Add batching strategy to more vector stores

Apply batching when adding Documents to the following vector stores:

- Azure vector store
- Cassandra
- MongoDB Atlas
- OpenSearch
- Oracle
- Pinecone

 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/azure/AzureVectorStoreAutoConfiguration.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.autoconfigure.vectorstore.azure;
 
 import com.azure.core.credential.AzureKeyCredential;
@@ -23,7 +24,9 @@ import io.micrometer.observation.ObservationRegistry;
 
 import java.util.List;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.azure.AzureVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -36,6 +39,7 @@ import org.springframework.context.annotation.Bean;
 
 /**
  * @author Christian Tzolov
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ EmbeddingModel.class, SearchIndexClient.class, AzureVectorStore.class })
@@ -51,15 +55,22 @@ public class AzureVectorStoreAutoConfiguration {
 			.buildClient();
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public AzureVectorStore vectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
 			AzureVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		var vectorStore = new AzureVectorStore(searchIndexClient, embeddingModel, properties.isInitializeSchema(),
 				List.of(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 
 		vectorStore.setIndexName(properties.getIndexName());
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStoreAutoConfiguration.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2024 - 2024 the original author or authors.
+ * Copyright 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.autoconfigure.vectorstore.cassandra;
 
 import java.time.Duration;
@@ -22,7 +23,9 @@ import com.datastax.oss.driver.api.core.config.DefaultDriverOption;
 
 import io.micrometer.observation.ObservationRegistry;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.CassandraVectorStore;
 import org.springframework.ai.vectorstore.CassandraVectorStoreConfig;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
@@ -38,6 +41,7 @@ import org.springframework.context.annotation.Bean;
 /**
  * @author Mick Semb Wever
  * @author Christian Tzolov
+ * @author Soby Chacko
  * @since 1.0.0
  */
 @AutoConfiguration(after = CassandraAutoConfiguration.class)
@@ -45,11 +49,18 @@ import org.springframework.context.annotation.Bean;
 @EnableConfigurationProperties(CassandraVectorStoreProperties.class)
 public class CassandraVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public CassandraVectorStore vectorStore(EmbeddingModel embeddingModel, CassandraVectorStoreProperties properties,
 			CqlSession cqlSession, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		var builder = CassandraVectorStoreConfig.builder().withCqlSession(cqlSession);
 
@@ -69,7 +80,7 @@ public class CassandraVectorStoreAutoConfiguration {
 
 		return new CassandraVectorStore(builder.build(), embeddingModel,
 				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/gemfire/GemFireVectorStoreAutoConfiguration.java

@@ -16,7 +16,9 @@
 
 package org.springframework.ai.autoconfigure.vectorstore.gemfire;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.GemFireVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -47,11 +49,18 @@ public class GemFireVectorStoreAutoConfiguration {
 		return new GemFireVectorStoreAutoConfiguration.PropertiesGemFireConnectionDetails(properties);
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public GemFireVectorStore gemfireVectorStore(EmbeddingModel embeddingModel, GemFireVectorStoreProperties properties,
 			GemFireConnectionDetails gemFireConnectionDetails, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		var builder = new GemFireVectorStore.GemFireVectorStoreConfig.Builder();
 
 		builder.setHost(gemFireConnectionDetails.getHost())
@@ -65,7 +74,7 @@ public class GemFireVectorStoreAutoConfiguration {
 			.setSslEnabled(properties.isSslEnabled());
 		return new GemFireVectorStore(builder.build(), embeddingModel, properties.isInitializeSchema(),
 				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 	private static class PropertiesGemFireConnectionDetails implements GemFireConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/mongo/MongoDBAtlasVectorStoreAutoConfiguration.java

@@ -13,9 +13,12 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.mongo;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.MongoDBAtlasVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -45,11 +48,18 @@ import java.util.Arrays;
 @EnableConfigurationProperties(MongoDBAtlasVectorStoreProperties.class)
 public class MongoDBAtlasVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	MongoDBAtlasVectorStore vectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
 			MongoDBAtlasVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		var builder = MongoDBAtlasVectorStore.MongoDBVectorStoreConfig.builder();
 
