---
title: Spring AI
weight: 2200
---
# Spring AI
[Spring AI](https://docs.spring.io/spring-ai/reference/) is a Java framework that provides a [Spring-friendly](https://spring.io/) API and abstractions for developing AI applications.
Qdrant is available as supported vector database for use within your Spring AI projects.
## Installation
You can find the Spring AI installation instructions [here](https://docs.spring.io/spring-ai/reference/getting-started.html).
Add the Qdrant boot starter package.
```xml
org.springframework.aispring-ai-qdrant-store-spring-boot-starter
```
## Usage
Configure Qdrant with Spring Boot’s `application.properties`.
```
spring.ai.vectorstore.qdrant.host=
spring.ai.vectorstore.qdrant.port=
spring.ai.vectorstore.qdrant.api-key=
spring.ai.vectorstore.qdrant.collection-name=
```
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
public QdrantVectorStoreConfig qdrantVectorStoreConfig() {
return QdrantVectorStoreConfig.builder()
.withHost("")
.withPort()
.withCollectionName("")
.withApiKey("")
.build();
}
```
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
@Bean
public VectorStore vectorStore(QdrantVectorStoreConfig config, EmbeddingClient embeddingClient) {
return new QdrantVectorStore(config, embeddingClient);
}
```
You can now use the `VectorStore` instance backed by Qdrant as a vector store in the Spring AI APIs.
## 📚 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)