diff --git a/README.md b/README.md index 3cfc9466..219aded0 100644 --- a/README.md +++ b/README.md @@ -6,8 +6,11 @@ > **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。** +> **启航电商ERP系统正在重构AI原生ERP系统。** ## 一、系统介绍 +**启航电商ERP系统正在重构AI原生ERP系统。** + #### 项目定位 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。 diff --git a/api/ai-agent/pom.xml b/api/ai-agent/pom.xml index d4e9568d..68341d95 100644 --- a/api/ai-agent/pom.xml +++ b/api/ai-agent/pom.xml @@ -142,7 +142,18 @@ - + + + dev.langchain4j + langchain4j + 1.11.0 + + + + dev.langchain4j + langchain4j-ollama + 1.11.0 + @@ -153,4 +164,4 @@ - + \ No newline at end of file diff --git a/api/ai-agent/src/main/java/cn/qihangerp/erp/controller/SseController.java b/api/ai-agent/src/main/java/cn/qihangerp/erp/controller/SseController.java index 0da6114e..2afbfa3f 100644 --- a/api/ai-agent/src/main/java/cn/qihangerp/erp/controller/SseController.java +++ b/api/ai-agent/src/main/java/cn/qihangerp/erp/controller/SseController.java @@ -64,13 +64,13 @@ public class SseController { } @GetMapping("/send") - public String sendMessage(@RequestParam String clientId, @RequestParam String message) { + public String sendMessage(@RequestParam String clientId, @RequestParam String message, @RequestParam(required = false, defaultValue = "llama3") String model) { log.info("=============来新消息了！"); SseEmitter emitter = emitters.get(clientId); if (emitter != null) { try { - // 使用AiService处理消息 - String response = aiService.processMessage(message); + // 使用AiService处理消息，传递模型参数 + String response = aiService.processMessage(message, model); emitter.send(SseEmitter.event() .name("message") diff --git a/api/ai-agent/src/main/java/cn/qihangerp/erp/serviceImpl/AiService.java b/api/ai-agent/src/main/java/cn/qihangerp/erp/serviceImpl/AiService.java index af8998e4..165ecc9b 100644 --- a/api/ai-agent/src/main/java/cn/qihangerp/erp/serviceImpl/AiService.java +++ b/api/ai-agent/src/main/java/cn/qihangerp/erp/serviceImpl/AiService.java @@ -1,67 +1,45 @@ package cn.qihangerp.erp.serviceImpl; -import cn.qihangerp.common.ResultVo; -import com.alibaba.fastjson2.JSONObject; +import dev.langchain4j.model.ollama.OllamaChatModel; import org.springframework.stereotype.Service; -import org.springframework.util.StringUtils; - -import java.io.IOException; -import java.net.URI; -import java.net.http.HttpClient; -import java.net.http.HttpRequest; -import java.net.http.HttpResponse; +import java.time.Duration; /** - * AI服务类，直接调用Ollama API处理聊天内容 + * AI服务类，使用LangChain4J调用Ollama模型处理聊天内容 */ @Service public class AiService { - private final HttpClient httpClient; - private final String ollamaUrl; - - public AiService() { - this.httpClient = HttpClient.newHttpClient(); - this.ollamaUrl = "http://localhost:11434/api/generate"; + /** + * 处理聊天消息 + * @param message 用户消息 + * @param model 模型名称 + * @return AI回复 + */ + public String processMessage(String message, String model) { + try { + // 根据模型名称创建对应的ChatModel + OllamaChatModel modelInstance = OllamaChatModel.builder() + .baseUrl("http://localhost:11434") // Ollama默认端口 + .modelName(model) // 使用指定的模型 + .temperature(0.7) + .timeout(Duration.ofSeconds(300)) // 超时时间设置为300秒（5分钟） + .build(); + + // 调用Ollama模型获取回复 + return modelInstance.chat(message); + } catch (Exception e) { + e.printStackTrace(); + return "错误: " + e.getMessage(); + } } /** - * 处理聊天消息 + * 处理聊天消息（使用默认模型） * @param message 用户消息 * @return AI回复 */ public String processMessage(String message) { - try { - // 构建请求体 - JSONObject requestBody = new JSONObject(); - requestBody.put("model", "llama3"); - requestBody.put("prompt", message); - requestBody.put("stream", false); - requestBody.put("temperature", 0.7); - - // 创建HTTP请求 - HttpRequest request = HttpRequest.newBuilder() - .uri(URI.create(ollamaUrl)) - .header("Content-Type", "application/json") - .POST(HttpRequest.BodyPublishers.ofString(requestBody.toJSONString())) - .build(); - - // 发送请求并获取响应 - HttpResponse response = httpClient.send(request, HttpResponse.BodyHandlers.ofString()); - - // 解析响应 - JSONObject responseBody = JSONObject.parseObject(response.body()); - - // 检查是否有错误 - if (responseBody.containsKey("error")) { - String errorMessage = responseBody.getString("error"); - return "错误: " + errorMessage; - } - - return responseBody.getString("response"); - } catch (IOException | InterruptedException e) { - e.printStackTrace(); - return "抱歉，我暂时无法处理您的请求，请稍后重试。"; - } + return processMessage(message, "llama3"); } } diff --git a/docs/preview.png b/docs/preview.png index b046d2ed..456bb9a2 100644 Binary files a/docs/preview.png and b/docs/preview.png differ diff --git a/vue/src/views/index.vue b/vue/src/views/index.vue index a231b9f0..9ba39f43 100644 --- a/vue/src/views/index.vue +++ b/vue/src/views/index.vue @@ -8,6 +8,13 @@ 工作助手
+ + + + + + + 在线
@@ -166,7 +173,8 @@ export default { sse: null, clientId: '', isSseConnected: false, - isLoading: false + isLoading: false, + selectedModel: 'qwen3.5:2b' } }, mounted() { @@ -259,13 +267,21 @@ export default { // 通过SSE发送消息到后端 if (this.isSseConnected) { + // 使用AbortController实现超时 + const controller = new AbortController(); + const timeoutId = setTimeout(() => controller.abort(), 300000); // 300秒超时 + // 使用fetch发送消息 - fetch(`${process.env.VUE_APP_BASE_API}/api/ai-agent/sse/send?clientId=${this.clientId}&message=${encodeURIComponent(this.inputMessage)}&token=${token}`) + fetch(`${process.env.VUE_APP_BASE_API}/api/ai-agent/sse/send?clientId=${this.clientId}&message=${encodeURIComponent(this.inputMessage)}&model=${this.selectedModel}&token=${token}`, { + signal: controller.signal + }) .then(response => response.text()) .then(data => { + clearTimeout(timeoutId); console.log('消息发送结果:', data); }) .catch(error => { + clearTimeout(timeoutId); console.error('消息发送失败:', error); // 发送失败时使用模拟回复 this.generateReply(this.inputMessage);