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
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jiao
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AGENTS.md
40
AGENTS.md
@ -20,17 +20,36 @@
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# 1. 本地构建
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cd frontend/sidebar && npm run build
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# 2. 同步到服务器
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# 2. 同步到服务器（注意带 JS hash 的文件名会变化）
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scp -r -o StrictHostKeyChecking=no -i root.pem frontend/sidebar/dist/* root@8.133.162.25:/www/wwwroot/deploy-package/frontend/sidebar/dist/
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# 3. SSH 登录服务器，重新构建镜像并重启容器
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# 3. SSH 登录服务器，更新 index.html 缓存戳并重启容器
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ssh -o StrictHostKeyChecking=no -i root.pem root@8.133.162.25 << 'EOF'
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cd /www/wwwroot/deploy-package/frontend/sidebar
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docker build -t deploy-package-sidebar .
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docker stop ai-assistant-sidebar
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docker rm ai-assistant-sidebar
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cd /www/wwwroot/deploy-package
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docker-compose up -d sidebar
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cd /www/wwwroot/deploy-package/frontend/sidebar/dist
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# 更新 index.html 中的 JS/CSS 引用，带上版本戳防缓存
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JS_FILE=$(ls assets/index-*.js | head -1)
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CSS_FILE=$(ls assets/index-*.css | head -1)
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cat > index.html << HTML
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<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
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<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate" />
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<title>AI坐席助手</title>
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<script src="https://res.wx.qq.com/open/js/jweixin-1.2.0.js"></script>
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<script type="module" crossorigin src="/sidebar/$JS_FILE?v=$(date +%s)"></script>
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<link rel="stylesheet" crossorigin href="/sidebar/$CSS_FILE?v=$(date +%s)">
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</head>
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<body>
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<div id="root"></div>
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</body>
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</html>
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HTML
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# 复制到容器并重启
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docker cp . ai-assistant-sidebar:/usr/share/nginx/html/
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docker exec ai-assistant-sidebar nginx -s reload
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docker restart ai-assistant-nginx
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EOF
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```
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@ -92,9 +111,12 @@ cd backend/auth-service && mvn clean package -DskipTests
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scp -o StrictHostKeyChecking=no -i root.pem target/*.jar root@8.133.162.25:/www/wwwroot/deploy-package/backend/auth-service/
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# 3. SSH 登录服务器，重启对应容器
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# ⚠️ 注意：Dockerfile 中 COPY 的是 app.jar，必须先把新 jar 复制为 app.jar
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ssh -o StrictHostKeyChecking=no -i root.pem root@8.133.162.25 << 'EOF'
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cd /www/wwwroot/deploy-package/backend/auth-service
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cp auth-service-*.jar app.jar
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cd /www/wwwroot/deploy-package
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docker-compose up -d --build auth-service
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docker-compose up -d --build --no-cache auth-service
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EOF
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```
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@ -65,15 +65,17 @@ public class ConversationController {
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@GetMapping("/last-message")
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public Result<Map<String, Object>> getLastMessage(
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@NotBlank(message = "customerId不能为空") @RequestParam("customerId") String customerId,
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@NotBlank(message = "staffId不能为空") @RequestParam("staffId") String staffId,
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@NotBlank(message = "corpId不能为空") @RequestParam("corpId") String corpId) {
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ArchiveMessage message = archiveMessageMapper.selectLastMessage(customerId, corpId);
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ArchiveMessage message = archiveMessageMapper.selectLastMessage(customerId, staffId, corpId);
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Map<String, Object> result = new HashMap<>();
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if (message != null) {
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result.put("content", message.getContent());
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result.put("msgTime", message.getMsgtime());
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result.put("msgType", message.getMsgtype());
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result.put("fromUser", message.getFromUser());
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result.put("fromRole", message.getFromRole());
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}
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return Result.success(result);
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}
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@ -9,11 +9,18 @@ import org.apache.ibatis.annotations.Select;
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@Mapper
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public interface ArchiveMessageMapper extends BaseMapper<ArchiveMessage> {
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/**
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* 获取指定学员在指定对话中的最后一条消息
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* 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
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*/
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@Select("SELECT * FROM archive_messages " +
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"WHERE (from_user = #{userId} OR to_user LIKE CONCAT('%', #{userId}, '%')) " +
