Files
wecom_it_smart_desk/backend/app/models/quiz.py
T
Simon 449c6d4875 feat: 2026-07-12~13 全量更新 - AI对话链路改造+H5 v4/v5+坐席端v5+上下文感知诊断+知识库迭代3
## H5 员工端 v4 (2026-07-13 00:48 已部署)
- 人工按钮三态文案统一为"人工坐席"
- 按钮位置移至发送键和语音按钮上方(垂直堆叠)
- 点按钮直接调 store.shakeAgent(),删除 CallAgentModal 弹窗动画
- 截图快捷键提示改为"截图->粘贴:Alt+Shift+A-Ctrl+V ---> Ctrl+V"
- 移动端隐藏截图提示(CSS 媒体查询)
- AI转人工提示改为"已为您呼叫人工坐席,请稍等!"
- 坐席接入提示改为"坐席正在查看您的信息,请等待处理回复!"
- 删除"摇铃呼叫坐席"入口和文案
- 删除孤儿组件 MessageList.vue + shake 动画 CSS

## H5 员工端 v5 (2026-07-13 02:08 已部署)
- RightPanel v2.1:删除"软件安装"和"资源权限"标签页
- 移除标签栏,智能推荐(DynamicRecommend)直接展示
- 删除 SoftwareDownloads/ApprovalLinks 引用和相关 CSS

## AI 对话链路全栈改造 Phase 1-6 (已部署)
- Phase 1: Dify JSON输出 + 后端blocking解析 + 双WS推送 + 错误降级
- Phase 2: 关键词收窄(~25强意图词) + 两级分类Prompt + 删除前端checkApprovalIntent
- Phase 3: WS扩展(ai_thinking+dynamic_recommend) + ai_structured气泡 + RightPanel v2 + 选项回传
- Phase 4: VisionService接入 + 图片消息融合(5秒窗口) + 降级策略
- Phase 5: 坐席端ai_thinking指示器 + ai_structured/byod_card渲染 + handleNewMessage修复
- Phase 6: diagnosis_stage(6值) + response_time_ms计时 + 慢响应告警(>10s)

## 坐席端 v5 (2026-07-13 01:38 已部署)
- ai_structured/byod_card 只读渲染
- AI思考指示器 UI
- handleNewMessage 透传 msg_type/extra_data 修复
- 布局优化v2.0: QuickReplyBar L1+L2悬浮 + ReplyBox左右分区 + 右栏260/560px切换
- 键盘快捷键v2.3: 纯数字路由 + ESC分层撤销 + Shift+Space用event.code

## 上下文感知智能诊断闭环 (2026-07-12 已部署)
- 三层诊断(API→Script→AI) + 三段排队(VIP→info_locked→not locked)
- 答题插队 + 五场景关闭
- 迁移052(6表+6列) + queue_service + quiz_service + closing_service
- H5前端: QueueWaiting + RightPanel双Tab + InputBar三态 + ResolveConfirmCard
- 坐席前端: pending_close结单流程 + 信息锁定(Dify步骤完成+有效回答率≥70%)

## 知识库迭代3 (2026-07-12 已部署)
- 分诊交互(H5+坐席+Dify独立应用)
- 拓扑预览(ECharts只读)
- 代答排除(4种匹配器: keyword/regex/intent/category)
- 迁移051 + 44文件43测试通过

## 后端变更
- 6个Python文件改造(h5_ai_task.py/h5.py/ai_service.py/closing_service.py等)
- funny_phrase_service.py: shake/connected/keyword 默认文案更新
- session_service.py: 企微消息文案同步
- 新增: queue.py/quiz.py/triage.py/exclusion_rules.py 等API端点
- 新增: diagnostic.py/quiz.py/triage_session.py 等模型
- 新增: closing_service/queue_service/quiz_service/triage_service 等服务

## 文档更新
- CHANGELOG.md: 新增 [未发布] 区全部变更记录
- 项目管理主文档 v2.5: 新增v0.7.3版本 + 已完成看板 + 最近搞定
- 版本记录: 新增v0.7.3条目
- AI对话链路实施计划: Phase 1-6 全部标记已实施
- 新增架构图/时序图/类图(mermaid)

## 部署路径修正
- 服务器项目根路径: /opt/wecom-it-desk/
- 所有前端dist均为ro bind mount,只能在宿主机源路径操作
- 服务器nginx /h5/ 是静态文件服务(非proxy_pass)
- elFinder上传二进制不可靠(MD5不匹配),改用base64分块上传
2026-07-13 02:17:03 +08:00