@@ -66,7 +76,7 @@ public class MongoDBAtlasVectorStoreAutoConfiguration {
 
 		return new MongoDBAtlasVectorStore(mongoTemplate, 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/opensearch/OpenSearchVectorStoreAutoConfiguration.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.autoconfigure.vectorstore.opensearch;
 
 import org.apache.hc.client5.http.auth.AuthScope;
@@ -24,7 +25,10 @@ import org.opensearch.client.transport.OpenSearchTransport;
 import org.opensearch.client.transport.aws.AwsSdk2Transport;
 import org.opensearch.client.transport.aws.AwsSdk2TransportOptions;
 import org.opensearch.client.transport.httpclient5.ApacheHttpClient5TransportBuilder;
+
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.OpenSearchVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -58,17 +62,24 @@ public class OpenSearchVectorStoreAutoConfiguration {
 		return new PropertiesOpenSearchConnectionDetails(properties);
 	}
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	OpenSearchVectorStore vectorStore(OpenSearchVectorStoreProperties properties, OpenSearchClient openSearchClient,
 			EmbeddingModel embeddingModel, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		var indexName = Optional.ofNullable(properties.getIndexName()).orElse(OpenSearchVectorStore.DEFAULT_INDEX_NAME);
 		var mappingJson = Optional.ofNullable(properties.getMappingJson())
 			.orElse(OpenSearchVectorStore.DEFAULT_MAPPING_EMBEDDING_TYPE_KNN_VECTOR_DIMENSION_1536);
 		return new OpenSearchVectorStore(indexName, openSearchClient, embeddingModel, mappingJson,
 				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 	@Configuration(proxyBeanMethods = false)

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/oracle/OracleVectorStoreAutoConfiguration.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.oracle;
 
 import javax.sql.DataSource;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.OracleVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -35,22 +38,30 @@ import io.micrometer.observation.ObservationRegistry;
  * @author Loïc Lefèvre
  * @author Eddú Meléndez
  * @author Christian Tzolov
+ * @author Soby Chacko
  */
 @AutoConfiguration(after = JdbcTemplateAutoConfiguration.class)
 @ConditionalOnClass({ OracleVectorStore.class, DataSource.class, JdbcTemplate.class })
 @EnableConfigurationProperties(OracleVectorStoreProperties.class)
 public class OracleVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public OracleVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
 			OracleVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		return new OracleVectorStore(jdbcTemplate, embeddingModel, properties.getTableName(), properties.getIndexType(),
 				properties.getDistanceType(), properties.getDimensions(), properties.getSearchAccuracy(),
 				properties.isInitializeSchema(), properties.isRemoveExistingVectorStoreTable(),
 				properties.isForcedNormalization(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/pinecone/PineconeVectorStoreAutoConfiguration.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.pinecone;
 
+import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.vectorstore.PineconeVectorStore;
 import org.springframework.ai.vectorstore.PineconeVectorStore.PineconeVectorStoreConfig;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
@@ -30,17 +33,25 @@ import io.micrometer.observation.ObservationRegistry;
 
 /**
  * @author Christian Tzolov
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ PineconeVectorStore.class, EmbeddingModel.class })
 @EnableConfigurationProperties(PineconeVectorStoreProperties.class)
 public class PineconeVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy batchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public PineconeVectorStore vectorStore(EmbeddingModel embeddingModel, PineconeVectorStoreProperties properties,
 			ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		var config = PineconeVectorStoreConfig.builder()
 			.withApiKey(properties.getApiKey())
@@ -55,7 +66,7 @@ public class PineconeVectorStoreAutoConfiguration {
 
 		return new PineconeVectorStore(config, embeddingModel,
 				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
-				customObservationConvention.getIfAvailable(() -> null));
+				customObservationConvention.getIfAvailable(() -> null), batchingStrategy);
 	}
 
 }

vector-stores/spring-ai-azure-store/src/main/java/org/springframework/ai/vectorstore/azure/AzureVectorStore.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.azure;
 
 import java.util.ArrayList;
@@ -25,7 +26,10 @@ 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.model.EmbeddingUtils;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
@@ -73,6 +77,7 @@ import io.micrometer.observation.ObservationRegistry;
  * @author Christian Tzolov
  * @author Josh Long
  * @author Thomas Vitale
+ * @author Soby Chacko
  */
 public class AzureVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
@@ -116,6 +121,8 @@ public class AzureVectorStore extends AbstractObservationVectorStore implements
 
 	private final boolean initializeSchema;
 
