feat: 累积功能变更 — 聊天集成、租户管理、小程序更新、ETL 增强、迁移脚本
包含多个会话的累积代码变更： - backend: AI 聊天服务、触发器调度、认证增强、WebSocket、调度器最小间隔 - admin-web: ETL 状态页、任务管理、调度配置、登录优化 - miniprogram: 看板页面、聊天集成、UI 组件、导航更新 - etl: DWS 新任务（finance_area_daily/board_cache）、连接器增强 - tenant-admin: 项目初始化 - db: 19 个迁移脚本（etl_feiqiu 11 + zqyy_app 8） - packages/shared: 枚举和工具函数更新 - tools: 数据库工具、报表生成、健康检查 - docs: PRD/架构/部署/合约文档更新 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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docs/prd/Neo_Specs/review-audit/P5.1-NS3-10.md
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docs/prd/Neo_Specs/review-audit/P5.1-NS3-10.md
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# P5.1→NS3 缺失项 #10：AI 生成内容的审计日志
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## 简要结论
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- 状态：✅ 已解决
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- 风险等级：🟡 低
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- `biz.ai_conversations` + `biz.ai_messages` 两张表已完整记录"谁在什么时候对哪个客户生成了什么"，满足审计日志需求
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## 详细审查
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### 审查范围
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- `apps/backend/app/ai/conversation_service.py` — 对话持久化服务
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- `apps/backend/app/services/chat_service.py` — Chat 模块服务
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- `docs/database/ddl/zqyy_app__biz.sql` — biz schema DDL 基线
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- `db/zqyy_app/migrations/2026-03-20__rns14_chat_module_extend.sql` — Chat 模块扩展迁移
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- `apps/backend/app/ai/apps/app5_tactics.py` — 典型 App 调用流程（审计写入示例）
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### 发现
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#### ✅ 审计信息完整记录
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**1. `biz.ai_conversations` 表 — 对话级审计**
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| 字段 | 类型 | 审计用途 |
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|------|------|----------|
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| `id` | bigint PK | 对话唯一标识 |
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| `user_id` | varchar(50) NOT NULL | **谁**：操作用户 ID（系统自动调用时为 `'system'`） |
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| `nickname` | varchar(100) | 用户昵称 |
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| `app_id` | varchar(30) NOT NULL | **什么应用**：app1_chat / app2_finance / ... / app8_consolidation |
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| `site_id` | bigint NOT NULL | **哪个门店** |
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| `source_page` | varchar(100) | 触发来源页面 |
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| `source_context` | jsonb | 上下文信息（含 `assistant_id`、`member_id` 等 → **对哪个客户**） |
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| `context_type` | varchar(20) | 对话关联类型：task/customer/coach/general |
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| `context_id` | varchar(50) | 关联 ID（taskId/customerId/coachId） |
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| `title` | varchar(200) | 对话标题 |
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| `created_at` | timestamptz | **什么时候** |
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**2. `biz.ai_messages` 表 — 消息级审计**
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| 字段 | 类型 | 审计用途 |
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|------|------|----------|
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| `id` | bigint PK | 消息唯一标识 |
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| `conversation_id` | bigint FK | 关联对话 |
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| `role` | varchar(10) | system / user / assistant |
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| `content` | text NOT NULL | **生成了什么**：完整的 AI 输入和输出内容 |
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| `tokens_used` | integer | Token 消耗量 |
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| `reference_card` | jsonb | 引用卡片数据 |
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| `created_at` | timestamptz | 消息时间戳 |
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**3. 写入时机**
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所有 8 个 AI 应用在每次调用时都通过 `ConversationService` 写入完整审计链：
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```
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create_conversation(user_id, nickname, app_id, site_id, source_context)
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→ add_message(role="system", content=prompt)
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→ add_message(role="user", content=user_input)
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→ 调用百炼 API
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→ add_message(role="assistant", content=ai_output, tokens_used=N)
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```
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**4. 索引支持审计查询**
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```sql
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-- 按用户+门店查询历史对话
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CREATE INDEX idx_ai_conv_user_site ON biz.ai_conversations (user_id, site_id, created_at DESC);
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-- 按应用+门店查询
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CREATE INDEX idx_ai_conv_app_site ON biz.ai_conversations (app_id, site_id, created_at DESC);
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-- 按上下文查询（客户/任务/助教维度）
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CREATE INDEX idx_ai_conv_context ON biz.ai_conversations (user_id, site_id, context_type, context_id, ...);
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-- 按对话查询消息
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CREATE INDEX idx_ai_msg_conv ON biz.ai_messages (conversation_id, created_at);
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```
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### 证据
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**App5 审计写入示例（app5_tactics.py L240-268）**：
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```python
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# 创建对话记录
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conversation_id = conv_svc.create_conversation(
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user_id=user_id, nickname=nickname,
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app_id=APP_ID, site_id=site_id,
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source_context={"assistant_id": assistant_id, "member_id": member_id},
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)
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# 写入 system + user 消息
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conv_svc.add_message(conversation_id=conversation_id, role="system", content=...)
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conv_svc.add_message(conversation_id=conversation_id, role="user", content=...)
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# 调用 AI 后写入 assistant 消息
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result, tokens_used = await bailian.chat_json(messages)
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conv_svc.add_message(
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conversation_id=conversation_id, role="assistant",
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content=json.dumps(result, ensure_ascii=False),
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tokens_used=tokens_used,
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)
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```
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**DDL 基线确认（zqyy_app__biz.sql）**：
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```sql
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CREATE TABLE biz.ai_conversations (
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id bigint ... NOT NULL,
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user_id character varying(50) NOT NULL,
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nickname character varying(100) ...,
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app_id character varying(30) NOT NULL,
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site_id bigint NOT NULL,
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source_page character varying(100),
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source_context jsonb,
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context_type character varying(20),
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context_id character varying(50),
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...
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created_at timestamp with time zone DEFAULT now() NOT NULL
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);
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CREATE TABLE biz.ai_messages (
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id bigint ... NOT NULL,
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conversation_id bigint NOT NULL,
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role character varying(10) NOT NULL,
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content text NOT NULL,
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tokens_used integer,
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reference_card jsonb,
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created_at timestamp with time zone DEFAULT now() NOT NULL
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);
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```
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### 建议
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审计日志功能已完整实现，以下为可选增强方向（非必须）：
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1. **审计查询 API**：当前仅有面向用户的历史对话查询（`get_conversations`），可增加面向管理员的审计查询接口（按时间范围、app_id、site_id 筛选）
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2. **数据保留策略**：当前无自动清理机制，长期运行后 `ai_messages.content` 可能占用大量存储，建议制定保留策略
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