Phase 2.3 chat 上下文捕获链路从未真正激活到完整工作: - 14 处 ai-float-button 补 sourcePage,chat.ts 三分支同步设 pageFilters.contextId - 后端 page_context 4 层 BUG 修(列名错位 + RLS site_id 未重设) - xcx_chat filters.pop 破坏 body.page_context 引用 — dict() 浅拷贝隔离 - chat 流式 markdown 实时解析(表格/标题/列表/加粗 + KPI 富卡) - reference_card KPI 富卡接入 SSE 路径,db 真写入 - 维客线索 source 显示规则:AI 来源用机器人 icon 替代长文字 数据库: - public.member_retention_clue 加 emoji + runtime_mode + sandbox_instance_id - biz.ai_run_logs 加 assistant_id + 复合索引 - chk_ai_cache_type CHECK 约束 8 类应用名 - cache_type / app_type 命名统一(app6_note / app7_customer / app8_consolidation) - 历史 emoji 抽取脚本 44/44 成功 后端 silent failure 修: - cleanup_service WHERE app_type → cache_type(90 天清理 + 20K 上限重新生效) - _build_ai_insight 字段错位修复(app4 → app7 + 字段对齐 prompt schema) - task_manager talkingPoints 改 app5_tactics + tactics 字段 - task_manager aiSuggestion 改取 one_line_summary - cache_service.CACHE_EXPIRY_DAYS 加 app2a_finance_area - WS /ws/ai-cache 加 token + JWT + site_id 校验(P0 信息泄露漏洞) - internal_ai token 改 hmac.compare_digest 工具/文档: - main.py 加 RotatingFileHandler logs/backend.log + uvicorn /health 过滤 - 新建 utils/clue_category.py(VI 6 类配色 + emoji fallback + source 显示规则) - 新建 utils/markdown.ts(轻量 md 转 rich-text 解析 + streaming 容错) - audit + 数据库变更说明 + backlog §七 #14 收口 + #15-#38 残余子任务 - backlog 追加 §十一 App1 参数/MCP/沙箱审计 + §十二 百炼/SQL MCP 主任务线 实地 MCP 走查:14 入口数据层 + 5 代表入口 sourcePage 注入 + customer-detail 全模块 + chat md 渲染 + reference_card 富卡 都已验证。9 项预先 BUG/UX 登记 §七 #29-#38 后续修复。 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
171 lines
6.0 KiB
Python
171 lines
6.0 KiB
Python
"""应用 5 话术参考 Prompt 拼装。
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App4 完成后串行触发,接收 App4 返回结果作为 task_suggestion。
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- 数据源:fetch_assistant_info + fetch_service_history + fetch_member_consumption_data + fetch_member_notes + context.app4_result
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- 输出字段:tactics 数组(每条含 scenario + script)
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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 (
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fetch_assistant_info,
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fetch_member_consumption_data,
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fetch_member_notes,
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fetch_service_history,
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)
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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 = 8000
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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 App5 prompt 字符串。
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Args:
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context: site_id, assistant_id, member_id, app4_result(dict|None)
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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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assistant_id = context["assistant_id"]
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member_id = context["member_id"]
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task_suggestion = context.get("app4_result") or {}
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results = await asyncio.gather(
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fetch_assistant_info(site_id, assistant_id),
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fetch_service_history(site_id, assistant_id, member_id),
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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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assistant_info = results[0] if not isinstance(results[0], Exception) else {}
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if isinstance(results[0], Exception):
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warnings.append("助教信息获取失败")
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logger.warning("App5 助教信息获取失败: %s", results[0])
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service_history = results[1] if not isinstance(results[1], Exception) else []
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if isinstance(results[1], Exception):
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warnings.append("服务历史获取失败")
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logger.warning("App5 服务历史获取失败: %s", results[1])
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if isinstance(results[2], 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("App5 消费数据获取失败: %s", results[2])
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else:
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member_data = results[2]
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notes = results[3] if not isinstance(results[3], Exception) else []
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if isinstance(results[3], Exception):
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warnings.append("备注获取失败")
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logger.warning("App5 备注获取失败: %s", results[3])
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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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"assistant_id": assistant_id,
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"member_id": member_id,
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"task_suggestion": task_suggestion,
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"assistant_info": assistant_info or "⚠ 助教信息获取失败",
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"service_history": service_history or "暂无服务记录",
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"task_assignment_basis": {
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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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"customer_data": {
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"member_nickname": member_data.get("member_nickname", ""),
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"notes": notes or "暂无备注",
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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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"""组装最近 2 条 App8 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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history = cache_svc.get_history(
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CacheTypeEnum.APP8_CONSOLIDATION.value,
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site_id,
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str(member_id),
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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 service_history → 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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sh = payload.get("service_history")
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if isinstance(sh, list) and len(sh) > 5:
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payload["service_history"] = sh[:5]
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payload["_truncated_service_history"] = f"服务记录已截断,原始 {len(sh)} 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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records = payload["task_assignment_basis"].get("consumption_records")
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if isinstance(records, list) and len(records) > 5:
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payload["task_assignment_basis"]["consumption_records"] = records[:5]
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payload["task_assignment_basis"]["_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["customer_data"].get("notes")
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if isinstance(n, list) and len(n) > 10:
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payload["customer_data"]["notes"] = n[:10]
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payload["customer_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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