feat: 新增多风格话术流式生成功能，优化对话查询逻辑

1. 新增多风格话术生成SSE接口，支持亲和/专业/促单风格话术流式输出
2. 重构对话查询逻辑，增加staffId参数避免消息串扰，新增自动推断员工身份接口
3. 优化前端侧边栏，适配企微聊天上下文，新增员工信息展示和登录流程
4. 补充相关Mapper和Service代码，完善归档消息查询能力
5. 更新部署文档，优化前端缓存处理

AGENTS.md

@@ -20,17 +20,36 @@
 # 1. 本地构建
 cd frontend/sidebar && npm run build
 
-# 2. 同步到服务器
+# 2. 同步到服务器（注意带 JS hash 的文件名会变化）
 scp -r -o StrictHostKeyChecking=no -i root.pem frontend/sidebar/dist/* root@8.133.162.25:/www/wwwroot/deploy-package/frontend/sidebar/dist/
 
-# 3. SSH 登录服务器，重新构建镜像并重启容器
+# 3. SSH 登录服务器，更新 index.html 缓存戳并重启容器
 ssh -o StrictHostKeyChecking=no -i root.pem root@8.133.162.25 << 'EOF'
-cd /www/wwwroot/deploy-package/frontend/sidebar
+cd /www/wwwroot/deploy-package/frontend/sidebar/dist
-docker build -t deploy-package-sidebar .
+# 更新 index.html 中的 JS/CSS 引用，带上版本戳防缓存
-docker stop ai-assistant-sidebar
+JS_FILE=$(ls assets/index-*.js | head -1)
-docker rm ai-assistant-sidebar
+CSS_FILE=$(ls assets/index-*.css | head -1)
-cd /www/wwwroot/deploy-package
+cat > index.html << HTML
-docker-compose up -d sidebar
+<!DOCTYPE html>
+<html lang="zh-CN">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
+    <meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate" />
+    <title>AI坐席助手</title>
+    <script src="https://res.wx.qq.com/open/js/jweixin-1.2.0.js"></script>
+    <script type="module" crossorigin src="/sidebar/$JS_FILE?v=$(date +%s)"></script>
+    <link rel="stylesheet" crossorigin href="/sidebar/$CSS_FILE?v=$(date +%s)">
+  </head>
+  <body>
+    <div id="root"></div>
+  </body>
+</html>
+HTML
+# 复制到容器并重启
+docker cp . ai-assistant-sidebar:/usr/share/nginx/html/
+docker exec ai-assistant-sidebar nginx -s reload
+docker restart ai-assistant-nginx
 EOF
 ```
 
@@ -92,9 +111,12 @@ cd backend/auth-service && mvn clean package -DskipTests
 scp -o StrictHostKeyChecking=no -i root.pem target/*.jar root@8.133.162.25:/www/wwwroot/deploy-package/backend/auth-service/
 
 # 3. SSH 登录服务器，重启对应容器
+# ⚠️ 注意：Dockerfile 中 COPY 的是 app.jar，必须先把新 jar 复制为 app.jar
 ssh -o StrictHostKeyChecking=no -i root.pem root@8.133.162.25 << 'EOF'
+cd /www/wwwroot/deploy-package/backend/auth-service
+cp auth-service-*.jar app.jar
 cd /www/wwwroot/deploy-package
-docker-compose up -d --build auth-service
+docker-compose up -d --build --no-cache auth-service
 EOF
 ```
 

backend/conversation-service/src/main/java/com/artedu/conversation/controller/ConversationController.java

@@ -65,15 +65,17 @@ public class ConversationController {
     @GetMapping("/last-message")
     public Result<Map<String, Object>> getLastMessage(
             @NotBlank(message = "customerId不能为空") @RequestParam("customerId") String customerId,
+            @NotBlank(message = "staffId不能为空") @RequestParam("staffId") String staffId,
             @NotBlank(message = "corpId不能为空") @RequestParam("corpId") String corpId) {
 
-        ArchiveMessage message = archiveMessageMapper.selectLastMessage(customerId, corpId);
+        ArchiveMessage message = archiveMessageMapper.selectLastMessage(customerId, staffId, corpId);
         Map<String, Object> result = new HashMap<>();
         if (message != null) {
             result.put("content", message.getContent());
             result.put("msgTime", message.getMsgtime());
             result.put("msgType", message.getMsgtype());
             result.put("fromUser", message.getFromUser());
+            result.put("fromRole", message.getFromRole());
         }
         return Result.success(result);
     }

backend/conversation-service/src/main/java/com/artedu/conversation/mapper/ArchiveMessageMapper.java

@@ -9,11 +9,18 @@ import org.apache.ibatis.annotations.Select;
 @Mapper
 public interface ArchiveMessageMapper extends BaseMapper<ArchiveMessage> {
 
+    /**
+     * 获取指定学员在指定对话中的最后一条消息
+     * 通过 staffId 限定只查当前销售与学员的对话，避免学员同时和多个销售聊天时串消息
+     */
     @Select("SELECT * FROM archive_messages " +
-            "WHERE (from_user = #{userId} OR to_user LIKE CONCAT('%', #{userId}, '%')) " +
+            "WHERE from_user = #{userId} " +
+            "AND to_user LIKE CONCAT('%', #{staffId}, '%') " +
             "AND corp_id = #{corpId} " +
+            "AND from_role = 'EXTERNAL' " +
             "AND content IS NOT NULL AND content != '' " +
             "ORDER BY msgtime DESC LIMIT 1")
     ArchiveMessage selectLastMessage(@Param("userId") String userId,
+                                      @Param("staffId") String staffId,
                                       @Param("corpId") String corpId);
 }

backend/generation-service/src/main/java/com/artedu/generation/controller/GenerationController.java

@@ -9,13 +9,19 @@ import com.artedu.generation.service.PromptEngine;
 import com.artedu.generation.service.QianwenClient;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.http.MediaType;
 import org.springframework.validation.annotation.Validated;
 import org.springframework.web.bind.annotation.*;
+import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
 
 import javax.validation.constraints.NotBlank;
+import java.io.IOException;
+import java.util.ArrayList;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
 