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"WHERE from_user = #{userId} " +
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"AND to_user LIKE CONCAT('%', #{staffId}, '%') " +
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"AND corp_id = #{corpId} " +
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"AND from_role = 'EXTERNAL' " +
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"AND content IS NOT NULL AND content != '' " +
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"ORDER BY msgtime DESC LIMIT 1")
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ArchiveMessage selectLastMessage(@Param("userId") String userId,
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@Param("staffId") String staffId,
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@Param("corpId") String corpId);
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}
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@ -9,13 +9,19 @@ import com.artedu.generation.service.PromptEngine;
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import com.artedu.generation.service.QianwenClient;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.http.MediaType;
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import org.springframework.validation.annotation.Validated;
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import org.springframework.web.bind.annotation.*;
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import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
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import javax.validation.constraints.NotBlank;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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@Slf4j
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@Validated
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@ -35,6 +41,73 @@ public class GenerationController {
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@Autowired
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private ArchiveMessageMapper archiveMessageMapper;
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private final ExecutorService sseExecutor = Executors.newCachedThreadPool();
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private static final List<Map<String, String>> STYLES = List.of(
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Map.of("id", "friendly", "name", "亲和风格", "desc", "温暖亲切，像朋友聊天"),
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Map.of("id", "professional", "name", "专业风格", "desc", "数据驱动，专业权威"),
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Map.of("id", "urgent", "name", "促单风格", "desc", "制造紧迫感，促成决策")
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);
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/**
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* 根据当前聊天对象自动推断员工身份
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* 前端不知道 toUser 时调用，后端从聊天记录中反推
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*/
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@GetMapping("/whoami")
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public Result<Map<String, Object>> whoami(
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@RequestParam(value = "fromUser", required = false) String fromUser,
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@RequestParam(value = "roomid", required = false) String roomid) {
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String staffId = null;
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String chatType = null;
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if (roomid != null && !roomid.isEmpty()) {
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// 群聊：从群消息中找最近一条 INTERNAL 角色的发送者
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chatType = "group";
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List<ArchiveMessage> msgs = archiveMessageMapper.selectGroupChatMessages(
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roomid, get7DaysAgoStartTime(), getTodayEndTime());
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if (msgs != null && !msgs.isEmpty()) {
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for (ArchiveMessage msg : msgs) {
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if ("INTERNAL".equals(msg.getFromRole())) {
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staffId = msg.getFromUser();
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break;
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}
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}
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}
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} else if (fromUser != null && !fromUser.isEmpty()) {
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// 单聊：查该客户最近参与的所有消息，推断员工
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chatType = "single";
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List<ArchiveMessage> msgs = archiveMessageMapper.selectMessagesByFromUser(
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fromUser, get7DaysAgoStartTime(), getTodayEndTime());
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if (msgs != null && !msgs.isEmpty()) {
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// 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
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ArchiveMessage msg = msgs.get(0);
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if (fromUser.equals(msg.getFromUser())) {
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// 客户发的消息，to_user 里的是员工ID（JSON数组）
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staffId = msg.getToUser();
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} else {
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// 员工发的消息，from_user 就是员工ID
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staffId = msg.getFromUser();
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}
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// 清理 JSON 数组格式 ["userId"]
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if (staffId != null) {
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staffId = staffId.replaceAll("\\[|\\]|\"", "").trim();
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}
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}
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}
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if (staffId == null || staffId.isEmpty()) {
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return Result.fail("未找到聊天记录，无法推断员工身份");
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}
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Map<String, Object> result = new HashMap<>();
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result.put("userId", staffId);
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result.put("chatType", chatType);
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result.put("fromUser", fromUser);
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result.put("roomid", roomid);
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return Result.success(result);
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}
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@PostMapping("/utterance")
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public Result<Map<String, Object>> generateUtterance(
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@RequestParam(value = "fromUser", required = false) String fromUser,
