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 #907
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Soby Chacko
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Mark Pollack
Mark Pollack
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@@ -78,6 +78,24 @@ Add these dependencies to your project:
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TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.
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== Configuration Properties
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You can use the following properties in your Spring Boot configuration to customize the Apache Cassandra vector store.
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|===
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|Property|Default value
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|`spring.ai.vectorstore.cassandra.keyspace`|springframework
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|`spring.ai.vectorstore.cassandra.table`|ai_vector_store
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|`spring.ai.vectorstore.cassandra.initialze-schema`|false
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|`spring.ai.vectorstore.cassandra.index-name`|
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|`spring.ai.vectorstore.cassandra.content-column-name`|content
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|`spring.ai.vectorstore.cassandra.embedding-column-name`|embedding
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|`spring.ai.vectorstore.cassandra.return-embeddings`|false
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|`spring.ai.vectorstore.cassandra.fixed-thread-pool-executor-size`|16
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|===
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== Usage
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@@ -12,7 +12,7 @@ link:https://azure.microsoft.com/en-us/products/ai-services/ai-search/[Azure AI
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== Configuration
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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.
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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.
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NOTE: this is a breaking change! In earlier versions of Spring AI, this schema initialization happened by default.
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@@ -88,6 +88,24 @@ Add these dependencies to your project:
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TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.
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== Configuration Properties
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You can use the following properties in your Spring Boot configuration to customize the Azure vector store.
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|===
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|Property|Default value
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|`spring.ai.vectorstore.azure.url`|
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|`spring.ai.vectorstore.azure.api-key`|
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|`spring.ai.vectorstore.azure.initialze-schema`|false
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|`spring.ai.vectorstore.azure.index-name`|spring_ai_azure_vector_store
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|`spring.ai.vectorstore.azure.default-top-k`|4
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|`spring.ai.vectorstore.azure.default-similarity-threshold`|0.0
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|`spring.ai.vectorstore.azure.embedding-property`|embedding
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|`spring.ai.vectorstore.azure.index-name`|spring-ai-document-index
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|===
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== Sample Code
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To configure an Azure `SearchIndexClient` in your application, you can use the following code:
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@@ -66,7 +66,6 @@ A simple configuration can either be provided via Spring Boot's _application.pro
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[source,properties]
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----
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# Chroma Vector Store connection properties
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spring.ai.vectorstore.chroma.client.initialize-schema=<true or false>
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spring.ai.vectorstore.chroma.client.host=<your Chroma instance host>
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spring.ai.vectorstore.chroma.client.port=<your Chroma instance port>
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spring.ai.vectorstore.chroma.client.key-token=<your access token (if configure)>
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@@ -74,6 +73,7 @@ spring.ai.vectorstore.chroma.client.username=<your username (if configure)>
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spring.ai.vectorstore.chroma.client.password=<your password (if configure)>
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# Chroma Vector Store collection properties
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spring.ai.vectorstore.chroma.initialize-schema=<true or false>
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spring.ai.vectorstore.chroma.collection-name=<your collection name>
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# Chroma Vector Store configuration properties
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@@ -117,6 +117,7 @@ You can use the following properties in your Spring Boot configuration to custom
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|`spring.ai.vectorstore.chroma.client.username`| Access username (if configured) | -
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|`spring.ai.vectorstore.chroma.client.password`| Access password (if configured) | -
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|`spring.ai.vectorstore.chroma.collection-name`| Collection name | `SpringAiCollection`
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|`spring.ai.vectorstore.chroma.initialize-schema`| Whether to initialize the required schema | `false`
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|===
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[NOTE]
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@@ -140,6 +140,7 @@ Properties starting with the `spring.ai.vectorstore.elasticsearch.*` prefix are
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|===
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|Property | Description | Default Value
