AI大模型实用(一)SpringAI接入deepseek示例
一、SpringAI接入deepseek所需环境
- JDK17+(JDK8无法支持)
- SpringBoot 3.x
- maven 3.6+
官网地址
https://docs.spring.io/spring-ai/reference/api/chatclient.html
SpringAI接入deepseek方式有很多。 下面演示SpringAI原生方式接入deepseek.
二、pom依赖
1、 SpringBoot修改版本
<parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>3.4.5</version> <relativePath/> <!-- lookup parent from repository --> </parent>
2、SpringAI通过deepseek提供的openapi接入deepseek
<!-- springAI提供的openapi--> <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-openai-spring-boot-starter</artifactId> <version>1.0.0-M6</version> </dependency>
三、相关配置
spring.ai.openai.api-key=xxx(修改成自己的密匙) spring.ai.openai.base-url=https://api.deepseek.com spring.ai.openai.chat.options.model=deepseek-chat
四、代码
import org.springframework.ai.chat.client.ChatClient; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; @Configuration public class SpringAIConfig { @Bean public ChatClient chatClient(ChatClient.Builder builder) { return builder.defaultSystem("你是一名资深开发工程师，你的名称叫siri").build(); } }示例1：定义controller
package com.ai.controller; import org.springframework.ai.chat.client.ChatClient; import org.springframework.ai.model.Model; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.CrossOrigin; import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RestController; @RestController @RequestMapping(value = "/ChatController") public class ChatController { private final ChatClient chatClient; ChatController(ChatClient.Builder chatClientBuilder) { this.chatClient = chatClientBuilder.build(); } @GetMapping("/ai") String generation(String question) { return this.chatClient.prompt() .user(question) .call() .content(); } } 运行结果：
访问：
运行结果：http://127.0.0.1:8886/ChatController/chattest?question=%E4%BD%A0%E6%98%AF%E8%B0%81
示例2：定义controller（流式输出）
package com.ai.controller; import org.springframework.ai.chat.client.ChatClient; import org.springframework.ai.chat.messages.Message; import org.springframework.ai.chat.messages.UserMessage; import org.springframework.ai.chat.model.ChatModel; import org.springframework.ai.chat.model.Generation; import org.springframework.ai.chat.prompt.Prompt; import org.springframework.ai.chat.prompt.SystemPromptTemplate; import org.springframework.beans.factory.annotation.Value; import org.springframework.http.MediaType; import org.springframework.web.bind.annotation.RestController; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.*; import reactor.core.publisher.Flux; import java.util.List; import java.util.Map; import java.util.stream.Collectors; @RestController @RequestMapping(value = "/SpringAIController") public class SpringAIController { @Autowired private ChatClient chatClient; // private final ChatClient chatClient; //ChatClient底层是使用ChatModel作为属性的，在初始化ChatClient的时候可以指定ChatModel @Autowired private ChatModel chatModel; public SpringAIController(ChatClient.Builder chatClientBuilder) { this.chatClient = chatClientBuilder.defaultSystem("你是一个AI智能应用").build(); } @GetMapping("/chat") public String chat(@RequestParam(value = "msg",defaultValue = "介绍一下杜甫") String message) { //prompt:提示词 return this.chatClient.prompt() //用户输入的信息 .user(message) //请求大模型 .call() //返回文本 .content(); } //流式响应 @GetMapping(value = "/chatstream",produces="text/html;charset=UTF-8") public Flux<String> chatStream(@RequestParam(value = "message") String message) { return chatClient.prompt().user(message).stream().content(); } }访问：
注意： 不使用流式输出时，访问http://127.0.0.1:8886/SpringAIController/chat?question=%E4%BD%A0%E6%98%AF%E8%B0%81
结果出现超时： TimeoutException: Total timeout 10000 ms elapsed
