) {
-				var embedding = this.embeddingModel.embed(document);
-				document.setEmbedding(embedding);
 
+			this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
+			for (Document document : documents) {
+				document.setEmbedding(document.getEmbedding());
 				var fields = new HashMap<String, Object>();
-				fields.put(this.config.embeddingFieldName, embedding);
+				fields.put(this.config.embeddingFieldName, document.getEmbedding());
 				fields.put(this.config.contentFieldName, document.getContent());
 				fields.putAll(document.getMetadata());
 				pipeline.jsonSetWithEscape(key(document.getId()), JSON_SET_PATH, fields);

vector-stores/spring-ai-redis-store/src/test/java/org/springframework/ai/vectorstore/RedisVectorStoreObservationIT.java

@@ -26,6 +26,7 @@ import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
@@ -178,7 +179,7 @@ public class RedisVectorStoreObservationIT {
 						.build(),
 					embeddingModel,
 					new JedisPooled(jedisConnectionFactory.getHostName(), jedisConnectionFactory.getPort()), true,
-					observationRegistry, null);
+					observationRegistry, null, new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-typesense-store/src/main/java/org/springframework/ai/vectorstore/TypesenseVectorStore.java

@@ -26,7 +26,10 @@ import java.util.stream.Stream;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
@@ -85,6 +88,8 @@ public class TypesenseVectorStore extends AbstractObservationVectorStore impleme
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public static class TypesenseVectorStoreConfig {
 
 		private final String collectionName;
@@ -162,12 +167,13 @@ public class TypesenseVectorStore extends AbstractObservationVectorStore impleme
 	public TypesenseVectorStore(Client client, EmbeddingModel embeddingModel, TypesenseVectorStoreConfig config,
 			boolean initializeSchema) {
 
-		this(client, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+		this(client, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public TypesenseVectorStore(Client client, EmbeddingModel embeddingModel, TypesenseVectorStoreConfig config,
 			boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -178,19 +184,21 @@ public class TypesenseVectorStore extends AbstractObservationVectorStore impleme
 		this.embeddingModel = embeddingModel;
 		this.config = config;
 		this.initializeSchema = initializeSchema;
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	@Override
 	public void doAdd(List<Document> documents) {
 		Assert.notNull(documents, "Documents must not be null");
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		List<HashMap<String, Object>> documentList = documents.stream().map(document -> {
 			HashMap<String, Object> typesenseDoc = new HashMap<>();
 			typesenseDoc.put(DOC_ID_FIELD_NAME, document.getId());
 			typesenseDoc.put(CONTENT_FIELD_NAME, document.getContent());
 			typesenseDoc.put(METADATA_FIELD_NAME, document.getMetadata());
-			float[] embedding = this.embeddingModel.embed(document.getContent());
-			typesenseDoc.put(EMBEDDING_FIELD_NAME, embedding);
+			typesenseDoc.put(EMBEDDING_FIELD_NAME, document.getEmbedding());
 
 			return typesenseDoc;
 		}).toList();

vector-stores/spring-ai-typesense-store/src/test/java/org/springframework/ai/vectorstore/TypesenseVectorStoreObservationIT.java

@@ -27,6 +27,7 @@ import java.util.Map;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
@@ -169,7 +170,8 @@ public class TypesenseVectorStoreObservationIT {
 				.withEmbeddingDimension(embeddingModel.dimensions())
 				.build();
 
-			return new TypesenseVectorStore(client, embeddingModel, config, true, observationRegistry, null);
+			return new TypesenseVectorStore(client, embeddingModel, config, true, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-weaviate-store/src/main/java/org/springframework/ai/vectorstore/WeaviateVectorStore.java

@@ -13,6 +13,7 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.vectorstore;
 
 import java.util.ArrayList;
@@ -24,7 +25,10 @@ import java.util.Optional;
 import java.util.stream.Collectors;
 
 import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.model.EmbeddingUtils;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.ConsistentLevel;
@@ -96,6 +100,8 @@ public class WeaviateVectorStore extends AbstractObservationVectorStore {
 
 	private final String weaviateObjectClass;
 
+	private final BatchingStrategy batchingStrategy;
+
 	/**
 	 * List of metadata fields (as field name and type) that can be used in similarity
 	 * search query filter expressions. The {@link Document#getMetadata()} can contain
@@ -290,7 +296,8 @@ public class WeaviateVectorStore extends AbstractObservationVectorStore {
 	 */
 	public WeaviateVectorStore(WeaviateVectorStoreConfig vectorStoreConfig, EmbeddingModel embeddingModel,
 			WeaviateClient weaviateClient) {
-		this(vectorStoreConfig, embeddingModel, weaviateClient, ObservationRegistry.NOOP, null);
+		this(vectorStoreConfig, embeddingModel, weaviateClient, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	/**
@@ -303,7 +310,7 @@ public class WeaviateVectorStore extends AbstractObservationVectorStore {
 	 */
 	public WeaviateVectorStore(WeaviateVectorStoreConfig vectorStoreConfig, EmbeddingModel embeddingModel,
 			WeaviateClient weaviateClient, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -318,6 +325,7 @@ public class WeaviateVectorStore extends AbstractObservationVectorStore {
 				this.filterMetadataFields.stream().map(MetadataField::name).toList());
 		this.weaviateClient = weaviateClient;
 		this.weaviateSimilaritySearchFields = buildWeaviateSimilaritySearchFields();
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	private Field[] buildWeaviateSimilaritySearchFields() {
@@ -347,6 +355,8 @@ public class WeaviateVectorStore extends AbstractObservationVectorStore {
 			return;
 		}
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		List<WeaviateObject> weaviateObjects = documents.stream().map(this::toWeaviateObject).toList();
 
 		Result<ObjectGetResponse[]> response = this.weaviateClient.batch()
@@ -385,11 +395,6 @@ public class WeaviateVectorStore extends AbstractObservationVectorStore {
 
 	private WeaviateObject toWeaviateObject(Document document) {
 
-		if (document.getEmbedding() == null || document.getEmbedding().length == 0) {
-			float[] embedding = this.embeddingModel.embed(document);
-			document.setEmbedding(embedding);
-		}
-
 		// https://weaviate.io/developers/weaviate/config-refs/datatypes
 		Map<String, Object> fields = new HashMap<>();
 		fields.put(CONTENT_FIELD_NAME, document.getContent());

vector-stores/spring-ai-weaviate-store/src/test/java/org/springframework/ai/vectorstore/WeaviateVectorStoreObservationIT.java

@@ -25,6 +25,7 @@ import java.util.Map;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
@@ -165,7 +166,8 @@ public class WeaviateVectorStoreObservationIT {
 				.withConsistencyLevel(WeaviateVectorStoreConfig.ConsistentLevel.ONE)
 				.build();
 
-			return new WeaviateVectorStore(config, embeddingModel, weaviateClient, observationRegistry, null);
+			return new WeaviateVectorStore(config, embeddingModel, weaviateClient, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 
 		}