BREAKING CHANGE - Change vector store initialize-schema to false

* Change default schema initialization of vector stores from `true` to `false.`
  Users need to explicitly opt-in for schema initialization by setting the
  `initialize-schema` property on the corresponding vector store.
* Update integration tests
* Update docs

Fixes spring-projects#907

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/apache-cassandra.adoc

@@ -78,6 +78,24 @@ Add these dependencies to your project:
 
 TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.
 
+== Configuration Properties
+
+You can use the following properties in your Spring Boot configuration to customize the Apache Cassandra vector store.
+
+|===
+|Property|Default value
+
+|`spring.ai.vectorstore.cassandra.keyspace`|springframework
+|`spring.ai.vectorstore.cassandra.table`|ai_vector_store
+|`spring.ai.vectorstore.cassandra.initialze-schema`|false
+|`spring.ai.vectorstore.cassandra.index-name`|
+|`spring.ai.vectorstore.cassandra.content-column-name`|content
+|`spring.ai.vectorstore.cassandra.embedding-column-name`|embedding
+|`spring.ai.vectorstore.cassandra.return-embeddings`|false
+|`spring.ai.vectorstore.cassandra.fixed-thread-pool-executor-size`|16
+|===
+
+
 
 == Usage
 

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/azure.adoc

@@ -12,7 +12,7 @@ link:https://azure.microsoft.com/en-us/products/ai-services/ai-search/[Azure AI
 
 == Configuration
 
-On startup, the `AzureVectorStore` can  attempt to create a new index within your AI Search service instance if you've opted in by setting the relevant `initializeSchema` `boolean` property to `true` in the constructor or, if using Spring Boot, setting `...initialize-schema=true`  in your `application.properties` file.
+On startup, the `AzureVectorStore` can  attempt to create a new index within your AI Search service instance if you've opted in by setting the relevant `initialize-schema` `boolean` property to `true` in the constructor or, if using Spring Boot, setting `...initialize-schema=true`  in your `application.properties` file.
 
 
 NOTE: this is a breaking change! In earlier versions of Spring AI, this schema initialization happened by default.
@@ -88,6 +88,24 @@ Add these dependencies to your project:
 
 TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.
 
+== Configuration Properties
+
+You can use the following properties in your Spring Boot configuration to customize the Azure vector store.
+
+|===
+|Property|Default value
+
+|`spring.ai.vectorstore.azure.url`|
+|`spring.ai.vectorstore.azure.api-key`|
+|`spring.ai.vectorstore.azure.initialze-schema`|false
+|`spring.ai.vectorstore.azure.index-name`|spring_ai_azure_vector_store
+|`spring.ai.vectorstore.azure.default-top-k`|4
+|`spring.ai.vectorstore.azure.default-similarity-threshold`|0.0
+|`spring.ai.vectorstore.azure.embedding-property`|embedding
+|`spring.ai.vectorstore.azure.index-name`|spring-ai-document-index
+|===
+
+
 == Sample Code
 
 To configure an Azure `SearchIndexClient` in your application, you can use the following code:

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/chroma.adoc

@@ -66,14 +66,14 @@ A simple configuration can either be provided via Spring Boot's _application.pro
 [source,properties]
 ----
 # Chroma Vector Store connection properties
-spring.ai.vectorstore.chroma.client.initialize-schema=<true or false>
 spring.ai.vectorstore.chroma.client.host=<your Chroma instance host>
 spring.ai.vectorstore.chroma.client.port=<your Chroma instance port>
 spring.ai.vectorstore.chroma.client.key-token=<your access token (if configure)>
 spring.ai.vectorstore.chroma.client.username=<your username (if configure)>
 spring.ai.vectorstore.chroma.client.password=<your password (if configure)>
 
 # Chroma Vector Store collection properties
+spring.ai.vectorstore.chroma.initialize-schema=<true or false>
 spring.ai.vectorstore.chroma.collection-name=<your collection name>
 
 # Chroma Vector Store configuration properties
@@ -117,6 +117,7 @@ You can use the following properties in your Spring Boot configuration to custom
 |`spring.ai.vectorstore.chroma.client.username`| Access username (if configured) | -
 |`spring.ai.vectorstore.chroma.client.password`| Access password (if configured) | -
 |`spring.ai.vectorstore.chroma.collection-name`| Collection name | `SpringAiCollection`
+|`spring.ai.vectorstore.chroma.initialize-schema`| Whether to initialize the required schema  | `false`
 |===
 
 [NOTE]

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/elasticsearch.adoc

@@ -140,6 +140,7 @@ Properties starting with the `spring.ai.vectorstore.elasticsearch.*` prefix are
 |===
 |Property | Description | Default Value
 
