SpringAI 集成本地Ollama大模型
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")
;
}
@Bean
public 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 {
@Resource
private 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);
}
}