 @Slf4j
 @Validated
@@ -35,6 +41,73 @@ public class GenerationController {
     @Autowired
     private ArchiveMessageMapper archiveMessageMapper;
 
+    private final ExecutorService sseExecutor = Executors.newCachedThreadPool();
+
+    private static final List<Map<String, String>> STYLES = List.of(
+            Map.of("id", "friendly", "name", "亲和风格", "desc", "温暖亲切，像朋友聊天"),
+            Map.of("id", "professional", "name", "专业风格", "desc", "数据驱动，专业权威"),
+            Map.of("id", "urgent", "name", "促单风格", "desc", "制造紧迫感，促成决策")
+    );
+
+    /**
+     * 根据当前聊天对象自动推断员工身份
+     * 前端不知道 toUser 时调用，后端从聊天记录中反推
+     */
+    @GetMapping("/whoami")
+    public Result<Map<String, Object>> whoami(
+            @RequestParam(value = "fromUser", required = false) String fromUser,
+            @RequestParam(value = "roomid", required = false) String roomid) {
+
+        String staffId = null;
+        String chatType = null;
+
+        if (roomid != null && !roomid.isEmpty()) {
+            // 群聊：从群消息中找最近一条 INTERNAL 角色的发送者
+            chatType = "group";
+            List<ArchiveMessage> msgs = archiveMessageMapper.selectGroupChatMessages(
+                    roomid, get7DaysAgoStartTime(), getTodayEndTime());
+            if (msgs != null && !msgs.isEmpty()) {
+                for (ArchiveMessage msg : msgs) {
+                    if ("INTERNAL".equals(msg.getFromRole())) {
+                        staffId = msg.getFromUser();
+                        break;
+                    }
+                }
+            }
+        } else if (fromUser != null && !fromUser.isEmpty()) {
+            // 单聊：查该客户最近参与的所有消息，推断员工
+            chatType = "single";
+            List<ArchiveMessage> msgs = archiveMessageMapper.selectMessagesByFromUser(
+                    fromUser, get7DaysAgoStartTime(), getTodayEndTime());
+            if (msgs != null && !msgs.isEmpty()) {
+                // 取最近一条，fromUser 是客户则 from_user=客户/to_user=员工 或 from_user=员工/to_user=客户
+                ArchiveMessage msg = msgs.get(0);
+                if (fromUser.equals(msg.getFromUser())) {
+                    // 客户发的消息，to_user 里的是员工ID（JSON数组）
+                    staffId = msg.getToUser();
+                } else {
+                    // 员工发的消息，from_user 就是员工ID
+                    staffId = msg.getFromUser();
+                }
+                // 清理 JSON 数组格式 ["userId"]
+                if (staffId != null) {
+                    staffId = staffId.replaceAll("\\[|\\]|\"", "").trim();
+                }
+            }
+        }
+
+        if (staffId == null || staffId.isEmpty()) {
+            return Result.fail("未找到聊天记录，无法推断员工身份");
+        }
+
+        Map<String, Object> result = new HashMap<>();
+        result.put("userId", staffId);
+        result.put("chatType", chatType);
+        result.put("fromUser", fromUser);
+        result.put("roomid", roomid);
+        return Result.success(result);
+    }
+
     @PostMapping("/utterance")
     public Result<Map<String, Object>> generateUtterance(
             @RequestParam(value = "fromUser", required = false) String fromUser,
@@ -62,18 +135,25 @@ public class GenerationController {
         List<ArchiveMessage> messages;
         boolean isGroupChat = roomid != null && !roomid.isEmpty();
 
-        long startTime = getTodayStartTime();
+        // 查最近 7 天，避免今天没聊天就找不到记录
+        long startTime = get7DaysAgoStartTime();
         long endTime = getTodayEndTime();
 
         if (isGroupChat) {
             messages = archiveMessageMapper.selectGroupChatMessages(roomid, startTime, endTime);
         } else {
-            if (fromUser == null || fromUser.isEmpty() || toUser == null || toUser.isEmpty()) {
+            if (fromUser == null || fromUser.isEmpty()) {
-                log.warn("单聊模式需要fromUser和toUser参数");
+                log.warn("单聊模式需要fromUser参数");
                 return null;
             }
-            toUser = "[\""+toUser+"\"]";
+            // toUser 为空或无效时，用兜底查询（根据 fromUser 查所有相关记录）
-            messages = archiveMessageMapper.selectSingleChatMessages(fromUser, toUser, startTime, endTime);
+            if (toUser == null || toUser.isEmpty() || "staff_001".equals(toUser)) {
+                log.warn("toUser无效，使用兜底查询, fromUser={}, toUser={}", fromUser, toUser);
+                messages = archiveMessageMapper.selectMessagesByFromUser(fromUser, startTime, endTime);
+            } else {
+                toUser = "[\""+toUser+"\"]";
+                messages = archiveMessageMapper.selectSingleChatMessages(fromUser, toUser, startTime, endTime);
+            }
         }
 
         if (messages == null || messages.isEmpty()) {
@@ -95,6 +175,120 @@ public class GenerationController {
         return java.time.LocalDate.now().plusDays(1).atStartOfDay(java.time.ZoneId.systemDefault()).toInstant().toEpochMilli() - 1;
     }
 
