随着AI的发展，我们的编程也发生了改变，那么AI给我们带来了哪些改变和提升呢？本文就Spring AI框架引入大模型来看一下基于SpringAI框架下的大模型开发。
一、大模型部署
首先，我们看一下国内的大模型的部署，这里使用的是阿里云百炼：
Ollama下载ollama并安装： Ollama
运行：
此时，一个Deepseek的本地大模型就部署完成，我们测试一下：
二、大模型调用
使用Postmain调用：
三、SpringAI
3.1 对话机器人
3.1.1创建spring boot项目，并导入以下依赖：
<dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-ollama-spring-boot-starter</artifactId></dependency><dependency><groupId>com.mysql</groupId><artifactId>mysql-connector-j</artifactId><scope>runtime</scope></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><version>1.18.22</version></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope></dependency>
</dependencies>注意：上面的lombok推荐使用手动配置，不要使用spring boot创建时自带的（有问题）
3.1.2 配置文件
spring:application:name: ollama-aiai:ollama:
# base-url: http://localhost:11434chat:model: deepseek-r1:1.5b3.1.3 配置类
package com.song.ollama.config;import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;/*** @author TonySong* @date 2025/4/11 0011* @time 17:32*/
@Configuration
public class CommonConfig {@Beanpublic ChatClient chatClient(OllamaChatModel ollamaChatModel) {return ChatClient.builder(ollamaChatModel).build();}
}3.1.4 控制器
package com.song.ollama.controller;import lombok.RequiredArgsConstructor;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;/*** @author TonySong* @date 2025/4/11 0011* @time 17:39*/
@RestController
@RequestMapping("/ai")
@RequiredArgsConstructor//启用带参构造完成创建
public class ChatController {private final ChatClient chatClient;// public ChatController(ChatClient chatClient) {
// this.chatClient = chatClient;
// }@RequestMapping("/chat") public String chat(@RequestParam(value = "message",defaultValue = "你是谁") String message) {return chatClient.prompt().user(message).call().content();}
}测试并检查输出结果:
以上的输出需要等待一会儿（阻塞式），修改代码为非阻塞（Stram）调用：
@RequestMapping("/chat")
public Flux<String> chat(@RequestParam(value = "message",defaultValue = "你是谁") String message) {return chatClient.prompt().user(message).stream().content();
}
我们可以看到输出结果是乱码，修改代码：
@RequestMapping(value = "/chat",produces = "text/html;charset=utf-8")
public Flux<String> chat(@RequestParam(value = "message",defaultValue = "你是谁") String message) {return chatClient.prompt().user(message).stream().content();
}3.1.5 会话日志
修改配置类：
@Configuration
public class CommonConfig {@Beanpublic ChatClient chatClient(OllamaChatModel ollamaChatModel) {return ChatClient.builder(ollamaChatModel).defaultAdvisors(new SimpleLoggerAdvisor()) //新增简单日志.build();}
}修改配置文件，新增日志相关：
logging:level:org.springframework.ai.chat.client.advisor: debugcom.song.ollama: debug此时，我们看控制台输出：
3.1.6 会话记忆
在配置类中，新增如下代码：
@Bean
public ChatMemory chatMemory() {return new InMemoryChatMemory();
}@Bean
public ChatClient chatClient(OllamaChatModel ollamaChatModel,ChatMemory chatMemory) {return ChatClient.builder(ollamaChatModel).defaultAdvisors(new SimpleLoggerAdvisor(),new MessageChatMemoryAdvisor(chatMemory)).build();
}3.1.7 会话历史
新增接口：
public interface ChatHistoryRepository {/*** 保存会话记录* @param type* @param charId*/void save(String type,String charId);/*** 获取会话记录* @param type* @return*/List<String> getChatIds(String type);
}接口实现：
package com.song.ollama.repository;import org.springframework.stereotype.Component;import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;/*** @author TonySong* @date 2025/4/12 0012* @time 10:35*/
@Component
public class InMemoryChatRepository implements ChatHistoryRepository{private final Map<String,List<String>> chatHistory= new HashMap<>();@Overridepublic void save(String type, String charId) {
// if(!chatHistory.containsKey(type)){
// chatHistory.put(charId,new ArrayList<>());
// }
// List<String> charIds = chatHistory.get(type);List<String> charIds = chatHistory.computeIfAbsent(type, k -> new ArrayList<>());if(charIds.contains(charId)){return;}charIds.add(charId);}@Overridepublic List<String> getChatIds(String type) {
// List<String> list = chatHistory.get(type);
// return list==null? List.of():list;return chatHistory.getOrDefault(type,List.of());}
}修改会话实现：
package com.song.ollama.controller;import com.song.ollama.repository.ChatHistoryRepository;
import lombok.RequiredArgsConstructor;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;/*** @author TonySong* @date 2025/4/11 0011* @time 17:39*/
@RestController
@RequestMapping("/ai")
@RequiredArgsConstructor//启用带参构造完成创建
public class ChatController {private final ChatClient chatClient;private final ChatHistoryRepository chatHistoryRepository;@RequestMapping(value = "/chat",produces = "text/html;charset=utf-8")public Flux<String> chat(@RequestParam(value = "message",defaultValue = "你是谁") String message) {//1、保存会话chatHistoryRepository.save("chat",message);//2、获取会话return chatClient.prompt().user(message).stream().content();}
}