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docs: TestContainers integration (#710)

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* docs: TestContainers integration

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Co-authored-by: Eddú Meléndez Gonzales <eddu.melendez@gmail.com>

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Co-authored-by: Mike Jang <michael.jang@qdrant.io>

* Update qdrant-landing/content/documentation/frameworks/spring-ai.md

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---------

Co-authored-by: Eddú Meléndez Gonzales <eddu.melendez@gmail.com>
Co-authored-by: Mike Jang <michael.jang@qdrant.io>
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2024-03-20 10:16:32 +05:30
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@@ -11,32 +11,31 @@ Qdrant is available as supported vector database for use within your Spring AI p
## Installation
To acquire Spring AI artifacts, declare the Spring Snapshot repository in your `pom.xml`.
You can find the Spring AI installation instructions [here](https://docs.spring.io/spring-ai/reference/getting-started.html).
```xml
<repository>
<id>spring-snapshots</id>
<name>Spring Snapshots</name>
<url>https://repo.spring.io/snapshot</url>
<releases>
<enabled>false</enabled>
</releases>
</repository>
```
Add the `spring-ai-qdrant` package.
Add the Qdrant boot starter package.
```xml
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qdrant</artifactId>
<version>VERSION</version>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qdrant-store-spring-boot-starter</artifactId>
</dependency>
```
## Usage
You can set up the Qdrant vector store with the `QdrantVectorStoreConfig` options.
Configure Qdrant with Spring Boot’s `application.properties`.
```
spring.ai.vectorstore.qdrant.host=<host of your qdrant instance>
spring.ai.vectorstore.qdrant.port=<the GRPC port of your qdrant instance>
spring.ai.vectorstore.qdrant.api-key=<your api key>
spring.ai.vectorstore.qdrant.collection-name=<The name of the collection to use in Qdrant>
```
Learn more about these options in the [configuration reference](https://docs.spring.io/spring-ai/reference/api/vectordbs/qdrant.html#qdrant-vectorstore-properties).
Or you can set up the Qdrant vector store with the `QdrantVectorStoreConfig` options.
```java
@Bean
@@ -51,8 +50,6 @@ public QdrantVectorStoreConfig qdrantVectorStoreConfig() {
}
```
<aside role="status">You'll need to <a href="/documentation/concepts/collections/#create-a-collection">create a collection</a> with the appropriate vector dimensions and configurations in advance.</aside>
Build the vector store using the config and any of the support [Spring AI embedding providers](https://docs.spring.io/spring-ai/reference/api/embeddings.html#available-implementations).
```java
@@ -64,6 +61,9 @@ public VectorStore vectorStore(QdrantVectorStoreConfig config, EmbeddingClient e
You can now use the `VectorStore` instance backed by Qdrant as a vector store in the Spring AI APIs.
## Further Reading
<aside role="status">If the collection is not <a href="/documentation/concepts/collections/#create-a-collection">created in advance</a>, <code>QdrantVectorStore</code> will attempt to create one using cosine similarity and the dimension of the configured <code>EmbeddingClient</code>.</aside>
- 📚 Spring AI [reference](https://docs.spring.io/spring-ai/reference/index.html)
## 📚 Further Reading
- Spring AI [Qdrant reference](https://docs.spring.io/spring-ai/reference/api/vectordbs/qdrant.html)
- Spring AI [API reference](https://docs.spring.io/spring-ai/reference/index.html)