+    private long get7DaysAgoStartTime() {
+        return java.time.LocalDate.now().minusDays(7).atStartOfDay(java.time.ZoneId.systemDefault()).toInstant().toEpochMilli();
+    }
+
+    /**
+     * 流式生成多风格话术（SSE）
+     * 页面打开即自动推荐 3 条不同风格话术
+     */
+    @GetMapping(value = "/utterance-stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
+    public SseEmitter streamUtterance(
+            @RequestParam("fromUser") String fromUser,
+            @RequestParam("toUser") String toUser,
+            @RequestParam(value = "roomid", required = false) String roomid) {
+
+        SseEmitter emitter = new SseEmitter(120000L);
+
+        sseExecutor.execute(() -> {
+            try {
+                Map<String, Object> startEvent = new HashMap<>();
+                startEvent.put("type", "start");
+                startEvent.put("styles", STYLES);
+                emitter.send(SseEmitter.event().name("start").data(startEvent));
+
+                String chatContext = buildChatContext(fromUser, toUser, roomid);
+                if (chatContext == null || chatContext.isEmpty()) {
+                    Map<String, Object> err = new HashMap<>();
+                    err.put("type", "error");
+                    err.put("message", "未找到聊天记录");
+                    emitter.send(SseEmitter.event().name("error").data(err));
+                    emitter.complete();
+                    return;
+                }
+
+                String systemPrompt = promptEngine.buildSystemPrompt(chatContext);
+                String userPrompt = promptEngine.buildMultiStyleUserPrompt();
+
+                long startTime = System.currentTimeMillis();
+                String generated = qianwenClient.generate(systemPrompt, userPrompt, 1200);
+                log.info("多风格话术生成完成, elapsed={}ms", System.currentTimeMillis() - startTime);
+
+                List<String> utterances = parseMultiStyle(generated);
+                if (utterances.size() < 3) {
+                    while (utterances.size() < 3) {
+                        utterances.add(generated != null ? generated : "生成失败，请稍后重试");
+                    }
+                }
+
+                for (int i = 0; i < Math.min(3, utterances.size()); i++) {
+                    String text = utterances.get(i);
+                    String styleId = STYLES.get(i).get("id");
+
+                    Map<String, Object> itemStart = new HashMap<>();
+                    itemStart.put("type", "item-start");
+                    itemStart.put("styleId", styleId);
+                    itemStart.put("index", i);
+                    emitter.send(SseEmitter.event().name("item-start").data(itemStart));
+
+                    for (int j = 0; j < text.length(); j++) {
+                        String ch = text.substring(j, j + 1);
+                        Map<String, Object> chunk = new HashMap<>();
+                        chunk.put("type", "chunk");
+                        chunk.put("styleId", styleId);
+                        chunk.put("text", ch);
+                        chunk.put("index", i);
+                        emitter.send(SseEmitter.event().name("chunk").data(chunk));
+                        Thread.sleep(25);
+                    }
+
+                    Map<String, Object> complete = new HashMap<>();
+                    complete.put("type", "complete");
+                    complete.put("styleId", styleId);
+                    complete.put("fullText", text);
+                    complete.put("index", i);
+                    emitter.send(SseEmitter.event().name("complete").data(complete));
+                }
+
+                Map<String, Object> done = new HashMap<>();
+                done.put("type", "done");
+                done.put("model", qianwenClient.getCurrentModel() != null
+                        ? qianwenClient.getCurrentModel().getModelName() : "default");
+                emitter.send(SseEmitter.event().name("done").data(done));
+                emitter.complete();
+
+            } catch (Exception e) {
+                log.error("流式生成失败", e);
+                try {
+                    Map<String, Object> error = new HashMap<>();
+                    error.put("type", "error");
+                    error.put("message", e.getMessage());
+                    emitter.send(SseEmitter.event().name("error").data(error));
+                } catch (IOException ignored) {}
+                emitter.completeWithError(e);
+            }
+        });
+
+        return emitter;
+    }
+
+    /**
+     * 解析多风格话术，按 "|||" 分隔
+     */
+    private List<String> parseMultiStyle(String text) {
+        List<String> result = new ArrayList<>();
+        if (text == null || text.isEmpty()) return result;
+        String[] parts = text.split("\\|\\|\\|");
+        for (String part : parts) {
+            String trimmed = part.trim();
+            if (!trimmed.isEmpty() && trimmed.length() > 5) {
+                result.add(trimmed);
+            }
+        }
+        return result;
+    }
+
     @PostMapping("/summary")
     public Result<Map<String, Object>> generateSummary(
             @NotBlank(message = "context不能为空") @RequestParam("context") String context) {

backend/generation-service/src/main/java/com/artedu/generation/mapper/ArchiveMessageMapper.java

@@ -36,4 +36,26 @@ public interface ArchiveMessageMapper extends BaseMapper<ArchiveMessage> {
     List<ArchiveMessage> selectGroupChatMessages(@Param("roomid") String roomid,
                                                  @Param("startTime") Long startTime,
                                                  @Param("endTime") Long endTime);
+
+    /**
+     * 根据 fromUser 查询该用户参与的所有单聊记录（不限制 toUser，用于 toUser 未知时兜底）
+     */
+    @Select("SELECT msgtime, created_at, from_user, to_user, from_role, content FROM archive_messages " +
+            "WHERE (from_user = #{fromUser} OR to_user = #{fromUser}) " +
+            "AND msgtime >= #{startTime} AND msgtime < #{endTime} AND msgtype='text' " +
+            "AND content IS NOT NULL AND content != '' " +
+            "ORDER BY msgtime DESC LIMIT 100")
+    List<ArchiveMessage> selectMessagesByFromUser(@Param("fromUser") String fromUser,
+                                                  @Param("startTime") Long startTime,
+                                                  @Param("endTime") Long endTime);
+
+    /**
+     * 根据 fromUser 查询最近一条消息的 to_user（推断员工身份）
+     * to_user 格式为 JSON 数组 ["userId"]
+     */
+    @Select("SELECT to_user FROM archive_messages " +
+            "WHERE (from_user = #{fromUser} OR to_user LIKE CONCAT('%', #{fromUser}, '%')) " +
+            "AND msgtype='text' AND content IS NOT NULL AND content != '' " +
+            "ORDER BY msgtime DESC LIMIT 1")
+    String selectRecentToUserByFromUser(@Param("fromUser") String fromUser);
 }

backend/generation-service/src/main/java/com/artedu/generation/service/PromptEngine.java

@@ -129,6 +129,30 @@ public class PromptEngine {
         return sb.toString();
     }
 
