115 lines
4.1 KiB
Java
115 lines
4.1 KiB
Java
package com.emotion.controller;
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import com.emotion.service.AiChatService;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.messaging.handler.annotation.MessageMapping;
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import org.springframework.messaging.handler.annotation.Payload;
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import org.springframework.messaging.simp.SimpMessageHeaderAccessor;
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import org.springframework.messaging.simp.SimpMessagingTemplate;
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import org.springframework.stereotype.Controller;
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import org.springframework.web.bind.annotation.GetMapping;
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import org.springframework.web.bind.annotation.ResponseBody;
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import java.util.HashMap;
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import java.util.Map;
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/**
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* WebSocket控制器
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*
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* @author emotion-museum
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* @date 2025-07-22
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*/
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@Controller
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public class WebSocketController {
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private static final Logger log = LoggerFactory.getLogger(WebSocketController.class);
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@Autowired
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private SimpMessagingTemplate messagingTemplate;
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@Autowired
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private AiChatService aiChatService;
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// 已移除旧的WebSocket消息处理方法，使用新的ChatWebSocketController
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// 已移除旧的用户连接处理方法，使用新的ChatWebSocketController
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/**
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* 处理AI聊天消息
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*/
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@MessageMapping("/chat.ai")
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public void handleAiChat(@Payload Map<String, Object> chatMessage,
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SimpMessageHeaderAccessor headerAccessor) {
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log.info("收到AI聊天消息: {}", chatMessage);
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try {
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String content = (String) chatMessage.get("content");
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String conversationId = (String) chatMessage.get("conversationId");
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String userId = (String) chatMessage.get("userId");
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// 调用AI服务
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String aiReply = aiChatService.sendMessage(conversationId, content, userId);
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// 构建AI回复消息
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Map<String, Object> aiResponse = new HashMap<>();
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aiResponse.put("content", aiReply);
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aiResponse.put("sender", "AI助手");
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aiResponse.put("type", "AI_REPLY");
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aiResponse.put("conversationId", conversationId);
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aiResponse.put("timestamp", System.currentTimeMillis());
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// 发送给特定用户
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if (userId != null) {
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messagingTemplate.convertAndSendToUser(userId, "/queue/messages", aiResponse);
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} else {
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// 发送到公共频道
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messagingTemplate.convertAndSend("/topic/conversation/" + conversationId, aiResponse);
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}
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} catch (Exception e) {
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log.error("处理AI聊天失败", e);
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Map<String, Object> errorResponse = new HashMap<>();
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errorResponse.put("content", "AI服务暂时不可用，请稍后再试");
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errorResponse.put("sender", "System");
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errorResponse.put("type", "ERROR");
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errorResponse.put("timestamp", System.currentTimeMillis());
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String userId = (String) chatMessage.get("userId");
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if (userId != null) {
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messagingTemplate.convertAndSendToUser(userId, "/queue/messages", errorResponse);
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}
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}
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}
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/**
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* 发送系统消息
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*/
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public void sendSystemMessage(String destination, String message) {
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Map<String, Object> systemMessage = new HashMap<>();
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systemMessage.put("content", message);
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systemMessage.put("sender", "System");
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systemMessage.put("type", "SYSTEM");
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systemMessage.put("timestamp", System.currentTimeMillis());
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messagingTemplate.convertAndSend(destination, systemMessage);
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}
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/**
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* WebSocket状态监控接口
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*/
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@GetMapping("/api/ws/status")
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@ResponseBody
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public Map<String, Object> getWebSocketStatus() {
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Map<String, Object> status = new HashMap<>();
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status.put("status", "active");
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status.put("timestamp", System.currentTimeMillis());
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status.put("endpoint", "/ws/chat");
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status.put("protocols", new String[]{"websocket", "sockjs"});
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status.put("message", "WebSocket服务正常运行");
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return status;
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}
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}
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