feat: 2026-04-15~05-02 累积变更基线 — AI 重构 + Runtime Context + DWS 修复
涵盖（每条对应已存的审计记录）： - AI 模块拆分：apps/backend/app/ai/apps -> prompts/（8 个 APP + app2a 派生） audit: 2026-04-20__ai-module-complete.md - admin-web AI 管理套件：AIDashboard / AIOperations / AIRunLogs / AITriggers / TriggerManager audit: 2026-04-21__admin-web-ai-management-suite.md - App2 财务洞察 prompt v3 -> v5.1 + 小程序 AI 接入（chat / board-finance） audit: 2026-04-22__app2_prompt_v5_1_and_miniprogram_ai_insight.md - App2 prewarm 全过滤器 + AI 触发器 cron reschedule audit: 2026-04-21__app2-finance-prewarm-all-filters.md migration: 20260420_ai_trigger_jobs_and_app2_prewarm.sql / 20260421_app2_prewarm_cron_reschedule.sql - AppType 联合类型对齐 + adminAiAppTypes.test.ts audit: 2026-04-30__admin_web_ai_app_type_alignment.md - DashScope tokens_used 提取修复 audit: 2026-04-30__backend_dashscope_tokens_used_extraction.md - App3 线索完整详情 prompt audit: 2026-05-01__backend_app3_full_detail_prompt.md - Runtime Context 沙箱（5-1~5-2 主线）： - 后端 schema/service + admin_runtime_context / xcx_runtime_clock 两个 router - admin-web RuntimeContext.tsx + miniprogram runtime-clock.ts - migration: 20260501__runtime_context_sandbox.sql - tools/db/verify_admin_web_sandbox.py + verify_sandbox_end_to_end.py - database/changes: 7 份 sandbox_* 验证报告 - 飞球 DWS 修复：finance_area_daily 区域汇总 + task_engine 调整 + RLS 视图业务日上界（migration 20260502 + scripts/ops/gen_rls_business_date_migration.py） 合规： - .gitignore 启用 tmp/ 排除 - 不入仓：apps/etl/connectors/feiqiu/.env（API_TOKEN secret，本地修改保留） 待验证清单： - docs/audit/changes/2026-05-04__cumulative_baseline_pending_verification.md 每个主题的功能完整性 / 上线验证几乎都未收口，按优先级 P0~P3 逐一处理
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apps/backend/app/ai/prompts/app7_customer_prompt.py
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apps/backend/app/ai/prompts/app7_customer_prompt.py
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"""应用 7 客户分析 Prompt 拼装。
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消费链 App8 完成后串行触发，生成客户全量分析与运营策略。
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- 数据源：fetch_member_consumption_data + fetch_member_notes
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- 备注内容标注【来源：XXX，请甄别信息真实性】
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- 输出字段：strategies 数组 + summary
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- system prompt 在百炼控制台配置
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返回：单个 prompt 字符串。
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"""
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from __future__ import annotations
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import asyncio
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import json
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import logging
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from typing import Any
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from app.ai.cache_service import AICacheService
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from app.ai.data_fetchers import fetch_member_consumption_data, fetch_member_notes
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from app.ai.schemas import CacheTypeEnum
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from app.services.runtime_context import as_runtime_business_now_str
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logger = logging.getLogger(__name__)
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_MAX_PROMPT_LEN = 5000
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async def build_prompt(
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context: dict,
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cache_svc: AICacheService | None = None,
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) -> str:
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"""构建 App7 prompt 字符串。
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Args:
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context: site_id, member_id
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Returns:
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JSON 序列化后的 prompt 字符串
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"""
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site_id = context["site_id"]
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member_id = context["member_id"]
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results = await asyncio.gather(
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fetch_member_consumption_data(site_id, member_id),
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fetch_member_notes(site_id, member_id),
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return_exceptions=True,
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)
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warnings: list[str] = []
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if isinstance(results[0], Exception):
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member_data = _default_member_data()
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warnings.append("消费数据获取失败")
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logger.warning("App7 消费数据获取失败: %s", results[0])
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else:
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member_data = results[0]
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notes_raw = results[1] if not isinstance(results[1], Exception) else []
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if isinstance(results[1], Exception):
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warnings.append("备注获取失败")
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logger.warning("App7 备注获取失败: %s", results[1])
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# 主观信息标注来源
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if notes_raw:
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annotated = []
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for note in notes_raw:
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recorded_by = note.get("recorded_by", "未知")
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n = dict(note)
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n["content"] = (
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f"{note.get('content', '')}"
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f"【来源：{recorded_by}，请甄别信息真实性】"
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)
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annotated.append(n)
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subjective_notes: Any = annotated
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else:
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subjective_notes = "该客户暂无主观备注信息"
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payload: dict[str, Any] = {
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"current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
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"member_id": member_id,
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"member_nickname": member_data.get("member_nickname", ""),
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"objective_data": {
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"consumption_records": member_data.get("consumption_records", []) or "该客户暂无消费记录",
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"member_cards": member_data.get("member_cards", []),
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"card_balance_total": member_data.get("card_balance_total", 0),
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"stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
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"expected_visit_date": member_data.get("expected_visit_date"),
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"days_since_last_visit": member_data.get("days_since_last_visit"),
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},
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"subjective_data": {
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"notes": subjective_notes,
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},
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"reference": _build_reference(site_id, member_id, cache_svc),
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}
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if warnings:
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payload["_data_warnings"] = warnings
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return _truncate_payload(payload)
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def _default_member_data() -> dict:
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return {
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"member_nickname": "",
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"consumption_records": [],
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"member_cards": [],
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"card_balance_total": 0,
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"stored_value_balance_total": 0,
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"expected_visit_date": None,
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"days_since_last_visit": None,
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}
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def _build_reference(
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site_id: int,
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member_id: int,
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cache_svc: AICacheService | None,
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) -> dict:
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"""组装 App8 最新 + 最近 2 条历史。"""
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if cache_svc is None:
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return {}
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ref: dict = {}
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target_id = str(member_id)
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latest = cache_svc.get_latest(
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CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id,
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)
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if latest:
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ref["app8_latest"] = {
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"result_json": latest.get("result_json"),
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"generated_at": latest.get("created_at"),
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}
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history = cache_svc.get_history(
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CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
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)
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if history:
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ref["app8_history"] = [
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{"result_json": h.get("result_json"), "generated_at": h.get("created_at")}
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for h in history
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]
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return ref
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def _truncate_payload(payload: dict) -> str:
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"""按优先级截断 consumption_records → notes。"""
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text = json.dumps(payload, ensure_ascii=False, default=str)
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if len(text) <= _MAX_PROMPT_LEN:
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return text
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records = payload["objective_data"].get("consumption_records")
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if isinstance(records, list) and len(records) > 5:
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payload["objective_data"]["consumption_records"] = records[:5]
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payload["objective_data"]["_truncated"] = f"消费记录已截断，原始 {len(records)} 条"
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text = json.dumps(payload, ensure_ascii=False, default=str)
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if len(text) > _MAX_PROMPT_LEN:
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n = payload["subjective_data"].get("notes")
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if isinstance(n, list) and len(n) > 10:
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payload["subjective_data"]["notes"] = n[:10]
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payload["subjective_data"]["_truncated_notes"] = f"备注已截断，原始 {len(n)} 条"
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text = json.dumps(payload, ensure_ascii=False, default=str)
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return text
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