+    /**
+     * 多风格话术生成的用户提示词
+     * 要求 LLM 输出 3 条不同风格话术，用 ||| 分隔
+     */
+    public String buildMultiStyleUserPrompt() {
+        StringBuilder sb = new StringBuilder();
+        sb.append("请根据上述对话历史，生成 3 条不同风格的推荐回复话术。\n\n");
+        sb.append("风格要求（严格按顺序输出）：\n");
+        sb.append("第1条 - 亲和风格：温暖亲切，像朋友聊天，拉近距离\n");
+        sb.append("第2条 - 专业风格：用数据、案例、专业分析增强说服力\n");
+        sb.append("第3条 - 促单风格：制造紧迫感，强调限时优惠或名额有限\n\n");
+        sb.append("输出要求（必须遵守）：\n");
+        sb.append("- 每条话术 80-150 字，简洁自然\n");
+        sb.append("- 话术之间用「|||」分隔，不要加序号、标题或任何解释\n");
+        sb.append("- 直接输出话术内容，不要有开场白、总结、备注\n\n");
+        sb.append("输出格式示例：\n");
+        sb.append("亲和风格的话术内容...\n");
+        sb.append("|||\n");
+        sb.append("专业风格的话术内容...\n");
+        sb.append("|||\n");
+        sb.append("促单风格的话术内容...");
+        return sb.toString();
+    }
+
     public String buildSummaryPrompt(String context) {
         return "请对以下对话进行简要总结（50字以内），提炼学员核心需求和当前阶段：\n\n" + context;
     }

backend/generation-service/target/maven-status/maven-compiler-plugin/compile/default-compile/createdFiles.lst

@@ -1,7 +1,9 @@
 com\artedu\generation\service\QianwenClient.class
 com\artedu\generation\controller\GenerateRequest.class
+com\artedu\generation\entity\ArchiveMessage.class
 com\artedu\generation\service\LlmModelService.class
 com\artedu\generation\client\DoubaoClient.class
+com\artedu\generation\mapper\ArchiveMessageMapper.class
 com\artedu\generation\client\LLMClientFactory.class
 com\artedu\generation\controller\LlmModelController.class
 com\artedu\generation\mapper\LlmModelMapper.class

backend/generation-service/target/maven-status/maven-compiler-plugin/compile/default-compile/inputFiles.lst

@@ -7,8 +7,10 @@ D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\controller\GenerateRequest.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\controller\GenerationController.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\controller\LlmModelController.java
+D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\entity\ArchiveMessage.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\entity\LlmModel.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\GenerationServiceApplication.java
+D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\mapper\ArchiveMessageMapper.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\mapper\LlmModelMapper.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\service\LlmModelService.java
 D:\www\agent_9art\backend\generation-service\src\main\java\com\artedu\generation\service\PromptEngine.java

frontend/sidebar/src/App.tsx

@@ -1,86 +1,129 @@
-import { useEffect, useState } from 'react'
+import { useEffect, useState, useCallback } from 'react'
-import { Tabs, Toast } from 'antd-mobile'
 import ScriptRecommendStream from './components/ScriptRecommendStream'
-import ConversationAnalysis from './components/ConversationAnalysis'
 import './styles.css'
 
+const CORPID = 'wwd483c2fba24ae30a'
+const AGENTID = '1000021'
+const REDIRECT_URI = encodeURIComponent('https://ai.9artedu.com/sidebar/')
+
 function App() {
-  const [activeTab, setActiveTab] = useState('recommend')
+  const [authState, setAuthState] = useState<'loading' | 'authed' | 'needLogin' | 'error'>('loading')
-  const [authState, setAuthState] = useState<'loading' | 'authed' | 'error'>('loading')
   const [userInfo, setUserInfo] = useState<any>(null)
   const [currentCustomerId, setCurrentCustomerId] = useState<string>('')
-
+  const [chatContext, setChatContext] = useState<{ chatType?: string; chatId?: string }>({})
 
   useEffect(() => {
-    initWeCom()
+    initAuth()
   }, [])
 
-  const initWeCom = async () => {
+  useEffect(() => {
+    if (authState === 'authed') {
+      initWxConfig()
+    }
+  }, [authState])
+
+  const noCacheFetch = useCallback(async (url: string, options?: RequestInit) => {
+    const sep = url.includes('?') ? '&' : '?'
+    const nocacheUrl = `${url}${sep}_t=${Date.now()}`
+    return fetch(nocacheUrl, {
+      ...options,
+      headers: {
+        'Cache-Control': 'no-cache, no-store, must-revalidate',
+        'Pragma': 'no-cache',
+        ...options?.headers
+      }
+    })
+  }, [])
+
+  // ========== 认证流程 ==========
+  const initAuth = async () => {
     try {
       const urlParams = new URLSearchParams(window.location.search)
       const code = urlParams.get('code')
 
+      // 1. URL 中有 code → 移除并登录
       if (code) {
-        const res = await fetch(`/api/v1/auth/login?code=${encodeURIComponent(code)}`, { method: 'POST' })
+        const cleanUrl = window.location.pathname + window.location.hash
-        const data = await res.json()
+        window.history.replaceState({}, document.title, cleanUrl)
-        if (data.code === 0 && data.data) {
+
-          localStorage.setItem('staff_token', data.data.token)
+        const ok = await tryCodeLogin(code)
-          setUserInfo(data.data)
+        if (ok) return
-          setAuthState('authed')
+        // login 失败 → 可能是 code 过期/已被使用，显示登录按钮让用户手动重试
-        } else {
+        setAuthState('needLogin')
-          setAuthState('error')
+        return
-          Toast.show({ content: '登录失败: ' + (data.message || '未知错误'), icon: 'fail' })
-        }
-      } else {
-        const token = localStorage.getItem('staff_token')
-        if (token) {
-          const res = await fetch('/api/v1/auth/info', {
-            headers: { Authorization: `Bearer ${token}` }
-          })
-          const data = await res.json()
-          if (data.code === 0 && data.data) {
-            setUserInfo(data.data)
-            setAuthState('authed')
-          } else {
-            redirectToOAuth()
-          }
-        } else {
-          redirectToOAuth()
-        }
       }
+
+      // 2. 无 code → 检查 localStorage 缓存
+      const cachedUserId = localStorage.getItem('staff_user_id')
+      const cachedUserName = localStorage.getItem('staff_user_name')
+      const cachedToken = localStorage.getItem('staff_token')
+      if (cachedUserId && cachedToken) {
+        setUserInfo({
+          userId: cachedUserId,
+          userName: cachedUserName || cachedUserId,
+          avatar: localStorage.getItem('staff_avatar') || '',
+          corpId: CORPID,
+          role: localStorage.getItem('staff_role') || 'SEAT'
+        })
+        setAuthState('authed')
+        console.log('使用缓存员工信息:', cachedUserId)
+        return
+      }
+
+      // 3. 无 code 无缓存 → 显示登录按钮（iframe 中自动跳转可能被拦截）
+      setAuthState('needLogin')
+
     } catch (e) {
+      console.error('initAuth error:', e)
       setAuthState('error')
-      Toast.show({ content: '初始化失败', icon: 'fail' })
     }
   }
 
