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Improve the OpenSearch doc structure

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This commit is contained in:
Christian Tzolov
2024-10-25 12:56:14 +02:00
parent e9b70f4ea5
commit b6222d42e8
1 changed files with 55 additions and 28 deletions
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83
spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/opensearch.adoc
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@@ -17,6 +17,10 @@ embeddings stored by the `OpenSearchVectorStore`.
Add the OpenSearch Vector Store dependency to your project:
[tabs]
======
Maven::
+
[source,xml]
----
<dependency>
@@ -25,14 +29,15 @@ Add the OpenSearch Vector Store dependency to your project:
</dependency>
----
or to your Gradle `build.gradle` build file.
Gradle::
+
[source,groovy]
----
dependencies {
implementation 'org.springframework.ai:spring-ai-opensearch-store'
}
----
======
TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.
@@ -66,9 +71,15 @@ TIP: Check the list of xref:#_configuration_properties[configuration parameters]
== Auto-configuration
Spring AI provides Spring Boot auto-configuration for the OpenSearch Vector Store.
To enable it, add the following dependency to your project's Maven `pom.xml` file:
=== Self-Managed OpenSearch
Spring AI provides Spring Boot auto-configuration for the OpenSearch Vector Store.
To enable it, add the following dependency to your project's Maven `pom.xml` or Gradle `build.gradle` build files:
[tabs]
======
Maven::
+
[source,xml]
----
<dependency>
@@ -77,14 +88,45 @@ To enable it, add the following dependency to your project's Maven `pom.xml` fil
</dependency>
----
or to your Gradle `build.gradle` build file.
Gradle::
+
[source,groovy]
----
dependencies {
implementation 'org.springframework.ai:spring-ai-opensearch-store-spring-boot-starter'
}
----
======
Then use the `spring.ai.vectorstore.opensearch.*` properties to configure the connection to the self-managed OpenSearch instance.
=== Amazon OpenSearch Service
To enable Amazon OpenSearch Service., add the following dependency to your project's Maven `pom.xml` or Gradle `build.gradle` build files:
[tabs]
======
Maven::
+
[source,xml]
----
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-aws-opensearch-store-spring-boot-starter</artifactId>
</dependency>
----
Gradle::
+
[source,groovy]
----
dependencies {
implementation 'org.springframework.ai:spring-ai-aws-opensearch-store-spring-boot-starter'
}
----
======
Then use the `spring.ai.vectorstore.opensearch.aws.*` properties to configure the connection to the Amazon OpenSearch Service.
TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file.
@@ -154,32 +196,16 @@ In cases where the Spring Boot auto-configured OpenSearchClient with `Apache Htt
you want or need, you can still define your own bean.
Please read the link:https://opensearch.org/docs/latest/clients/java/[OpenSearch Java Client Documentation]
for more in-depth information about the configuration of Amazon OpenSearch Service.
To enable it, add the following dependency to your project's Maven `pom.xml` file:
[source,xml]
----
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-aws-opensearch-store-spring-boot-starter</artifactId>
</dependency>
----
or to your Gradle `build.gradle` build file.
[source,groovy]
----
dependencies {
implementation 'org.springframework.ai:spring-ai-aws-opensearch-store-spring-boot-starter'
}
----
== Metadata Filtering
You can leverage the generic, portable xref:api/vectordbs.adoc#metadata-filters[metadata filters] with OpenSearch as well.
For example, you can use either the text expression language:
[tabs]
======
SQL filter syntax::
+
[source,java]
----
vectorStore.similaritySearch(SearchRequest.defaults()
@@ -189,8 +215,8 @@ vectorStore.similaritySearch(SearchRequest.defaults()
.withFilterExpression("author in ['john', 'jill'] && 'article_type' == 'blog'"));
----
or programmatically using the `Filter.Expression` DSL:
`Filter.Expression` DSL::
+
[source,java]
----
FilterExpressionBuilder b = new FilterExpressionBuilder();
@@ -203,6 +229,7 @@ vectorStore.similaritySearch(SearchRequest.defaults()
b.in("john", "jill"),
b.eq("article_type", "blog")).build()));
----
======
NOTE: Those (portable) filter expressions get automatically converted into the proprietary OpenSearch link:https://opensearch.org/docs/latest/query-dsl/full-text/query-string/[Query string query].