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# =============================================================================
# 企微IT智能服务台 — 答题与积分模型
# =============================================================================
# 说明:包含3张表,支撑排队等待期间的答题+积分系统:
# 1. quiz_questions: IT知识题库(7类×10题=70题起步)
# 2. quiz_answers: 答题记录(每次答题一条记录)
# 3. employee_points: 员工积分账户(跨会话累积,5级等级体系)
#
# 答题双模式:
# 模式Ainfo_locked=false)— 诊断题:与当前问题相关的选择题,答案附加到会话上下文
# 模式Binfo_locked=true — IT知识题:纯教育性质,提升IT素养
#
# 插队规则:
# queue_priority = min(quiz_answered_count // 3, 2) # 每答3题前移1位,上限2位
# 积分规则:
# 答对 +10分,答错不扣分,跨会话累积
# 0-99 IT小白 → 100-299 IT入门 → 300-599 IT达人 → 600-999 IT专家 → 1000+ IT大师
# =============================================================================
import uuid
from datetime import datetime
from typing import Any, Dict, List, Optional
from sqlalchemy import Boolean, DateTime, Index, Integer, JSON, String, Text
from sqlalchemy.orm import Mapped, mapped_column
from app.database import Base
class QuizQuestion(Base):
"""IT知识题库 — 排队等待期间向员工推送的选择题。
分为两类(通过 type 字段区分):
- knowledge: IT知识题(模式Binfo_locked=true时推送)
- diagnostic: 诊断题(模式Ainfo_locked=false时推送,答案附加到会话上下文)
诊断题按 problem_category 组织,每类3-5题。
知识题按 category 组织,每类10题。
Attributes:
id: 题目唯一标识(UUID)
type: 题目类型(knowledge=IT知识题 / diagnostic=诊断题)
category: 题目类别(network/vpn/email/system/printer/security/office
problem_category: 诊断题对应的问题类别(仅diagnostic类型有效,如"vpn_disconnect"
difficulty: 难度(easy/medium/hard
question: 题目文本
options: 选项数组(JSON["选项A", "选项B", "选项C", "选项D"]
correct_index: 正确答案索引(0-3
explanation: 答案解析
is_active: 是否启用
created_at: 创建时间
"""
__tablename__ = "quiz_questions"
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
)
type: Mapped[str] = mapped_column(
String(20), nullable=False, default="knowledge",
comment="题目类型: knowledge(IT知识题) / diagnostic(诊断题)"
)
category: Mapped[str] = mapped_column(
String(50), nullable=False,
comment="题目类别: network/vpn/email/system/printer/security/office"
)
problem_category: Mapped[Optional[str]] = mapped_column(
String(100), nullable=True,
comment="诊断题对应的问题类别(仅diagnostic类型有效)"
)
difficulty: Mapped[str] = mapped_column(
String(20), nullable=False, default="medium",
comment="难度: easy/medium/hard"
)
question: Mapped[str] = mapped_column(
Text, nullable=False, comment="题目文本"
)
options: Mapped[list] = mapped_column(
JSON, nullable=False, comment="选项数组: ['选项A', '选项B', ...]"
)
correct_index: Mapped[int] = mapped_column(
Integer, nullable=False, comment="正确答案索引(0-based)"
)
explanation: Mapped[Optional[str]] = mapped_column(
Text, nullable=True, comment="答案解析"
)
is_active: Mapped[bool] = mapped_column(
Boolean, nullable=False, default=True, comment="是否启用"
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=datetime.now,
comment="创建时间"
)
__table_args__ = (
Index("idx_quiz_q_type", "type"),
Index("idx_quiz_q_category", "category"),
Index("idx_quiz_q_active", "is_active"),
)
def __repr__(self) -> str:
return f"<QuizQuestion(id={self.id}, type={self.type}, category={self.category})>"
class QuizAnswer(Base):
"""答题记录 — 每次答题一条记录。
Attributes:
id: 记录ID
employee_id: 员工ID
conversation_id: 关联会话ID(可空,非排队时答题无会话)
question_id: 题目ID
selected_index: 员工选择的答案索引
is_correct: 是否答对
points_earned: 获得积分(答对=10,答错=0)
created_at: 答题时间
"""
__tablename__ = "quiz_answers"
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
)
employee_id: Mapped[str] = mapped_column(
String(64), nullable=False, comment="员工ID"
)
conversation_id: Mapped[Optional[str]] = mapped_column(
String(36), nullable=True, comment="关联会话ID"
)
question_id: Mapped[str] = mapped_column(
String(36), nullable=False, comment="题目ID"
)
selected_index: Mapped[int] = mapped_column(
Integer, nullable=False, comment="选择的答案索引"
)
is_correct: Mapped[bool] = mapped_column(
Boolean, nullable=False, comment="是否答对"
)
points_earned: Mapped[int] = mapped_column(
Integer, nullable=False, default=0, comment="获得积分"
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=datetime.now,
comment="答题时间"
)
__table_args__ = (
Index("idx_quiz_a_employee", "employee_id"),
Index("idx_quiz_a_conversation", "conversation_id"),
Index("idx_quiz_a_created", "created_at"),
)
def __repr__(self) -> str:
return f"<QuizAnswer(id={self.id}, employee={self.employee_id}, correct={self.is_correct})>"
class EmployeePoints(Base):
"""员工积分账户 — 跨会话累积,5级等级体系。
积分规则:答对一题 +10分,答错不扣分。
等级体系:
0-99 IT小白 (灰色)
100-299 IT入门 (蓝色)
300-599 IT达人 (绿色)
600-999 IT专家 (琥珀)
1000+ IT大师 (珊瑚红)
Attributes:
employee_id: 员工ID(主键)
total_points: 累计积分
answered_count: 答题总数
correct_count: 答对总数
level: 当前等级名称
updated_at: 最后更新时间
"""
__tablename__ = "employee_points"
employee_id: Mapped[str] = mapped_column(
String(64), primary_key=True, comment="员工ID"
)
total_points: Mapped[int] = mapped_column(
Integer, nullable=False, default=0, comment="累计积分"
)
answered_count: Mapped[int] = mapped_column(
Integer, nullable=False, default=0, comment="答题总数"
)
correct_count: Mapped[int] = mapped_column(
Integer, nullable=False, default=0, comment="答对总数"
)
level: Mapped[str] = mapped_column(
String(20), nullable=False, default="IT小白", comment="当前等级"
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=datetime.now,
onupdate=datetime.now, comment="最后更新时间"
)
def __repr__(self) -> str:
return f"<EmployeePoints(employee={self.employee_id}, points={self.total_points}, level={self.level})>"
@staticmethod
def calculate_level(points: int) -> str:
"""根据积分计算等级名称。
Args:
points: 当前累计积分
Returns:
等级名称字符串
"""
if points >= 1000:
return "IT大师"
elif points >= 600:
return "IT专家"
elif points >= 300:
return "IT达人"
elif points >= 100:
return "IT入门"
else:
return "IT小白"