-  const redirectToOAuth = () => {
+  // 用 code 调后端 login 接口
-    setAuthState('authed')
+  const tryCodeLogin = async (code: string): Promise<boolean> => {
-    setUserInfo({
+    try {
-      userId: 'staff_001',
+      const res = await noCacheFetch(`/api/v1/auth/login?code=${encodeURIComponent(code)}`, { method: 'POST' })
-      userName: '测试顾问',
+      const data = await res.json()
-      corpId: 'wwd483c2fba24ae30a',
+      if (data.code === 0 && data.data) {
-      role: 'SEAT'
+        const info = data.data
-    })
+        localStorage.setItem('staff_token', info.token)
+        localStorage.setItem('staff_user_id', info.userId)
+        localStorage.setItem('staff_user_name', info.userName || '')
+        localStorage.setItem('staff_avatar', info.avatar || '')
+        localStorage.setItem('staff_role', info.role || 'SEAT')
+        setUserInfo(info)
+        setAuthState('authed')
+        console.log('OAuth 登录成功:', info.userId, info.userName)
+        return true
+      }
+      console.error('OAuth login failed:', data.message)
+    } catch (e) {
+      console.error('Code login error:', e)
+    }
+    return false
   }
 
+  // 跳转企微 OAuth 授权页
+  const redirectToWeComOAuth = () => {
+    const oauthUrl = `https://open.weixin.qq.com/connect/oauth2/authorize?appid=${CORPID}&redirect_uri=${REDIRECT_URI}&response_type=code&scope=snsapi_base&agentid=${AGENTID}&state=sidebar#wechat_redirect`
+    console.log('跳转企微 OAuth:', oauthUrl)
+    window.location.href = oauthUrl
+  }
+
+  // ========== JS-SDK 初始化（认证完成后调用）==========
   const initWxConfig = async () => {
     const wx = (window as any).wx
     if (!wx || !wx.config) {
-      console.log('非企微环境，跳过JS-SDK初始化')
+      console.log('非企微环境，跳过 JS-SDK')
       return
     }
 
-    try {
+    const currentUrl = window.location.href.split('#')[0]
-      const currentUrl = window.location.href.split('#')[0]
 
-      // 1. 企业级 wx.config
+    try {
-      const corpRes = await fetch(`/api/v1/auth/signature?url=${encodeURIComponent(currentUrl)}`)
+      const corpRes = await noCacheFetch(`/api/v1/auth/signature?url=${encodeURIComponent(currentUrl)}`)
       const corpData = await corpRes.json()
-      if (corpData.code !== 0 || !corpData.data) {
+      if (corpData.code !== 0 || !corpData.data) return
-        console.error('获取JS-SDK企业签名失败')
-        return
-      }
 
       const cfg = corpData.data
       wx.config({
@@ -94,13 +137,9 @@ function App() {
       })
 
       wx.ready(async () => {
-        console.log('JS-SDK wx.config 成功')
-
-        // 2. 尝试应用级 agentConfig（获取客户联系权限）
         try {
-          const agentRes = await fetch(`/api/v1/auth/signature?type=agent&agentId=1000021&url=${encodeURIComponent(currentUrl)}`)
+          const agentRes = await noCacheFetch(`/api/v1/auth/signature?type=agent&agentId=${AGENTID}&url=${encodeURIComponent(currentUrl)}`)
           const agentData = await agentRes.json()
-
           if (agentData.code === 0 && agentData.data) {
             const ac = agentData.data
             wx.agentConfig({
@@ -111,78 +150,140 @@ function App() {
               signature: ac.signature,
               jsApiList: ['sendChatMessage', 'getContext', 'getCurExternalContact'],
               success: () => {
-                console.log('✅ agentConfig 成功，已获取客户联系权限')
+                wx.invoke('getContext', {}, (ctx: any) => {
-                // agentConfig 成功后，获取当前客户ID
+                  if (ctx.err_msg === 'getContext:ok') {
+                    setChatContext({ chatType: ctx.chatType, chatId: ctx.chatId })
+                    if (ctx.chatType === 'single' && ctx.chatId) {
+                      localStorage.setItem('current_customer_id', ctx.chatId)
+                      setCurrentCustomerId(ctx.chatId)
+                    }
+                  }
+                })
                 wx.invoke('getCurExternalContact', {}, (res: any) => {
                   if (res.err_msg === 'getCurExternalContact:ok' && res.userId) {
-                    console.log('✅ 获取到客户ID:', res.userId)
                     localStorage.setItem('current_customer_id', res.userId)
                     setCurrentCustomerId(res.userId)
-                  } else {
-                    console.warn('getCurExternalContact 失败:', res.err_msg)
-                    fallbackToCachedId()
                   }
                 })
               },
-              fail: (err: any) => {
+              fail: (err: any) => console.warn('agentConfig fail:', err)
-                console.warn('⚠️ agentConfig 失败（无客户联系权限）:', err.err_msg || err)
-                fallbackToCachedId()
-              }
             })
-          } else {
-            console.warn('⚠️ 获取应用签名失败:', agentData.message)
-            fallbackToCachedId()
           }
         } catch (e) {
-          console.warn('⚠️ agentConfig 流程异常:', e)
+          console.error('agentConfig error:', e)
-          fallbackToCachedId()
         }
       })
 
