Spring AI RAG示例

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项目配置说明

Maven依赖

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>3.4.5</version>
        <relativePath/> <!-- lookup parent from repository -->
    </parent>
    <groupId>com.tech</groupId>
    <artifactId>jackal-spring-ai</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>jackal-spring-ai</name>
    <description>Spring AI demo</description>
    <properties>
        <java.version>21</java.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.ai</groupId>
            <artifactId>spring-ai-starter-model-openai</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.ai</groupId>
            <artifactId>spring-ai-starter-vector-store-qdrant</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.ai</groupId>
            <artifactId>spring-ai-advisors-vector-store</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.ai</groupId>
            <artifactId>spring-ai-rag</artifactId>
        </dependency>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
    </dependencies>

    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>org.springframework.ai</groupId>
                <artifactId>spring-ai-bom</artifactId>
                <version>1.0.0-SNAPSHOT</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>

    <repositories>
        <repository>
            <id>spring-milestones</id>
            <name>Spring Milestones</name>
            <url>https://repo.spring.io/milestone</url>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </repository>
        <repository>
            <id>spring-snapshots</id>
            <name>Spring Snapshots</name>
            <url>https://repo.spring.io/snapshot</url>
            <releases>
                <enabled>false</enabled>
            </releases>
        </repository>
    </repositories>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <annotationProcessorPaths>
                        <path>
                            <groupId>org.projectlombok</groupId>
                            <artifactId>lombok</artifactId>
                        </path>
                    </annotationProcessorPaths>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
                <configuration>
                    <excludes>
                        <exclude>
                            <groupId>org.projectlombok</groupId>
                            <artifactId>lombok</artifactId>
                        </exclude>
                    </excludes>
                </configuration>
            </plugin>
        </plugins>
    </build>

</project>

应用配置

spring:
  application:
    name: jackal-spring-ai-openai
  ai:
    openai:
      api-key: ${DEEPSEEK_KEY}
      base-url: "https://api.deepseek.com"
      chat:
        options:
          model: deepseek-chat
    siliconflow:
      api-key: ${SILICOFLOW_KEY}
      endpoint: "https://api.siliconflow.cn"
      embeddingModel: "BAAI/bge-m3"
    vectorstore:
      qdrant:
        host: localhost
        port: 6334
        collection-name: rag
        use-tls: false
        initialize-schema: true
  • spring.ai.openai.api-key 必须配置，否则会报错，但该配置在项目中暂时无用。
  • DeepSeek大模型可以在 DeepSeek控制台 获取API-KEY。
  • Deepseek模型名可以在 DeepSeek官方文档 中获取。
  • 这里使用了硅基流动的嵌入模型，在 硅基流动控制台 获取API-KEY。
  • Qdrant此处使用Docker本地部署，部署细节参考Qdrant官方文档

核心代码实现

注入模型配置

@Configuration
public class ModelConfig {

    @Value("${spring.ai.siliconflow.api-key}")
    private String siliconflowApiKey;
    @Value("${spring.ai.siliconflow.endpoint}")
    private String siliconflowEndpoint;
    @Value("${spring.ai.siliconflow.embeddingModel}")
    private String siliconflowEmbeddingModel;

    @Primary
    @Bean(name = "siliconflowEmbeddingModel")
    public EmbeddingModel siliconflowEmbeddingModel() {
        OpenAiApi openAiApi = OpenAiApi.builder()
                .baseUrl(siliconflowEndpoint)
                .apiKey(siliconflowApiKey)
                .build();
        OpenAiEmbeddingOptions openAiEmbeddingOptions = OpenAiEmbeddingOptions.builder()
                .model(siliconflowEmbeddingModel)
                .build();
        return new OpenAiEmbeddingModel(openAiApi, MetadataMode.EMBED, openAiEmbeddingOptions);
    }
}

Service 层

@Service
public class ChatService {

    private final ChatClient chatClient;
    private final VectorStore vectorStore;

    public ChatService(ChatClient.Builder chatClientBuilder, VectorStore vectorStore) {
        this.chatClient = chatClientBuilder.build();
        this.vectorStore = vectorStore;
    }

    public String rag(String input) {
        Advisor retrievalAugmentationAdvisor = RetrievalAugmentationAdvisor.builder()
                .documentRetriever(VectorStoreDocumentRetriever.builder()
                        .similarityThreshold(0.50)
                        .vectorStore(vectorStore)
                        .build())
                .queryAugmenter(ContextualQueryAugmenter.builder()
                        .allowEmptyContext(true)
                        .build())
                .build();
        return chatClient.prompt()
                .advisors(retrievalAugmentationAdvisor)
                .user(input)
                .call()
                .content();
    }
}

@Service
public class RagService {

    private final VectorStore vectorStore;
    private final EmbeddingModel embeddingModel;

    public RagService(
            VectorStore vectorStore,
            @Qualifier("siliconflowEmbeddingModel") EmbeddingModel embeddingModel) {
        this.vectorStore = vectorStore;
        this.embeddingModel = embeddingModel;
    }

    public float[] embed(String input) {
        return embeddingModel.embed(input);
    }

    public void addVector(String input) {
        List<Document> documents = List.of(new Document(input));
        vectorStore.add(documents);
    }

    public List<Document> searchVector(String input) {
        SearchRequest request = SearchRequest.builder().query(input).topK(5).build();
        return vectorStore.similaritySearch(request);
    }
}

Controller 层

@RestController
@RequestMapping("/ai")
@RequiredArgsConstructor
public class SpringAiController {
    private final ChatService chatService;
    private final RagService ragService;

    @PostMapping("/rag/addVector")
    public void addVector(String input) {
        ragService.addVector(input);
    }

    @PostMapping("/rag/searchVector")
    public List<Document> searchVector(String input) {
        return ragService.searchVector(input);
    }

    @PostMapping("/chat/rag")
    public String rag(String input) {
        return chatService.rag(input);
    }
}
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