+	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
@@ -175,7 +182,8 @@ public class AzureVectorStore extends AbstractObservationVectorStore implements
 	 */
 	public AzureVectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
 			boolean initializeSchema, List<MetadataField> filterMetadataFields) {
-		this(searchIndexClient, embeddingModel, initializeSchema, filterMetadataFields, ObservationRegistry.NOOP, null);
+		this(searchIndexClient, embeddingModel, initializeSchema, filterMetadataFields, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	/**
@@ -191,7 +199,7 @@ public class AzureVectorStore extends AbstractObservationVectorStore implements
 	 */
 	public AzureVectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
 			boolean initializeSchema, List<MetadataField> filterMetadataFields, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -204,6 +212,7 @@ public class AzureVectorStore extends AbstractObservationVectorStore implements
 		this.embeddingModel = embeddingModel;
 		this.filterMetadataFields = filterMetadataFields;
 		this.filterExpressionConverter = new AzureAiSearchFilterExpressionConverter(filterMetadataFields);
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	/**
@@ -243,11 +252,12 @@ public class AzureVectorStore extends AbstractObservationVectorStore implements
 			return; // nothing to do;
 		}
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		final var searchDocuments = documents.stream().map(document -> {
-			final var embeddings = this.embeddingModel.embed(document);
 			SearchDocument searchDocument = new SearchDocument();
 			searchDocument.put(ID_FIELD_NAME, document.getId());
-			searchDocument.put(EMBEDDING_FIELD_NAME, embeddings);
+			searchDocument.put(EMBEDDING_FIELD_NAME, document.getEmbedding());
 			searchDocument.put(CONTENT_FIELD_NAME, document.getContent());
 			searchDocument.put(METADATA_FIELD_NAME, new JSONObject(document.getMetadata()).toJSONString());
 

vector-stores/spring-ai-azure-store/src/test/java/org/springframework/ai/vectorstore/azure/AzureVectorStoreIT.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.
@@ -80,9 +80,9 @@ public class AzureVectorStoreIT {
 
 			vectorStore.add(documents);
 
-			Awaitility.await().until(() -> {
-				return vectorStore.similaritySearch(SearchRequest.query("Great Depression").withTopK(1));
-			}, hasSize(1));
+			Awaitility.await()
+				.until(() -> vectorStore.similaritySearch(SearchRequest.query("Great Depression").withTopK(1)),
+						hasSize(1));
 
 			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Great Depression").withTopK(1));
 
@@ -97,9 +97,8 @@ public class AzureVectorStoreIT {
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
-			Awaitility.await().until(() -> {
-				return vectorStore.similaritySearch(SearchRequest.query("Hello").withTopK(1));
-			}, hasSize(0));
+			Awaitility.await()
+				.until(() -> vectorStore.similaritySearch(SearchRequest.query("Hello").withTopK(1)), hasSize(0));
 		});
 	}
 
@@ -206,9 +205,7 @@ public class AzureVectorStoreIT {
 
 			SearchRequest springSearchRequest = SearchRequest.query("Spring").withTopK(5);
 
-			Awaitility.await().until(() -> {
-				return vectorStore.similaritySearch(springSearchRequest);
-			}, hasSize(1));
+			Awaitility.await().until(() -> vectorStore.similaritySearch(springSearchRequest), hasSize(1));
 
 			List<Document> results = vectorStore.similaritySearch(springSearchRequest);
 
@@ -227,9 +224,9 @@ public class AzureVectorStoreIT {
 
 			SearchRequest fooBarSearchRequest = SearchRequest.query("FooBar").withTopK(5);
 
-			Awaitility.await().until(() -> {
-				return vectorStore.similaritySearch(fooBarSearchRequest).get(0).getContent();
-			}, equalTo("The World is Big and Salvation Lurks Around the Corner"));
+			Awaitility.await()
+				.until(() -> vectorStore.similaritySearch(fooBarSearchRequest).get(0).getContent(),
+						equalTo("The World is Big and Salvation Lurks Around the Corner"));
 
 			results = vectorStore.similaritySearch(fooBarSearchRequest);
 