-      wx.error((err: any) => {
+      wx.error((err: any) => console.error('wx.config error:', err))
-        console.error('JS-SDK wx.config 失败:', err)
-        fallbackToCachedId()
-      })
     } catch (e) {
-      console.error('初始化JS-SDK异常:', e)
+      console.error('initWxConfig error:', e)
-      fallbackToCachedId()
     }
   }
 
-  const fallbackToCachedId = () => {
-    const cachedId = localStorage.getItem('current_customer_id')
-    if (cachedId && cachedId !== '${userId}') {
-      setCurrentCustomerId(cachedId)
-    }
-  }
-
-  useEffect(() => {
-    if (authState === 'authed') {
-      initWxConfig()
-    }
-  }, [authState])
-
   if (authState === 'loading') {
     return (
       <div className="app" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center', height: '100vh' }}>
         <div style={{ textAlign: 'center', color: '#999' }}>
           <div style={{ fontSize: 16, marginBottom: 8 }}>加载中...</div>
-          <div style={{ fontSize: 13 }}>正在连接企微</div>
+          <div style={{ fontSize: 13 }}>正在识别员工身份...</div>
         </div>
       </div>
     )
   }
 
+  if (authState === 'needLogin') {
+    return (
+      <div className="app" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center', height: '100vh', padding: 20 }}>
+        <div style={{ textAlign: 'center' }}>
+          <div style={{ fontSize: 18, marginBottom: 8, color: '#333', fontWeight: 500 }}>AI 坐席助手</div>
+          <div style={{ fontSize: 13, color: '#999', marginBottom: 24 }}>请登录以获取员工身份</div>
+          <button
+            onClick={redirectToWeComOAuth}
+            style={{
+              padding: '10px 32px',
+              background: '#1677ff',
+              color: '#fff',
+              border: 'none',
+              borderRadius: 6,
+              fontSize: 15,
+              cursor: 'pointer',
+              fontWeight: 500
+            }}
+          >
+            企微一键登录
+          </button>
+          <div style={{ fontSize: 12, color: '#bbb', marginTop: 16 }}>
+            登录后即可使用智能推荐和对话分析
+          </div>
+        </div>
+      </div>
+    )
+  }
+
+  if (authState === 'error') {
+    return (
+      <div className="app" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center', height: '100vh', padding: 20 }}>
+        <div style={{ textAlign: 'center' }}>
+          <div style={{ fontSize: 16, marginBottom: 8, color: '#cf1322' }}>⚠️ 登录失败</div>
+          <div style={{ fontSize: 13, color: '#999', marginBottom: 16 }}>请关闭侧边栏后重新打开</div>
+          <button
+            onClick={() => { localStorage.clear(); window.location.reload() }}
+            style={{ padding: '8px 16px', background: '#1677ff', color: '#fff', border: 'none', borderRadius: 4, cursor: 'pointer' }}
+          >
+            清除缓存重试
+          </button>
+        </div>
+      </div>
+    )
+  }
+
+  // ========== 主界面（认证成功）==========
   return (
     <div className="app">
-      <Tabs activeKey={activeTab} onChange={setActiveTab}>
+      {/* 顶部员工信息栏 */}
-        <Tabs.Tab title="智能推荐" key="recommend">
+      <div style={{
-          <ScriptRecommendStream userInfo={userInfo} customerId={currentCustomerId} />
+        display: 'flex',
-        </Tabs.Tab>
+        alignItems: 'center',
-        <Tabs.Tab title="对话分析" key="analysis">
+        justifyContent: 'space-between',
-          <ConversationAnalysis userInfo={userInfo} />
+        padding: '8px 12px',
-        </Tabs.Tab>
+        background: '#fff',
-      </Tabs>
+        borderBottom: '1px solid #f0f0f0',
+        position: 'sticky',
+        top: 0,
+        zIndex: 10
+      }}>
+        <div style={{ display: 'flex', alignItems: 'center', gap: 8 }}>
+          {userInfo?.avatar ? (
+            <img
+              src={userInfo.avatar}
+              alt="avatar"
+              style={{ width: 28, height: 28, borderRadius: '50%', objectFit: 'cover' }}
+            />
+          ) : (
+            <div style={{
+              width: 28, height: 28, borderRadius: '50%',
+              background: '#1677ff', color: '#fff',
+              display: 'flex', alignItems: 'center', justifyContent: 'center',
+              fontSize: 12, fontWeight: 'bold'
+            }}>
+              {(userInfo?.userName || userInfo?.userId || '?').charAt(0)}
+            </div>
+          )}
+          <div>
+            <div style={{ fontSize: 14, fontWeight: 500, color: '#333', lineHeight: '20px' }}>
+              {userInfo?.userName || userInfo?.userId || '未知员工'}
+            </div>
+            <div style={{ fontSize: 11, color: '#999', lineHeight: '16px' }}>
+              {userInfo?.userId}
+            </div>
+          </div>
+        </div>
+        <div style={{ fontSize: 13, color: '#1677ff', fontWeight: 500 }}>
+          AI 坐席助手
+        </div>
+      </div>
+
+      <ScriptRecommendStream userInfo={userInfo} customerId={currentCustomerId} chatContext={chatContext} />
     </div>
   )
 }

frontend/sidebar/src/components/ScriptRecommendStream.tsx

@@ -19,6 +19,7 @@ interface UtteranceItem {
 interface Props {
   userInfo?: any
   customerId?: string
+  chatContext?: { chatType?: string; chatId?: string }
 }
 
 const STYLES: StyleConfig[] = [
@@ -27,21 +28,24 @@ const STYLES: StyleConfig[] = [
   { id: 'urgent', name: '促单风格', desc: '制造紧迫感，促成决策', color: '#fa8c16', bgColor: '#fff7e6' }
 ]
 
