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Spring-GPT智谱清言AI项目(附源码)

news 2025/8/16 16:51:30

一、项目介绍

本项目是Spring AI第三方调用整合智谱请言（官网是：https://open.bigmodel.cn）的案例，回答响应流式输出显示，这里使用的是免费模型，需要其他模型可以去 https://www.bigmodel.cn/pricing 切换。

在这里主要是完整地描述前后端开发和第三方调用的过程，SSE流式请求响应，MD稳定渲染显示等。

二、后端开发

后端使用的是Java，版本是JDK17，spring-boot版本是3.0.2，下面是pom.xml配置文件:

<?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><groupId>com</groupId><artifactId>spring-gpt-service</artifactId><version>0.0.9</version><name>spring-gpt-service</name><description>spring-gpt-service</description><!-- 版本信息 --><properties><java.version>17</java.version><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding><spring-boot.version>3.0.2</spring-boot.version></properties><!-- 依赖 --><dependencies><!-- web --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><!-- lombok --><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><optional>true</optional></dependency><!-- test --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope></dependency><!-- oapi --><dependency><groupId>cn.bigmodel.openapi</groupId><artifactId>oapi-java-sdk</artifactId><version>release-V4-2.3.0</version></dependency><!-- okhttp --><dependency><groupId>com.squareup.okhttp3</groupId><artifactId>okhttp</artifactId><version>4.9.3</version></dependency><!-- gson --><dependency><groupId>com.google.code.gson</groupId><artifactId>gson</artifactId><version>2.8.8</version></dependency><dependency><groupId>com.alibaba</groupId><artifactId>fastjson</artifactId><version>1.2.75</version></dependency><!-- flux --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-webflux</artifactId></dependency></dependencies><dependencyManagement><dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-dependencies</artifactId><version>${spring-boot.version}</version><type>pom</type><scope>import</scope></dependency></dependencies></dependencyManagement><build><plugins><!--打包jar插件配置--><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-compiler-plugin</artifactId><version>3.8.1</version><configuration><source>17</source><target>17</target><encoding>UTF-8</encoding></configuration></plugin><plugin><groupId>org.springframework.boot</groupId><artifactId>spring-boot-maven-plugin</artifactId><version>${spring-boot.version}</version><executions><execution><goals><goal>repackage</goal></goals></execution></executions></plugin></plugins></build></project>

由于Get请求参数直接在链接上会受到换行符\n或\r的限制，改用Post请求，使用json封装请求参数，下面是RequestData类：

import lombok.Data;@Data
public class RequestData {private String msg;
}

接口层accumulator.getDelta().getContent()这句代码是返回每次的具体结果

 /*** 通过ModelApiResponse.getFlowable()获取流式数据，最后通过blockingGet()获取最终结果* System.out.print(accumulator.getDelta().getContent());  // 这句代码是返回的具体结果* 因为直接SSE传text,受结束符\n影响，可以使用base64传输*/ 
@PostMapping(value = "/zp2", produces = MediaType.TEXT_EVENT_STREAM_VALUE)public Flux<String> testSseInvoke(@RequestBody RequestData requestData) {String msg = requestData.getMsg();List<ChatMessage> messages = new ArrayList<>();ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), msg);messages.add(chatMessage);String requestId = String.format(requestIdTemplate, System.currentTimeMillis());ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder().model(Constants.ModelChatGLM4).stream(Boolean.TRUE).messages(messages).requestId(requestId).build();Flux<String> flux = Flux.create(emitter -> {ModelApiResponse sseModelApiResp = client.invokeModelApi(chatCompletionRequest);if (sseModelApiResp.isSuccess()) {AtomicBoolean isFirst = new AtomicBoolean(true);mapStreamToAccumulator(sseModelApiResp.getFlowable()).doOnNext(accumulator -> {
//                            if (isFirst.getAndSet(false)) {
//                                String base64Msg = Base64.getEncoder().encodeToString("Response: ".getBytes(StandardCharsets.UTF_8));
//                                emitter.next(base64Msg);
//                            }if (accumulator.getDelta() != null && accumulator.getDelta().getTool_calls() != null) {try {String jsonString = mapper.writeValueAsString(accumulator.getDelta().getTool_calls());String tool = "tool_calls: " + jsonString;String base64Msg = Base64.getEncoder().encodeToString(tool.getBytes(StandardCharsets.UTF_8));emitter.next(base64Msg);} catch (Exception e) {String err = "Error converting tool_calls to JSON: " + e.getMessage();String base64Msg = Base64.getEncoder().encodeToString(err.getBytes(StandardCharsets.UTF_8));emitter.next(base64Msg);}}if (accumulator.getDelta() != null && accumulator.getDelta().getContent() != null) {String content = accumulator.getDelta().getContent();String base64Msg = Base64.getEncoder().encodeToString(content.getBytes(StandardCharsets.UTF_8));// 具体结果// System.out.print(content);emitter.next(base64Msg);}}).doOnComplete(() -> {emitter.next("\n");emitter.complete();}).subscribe();} else {emitter.next("Error: " + sseModelApiResp.getError() + "\n");emitter.complete();}});return flux;}

三、前端实现

前端使用Vue3，具体其他库详见项目的package.json文件

pnpm create vue@latest

其中使用md-editor-v3来做MD文档格式显示

 pnpm add md-editor-v3

下面是在组件中的具体使用：

<script lang="ts" setup>
import { MdPreview } from 'md-editor-v3';
import 'md-editor-v3/lib/preview.css';
</script><LayoutContent class="content"><!-- 聊天列表 --><ul class="chat-list" ref="messageListRef"><li class="chat-item" :class="`chat-item--${msg.role}`" v-for="msg in chatMessages"><MdPreview style="padding: 0; background-color: transparent;" type="String" :model-value="msg.content"/></li><li class="chat-item chat-item--system" :class="{ hidden: !isLoading }"><MdPreview :model-value="messagePlaceholder"/><Spin/></li></ul>
</LayoutContent>