Add batching strategy for embedding documents in PgVectorStore

- Precompute all embeddings using a BatchingStrategy before inserting into the vector store

This optimization improves efficiency when adding multiple documents

Related to #1261

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/pgvector/PgVectorStoreAutoConfiguration.java

@@ -13,11 +13,14 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 package org.springframework.ai.autoconfigure.vectorstore.pgvector;
 
 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.PgVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.ObjectProvider;
@@ -34,17 +37,26 @@
 /**
  * @author Christian Tzolov
  * @author Josh Long
+ * @author Soby Chacko
+ * @since 1.0.0
  */
 @AutoConfiguration(after = JdbcTemplateAutoConfiguration.class)
 @ConditionalOnClass({ PgVectorStore.class, DataSource.class, JdbcTemplate.class })
 @EnableConfigurationProperties(PgVectorStoreProperties.class)
 public class PgVectorStoreAutoConfiguration {
 
+	@Bean
+	@ConditionalOnMissingBean(BatchingStrategy.class)
+	BatchingStrategy pgVectorStoreBatchingStrategy() {
+		return new TokenCountBatchingStrategy();
+	}
+
 	@Bean
 	@ConditionalOnMissingBean
 	public PgVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
 			PgVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		var initializeSchema = properties.isInitializeSchema();
 
@@ -58,6 +70,7 @@ public PgVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embed
 			.withInitializeSchema(initializeSchema)
 			.withObservationRegistry(observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP))
 			.withSearchObservationConvention(customObservationConvention.getIfAvailable(() -> null))
+			.withBatchingStrategy(batchingStrategy)
 			.build();
 	}
 

vector-stores/spring-ai-pgvector-store/src/main/java/org/springframework/ai/vectorstore/PgVectorStore.java

@@ -27,7 +27,10 @@
 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.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
@@ -57,6 +60,8 @@
  * @author Josh Long
  * @author Muthukumaran Navaneethakrishnan
  * @author Thomas Vitale
+ * @author Soby Chacko
+ * @since 1.0.0
  */
 public class PgVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
@@ -90,17 +95,19 @@ public class PgVectorStore extends AbstractObservationVectorStore implements Ini
 
 	private final boolean initializeSchema;
 
-	private int dimensions;
+	private final int dimensions;
 
-	private PgDistanceType distanceType;
+	private final PgDistanceType distanceType;
 
-	private ObjectMapper objectMapper = new ObjectMapper();
+	private final ObjectMapper objectMapper = new ObjectMapper();
 
-	private boolean removeExistingVectorStoreTable;
+	private final boolean removeExistingVectorStoreTable;
 
-	private PgIndexType createIndexMethod;
+	private final PgIndexType createIndexMethod;
 
-	private PgVectorSchemaValidator schemaValidator;
+	private final PgVectorSchemaValidator schemaValidator;
+
+	private final BatchingStrategy batchingStrategy;
 
 	public PgVectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel) {
 		this(jdbcTemplate, embeddingModel, INVALID_EMBEDDING_DIMENSION, PgDistanceType.COSINE_DISTANCE, false,
@@ -134,13 +141,14 @@ private PgVectorStore(String schemaName, String vectorTableName, boolean vectorT
 
 		this(schemaName, vectorTableName, vectorTableValidationsEnabled, jdbcTemplate, embeddingModel, dimensions,
 				distanceType, removeExistingVectorStoreTable, createIndexMethod, initializeSchema,
-				ObservationRegistry.NOOP, null);
+				ObservationRegistry.NOOP, null, new TokenCountBatchingStrategy());
 	}
 
 	private PgVectorStore(String schemaName, String vectorTableName, boolean vectorTableValidationsEnabled,
 			JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel, int dimensions, PgDistanceType distanceType,
 			boolean removeExistingVectorStoreTable, PgIndexType createIndexMethod, boolean initializeSchema,
-			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention,
+			BatchingStrategy batchingStrategy) {
 
 		super(observationRegistry, customObservationConvention);
 
@@ -163,6 +171,7 @@ private PgVectorStore(String schemaName, String vectorTableName, boolean vectorT
 		this.createIndexMethod = createIndexMethod;
 		this.initializeSchema = initializeSchema;
 		this.schemaValidator = new PgVectorSchemaValidator(jdbcTemplate);
+		this.batchingStrategy = batchingStrategy;
 	}
 
 	public PgDistanceType getDistanceType() {
@@ -174,6 +183,8 @@ public void doAdd(List<Document> documents) {
 
 		int size = documents.size();
 
+		this.embeddingModel.embed(documents, EmbeddingOptionsBuilder.builder().build(), this.batchingStrategy);
+
 		this.jdbcTemplate.batchUpdate(
 				"INSERT INTO " + getFullyQualifiedTableName()
 						+ " (id, content, metadata, embedding) VALUES (?, ?, ?::jsonb, ?) " + "ON CONFLICT (id) DO "
@@ -185,8 +196,7 @@ public void setValues(PreparedStatement ps, int i) throws SQLException {
 						var document = documents.get(i);
 						var content = document.getContent();
 						var json = toJson(document.getMetadata());
-						var embedding = embeddingModel.embed(document);
-						document.setEmbedding(embedding);
+						var embedding = document.getEmbedding();
 						var pGvector = new PGvector(embedding);
 
 						StatementCreatorUtils.setParameterValue(ps, 1, SqlTypeValue.TYPE_UNKNOWN,
@@ -497,6 +507,8 @@ public static class Builder {
 
 		private ObservationRegistry observationRegistry = ObservationRegistry.NOOP;
 
+		private BatchingStrategy batchingStrategy = new TokenCountBatchingStrategy();
+
 		@Nullable
 		private VectorStoreObservationConvention searchObservationConvention;
 
@@ -559,10 +571,16 @@ public Builder withSearchObservationConvention(VectorStoreObservationConvention
 			return this;
 		}
 
+		public Builder withBatchingStrategy(BatchingStrategy batchingStrategy) {
+			this.batchingStrategy = batchingStrategy;
+			return this;
+		}
+
 		public PgVectorStore build() {
-			return new PgVectorStore(schemaName, vectorTableName, vectorTableValidationsEnabled, jdbcTemplate,
-					embeddingModel, dimensions, distanceType, removeExistingVectorStoreTable, indexType,
-					initializeSchema, observationRegistry, searchObservationConvention);
+			return new PgVectorStore(this.schemaName, this.vectorTableName, this.vectorTableValidationsEnabled,
+					this.jdbcTemplate, this.embeddingModel, this.dimensions, this.distanceType,
+					this.removeExistingVectorStoreTable, this.indexType, this.initializeSchema,
+					this.observationRegistry, this.searchObservationConvention, this.batchingStrategy);
 		}
 
 	}