@@ -242,9 +239,7 @@ public class AzureVectorStoreIT {
 
 			// Remove all documents from the store
 			vectorStore.delete(List.of(document.getId()));
-			Awaitility.await().until(() -> {
-				return vectorStore.similaritySearch(fooBarSearchRequest);
-			}, hasSize(0));
+			Awaitility.await().until(() -> vectorStore.similaritySearch(fooBarSearchRequest), hasSize(0));
 
 		});
 	}
@@ -258,10 +253,10 @@ public class AzureVectorStoreIT {
 
 			vectorStore.add(documents);
 
-			Awaitility.await().until(() -> {
-				return vectorStore
-					.similaritySearch(SearchRequest.query("Depression").withTopK(50).withSimilarityThresholdAll());
-			}, hasSize(3));
+			Awaitility.await()
+				.until(() -> vectorStore
+					.similaritySearch(SearchRequest.query("Depression").withTopK(50).withSimilarityThresholdAll()),
+						hasSize(3));
 
 			List<Document> fullResult = vectorStore
 				.similaritySearch(SearchRequest.query("Depression").withTopK(5).withSimilarityThresholdAll());
@@ -284,9 +279,8 @@ public class AzureVectorStoreIT {
 
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
-			Awaitility.await().until(() -> {
-				return vectorStore.similaritySearch(SearchRequest.query("Hello").withTopK(1));
-			}, hasSize(0));
+			Awaitility.await()
+				.until(() -> vectorStore.similaritySearch(SearchRequest.query("Hello").withTopK(1)), hasSize(0));
 		});
 	}
 

vector-stores/spring-ai-azure-store/src/test/java/org/springframework/ai/vectorstore/azure/AzureVectorStoreObservationIT.java

@@ -30,6 +30,7 @@ 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.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
@@ -179,7 +180,7 @@ public class AzureVectorStoreObservationIT {
 			var filterableMetaFields = List.of(MetadataField.text("country"), MetadataField.int64("year"),
 					MetadataField.date("activationDate"));
 			return new AzureVectorStore(searchIndexClient, embeddingModel, true, filterableMetaFields,
-					observationRegistry, null);
+					observationRegistry, null, new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-cassandra-store/src/main/java/org/springframework/ai/vectorstore/CassandraVectorStore.java

@@ -1,5 +1,5 @@
 /*
- * Copyright 2024 - 2024 the original author or authors.
+ * Copyright 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 com.datastax.oss.driver.api.core.cql.BoundStatement;
@@ -35,7 +36,10 @@ 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;
@@ -96,6 +100,7 @@ import java.util.concurrent.ConcurrentMap;
  * @author Mick Semb Wever
  * @author Christian Tzolov
  * @author Thomas Vitale
+ * @author Soby Chacko
  * @see VectorStore
  * @see org.springframework.ai.vectorstore.CassandraVectorStoreConfig
  * @see EmbeddingModel
@@ -137,12 +142,15 @@ public class CassandraVectorStore extends AbstractObservationVectorStore impleme
 
 	private final Similarity similarity;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public CassandraVectorStore(CassandraVectorStoreConfig conf, EmbeddingModel embeddingModel) {
-		this(conf, embeddingModel, ObservationRegistry.NOOP, null);
+		this(conf, embeddingModel, ObservationRegistry.NOOP, null, new TokenCountBatchingStrategy());
 	}
 
 	public CassandraVectorStore(CassandraVectorStoreConfig conf, EmbeddingModel embeddingModel,
-			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -166,21 +174,20 @@ public class CassandraVectorStore extends AbstractObservationVectorStore impleme
 
 		this.filterExpressionConverter = new CassandraFilterExpressionConverter(
 				cassandraMetadata.getColumns().values());
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	@Override
 	public void doAdd(List<Document> documents) {
 		var futures = new CompletableFuture[documents.size()];
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		int i = 0;
 		for (Document d : documents) {
 			futures[i++] = CompletableFuture.runAsync(() -> {
 				List<Object> primaryKeyValues = this.conf.documentIdTranslator.apply(d.getId());
 