+|`spring.ai.vectorstore.elasticsearch.initialize-schema`| Whether to initialize the required schema  | `false`
 |`spring.ai.vectorstore.elasticsearch.index-name` | The name of the index to store the vectors. | spring-ai-document-index
 |`spring.ai.vectorstore.elasticsearch.dimensions` | The number of dimensions in the vector. | 1536
 |`spring.ai.vectorstore.elasticsearch.similarity` | The similarity function to use. | `cosine`

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/gemfire.adoc

@@ -44,6 +44,7 @@ You can use the following properties in your Spring Boot configuration to furthe
 
 |`spring.ai.vectorstore.gemfire.host`|localhost
 |`spring.ai.vectorstore.gemfire.port`|8080
+|`spring.ai.vectorstore.gemfire.initialize-schema`| `false`
 |`spring.ai.vectorstore.gemfire.index-name`|spring-ai-gemfire-store
 |`spring.ai.vectorstore.gemfire.beam-width`|100
 |`spring.ai.vectorstore.gemfire.max-connections`|16

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/opensearch.adoc

@@ -120,11 +120,11 @@ You can use the following properties in your Spring Boot configuration to custom
 |===
 |Property| Description | Default value
 
-|`spring.opensearch.uris`| URIs of the OpenSearch cluster endpoints. | -
-|`spring.opensearch.username`| Username for accessing the OpenSearch cluster. | -
-|`spring.opensearch.password`| Password for the specified username. | -
-|`spring.opensearch.indexName`| Name of the default index to be used within the OpenSearch cluster. | `spring-ai-document-index`
-|`spring.opensearch.mappingJson`| JSON string defining the mapping for the index; specifies how documents and their
+|`spring.ai.vectorstore.opensearch.uris`| URIs of the OpenSearch cluster endpoints. | -
+|`spring.ai.vectorstore.opensearch.username`| Username for accessing the OpenSearch cluster. | -
+|`spring.ai.vectorstore.opensearch.password`| Password for the specified username. | -
+|`spring.ai.vectorstore.opensearch.indexName`| Name of the default index to be used within the OpenSearch cluster. | `spring-ai-document-index`
+|`spring.ai.vectorstore.opensearch.mappingJson`| JSON string defining the mapping for the index; specifies how documents and their
 fields are stored and indexed. |
 {
     "properties":{

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/redis.adoc

@@ -108,7 +108,7 @@ You can use the following properties in your Spring Boot configuration to custom
 
 |`spring.ai.vectorstore.redis.uri`| Server connection URI | `redis://localhost:6379`
 |`spring.ai.vectorstore.redis.index`| Index name  | `default-index`
-|`spring.ai.vectorstore.redis.initialize-schema`| whether to initialize the required schema  | `false`
+|`spring.ai.vectorstore.redis.initialize-schema`| Whether to initialize the required schema  | `false`
 |`spring.ai.vectorstore.redis.prefix`| Prefix | `default:`
 
 |===

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/typesense.adoc

@@ -103,8 +103,9 @@ You can use the following properties in your Spring Boot configuration to custom
 |`spring.ai.vectorstore.typesense.client.host`| Hostname | `localhost`
 |`spring.ai.vectorstore.typesense.client.port`| Port | `8108`
 |`spring.ai.vectorstore.typesense.client.apiKey`| ApiKey | `xyz`
-|`spring.ai.vectorstore.typesense.collectionName`| Collection Name | `vector_store`
-|`spring.ai.vectorstore.typesense.embeddingDimension`| Embedding Dimension | `1536`
+|`spring.ai.vectorstore.typesense.initialize-schema`| Whether to initialize the required schema  | `false`
+|`spring.ai.vectorstore.typesense.collection-name`| Collection Name | `vector_store`
+|`spring.ai.vectorstore.typesense.embedding-dimension`| Embedding Dimension | `1536`
 
 |===
 

spring-ai-docs/src/main/antora/modules/ROOT/pages/upgrade-notes.adoc

@@ -5,6 +5,16 @@
 
 * The configuration prefix for the Chroma Vector Store has been changes from `spring.ai.vectorstore.chroma.store` to `spring.ai.vectorstore.chroma` in order to align with the naming conventions of other vector stores.
 
+* The default value of the `initialize-schema` property on vector stores capable of initializing a schema is now set to `false`.
+This implies that the applications now need to explicitly opt-in for schema initialization on supported vector stores, if the schema is expected to be created at application startup.
+Not all vector stores support this property.
+See the corresponding vector store documentation for more details.
+The following are the vector stores that currently don't support the `initialize-schema` property.
+
+1. Hana
+2. Pinecone
+3. Weaviate
+
 == Upgrading to 1.0.0.M1
 
 On our march to release 1.0.0 M1 we have made several breaking changes.  Apologies, it is for the best!