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@ -62,18 +135,25 @@ public class GenerationController {
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List<ArchiveMessage> messages;
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boolean isGroupChat = roomid != null && !roomid.isEmpty();
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long startTime = getTodayStartTime();
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// 查最近 7 天，避免今天没聊天就找不到记录
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long startTime = get7DaysAgoStartTime();
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long endTime = getTodayEndTime();
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if (isGroupChat) {
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messages = archiveMessageMapper.selectGroupChatMessages(roomid, startTime, endTime);
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} else {
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if (fromUser == null || fromUser.isEmpty() || toUser == null || toUser.isEmpty()) {
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log.warn("单聊模式需要fromUser和toUser参数");
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if (fromUser == null || fromUser.isEmpty()) {
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log.warn("单聊模式需要fromUser参数");
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return null;
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}
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toUser = "[\""+toUser+"\"]";
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messages = archiveMessageMapper.selectSingleChatMessages(fromUser, toUser, startTime, endTime);
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// toUser 为空或无效时，用兜底查询（根据 fromUser 查所有相关记录）
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if (toUser == null || toUser.isEmpty() || "staff_001".equals(toUser)) {
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log.warn("toUser无效，使用兜底查询, fromUser={}, toUser={}", fromUser, toUser);
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messages = archiveMessageMapper.selectMessagesByFromUser(fromUser, startTime, endTime);
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} else {
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toUser = "[\""+toUser+"\"]";
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messages = archiveMessageMapper.selectSingleChatMessages(fromUser, toUser, startTime, endTime);
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}
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}
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if (messages == null || messages.isEmpty()) {
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@ -95,6 +175,120 @@ public class GenerationController {
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return java.time.LocalDate.now().plusDays(1).atStartOfDay(java.time.ZoneId.systemDefault()).toInstant().toEpochMilli() - 1;
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}
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private long get7DaysAgoStartTime() {
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return java.time.LocalDate.now().minusDays(7).atStartOfDay(java.time.ZoneId.systemDefault()).toInstant().toEpochMilli();
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}
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/**
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* 流式生成多风格话术（SSE）
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* 页面打开即自动推荐 3 条不同风格话术
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*/
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@GetMapping(value = "/utterance-stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
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public SseEmitter streamUtterance(
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@RequestParam("fromUser") String fromUser,
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@RequestParam("toUser") String toUser,
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@RequestParam(value = "roomid", required = false) String roomid) {
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SseEmitter emitter = new SseEmitter(120000L);
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sseExecutor.execute(() -> {
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try {
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Map<String, Object> startEvent = new HashMap<>();
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startEvent.put("type", "start");
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startEvent.put("styles", STYLES);
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emitter.send(SseEmitter.event().name("start").data(startEvent));
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String chatContext = buildChatContext(fromUser, toUser, roomid);
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if (chatContext == null || chatContext.isEmpty()) {
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Map<String, Object> err = new HashMap<>();
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err.put("type", "error");
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err.put("message", "未找到聊天记录");
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emitter.send(SseEmitter.event().name("error").data(err));
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emitter.complete();
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return;
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}
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String systemPrompt = promptEngine.buildSystemPrompt(chatContext);
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String userPrompt = promptEngine.buildMultiStyleUserPrompt();
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long startTime = System.currentTimeMillis();
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String generated = qianwenClient.generate(systemPrompt, userPrompt, 1200);
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log.info("多风格话术生成完成, elapsed={}ms", System.currentTimeMillis() - startTime);
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List<String> utterances = parseMultiStyle(generated);
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if (utterances.size() < 3) {
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while (utterances.size() < 3) {
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utterances.add(generated != null ? generated : "生成失败，请稍后重试");
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}
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}
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for (int i = 0; i < Math.min(3, utterances.size()); i++) {
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String text = utterances.get(i);
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String styleId = STYLES.get(i).get("id");
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Map<String, Object> itemStart = new HashMap<>();
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itemStart.put("type", "item-start");
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itemStart.put("styleId", styleId);
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itemStart.put("index", i);
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emitter.send(SseEmitter.event().name("item-start").data(itemStart));