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|`spring.ai.vectorstore.elasticsearch.initialize-schema`| Whether to initialize the required schema | `false`
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|`spring.ai.vectorstore.elasticsearch.index-name` | The name of the index to store the vectors. | spring-ai-document-index
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|`spring.ai.vectorstore.elasticsearch.dimensions` | The number of dimensions in the vector. | 1536
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|`spring.ai.vectorstore.elasticsearch.similarity` | The similarity function to use. | `cosine`
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@@ -44,6 +44,7 @@ You can use the following properties in your Spring Boot configuration to furthe
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|`spring.ai.vectorstore.gemfire.host`|localhost
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|`spring.ai.vectorstore.gemfire.port`|8080
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|`spring.ai.vectorstore.gemfire.initialize-schema`| `false`
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|`spring.ai.vectorstore.gemfire.index-name`|spring-ai-gemfire-store
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|`spring.ai.vectorstore.gemfire.beam-width`|100
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|`spring.ai.vectorstore.gemfire.max-connections`|16
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@@ -120,11 +120,11 @@ You can use the following properties in your Spring Boot configuration to custom
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|===
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|Property| Description | Default value
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|`spring.opensearch.uris`| URIs of the OpenSearch cluster endpoints. | -
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|`spring.opensearch.username`| Username for accessing the OpenSearch cluster. | -
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|`spring.opensearch.password`| Password for the specified username. | -
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|`spring.opensearch.indexName`| Name of the default index to be used within the OpenSearch cluster. | `spring-ai-document-index`
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|`spring.opensearch.mappingJson`| JSON string defining the mapping for the index; specifies how documents and their
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|`spring.ai.vectorstore.opensearch.uris`| URIs of the OpenSearch cluster endpoints. | -
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|`spring.ai.vectorstore.opensearch.username`| Username for accessing the OpenSearch cluster. | -
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|`spring.ai.vectorstore.opensearch.password`| Password for the specified username. | -
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|`spring.ai.vectorstore.opensearch.indexName`| Name of the default index to be used within the OpenSearch cluster. | `spring-ai-document-index`
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|`spring.ai.vectorstore.opensearch.mappingJson`| JSON string defining the mapping for the index; specifies how documents and their
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fields are stored and indexed. |
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{
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"properties":{
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@@ -108,7 +108,7 @@ You can use the following properties in your Spring Boot configuration to custom
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|`spring.ai.vectorstore.redis.uri`| Server connection URI | `redis://localhost:6379`
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|`spring.ai.vectorstore.redis.index`| Index name | `default-index`
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|`spring.ai.vectorstore.redis.initialize-schema`| whether to initialize the required schema | `false`
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|`spring.ai.vectorstore.redis.initialize-schema`| Whether to initialize the required schema | `false`
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|`spring.ai.vectorstore.redis.prefix`| Prefix | `default:`
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|===
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@@ -103,8 +103,9 @@ You can use the following properties in your Spring Boot configuration to custom
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|`spring.ai.vectorstore.typesense.client.host`| Hostname | `localhost`
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|`spring.ai.vectorstore.typesense.client.port`| Port | `8108`
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|`spring.ai.vectorstore.typesense.client.apiKey`| ApiKey | `xyz`
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|`spring.ai.vectorstore.typesense.collectionName`| Collection Name | `vector_store`
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|`spring.ai.vectorstore.typesense.embeddingDimension`| Embedding Dimension | `1536`
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|`spring.ai.vectorstore.typesense.initialize-schema`| Whether to initialize the required schema | `false`
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|`spring.ai.vectorstore.typesense.collection-name`| Collection Name | `vector_store`
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|`spring.ai.vectorstore.typesense.embedding-dimension`| Embedding Dimension | `1536`
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|===
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@@ -5,6 +5,16 @@
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* 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.
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* The default value of the `initialize-schema` property on vector stores capable of initializing a schema is now set to `false`.
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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.
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Not all vector stores support this property.
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See the corresponding vector store documentation for more details.
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The following are the vector stores that currently don't support the `initialize-schema` property.
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1. Hana
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2. Pinecone
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3. Weaviate
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== Upgrading to 1.0.0.M1
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On our march to release 1.0.0 M1 we have made several breaking changes. Apologies, it is for the best!
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