-export default function ScriptRecommendStream({ userInfo, customerId: propCustomerId }: Props) {
+export default function ScriptRecommendStream({ userInfo, customerId: propCustomerId, chatContext }: Props) {
   const [loading, setLoading] = useState(true)
   const [generating, setGenerating] = useState(false)
   const [customerMsg, setCustomerMsg] = useState('')
   const [profileTags, setProfileTags] = useState<string[]>([])
   const [utterances, setUtterances] = useState<UtteranceItem[]>([])
-  const [progress, setProgress] = useState(0)
   const [error, setError] = useState('')
   const sseRef = useRef<EventSource | null>(null)
 
-  const sessionId = localStorage.getItem('current_session_id') || `session_${Date.now()}`
+  const customerId = propCustomerId || localStorage.getItem('current_customer_id') || ''
-  const customerId = propCustomerId || localStorage.getItem('current_customer_id') || 'wx_001'
+  const staffId = userInfo?.userId || ''
-  const staffId = userInfo?.userId || 'staff_001'
   const corpId = userInfo?.corpId || 'wwd483c2fba24ae30a'
 
+  const chatType = chatContext?.chatType
+  const chatId = chatContext?.chatId
+  const isGroupChat = chatType === 'group'
+  const isSingleChat = chatType === 'single'
+
   const closeSse = useCallback(() => {
     if (sseRef.current) {
       sseRef.current.close()
@@ -77,102 +81,68 @@ export default function ScriptRecommendStream({ userInfo, customerId: propCustom
   const handleRegenerate = () => {
     closeSse()
     setUtterances([])
-    setProgress(0)
     setError('')
     startGeneration()
   }
 
+  // 判断是否可以开始生成
+  const canStartGeneration = useCallback(() => {
+    if (isGroupChat && chatId) return true
+    if (isSingleChat && customerId && staffId) return true
+    // 兼容：没有 chatContext 时（非企微/测试环境）
+    if (!chatType && customerId && staffId) return true
+    return false
+  }, [isGroupChat, isSingleChat, chatId, customerId, staffId, chatType])
+
+  // 核心：开始流式生成
   const startGeneration = useCallback(async () => {
-    if (!customerMsg.trim()) {
+    if (!canStartGeneration()) {
-      setError('暂无学员消息')
+      setError('未获取到聊天信息')
       setLoading(false)
       return
     }
 
     setGenerating(true)
     setLoading(false)
-    setProgress(10)
 
     try {
-      const [profileRes, contextRes, recommendRes] = await Promise.all([
+      // 单聊才获取画像标签
-        fetch(`/api/v1/intent/profile/${encodeURIComponent(customerId)}?corpId=${corpId}`),
+      if (!isGroupChat && customerId) {
-        fetch(`/api/v1/conversations/${sessionId}/context`).catch(() => null),
+        const profileRes = await fetch(`/api/v1/intent/profile/${encodeURIComponent(customerId)}?corpId=${corpId}`)
-        fetch(`/api/v1/recommend/get?${new URLSearchParams({
+        const profileData = await profileRes.json()
-          sessionId, customerId, staffId, corpId,
+        if (profileData.code === 0 && profileData.data) {
-          intentCode: 'INT-COURSE-01',
+          const p = profileData.data
-          stage: 'STAGE-03',
+          const tags: string[] = []
-          studentType: '零基础',
+          if (p.currentOccupation) tags.push(p.currentOccupation)
-          message: customerMsg
+          if (p.studentType) tags.push(p.studentType)
-        }).toString()}`, { method: 'POST' }).catch(() => null)
+          if (p.skillLevel) tags.push(p.skillLevel)
-      ])
+          if (p.intentLevel) tags.push(p.intentLevel)
-
+          if (p.concernFocus) tags.push(p.concernFocus)
-      let customerProfileStr = ''
+          if (p.decisionStage) tags.push(p.decisionStage)
-      let tags: string[] = []
+          setProfileTags(tags)
-      const profileData = await profileRes.json()
-      if (profileData.code === 0 && profileData.data) {
-        const p = profileData.data
-        if (p.currentOccupation) { tags.push(p.currentOccupation) }
-        if (p.studentType) { tags.push(p.studentType) }
-        if (p.skillLevel) { tags.push(p.skillLevel) }
-        if (p.intentLevel) { tags.push(p.intentLevel) }
-        if (p.concernFocus) { tags.push(p.concernFocus) }
-        if (p.decisionStage) { tags.push(p.decisionStage) }
-        customerProfileStr = [
-          p.currentOccupation ? `身份/职业：${p.currentOccupation}` : '',
-          p.studentType ? `学员类型：${p.studentType}` : '',
-          p.skillLevel ? `基础水平：${p.skillLevel}` : '',
-          p.intentLevel ? `意向度：${p.intentLevel}（${p.intentScore != null ? Math.round(p.intentScore) : 0}分）` : '',
-          p.concernFocus ? `关注方向：${p.concernFocus}` : '',
-          p.decisionStage ? `决策阶段：${p.decisionStage}` : ''
-        ].filter(Boolean).join('\n')
-      }
-      setProfileTags(tags)
-      setProgress(30)
-
-      let conversationContextStr = ''
-      if (contextRes) {
-        const contextData = await contextRes.json()
-        if (contextData.code === 0 && contextData.data?.messages) {
-          const msgs = contextData.data.messages as Array<{ role: string; content: string }>
-          conversationContextStr = msgs.slice(-3).map(m => {
-            const roleName = m.role === 'student' ? '学员' : '顾问'
-            return `${roleName}：${m.content}`
-          }).join('\n')
         }
       }
 
-      let referenceUtterancesStr = ''
+      // 构建 SSE URL：群聊传 roomid，单聊传 fromUser+toUser
-      if (recommendRes) {
+      const params = new URLSearchParams()
-        const recData = await recommendRes.json()
+      if (isGroupChat && chatId) {
-        if (recData.code === 0 && recData.data) {
+        params.append('roomid', chatId)
-          const top3 = recData.data.slice(0, 3)
+      } else if (customerId && staffId) {
-          referenceUtterancesStr = top3.map((s: any, i: number) => `${i + 1}. "${s.contentText || s.content || s.title}"`).join('\n')
+        params.append('fromUser', customerId)
-        }
+        params.append('toUser', staffId)
       }
-      setProgress(50)
-
-      const params = new URLSearchParams({
-        message: customerMsg,
-        intent: 'INT-COURSE-01',
-        stage: 'STAGE-03',
-        stageLabel: '方案呈现',
-        intentLabel: '课程咨询'
-      })
-      if (customerProfileStr) params.append('customerProfile', customerProfileStr)
-      if (conversationContextStr) params.append('conversationContext', conversationContextStr)
-      if (referenceUtterancesStr) params.append('referenceUtterances', referenceUtterancesStr)
 
       const url = `/api/v1/generation/utterance-stream?${params.toString()}`
+      console.log('SSE connect:', url)
       const es = new EventSource(url)
       sseRef.current = es
 
       setUtterances(STYLES.map(s => ({ styleId: s.id, text: '', isComplete: false, isTyping: false })))
 