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for (int j = 0; j < text.length(); j++) {
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String ch = text.substring(j, j + 1);
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Map<String, Object> chunk = new HashMap<>();
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chunk.put("type", "chunk");
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chunk.put("styleId", styleId);
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chunk.put("text", ch);
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chunk.put("index", i);
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emitter.send(SseEmitter.event().name("chunk").data(chunk));
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Thread.sleep(25);
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}
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Map<String, Object> complete = new HashMap<>();
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complete.put("type", "complete");
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complete.put("styleId", styleId);
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complete.put("fullText", text);
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complete.put("index", i);
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emitter.send(SseEmitter.event().name("complete").data(complete));
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}
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Map<String, Object> done = new HashMap<>();
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done.put("type", "done");
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done.put("model", qianwenClient.getCurrentModel() != null
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? qianwenClient.getCurrentModel().getModelName() : "default");
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emitter.send(SseEmitter.event().name("done").data(done));
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emitter.complete();
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} catch (Exception e) {
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log.error("流式生成失败", e);
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try {
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Map<String, Object> error = new HashMap<>();
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error.put("type", "error");
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error.put("message", e.getMessage());
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emitter.send(SseEmitter.event().name("error").data(error));
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} catch (IOException ignored) {}
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emitter.completeWithError(e);
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}
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});
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return emitter;
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}
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/**
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* 解析多风格话术，按 "|||" 分隔
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*/
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private List<String> parseMultiStyle(String text) {
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List<String> result = new ArrayList<>();
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if (text == null || text.isEmpty()) return result;
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String[] parts = text.split("\\|\\|\\|");
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for (String part : parts) {
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String trimmed = part.trim();
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if (!trimmed.isEmpty() && trimmed.length() > 5) {
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result.add(trimmed);
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}
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}
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return result;
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}
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@PostMapping("/summary")
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public Result<Map<String, Object>> generateSummary(
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@NotBlank(message = "context不能为空") @RequestParam("context") String context) {
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@ -36,4 +36,26 @@ public interface ArchiveMessageMapper extends BaseMapper<ArchiveMessage> {
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List<ArchiveMessage> selectGroupChatMessages(@Param("roomid") String roomid,
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@Param("startTime") Long startTime,
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@Param("endTime") Long endTime);
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/**
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* 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）
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*/
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@Select("SELECT msgtime, created_at, from_user, to_user, from_role, content FROM archive_messages " +
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"WHERE (from_user = #{fromUser} OR to_user = #{fromUser}) " +
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"AND msgtime >= #{startTime} AND msgtime < #{endTime} AND msgtype='text' " +
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"AND content IS NOT NULL AND content != '' " +
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"ORDER BY msgtime DESC LIMIT 100")
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List<ArchiveMessage> selectMessagesByFromUser(@Param("fromUser") String fromUser,
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@Param("startTime") Long startTime,
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@Param("endTime") Long endTime);
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/**
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* 根据 fromUser 查询最近一条消息的 to_user（推断员工身份）
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* to_user 格式为 JSON 数组 ["userId"]
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*/
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@Select("SELECT to_user FROM archive_messages " +
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"WHERE (from_user = #{fromUser} OR to_user LIKE CONCAT('%', #{fromUser}, '%')) " +
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"AND msgtype='text' AND content IS NOT NULL AND content != '' " +
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"ORDER BY msgtime DESC LIMIT 1")
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String selectRecentToUserByFromUser(@Param("fromUser") String fromUser);
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}
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@ -129,6 +129,30 @@ public class PromptEngine {
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return sb.toString();
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}
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/**
|
||||
* 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;
|
||||
}
|
||||
|
||||
Binary file not shown.
