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随着人工智能技术的快速演进，DeepSeek 作为国内领先的大模型研发团队，其开源的 R1 系列模型凭借 "低成本、高性能" 的特性，在数学推理、代码生成等领域展现出与国际顶尖模型相媲美的能力。与此同时，Spring AI 作为 Spring 生态体系中专门针对 AI 工程化的框架，通过模块化设计和多模型适配能力，为 Java 开发者提供了便捷的 AI 集成方案。二者的结合，为企业级智能应用开发带来了新的技术路径。

关于如何在本地搭建deepSeek，可参考文献：基于DeepSeek R1 微调自己的大模型&Ollama本地部署_如何使用魔搭微调deepseek,并将大模型部署在本地-CSDN博客

SpringAi工程搭建

在idea中创建一个普通的Maven项目

添加项目依赖：

<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 http://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>3.2.4</version><relativePath/> <!-- lookup parent from repository --></parent><artifactId>springAi</artifactId><version>1.0.0</version><packaging>jar</packaging><properties><maven.compiler.source>22</maven.compiler.source><maven.compiler.target>22</maven.compiler.target><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><spring-ai.version>1.0.0-M5</spring-ai.version></properties><dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><!--spring ai的starter依赖，启动依赖--><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-ollama-spring-boot-starter</artifactId><version>${spring-ai.version}</version></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-devtools</artifactId><scope>runtime</scope><optional>true</optional></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><optional>true</optional></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope></dependency></dependencies><build><plugins><plugin><groupId>org.springframework.boot</groupId><artifactId>spring-boot-maven-plugin</artifactId><version>3.2.3</version><configuration><excludes><exclude><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId></exclude></excludes></configuration></plugin></plugins></build><!--配置本项目的仓库：因为maven中心仓库还没有更新spring ai的jar包--><repositories><repository><id>spring-milestones</id><url>https://repo.spring.io/milestone</url></repository></repositories></project>

这里注意，一定要指定milestones的仓库，因为在正式的仓库中还没有spring-ai的package。

 

属性文件application.properties配置

属性文件的配置，一定要根据引入jar合适使用。网上有很多

上述做法都是错误的，依赖的jar没有相关的视线类，或者类根本不存在。

翻看OllamaChatModel的源码，可以找到实现类：

@AutoConfiguration(after = RestClientAutoConfiguration.class)
@ConditionalOnClass(OllamaApi.class)
@EnableConfigurationProperties({ OllamaChatProperties.class, OllamaEmbeddingProperties.class,OllamaConnectionProperties.class, OllamaInitializationProperties.class })
@ImportAutoConfiguration(classes = { RestClientAutoConfiguration.class, WebClientAutoConfiguration.class })
public class OllamaAutoConfiguration {
...
}

找到属性配置类：

 配置属性文件application.properties

server.port=8080
spring.application.name=SpringAi# local ollama chat model
spring.ai.ollama.base-url=http://localhost:11434
spring.ai.ollama.chat.model=divine:latest# self define model parameters
spring.ai.ollama.parameters.temperature=0.7
spring.ai.ollama.parameters.max_tokens=2048
spring.ai.ollama.parameters.streaming=true

配置类：

package com.test.ai;import org.springframework.ai.autoconfigure.ollama.OllamaConnectionDetails;
import org.springframework.ai.ollama.api.OllamaApi;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.http.client.JdkClientHttpRequestFactory;
import org.springframework.web.client.RestClient;
import org.springframework.web.reactive.function.client.WebClient;import java.net.http.HttpClient;
import java.time.Duration;@Configuration
public class OllamaConfig {// 配置restClient超时时间@Bean@Qualifier("OllamaRestClientBuilder")public RestClient.Builder ollamaRestClientBuilder() {JdkClientHttpRequestFactory requestFactory = new JdkClientHttpRequestFactory(HttpClient.newHttpClient());requestFactory.setReadTimeout(Duration.ofMinutes(3));return RestClient.builder().requestFactory(requestFactory);}// 配置WebClient超时时间@Bean@Qualifier("OllamaWebClientBuilder")public WebClient.Builder ollamaWebClientBuilder() {return WebClient.builder().defaultHeader("Content-Type", "application/json");}@Beanpublic OllamaApi ollamaApi(OllamaConnectionDetails connectionDetails,@Qualifier("OllamaRestClientBuilder") RestClient.Builder restClientBuilder,@Qualifier("OllamaWebClientBuilder") WebClient.Builder ollamaWebClientBuilder) {return new OllamaApi(connectionDetails.getBaseUrl(), restClientBuilder, ollamaWebClientBuilder);}}

RestController类:

package com.test.ai;import jakarta.annotation.Resource;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;@RestController
public class ChatController {@Resourceprivate OllamaChatModel chatModel;@GetMapping("/chat")public String generate(@RequestParam String prompt) {return chatModel.call(prompt);}
}

启动配置类:

package com.test.ai;import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;@SpringBootApplication
public class SpringAiApplication {public static void main(String[] args) {SpringApplication.run(SpringAiApplication.class, args);}
}