-				if (null == d.getEmbedding() || d.getEmbedding().length == 0) {
-					d.setEmbedding(this.embeddingModel.embed(d));
-				}
-
 				BoundStatementBuilder builder = prepareAddStatement(d.getMetadata().keySet()).boundStatementBuilder();
 				for (int k = 0; k < primaryKeyValues.size(); ++k) {
 					SchemaColumn keyColumn = this.conf.getPrimaryKeyColumn(k);

vector-stores/spring-ai-cassandra-store/src/test/java/org/springframework/ai/vectorstore/CassandraVectorStoreObservationIT.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.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.CassandraVectorStoreConfig.SchemaColumn;
@@ -173,7 +174,8 @@ public class CassandraVectorStoreObservationIT {
 				.build();
 
 			conf.dropKeyspace();
-			return new CassandraVectorStore(conf, embeddingModel, observationRegistry, null);
+			return new CassandraVectorStore(conf, embeddingModel, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-gemfire-store/src/main/java/org/springframework/ai/vectorstore/GemFireVectorStore.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 static org.springframework.http.HttpStatus.BAD_REQUEST;
@@ -26,7 +27,10 @@ import java.util.Optional;
 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.observation.AbstractObservationVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
@@ -75,6 +79,8 @@ public class GemFireVectorStore extends AbstractObservationVectorStore implement
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	/**
 	 * Configures and initializes a GemFireVectorStore instance based on the provided
 	 * configuration.
@@ -84,7 +90,8 @@ public class GemFireVectorStore extends AbstractObservationVectorStore implement
 	 */
 	public GemFireVectorStore(GemFireVectorStoreConfig config, EmbeddingModel embeddingModel,
 			boolean initializeSchema) {
-		this(config, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null);
+		this(config, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	/**
@@ -99,7 +106,8 @@ public class GemFireVectorStore extends AbstractObservationVectorStore implement
 	 * observing operations
 	 */
 	public GemFireVectorStore(GemFireVectorStoreConfig config, EmbeddingModel embeddingModel, boolean initializeSchema,
-			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -118,6 +126,7 @@ public class GemFireVectorStore extends AbstractObservationVectorStore implement
 			.build(config.sslEnabled ? "s" : "", config.host, config.port)
 			.toString();
 		this.client = WebClient.create(base);
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	// Create Index Parameters
@@ -404,13 +413,11 @@ public class GemFireVectorStore extends AbstractObservationVectorStore implement
 
 	@Override
 	public void doAdd(List<Document> documents) {
-		UploadRequest upload = new UploadRequest(documents.stream().map(document -> {
-			// Compute and assign an embedding to the document.
-			document.setEmbedding(this.embeddingModel.embed(document));
-			float[] floatVector = document.getEmbedding();
-			return new UploadRequest.Embedding(document.getId(), floatVector, DOCUMENT_FIELD, document.getContent(),
-					document.getMetadata());
-		}).toList());
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+		UploadRequest upload = new UploadRequest(documents.stream()
+			.map(document -> new UploadRequest.Embedding(document.getId(), document.getEmbedding(), DOCUMENT_FIELD,
+					document.getContent(), document.getMetadata()))
+			.toList());
 
 		ObjectMapper objectMapper = new ObjectMapper();
 		String embeddingsJson = null;

vector-stores/spring-ai-gemfire-store/src/test/java/org/springframework/ai/vectorstore/GemFireVectorStoreObservationIT.java

@@ -28,6 +28,7 @@ import org.junit.jupiter.api.BeforeAll;
 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;
@@ -199,7 +200,7 @@ public class GemFireVectorStoreObservationIT {
 				.setHost("localhost")
 				.setPort(HTTP_SERVICE_PORT)
 				.setIndexName(TEST_INDEX_NAME)
-				.build(), embeddingModel, true, observationRegistry, null);
+				.build(), embeddingModel, true, observationRegistry, null, new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-mongodb-atlas-store/src/main/java/org/springframework/ai/vectorstore/MongoDBAtlasVectorStore.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 static org.springframework.data.mongodb.core.query.Criteria.where;
@@ -24,7 +25,10 @@ import java.util.Map;
 import java.util.Optional;
 