-      // ===== 关键修复：用 addEventListener 接收命名事件 =====
       es.addEventListener('start', (event: MessageEvent) => {
         try {
           const data = JSON.parse(event.data)
-          if (data.type === 'start') setProgress(60)
+          if (data.type === 'start') { /* 可处理 styles 信息 */ }
         } catch (e) { console.error('SSE start error:', e) }
       })
 
@@ -214,7 +184,6 @@ export default function ScriptRecommendStream({ userInfo, customerId: propCustom
           const data = JSON.parse(event.data)
           if (data.type === 'done') {
             setGenerating(false)
-            setProgress(100)
             es.close()
           }
         } catch (e) { console.error('SSE done error:', e) }
@@ -236,48 +205,49 @@ export default function ScriptRecommendStream({ userInfo, customerId: propCustom
       setError('网络错误，请重试')
       setGenerating(false)
     }
-  }, [customerMsg, customerId, corpId, sessionId, staffId])
+  }, [canStartGeneration, isGroupChat, customerId, staffId, chatId, corpId])
 
   useEffect(() => {
     const init = async () => {
       setLoading(true)
       try {
-        const res = await fetch(`/api/v1/conversations/last-message?customerId=${customerId}&corpId=${corpId}`)
+        // 单聊获取最后一条消息用于展示（限定当前销售与学员的对话，避免串消息）
-        const data = await res.json()
+        if (!isGroupChat && customerId && staffId) {
-        if (data.code === 0 && data.data?.content) {
+          const res = await fetch(`/api/v1/conversations/last-message?customerId=${customerId}&staffId=${staffId}&corpId=${corpId}`)
-          setCustomerMsg(data.data.content)
+          const data = await res.json()
-        } else {
+          if (data.code === 0 && data.data?.content) {
-          setLoading(false)
+            setCustomerMsg(data.data.content)
-          setError('暂无学员最新消息')
+          }
         }
       } catch (e) {
-        console.error('初始化失败:', e)
+        console.error('获取学员消息失败:', e)
+      }
+
+      if (canStartGeneration()) {
+        startGeneration()
+      } else {
         setLoading(false)
-        setError('获取学员消息失败')
+        setError('未获取到聊天上下文')
       }
     }
     init()
     return () => { closeSse() }
-  }, [customerId, corpId, closeSse])
+  }, [customerId, staffId, corpId, chatContext, isGroupChat, closeSse, startGeneration, canStartGeneration])
-
-  useEffect(() => {
-    if (customerMsg.trim() && !generating && utterances.length === 0) {
-      startGeneration()
-    }
-  }, [customerMsg, generating, utterances.length, startGeneration])
 
   if (loading && !generating && utterances.length === 0) {
     return (
       <div style={{ padding: 60, textAlign: 'center' }}>
         <SpinLoading style={{ '--size': '32px' } as any} />
-        <div style={{ marginTop: 16, color: '#999', fontSize: 14 }}>正在分析学员消息...</div>
+        <div style={{ marginTop: 16, color: '#999', fontSize: 14 }}>
+          {isGroupChat ? '正在分析群聊消息...' : '正在分析学员消息...'}
+        </div>
       </div>
     )
   }
 
   return (
     <div style={{ padding: 12, background: '#f5f5f5', minHeight: '100vh' }}>
-      {/* 学员消息 + 标签 */}
+      {/* 学员/群聊消息 + 标签 */}
       <div style={{
         background: '#fff',
         borderRadius: 12,
@@ -286,7 +256,9 @@ export default function ScriptRecommendStream({ userInfo, customerId: propCustom
         boxShadow: '0 1px 4px rgba(0,0,0,0.06)'
       }}>
         <div style={{ fontSize: 13, color: '#666', marginBottom: 8 }}>
-          💬 <span style={{ color: '#999' }}>学员消息：</span>
+          💬 <span style={{ color: '#999' }}>
+            {isGroupChat ? '群聊消息' : '学员消息'}：
+          </span>
           <span style={{ color: '#333', fontWeight: 500 }}>{customerMsg || '暂无'}</span>
         </div>
         {profileTags.length > 0 && (
@@ -298,8 +270,8 @@ export default function ScriptRecommendStream({ userInfo, customerId: propCustom
         )}
       </div>
 
-      {/* 生成进度 */}
+      {/* 生成中状态 */}
-      {generating && progress < 100 && (
+      {generating && utterances.every(u => !u.isComplete) && (
         <div style={{
           background: '#fff',
           borderRadius: 12,
@@ -310,14 +282,7 @@ export default function ScriptRecommendStream({ userInfo, customerId: propCustom
           gap: 12
         }}>
           <SpinLoading style={{ '--size': '20px' } as any} />
-          <div style={{ flex: 1 }}>
+          <div style={{ fontSize: 13, color: '#666' }}>AI 正在生成推荐话术...</div>
-            <div style={{ fontSize: 13, color: '#666' }}>
-              {progress < 60 ? '正在分析学员画像和对话历史...' : 'AI 正在生成推荐话术...'}
-            </div>
-            <div style={{ height: 4, background: '#e8e8e8', borderRadius: 2, marginTop: 6, overflow: 'hidden' }}>
-              <div style={{ width: `${progress}%`, height: '100%', background: '#1677ff', borderRadius: 2, transition: 'width 0.3s' }} />
-            </div>
-          </div>
         </div>
       )}