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@ -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
|
||||
|
||||
@ -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
|
||||
|
||||
@ -1,86 +1,129 @@
|
||||
import { useEffect, useState } from 'react'
|
||||
import { Tabs, Toast } from 'antd-mobile'
|
||||
import { useEffect, useState, useCallback } from 'react'
|
||||
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' | 'error'>('loading')
|
||||
const [authState, setAuthState] = useState<'loading' | 'authed' | 'needLogin' | '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 data = await res.json()
|
||||
if (data.code === 0 && data.data) {
|
||||
localStorage.setItem('staff_token', data.data.token)
|
||||
setUserInfo(data.data)
|
||||
setAuthState('authed')
|
||||
} else {
|
||||
setAuthState('error')
|
||||
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 ${token}` }
|
||||
})
|
||||
const data = await res.json()
|
||||
if (data.code === 0 && data.data) {
|
||||
setUserInfo(data.data)
|
||||
setAuthState('authed')
|
||||
} else {
|
||||
redirectToOAuth()
|
||||
}
|
||||
} else {
|
||||
redirectToOAuth()
|
||||
}
|
||||
const cleanUrl = window.location.pathname + window.location.hash
|
||||
window.history.replaceState({}, document.title, cleanUrl)
|
||||
|
||||
const ok = await tryCodeLogin(code)
|
||||
if (ok) return
|
||||
// login 失败 → 可能是 code 过期/已被使用，显示登录按钮让用户手动重试
|
||||
setAuthState('needLogin')
|
||||
return
|
||||
}
|
||||
|
||||
// 2. 无 code → 检查 localStorage 缓存
|
||||
const cachedUserId = localStorage.getItem('staff_user_id')
|
||||
const cachedUserName = localStorage.getItem('staff_user_name')
|
||||
const cachedToken = localStorage.getItem('staff_token')
|
||||
if (cachedUserId && cachedToken) {
|
||||
setUserInfo({
|
||||
userId: cachedUserId,
|
||||
userName: cachedUserName || cachedUserId,
|
||||
avatar: localStorage.getItem('staff_avatar') || '',
|
||||
corpId: CORPID,
|
||||
role: localStorage.getItem('staff_role') || 'SEAT'
|
||||
})
|
||||
setAuthState('authed')
|
||||
console.log('使用缓存员工信息:', cachedUserId)
|
||||
return
|
||||
}
|
||||
|
||||
// 3. 无 code 无缓存 → 显示登录按钮（iframe 中自动跳转可能被拦截）
|
||||
setAuthState('needLogin')
|
||||
|
||||
} catch (e) {
|
||||
console.error('initAuth error:', e)
|
||||
setAuthState('error')
|
||||
Toast.show({ content: '初始化失败', icon: 'fail' })
|
||||
}
|
||||
}
|
||||
|
||||
const redirectToOAuth = () => {
|
||||
setAuthState('authed')
|
||||
setUserInfo({
|
||||
userId: 'staff_001',
|
||||
userName: '测试顾问',
|
||||
corpId: 'wwd483c2fba24ae30a',
|
||||
role: 'SEAT'
|
||||
})
|
||||
// 用 code 调后端 login 接口
|
||||
const tryCodeLogin = async (code: string): Promise<boolean> => {
|
||||
try {
|
||||
const res = await noCacheFetch(`/api/v1/auth/login?code=${encodeURIComponent(code)}`, { method: 'POST' })
|
||||
const data = await res.json()
|
||||
if (data.code === 0 && data.data) {
|
||||
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=${AGENTID}&state=sidebar#wechat_redirect`
|
||||
console.log('跳转企微 OAuth:', oauthUrl)
|
||||
window.location.href = oauthUrl
|
||||
}
|
||||
|
||||
// ========== JS-SDK 初始化（认证完成后调用）==========
|
||||
const initWxConfig = async () => {
|
||||
const wx = (window as any).wx
|
||||
if (!wx || !wx.config) {
|
||||
console.log('非企微环境，跳过JS-SDK初始化')
|
||||
console.log('非企微环境，跳过 JS-SDK')
|
||||
return
|
||||
}
|
||||
|
||||
try {
|
||||
const currentUrl = window.location.href.split('#')[0]
|
||||
const currentUrl = window.location.href.split('#')[0]