 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.observation.AbstractObservationVectorStore;
@@ -81,6 +85,8 @@ public class MongoDBAtlasVectorStore extends AbstractObservationVectorStore impl
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public MongoDBAtlasVectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
 			boolean initializeSchema) {
 		this(mongoTemplate, embeddingModel, MongoDBVectorStoreConfig.defaultConfig(), initializeSchema);
@@ -88,12 +94,13 @@ public class MongoDBAtlasVectorStore extends AbstractObservationVectorStore impl
 
 	public MongoDBAtlasVectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
 			MongoDBVectorStoreConfig config, boolean initializeSchema) {
-		this(mongoTemplate, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+		this(mongoTemplate, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public MongoDBAtlasVectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
 			MongoDBVectorStoreConfig config, boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -102,6 +109,7 @@ public class MongoDBAtlasVectorStore extends AbstractObservationVectorStore impl
 		this.config = config;
 
 		this.initializeSchema = initializeSchema;
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	@Override
@@ -175,9 +183,8 @@ public class MongoDBAtlasVectorStore extends AbstractObservationVectorStore impl
 
 	@Override
 	public void doAdd(List<Document> documents) {
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
 		for (Document document : documents) {
-			float[] embedding = this.embeddingModel.embed(document);
-			document.setEmbedding(embedding);
 			this.mongoTemplate.save(document, this.config.collectionName);
 		}
 	}

vector-stores/spring-ai-mongodb-atlas-store/src/test/java/org/springframework/ai/vectorstore/MongoDbVectorStoreObservationIT.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.observation.conventions.SpringAiKind;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.openai.OpenAiEmbeddingModel;
@@ -185,7 +186,7 @@ public class MongoDbVectorStoreObservationIT {
 					MongoDBAtlasVectorStore.MongoDBVectorStoreConfig.builder()
 						.withMetadataFieldsToFilter(List.of("country", "year"))
 						.build(),
-					true, observationRegistry, null);
+					true, observationRegistry, null, new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-opensearch-store/src/main/java/org/springframework/ai/vectorstore/OpenSearchVectorStore.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 org.opensearch.client.json.JsonData;
@@ -30,7 +31,10 @@ import org.opensearch.client.transport.endpoints.BooleanResponse;
 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.Filter;
@@ -91,6 +95,8 @@ public class OpenSearchVectorStore extends AbstractObservationVectorStore implem
 
 	private final boolean initializeSchema;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public OpenSearchVectorStore(OpenSearchClient openSearchClient, EmbeddingModel embeddingModel,
 			boolean initializeSchema) {
 		this(openSearchClient, embeddingModel, DEFAULT_MAPPING_EMBEDDING_TYPE_KNN_VECTOR_DIMENSION_1536,
@@ -104,12 +110,13 @@ public class OpenSearchVectorStore extends AbstractObservationVectorStore implem
 
 	public OpenSearchVectorStore(String index, OpenSearchClient openSearchClient, EmbeddingModel embeddingModel,
 			String mappingJson, boolean initializeSchema) {
-		this(index, openSearchClient, embeddingModel, mappingJson, initializeSchema, ObservationRegistry.NOOP, null);
+		this(index, openSearchClient, embeddingModel, mappingJson, initializeSchema, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public OpenSearchVectorStore(String index, OpenSearchClient openSearchClient, EmbeddingModel embeddingModel,
 			String mappingJson, boolean initializeSchema, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -124,6 +131,7 @@ public class OpenSearchVectorStore extends AbstractObservationVectorStore implem
 		// https://opensearch.org/docs/latest/search-plugins/knn/approximate-knn/#spaces
 		this.similarityFunction = COSINE_SIMILARITY_FUNCTION;
 		this.initializeSchema = initializeSchema;
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	public OpenSearchVectorStore withSimilarityFunction(String similarityFunction) {
@@ -133,12 +141,9 @@ public class OpenSearchVectorStore extends AbstractObservationVectorStore implem
 
 	@Override
 	public void doAdd(List<Document> documents) {
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
 		BulkRequest.Builder bulkRequestBuilder = new BulkRequest.Builder();
 		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.index).id(document.getId()).document(document)));
 		}

vector-stores/spring-ai-opensearch-store/src/test/java/org/springframework/ai/vectorstore/OpenSearchVectorStoreIT.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 org.apache.hc.core5.http.HttpHost;