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

@@ -1,11 +1,33 @@
+/*
+ * 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.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
 package org.springframework.ai.autoconfigure.vectorstore;
 
 /**
  * @author Josh Long
+ * @author Soby Chacko
  */
 public class CommonVectorStoreProperties {
 
-	private boolean initializeSchema = true;
+	/**
+	 * Vector stores do not initialize schema by default on application startup. The
+	 * applications explicitly need to opt-in for initializing the schema on startup. The
+	 * recommended way to initialize the schema on startup is to set the initialize-schema
+	 * property on the vector store. See {@link #setInitializeSchema(boolean)}.
+	 */
+	private boolean initializeSchema = false;
 
 	public boolean isInitializeSchema() {
 		return initializeSchema;

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/gemfire/GemFireVectorStoreAutoConfiguration.java

@@ -57,7 +57,7 @@ public GemFireVectorStore gemfireVectorStore(EmbeddingModel embeddingModel, GemF
 			.setVectorSimilarityFunction(properties.getVectorSimilarityFunction())
 			.setFields(properties.getFields())
 			.setSslEnabled(properties.isSslEnabled());
-		return new GemFireVectorStore(config, embeddingModel);
+		return new GemFireVectorStore(config, embeddingModel, properties.isInitializeSchema());
 	}
 
 	private static class PropertiesGemFireConnectionDetails implements GemFireConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/gemfire/GemFireVectorStoreProperties.java

@@ -16,14 +16,15 @@
 
 package org.springframework.ai.autoconfigure.vectorstore.gemfire;
 
+import org.springframework.ai.autoconfigure.vectorstore.CommonVectorStoreProperties;
 import org.springframework.ai.vectorstore.GemFireVectorStoreConfig;
 import org.springframework.boot.context.properties.ConfigurationProperties;
 
 /**
  * @author Geet Rawat
  */
 @ConfigurationProperties(GemFireVectorStoreProperties.CONFIG_PREFIX)
-public class GemFireVectorStoreProperties {
+public class GemFireVectorStoreProperties extends CommonVectorStoreProperties {
 
 	/**
 	 * Configuration prefix for Spring AI VectorStore GemFire.

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/opensearch/OpenSearchVectorStoreAutoConfiguration.java

@@ -61,7 +61,8 @@ OpenSearchVectorStore vectorStore(OpenSearchVectorStoreProperties properties, Op
 		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);
+		return new OpenSearchVectorStore(indexName, openSearchClient, embeddingModel, mappingJson,
+				properties.isInitializeSchema());
 	}
 
 	@Configuration(proxyBeanMethods = false)

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/opensearch/OpenSearchVectorStoreProperties.java

@@ -15,12 +15,13 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.opensearch;
 
+import org.springframework.ai.autoconfigure.vectorstore.CommonVectorStoreProperties;
 import org.springframework.boot.context.properties.ConfigurationProperties;
 
 import java.util.List;
 
 @ConfigurationProperties(prefix = OpenSearchVectorStoreProperties.CONFIG_PREFIX)
-public class OpenSearchVectorStoreProperties {
+public class OpenSearchVectorStoreProperties extends CommonVectorStoreProperties {
 
 	public static final String CONFIG_PREFIX = "spring.ai.vectorstore.opensearch";
 

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

@@ -1,3 +1,19 @@
+/*
+ * 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.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
 package org.springframework.ai.autoconfigure.vectorstore.typesense;
 
 import org.springframework.boot.context.properties.ConfigurationProperties;

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

@@ -57,7 +57,7 @@ public TypesenseVectorStore vectorStore(Client typesenseClient, EmbeddingModel e
 			.withEmbeddingDimension(properties.getEmbeddingDimension())
 			.build();
 
-		return new TypesenseVectorStore(typesenseClient, embeddingModel, config);
+		return new TypesenseVectorStore(typesenseClient, embeddingModel, config, properties.isInitializeSchema());
 	}
 
 	@Bean

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

@@ -1,13 +1,31 @@
+/*
+ * 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.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * 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.autoconfigure.vectorstore.CommonVectorStoreProperties;
 import org.springframework.ai.vectorstore.TypesenseVectorStore;
 import org.springframework.boot.context.properties.ConfigurationProperties;
 
