启航电商ERP系统正在重构AI原生ERP系统
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启航老齐
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> **启航电商ERP系统3.0版本在原版本基础上新增自动任务拉取订单、订单自动导入订单库等重大升级，进一步提升了开箱即用的特性。**
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> **启航电商ERP系统正在重构AI原生ERP系统。**
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## 一、系统介绍
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**启航电商ERP系统正在重构AI原生ERP系统。**
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#### 项目定位
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启航电商ERP系统是一个驱动电商企业数字化转型的电商业务中台系统底座。
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@ -142,7 +142,18 @@
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<!-- <scope>provided</scope>-->
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<!-- </dependency>-->
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<!-- LangChain4J 依赖 -->
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j</artifactId>
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<version>1.11.0</version>
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</dependency>
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<!-- Ollama 集成 -->
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-ollama</artifactId>
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<version>1.11.0</version>
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</dependency>
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</dependencies>
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<build>
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@ -153,4 +164,4 @@
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</plugin>
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</plugins>
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</build>
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</project>
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</project>
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@ -64,13 +64,13 @@ public class SseController {
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}
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@GetMapping("/send")
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public String sendMessage(@RequestParam String clientId, @RequestParam String message) {
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public String sendMessage(@RequestParam String clientId, @RequestParam String message, @RequestParam(required = false, defaultValue = "llama3") String model) {
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log.info("=============来新消息了！");
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SseEmitter emitter = emitters.get(clientId);
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if (emitter != null) {
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try {
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// 使用AiService处理消息
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String response = aiService.processMessage(message);
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// 使用AiService处理消息，传递模型参数
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String response = aiService.processMessage(message, model);
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emitter.send(SseEmitter.event()
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.name("message")
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@ -1,67 +1,45 @@
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package cn.qihangerp.erp.serviceImpl;
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import cn.qihangerp.common.ResultVo;
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import com.alibaba.fastjson2.JSONObject;
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import dev.langchain4j.model.ollama.OllamaChatModel;
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import org.springframework.stereotype.Service;
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import org.springframework.util.StringUtils;
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import java.io.IOException;
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import java.net.URI;
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import java.net.http.HttpClient;
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import java.net.http.HttpRequest;
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import java.net.http.HttpResponse;
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import java.time.Duration;
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/**
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* AI服务类，直接调用Ollama API处理聊天内容
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* AI服务类，使用LangChain4J调用Ollama模型处理聊天内容
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*/
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@Service
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public class AiService {
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private final HttpClient httpClient;
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private final String ollamaUrl;
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public AiService() {
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this.httpClient = HttpClient.newHttpClient();
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this.ollamaUrl = "http://localhost:11434/api/generate";
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/**
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* 处理聊天消息
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* @param message 用户消息
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* @param model 模型名称
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* @return AI回复
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*/
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public String processMessage(String message, String model) {
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try {
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// 根据模型名称创建对应的ChatModel
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OllamaChatModel modelInstance = OllamaChatModel.builder()
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.baseUrl("http://localhost:11434") // Ollama默认端口
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.modelName(model) // 使用指定的模型
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.temperature(0.7)
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.timeout(Duration.ofSeconds(300)) // 超时时间设置为300秒（5分钟）
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.build();
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// 调用Ollama模型获取回复
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return modelInstance.chat(message);
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} catch (Exception e) {
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e.printStackTrace();
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return "错误: " + e.getMessage();
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}
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}
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/**
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* 处理聊天消息
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* 处理聊天消息（使用默认模型）
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* @param message 用户消息
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* @return AI回复
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*/
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public String processMessage(String message) {
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try {
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// 构建请求体
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JSONObject requestBody = new JSONObject();
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requestBody.put("model", "llama3");
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requestBody.put("prompt", message);
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requestBody.put("stream", false);
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requestBody.put("temperature", 0.7);
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// 创建HTTP请求
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HttpRequest request = HttpRequest.newBuilder()
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.uri(URI.create(ollamaUrl))
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.header("Content-Type", "application/json")
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.POST(HttpRequest.BodyPublishers.ofString(requestBody.toJSONString()))
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.build();
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// 发送请求并获取响应
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HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
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// 解析响应
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JSONObject responseBody = JSONObject.parseObject(response.body());
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// 检查是否有错误
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if (responseBody.containsKey("error")) {
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String errorMessage = responseBody.getString("error");
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return "错误: " + errorMessage;
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}
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return responseBody.getString("response");
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} catch (IOException | InterruptedException e) {
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e.printStackTrace();
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return "抱歉，我暂时无法处理您的请求，请稍后重试。";
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}
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return processMessage(message, "llama3");
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}
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}
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@ -8,6 +8,13 @@
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<span class="title">工作助手</span>
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</div>
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<div class="header-right">
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<el-select v-model="selectedModel" size="mini" style="width: 120px; margin-right: 10px;">
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<el-option label="qwen3.5:2b" value="qwen3.5:2b"></el-option>
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<el-option label="Llama 3" value="llama3"></el-option>
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<el-option label="Gemini" value="gemini"></el-option>
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<el-option label="Claude" value="claude"></el-option>
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<el-option label="Gemma" value="gemma"></el-option>
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</el-select>
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<el-tag type="success" size="mini">在线</el-tag>
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</div>
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</div>
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@ -166,7 +173,8 @@ export default {
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sse: null,
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clientId: '',
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isSseConnected: false,
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isLoading: false
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isLoading: false,
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selectedModel: 'qwen3.5:2b'
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}
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},
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mounted() {
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@ -259,13 +267,21 @@ export default {
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// 通过SSE发送消息到后端
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if (this.isSseConnected) {
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// 使用AbortController实现超时
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const controller = new AbortController();
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const timeoutId = setTimeout(() => controller.abort(), 300000); // 300秒超时
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// 使用fetch发送消息
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fetch(`${process.env.VUE_APP_BASE_API}/api/ai-agent/sse/send?clientId=${this.clientId}&message=${encodeURIComponent(this.inputMessage)}&token=${token}`)
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fetch(`${process.env.VUE_APP_BASE_API}/api/ai-agent/sse/send?clientId=${this.clientId}&message=${encodeURIComponent(this.inputMessage)}&model=${this.selectedModel}&token=${token}`, {
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signal: controller.signal
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})
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.then(response => response.text())
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.then(data => {
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clearTimeout(timeoutId);
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console.log('消息发送结果:', data);
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})
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.catch(error => {
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clearTimeout(timeoutId);
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console.error('消息发送失败:', error);
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// 发送失败时使用模拟回复
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this.generateReply(this.inputMessage);
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