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

@@ -36,6 +36,7 @@ import org.opensearch.client.transport.httpclient5.ApacheHttpClient5TransportBui
 import org.opensearch.testcontainers.OpensearchContainer;
 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;
@@ -207,7 +208,7 @@ public class OpenSearchVectorStoreObservationIT {
 							.builder(HttpHost.create(opensearchContainer.getHttpHostAddress()))
 							.build()),
 						embeddingModel, OpenSearchVectorStore.DEFAULT_MAPPING_EMBEDDING_TYPE_KNN_VECTOR_DIMENSION_1536,
-						true, observationRegistry, null);
+						true, observationRegistry, null, new TokenCountBatchingStrategy());
 			}
 			catch (URISyntaxException e) {
 				throw new RuntimeException(e);

vector-stores/spring-ai-oracle-store/src/main/java/org/springframework/ai/vectorstore/OracleVectorStore.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 static org.springframework.ai.vectorstore.OracleVectorStore.OracleVectorStoreDistanceType.DOT;
@@ -33,7 +34,10 @@ import java.util.Optional;
 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;
@@ -78,6 +82,7 @@ import oracle.sql.json.OracleJsonValue;
  *
  * @author Loïc Lefèvre
  * @author Christian Tzolov
+ * @author Soby Chacko
  */
 public class OracleVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
@@ -215,6 +220,8 @@ public class OracleVectorStore extends AbstractObservationVectorStore implements
 
 	private final int searchAccuracy;
 
+	private final BatchingStrategy batchingStrategy;
+
 	public OracleVectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel) {
 		this(jdbcTemplate, embeddingModel, DEFAULT_TABLE_NAME, DEFAULT_INDEX_TYPE, DEFAULT_DISTANCE_TYPE,
 				DEFAULT_DIMENSIONS, DEFAULT_SEARCH_ACCURACY, false, false, false);
@@ -230,14 +237,15 @@ public class OracleVectorStore extends AbstractObservationVectorStore implements
 			int searchAccuracy, boolean initializeSchema, boolean removeExistingVectorStoreTable,
 			boolean forcedNormalization) {
 		this(jdbcTemplate, embeddingModel, tableName, indexType, distanceType, dimensions, searchAccuracy,
-				initializeSchema, removeExistingVectorStoreTable, forcedNormalization, ObservationRegistry.NOOP, null);
+				initializeSchema, removeExistingVectorStoreTable, forcedNormalization, ObservationRegistry.NOOP, null,
+				new TokenCountBatchingStrategy());
 	}
 
 	public OracleVectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel, String tableName,
 			OracleVectorStoreIndexType indexType, OracleVectorStoreDistanceType distanceType, int dimensions,
 			int searchAccuracy, boolean initializeSchema, boolean removeExistingVectorStoreTable,
 			boolean forcedNormalization, ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention, BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -269,17 +277,19 @@ public class OracleVectorStore extends AbstractObservationVectorStore implements
 		this.initializeSchema = initializeSchema;
 		this.removeExistingVectorStoreTable = removeExistingVectorStoreTable;
 		this.forcedNormalization = forcedNormalization;
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	@Override
 	public void doAdd(final List<Document> documents) {
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
 		this.jdbcTemplate.batchUpdate(getIngestStatement(), new BatchPreparedStatementSetter() {
 			@Override
 			public void setValues(PreparedStatement ps, int i) throws SQLException {
 				final Document document = documents.get(i);
 				final String content = document.getContent();
 				final byte[] json = toJson(document.getMetadata());
-				final VECTOR embeddingVector = toVECTOR(embeddingModel.embed(document));
+				final VECTOR embeddingVector = toVECTOR(document.getEmbedding());
 
 				setParameterValue(ps, 1, Types.VARCHAR, document.getId());
 				setParameterValue(ps, 2, Types.VARCHAR, content);

vector-stores/spring-ai-oracle-store/src/test/java/org/springframework/ai/vectorstore/OracleVectorStoreObservationIT.java

@@ -27,6 +27,7 @@ import javax.sql.DataSource;
 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;
@@ -183,7 +184,8 @@ public class OracleVectorStoreObservationIT {
 				ObservationRegistry observationRegistry) {
 			return new OracleVectorStore(jdbcTemplate, embeddingModel, OracleVectorStore.DEFAULT_TABLE_NAME,
 					OracleVectorStore.OracleVectorStoreIndexType.IVF, OracleVectorStoreDistanceType.COSINE, 384,
-					OracleVectorStore.DEFAULT_SEARCH_ACCURACY, true, true, true, observationRegistry, null);
+					OracleVectorStore.DEFAULT_SEARCH_ACCURACY, true, true, true, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 		}
 