|
||||
|
||||
// 1. 企业级 wx.config
|
||||
const corpRes = await fetch(`/api/v1/auth/signature?url=${encodeURIComponent(currentUrl)}`)
|
||||
try {
|
||||
const corpRes = await noCacheFetch(`/api/v1/auth/signature?url=${encodeURIComponent(currentUrl)}`)
|
||||
const corpData = await corpRes.json()
|
||||
if (corpData.code !== 0 || !corpData.data) {
|
||||
console.error('获取JS-SDK企业签名失败')
|
||||
return
|
||||
}
|
||||
if (corpData.code !== 0 || !corpData.data) return
|
||||
|
||||
const cfg = corpData.data
|
||||
wx.config({
|
||||
@ -94,13 +137,9 @@ function App() {
|
||||
})
|
||||
|
||||
wx.ready(async () => {
|
||||
console.log('JS-SDK wx.config 成功')
|
||||
|
||||
// 2. 尝试应用级 agentConfig（获取客户联系权限）
|
||||
try {
|
||||
const agentRes = await fetch(`/api/v1/auth/signature?type=agent&agentId=1000021&url=${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')
|
||||
// agentConfig 成功后，获取当前客户ID
|
||||
wx.invoke('getContext', {}, (ctx: any) => {
|
||||
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) => {
|
||||
console.warn('⚠️ agentConfig 失败（无客户联系权限）:', err.err_msg || err)
|
||||
fallbackToCachedId()
|
||||
}
|
||||
fail: (err: any) => console.warn('agentConfig fail:', err)
|
||||
})
|
||||
} else {
|
||||
console.warn('⚠️ 获取应用签名失败:', agentData.message)
|
||||
fallbackToCachedId()
|
||||
}
|
||||
} catch (e) {
|
||||
console.warn('⚠️ agentConfig 流程异常:', e)
|
||||
fallbackToCachedId()
|
||||
console.error('agentConfig error:', e)
|
||||
}
|
||||
})
|
||||
|
||||
wx.error((err: any) => {
|
||||
console.error('JS-SDK wx.config 失败:', err)
|
||||
fallbackToCachedId()
|
||||
})
|
||||
wx.error((err: any) => console.error('wx.config error:', err))
|
||||
} catch (e) {
|
||||
console.error('初始化JS-SDK异常:', e)
|
||||
fallbackToCachedId()
|
||||
console.error('initWxConfig error:', e)
|
||||
}
|
||||
}
|
||||
|
||||
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}>
|
||||
<Tabs.Tab title="智能推荐" key="recommend">
|
||||
<ScriptRecommendStream userInfo={userInfo} customerId={currentCustomerId} />
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab title="对话分析" key="analysis">
|
||||
<ConversationAnalysis userInfo={userInfo} />
|
||||
</Tabs.Tab>
|
||||
</Tabs>
|
||||
{/* 顶部员工信息栏 */}
|
||||
<div style={{
|
||||
display: 'flex',
|
||||
alignItems: 'center',
|
||||
justifyContent: 'space-between',
|
||||
padding: '8px 12px',
|
||||
background: '#fff',
|
||||
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>
|
||||
)
|
||||
}
|
||||
|
||||
@ -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') || 'wx_001'
|
||||
const staffId = userInfo?.userId || 'staff_001'
|
||||
const customerId = propCustomerId || localStorage.getItem('current_customer_id') || ''
|
||||
const staffId = userInfo?.userId || ''
|
||||
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()) {
|
||||
setError('暂无学员消息')
|
||||
if (!canStartGeneration()) {
|
||||
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([
|
||||
fetch(`/api/v1/intent/profile/${encodeURIComponent(customerId)}?corpId=${corpId}`),
|
||||
fetch(`/api/v1/conversations/${sessionId}/context`).catch(() => null),
|
||||
fetch(`/api/v1/recommend/get?${new URLSearchParams({
|
||||
sessionId, customerId, staffId, corpId,
|
||||
intentCode: 'INT-COURSE-01',
|
||||
stage: 'STAGE-03',
|
||||
studentType: '零基础',
|
||||
message: customerMsg
|
||||
}).toString()}`, { method: 'POST' }).catch(() => null)
|
||||
])
|
||||
|
||||
let customerProfileStr = ''
|
||||
