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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apps/backend/app/routers/admin_triggers.py
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177
apps/backend/app/routers/admin_triggers.py
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# -*- coding: utf-8 -*-
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"""管理端 — 触发器统一视图 API
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提供 1 个端点：
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- GET /api/admin/triggers/unified — 聚合三张表的触发器数据
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数据源：
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- biz.trigger_jobs（业务触发器）→ source="biz"
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- biz.ai_trigger_jobs（AI 事件链，最近 100 条）→ source="ai"
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- public.scheduled_tasks（ETL 调度）→ source="etl"
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某数据源查询失败时记录日志，返回其他数据源数据。
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需求: 4.1, 4.2, 4.3
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"""
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from __future__ import annotations
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import logging
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from fastapi import APIRouter, Depends
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from app.auth.dependencies import CurrentUser, get_current_user
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from app.database import get_connection
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from app.schemas.admin_triggers import UnifiedTriggerItem
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/admin/triggers", tags=["系统管理"])
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def _fetch_biz_triggers(conn) -> list[UnifiedTriggerItem]:
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"""查询 biz.trigger_jobs，映射 source='biz'。"""
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with conn.cursor() as cur:
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cur.execute(
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"""
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SELECT id, job_name, trigger_condition, status,
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last_run_at, next_run_at, last_error
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FROM biz.trigger_jobs
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ORDER BY id
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"""
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)
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rows = cur.fetchall()
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return [
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UnifiedTriggerItem(
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id=row[0],
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name=row[1],
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source="biz",
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trigger_condition=row[2] or "",
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status=row[3] or "",
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last_run_at=str(row[4]) if row[4] is not None else None,
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next_run_at=str(row[5]) if row[5] is not None else None,
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last_error=row[6],
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)
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for row in rows
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]
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def _fetch_ai_triggers(conn) -> list[UnifiedTriggerItem]:
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"""查询 biz.ai_trigger_jobs（最近 100 条），映射 source='ai'。
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字段映射（DDL 实际列 → UnifiedTriggerItem）：
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- id → id
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- event_type → name（ai_trigger_jobs 无 job_name 列）
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- 'event' → trigger_condition（AI 触发器均为事件驱动）
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- status → status
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- started_at → last_run_at（ai_trigger_jobs 无 last_run_at 列）
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- None → next_run_at（事件驱动无预定下次执行时间）
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- error_message → last_error（ai_trigger_jobs 列名为 error_message）
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"""
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with conn.cursor() as cur:
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cur.execute(
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"""
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SELECT id, event_type, status,
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started_at, error_message
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FROM biz.ai_trigger_jobs
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ORDER BY id DESC
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LIMIT 100
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"""
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)
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rows = cur.fetchall()
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return [
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UnifiedTriggerItem(
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id=row[0],
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name=row[1] or "",
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source="ai",
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trigger_condition="event",
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status=row[2] or "",
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last_run_at=str(row[3]) if row[3] is not None else None,
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next_run_at=None,
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last_error=row[4],
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)
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for row in rows
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]
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def _fetch_etl_triggers(conn) -> list[UnifiedTriggerItem]:
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"""查询 public.scheduled_tasks，映射 source='etl'。
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字段映射（DDL 实际列 → UnifiedTriggerItem）：
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- id → id（UUID，转为字符串后取 hashcode 作为 int 不合适，改用 row_number）
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- name → name
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- schedule_config->>'schedule_type' → trigger_condition
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- last_status / enabled → status（组合判断）
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- last_run_at → last_run_at
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- next_run_at → next_run_at
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- None → last_error（scheduled_tasks 无 last_error 列）
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注意：scheduled_tasks.id 是 UUID 类型，UnifiedTriggerItem.id 是 int。
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使用 ROW_NUMBER() 生成临时整数 ID，加 100000 偏移避免与其他数据源冲突。
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"""
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with conn.cursor() as cur:
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cur.execute(
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"""
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SELECT ROW_NUMBER() OVER (ORDER BY created_at) + 100000 AS row_id,
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name,
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schedule_config->>'schedule_type' AS schedule_type,
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CASE
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WHEN enabled = FALSE THEN 'disabled'
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WHEN last_status IS NOT NULL THEN last_status
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ELSE 'idle'
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END AS status,
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last_run_at,
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next_run_at
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FROM scheduled_tasks
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ORDER BY created_at
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"""
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)
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rows = cur.fetchall()
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return [
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UnifiedTriggerItem(
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id=int(row[0]),
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name=row[1] or "",
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source="etl",
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trigger_condition=row[2] or "unknown",
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status=row[3] or "idle",
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last_run_at=str(row[4]) if row[4] is not None else None,
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next_run_at=str(row[5]) if row[5] is not None else None,
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last_error=None,
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)
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for row in rows
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]
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@router.get("/unified", response_model=list[UnifiedTriggerItem])
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async def get_unified_triggers(
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user: CurrentUser = Depends(get_current_user),
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) -> list[UnifiedTriggerItem]:
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"""聚合三张表的触发器数据。
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依次查询 biz.trigger_jobs、biz.ai_trigger_jobs、scheduled_tasks，
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某数据源查询失败时记录日志并跳过，返回其他数据源的数据。
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"""
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results: list[UnifiedTriggerItem] = []
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conn = get_connection()
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try:
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# 数据源 1：biz.trigger_jobs
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try:
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results.extend(_fetch_biz_triggers(conn))
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except Exception:
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logger.warning("查询 biz.trigger_jobs 失败", exc_info=True)
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# 数据源 2：biz.ai_trigger_jobs
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try:
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results.extend(_fetch_ai_triggers(conn))
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except Exception:
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logger.warning("查询 biz.ai_trigger_jobs 失败", exc_info=True)
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# 数据源 3：public.scheduled_tasks
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try:
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results.extend(_fetch_etl_triggers(conn))
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except Exception:
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logger.warning("查询 scheduled_tasks 失败", exc_info=True)
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return results
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finally:
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conn.close()
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