 		@Bean

vector-stores/spring-ai-pinecone-store/src/main/java/org/springframework/ai/vectorstore/PineconeVectorStore.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.
@@ -22,7 +22,10 @@ import java.util.Map;
 import java.util.Optional;
 
 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.filter.FilterExpressionConverter;
@@ -57,6 +60,7 @@ import io.pinecone.proto.Vector;
  *
  * @author Christian Tzolov
  * @author Adam Bchouti
+ * @author Soby Chacko
  */
 public class PineconeVectorStore extends AbstractObservationVectorStore {
 
@@ -80,6 +84,8 @@ public class PineconeVectorStore extends AbstractObservationVectorStore {
 
 	private final ObjectMapper objectMapper;
 
+	private final BatchingStrategy batchingStrategy;
+
 	/**
 	 * Configuration class for the PineconeVectorStore.
 	 */
@@ -260,7 +266,7 @@ public class PineconeVectorStore extends AbstractObservationVectorStore {
 	 * @param embeddingModel The client for embedding operations.
 	 */
 	public PineconeVectorStore(PineconeVectorStoreConfig config, EmbeddingModel embeddingModel) {
-		this(config, embeddingModel, ObservationRegistry.NOOP, null);
+		this(config, embeddingModel, ObservationRegistry.NOOP, null, new TokenCountBatchingStrategy());
 	}
 
 	/**
@@ -271,7 +277,8 @@ public class PineconeVectorStore extends AbstractObservationVectorStore {
 	 * @param customObservationConvention The custom observation convention.
 	 */
 	public PineconeVectorStore(PineconeVectorStoreConfig config, EmbeddingModel embeddingModel,
-			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 		super(observationRegistry, customObservationConvention);
 		Assert.notNull(config, "PineconeVectorStoreConfig must not be null");
 		Assert.notNull(embeddingModel, "EmbeddingModel must not be null");
@@ -283,6 +290,7 @@ public class PineconeVectorStore extends AbstractObservationVectorStore {
 		this.pineconeDistanceMetadataFieldName = config.distanceMetadataFieldName;
 		this.pineconeConnection = new PineconeClient(config.clientConfig).connect(config.connectionConfig);
 		this.objectMapper = new ObjectMapper();
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	/**
@@ -291,17 +299,14 @@ public class PineconeVectorStore extends AbstractObservationVectorStore {
 	 * @param namespace The namespace to add the documents to
 	 */
 	public void add(List<Document> documents, String namespace) {
-
-		List<Vector> upsertVectors = documents.stream().map(document -> {
-			// Compute and assign an embedding to the document.
-			document.setEmbedding(this.embeddingModel.embed(document));
-
-			return Vector.newBuilder()
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+		List<Vector> upsertVectors = documents.stream()
+			.map(document -> Vector.newBuilder()
 				.setId(document.getId())
 				.addAllValues(EmbeddingUtils.toList(document.getEmbedding()))
 				.setMetadata(metadataToStruct(document))
-				.build();
-		}).toList();
+				.build())
+			.toList();
 
 		UpsertRequest upsertRequest = UpsertRequest.newBuilder()
 			.addAllVectors(upsertVectors)

vector-stores/spring-ai-pinecone-store/src/test/java/org/springframework/ai/vectorstore/PineconeVectorStoreObservationIT.java

@@ -31,6 +31,7 @@ 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.transformers.TransformersEmbeddingModel;
@@ -196,7 +197,8 @@ public class PineconeVectorStoreObservationIT {
 		@Bean
 		public VectorStore vectorStore(PineconeVectorStoreConfig config, EmbeddingModel embeddingModel,
 				ObservationRegistry observationRegistry) {
-			return new PineconeVectorStore(config, embeddingModel, observationRegistry, null);
+			return new PineconeVectorStore(config, embeddingModel, observationRegistry, null,
+					new TokenCountBatchingStrategy());
 		}
 
 		@Bean