 /**
  * @author Pablo Sanchidrian Herrera
+ * @author Soby Chacko
  */
 @ConfigurationProperties(TypesenseVectorStoreProperties.CONFIG_PREFIX)
-public class TypesenseVectorStoreProperties {
+public class TypesenseVectorStoreProperties extends CommonVectorStoreProperties {
 
 	public static final String CONFIG_PREFIX = "spring.ai.vectorstore.typesense";
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/weaviate/WeaviateVectorStoreAutoConfiguration.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.
@@ -32,6 +32,7 @@
 /**
  * @author Christian Tzolov
  * @author Eddú Meléndez
+ * @author Soby Chacko
  */
 @AutoConfiguration
 @ConditionalOnClass({ EmbeddingModel.class, WeaviateVectorStore.class })
@@ -72,8 +73,7 @@ public WeaviateVectorStore vectorStore(EmbeddingModel embeddingModel, WeaviateCl
 				.toList())
 			.withConsistencyLevel(properties.getConsistencyLevel());
 
-		return new WeaviateVectorStore(configBuilder.build(), embeddingModel, weaviateClient,
-				properties.isInitializeSchema());
+		return new WeaviateVectorStore(configBuilder.build(), embeddingModel, weaviateClient);
 	}
 
 	static class PropertiesWeaviateConnectionDetails implements WeaviateConnectionDetails {

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

@@ -27,7 +27,7 @@
  * @author Christian Tzolov
  */
 @ConfigurationProperties(WeaviateVectorStoreProperties.CONFIG_PREFIX)
-public class WeaviateVectorStoreProperties extends CommonVectorStoreProperties {
+public class WeaviateVectorStoreProperties {
 
 	public static final String CONFIG_PREFIX = "spring.ai.vectorstore.weaviate";
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/azure/AzureVectorStoreAutoConfigurationIT.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.
@@ -44,6 +44,7 @@
 
 /**
  * @author Christian Tzolov
+ * @author Soby Chacko
  */
 @EnabledIfEnvironmentVariable(named = "AZURE_AI_SEARCH_API_KEY", matches = ".+")
 @EnabledIfEnvironmentVariable(named = "AZURE_AI_SEARCH_ENDPOINT", matches = ".+")
@@ -68,7 +69,8 @@ public static String getText(String uri) {
 		.withConfiguration(AutoConfigurations.of(AzureVectorStoreAutoConfiguration.class))
 		.withUserConfiguration(Config.class)
 		.withPropertyValues("spring.ai.vectorstore.azure.apiKey=" + System.getenv("AZURE_AI_SEARCH_API_KEY"),
-				"spring.ai.vectorstore.azure.url=" + System.getenv("AZURE_AI_SEARCH_ENDPOINT"));
+				"spring.ai.vectorstore.azure.url=" + System.getenv("AZURE_AI_SEARCH_ENDPOINT"))
+		.withPropertyValues("spring.ai.vectorstore.azure.initialize-schema=true");
 
 	@BeforeAll
 	public static void beforeAll() {
@@ -81,8 +83,8 @@ public static void beforeAll() {
 	public void addAndSearchTest() {
 
 		contextRunner
-			.withPropertyValues("spring.ai.vectorstore.azure.indexName=my_test_index",
-					"spring.ai.vectorstore.azure.defaultTopK=6",
+			.withPropertyValues("spring.ai.vectorstore.azure.initializeSchema=true",
+					"spring.ai.vectorstore.azure.indexName=my_test_index", "spring.ai.vectorstore.azure.defaultTopK=6",
 					"spring.ai.vectorstore.azure.defaultSimilarityThreshold=0.75")
 			.run(context -> {
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStoreAutoConfigurationIT.java

@@ -59,6 +59,7 @@ class CassandraVectorStoreAutoConfigurationIT {
 		.withConfiguration(
 				AutoConfigurations.of(CassandraVectorStoreAutoConfiguration.class, CassandraAutoConfiguration.class))
 		.withUserConfiguration(Config.class)
+		.withPropertyValues("spring.ai.vectorstore.cassandra.initialize-schema=true")
 		.withPropertyValues("spring.ai.vectorstore.cassandra.keyspace=test_autoconfigure")
 		.withPropertyValues("spring.ai.vectorstore.cassandra.contentColumnName=doc_chunk");
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStorePropertiesTests.java

@@ -35,7 +35,7 @@ void defaultValues() {
 		assertThat(props.getContentColumnName()).isEqualTo(CassandraVectorStoreConfig.DEFAULT_CONTENT_COLUMN_NAME);
 		assertThat(props.getEmbeddingColumnName()).isEqualTo(CassandraVectorStoreConfig.DEFAULT_EMBEDDING_COLUMN_NAME);
 		assertThat(props.getIndexName()).isNull();
-		assertThat(props.getDisallowSchemaCreation()).isFalse();
+		assertThat(props.getDisallowSchemaCreation()).isTrue();
 		assertThat(props.getFixedThreadPoolExecutorSize())
 			.isEqualTo(CassandraVectorStoreConfig.DEFAULT_ADD_CONCURRENCY);
 	}