let tags: string[] = []
|
||||
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}：${m.content}`
|
||||
}).join('\n')
|
||||
// 单聊才获取画像标签
|
||||
if (!isGroupChat && customerId) {
|
||||
const profileRes = await fetch(`/api/v1/intent/profile/${encodeURIComponent(customerId)}?corpId=${corpId}`)
|
||||
const profileData = await profileRes.json()
|
||||
if (profileData.code === 0 && profileData.data) {
|
||||
const p = profileData.data
|
||||
const tags: string[] = []
|
||||
if (p.currentOccupation) tags.push(p.currentOccupation)
|
||||
if (p.studentType) tags.push(p.studentType)
|
||||
if (p.skillLevel) tags.push(p.skillLevel)
|
||||
if (p.intentLevel) tags.push(p.intentLevel)
|
||||
if (p.concernFocus) tags.push(p.concernFocus)
|
||||
if (p.decisionStage) tags.push(p.decisionStage)
|
||||
setProfileTags(tags)
|
||||
}
|
||||
}
|
||||
|
||||
let referenceUtterancesStr = ''
|
||||
if (recommendRes) {
|
||||
const recData = await recommendRes.json()
|
||||
if (recData.code === 0 && recData.data) {
|
||||
const top3 = recData.data.slice(0, 3)
|
||||
referenceUtterancesStr = top3.map((s: any, i: number) => `${i + 1}. "${s.contentText || s.content || s.title}"`).join('\n')
|
||||
}
|
||||
// 构建 SSE URL：群聊传 roomid，单聊传 fromUser+toUser
|
||||
const params = new URLSearchParams()
|
||||
if (isGroupChat && chatId) {
|
||||
params.append('roomid', chatId)
|
||||
} else if (customerId && staffId) {
|
||||
params.append('fromUser', customerId)
|
||||
params.append('toUser', staffId)
|
||||
}
|
||||
setProgress(50)
|
||||
|
||||
const params = new URLSearchParams({
|
||||
message: customerMsg,
|
||||
intent: 'INT-COURSE-01',
|
||||
stage: 'STAGE-03',
|
||||
stageLabel: '方案呈现',
|
||||
intentLabel: '课程咨询'
|
||||
})
|
||||
if (customerProfileStr) params.append('customerProfile', customerProfileStr)
|
||||
if (conversationContextStr) params.append('conversationContext', conversationContextStr)
|
||||
if (referenceUtterancesStr) params.append('referenceUtterances', referenceUtterancesStr)
|
||||
|
||||
const url = `/api/v1/generation/utterance-stream?${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}`)
|
||||
const data = await res.json()
|
||||
if (data.code === 0 && data.data?.content) {
|
||||
setCustomerMsg(data.data.content)
|
||||
} else {
|
||||
setLoading(false)
|
||||
setError('暂无学员最新消息')
|
||||
// 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）
|
||||
if (!isGroupChat && customerId && staffId) {
|
||||
const res = await fetch(`/api/v1/conversations/last-message?customerId=${customerId}&staffId=${staffId}&corpId=${corpId}`)
|
||||
const data = await res.json()
|
||||
if (data.code === 0 && data.data?.content) {
|
||||
setCustomerMsg(data.data.content)
|
||||
}
|
||||
}
|
||||
} 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])
|
||||
|
||||
useEffect(() => {
|
||||
if (customerMsg.trim() && !generating && utterances.length === 0) {
|
||||
startGeneration()
|
||||
}
|
||||
}, [customerMsg, generating, utterances.length, startGeneration])
|
||||
}, [customerId, staffId, corpId, chatContext, isGroupChat, closeSse, startGeneration, canStartGeneration])
|
||||
|
||||
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 */}
|
||||
{generating && progress < 100 && (
|
||||
{/* 生成中状态 */}
|
||||
{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' }}>
|
||||
{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 style={{ fontSize: 13, color: '#666' }}>AI 正在生成推荐话术...</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user