当前位置：首页 > news >正文

Springboot整合ollama运行本地AI大模型

news 来源：原创 2025/6/18 15:36:38

1.安装启动ollama

ollama部署开源大模型-CSDN博客

我的这篇文章已经详细阐述了，这里就不介绍了

2.创建SpringBoot项目

照着我图片上的来即可 JKD要》=17 因为我们要使用Springboot3.x.x只有JDK17及以上才支持

1.导入pom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>3.4.6</version><relativePath/> <!-- lookup parent from repository --></parent><groupId>org.example</groupId><artifactId>springboot-ai</artifactId><version>0.0.1-SNAPSHOT</version><name>springboot-ai</name><description>springboot-ai</description><properties><java.version>17</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-test</artifactId><scope>test</scope></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><!-- Spring Boot DevTools (Optional for auto-reloading during development) --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-devtools</artifactId><scope>runtime</scope></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><version>1.18.34</version></dependency><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-ollama</artifactId><version>1.0.0</version></dependency></dependencies><build><plugins><plugin><groupId>org.springframework.boot</groupId><artifactId>spring-boot-maven-plugin</artifactId></plugin></plugins></build></project>

2.在resources中创建application.yml文件并且编辑

把默认的application.properties文件删除，然后下面是yml的配置内容

spring:ai:ollama:base-url: http://localhost:11434chat:option:model: gemma3:4btemperature: 0.7  # 生成随机性（0~1，越大越随机）max-tokens: 512   # 最大生成 Token 数
server:port: 8080

3.创建AIconfig配置文件

package com.example.demo.config;import io.micrometer.observation.ObservationRegistry;
import org.springframework.ai.model.tool.ToolCallingManager;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.api.OllamaApi;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.ai.ollama.management.ModelManagementOptions;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;@Configuration
public class AiConfig {@Beanpublic OllamaChatModel ollamaChatModel() {// 1. 创建 OllamaApi（与 Ollama 服务通信）OllamaApi ollamaApi = OllamaApi.builder().baseUrl("http://localhost:11434").build();// 2. 配置默认参数OllamaOptions defaultOptions = OllamaOptions.builder().model("gemma3:4b").temperature(0.7).build();// 3. 构建 ToolCallingManager（支持工具调用）ToolCallingManager toolCallingManager = ToolCallingManager.builder().build();// 4. 构建 ObservationRegistry（监控）ObservationRegistry observationRegistry = ObservationRegistry.NOOP;// 5. 模型管理配置ModelManagementOptions modelManagementOptions = ModelManagementOptions.defaults();// 6. 最终创建 OllamaChatModelreturn new OllamaChatModel(ollamaApi,defaultOptions,toolCallingManager,observationRegistry,modelManagementOptions);}
}

4.创建AIController

package com.example.demo.controller;import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;@RestController
public class AiController {// 注入 OllamaChatModel，用于调用 Ollama 模型@Autowiredprivate OllamaChatModel ollamaChatModel;/*** 简单文本对话接口（直接传字符串消息）* @param msg 用户输入的消息* @return 模型返回的文本内容*/@GetMapping("/ollama/chat/msg")public String ollamaChat(@RequestParam String msg) {return ollamaChatModel.call(msg);}/*** 基于 Prompt 对象的对话接口* @param msg 用户输入的消息* @return 模型返回的结果（Object 类型，通常是包含详细信息的响应）*/@GetMapping("/ollama/chat/prompt")public Object ollamaChatV2(@RequestParam String msg) {Prompt prompt = new Prompt(msg);return ollamaChatModel.call(prompt);}}

5. 编辑启动类（可以省略）

package dbcs.springai01;import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;@SpringBootApplication
public class SpringAi01Application {public static void main(String[] args) {SpringApplication.run(SpringAi01Application.class, args);System.out.println("http://localhost:8080/ollama/chat/msg?msg=你好");}}