Neo-ZQYY/apps/backend/app/ai/prompts/app3_clue_prompt.py

"""应用 3 客户数据维客线索分析 Prompt 拼装。

消费事件触发，从客户消费数据提取维客线索。
- 数据源：fetch_member_consumption_data（DWS）
- 金额口径：items_sum（禁止 consume_money）
- 线索 category：客户基础 / 消费习惯 / 玩法偏好（3 选 1）
- 线索 providers 统一为"系统"
- system prompt 在百炼控制台配置，本模块只拼数据上下文 JSON

返回：单个 prompt 字符串（直接传给 Application.call）。
"""

from __future__ import annotations

import json
import logging
from typing import Any

from app.ai.cache_service import AICacheService
from app.ai.data_fetchers import fetch_member_consumption_data
from app.ai.schemas import CacheTypeEnum
from app.services.runtime_context import as_runtime_business_now_str

logger = logging.getLogger(__name__)

# prompt 观测阈值：历史上 4000 字会触发裁剪；现保留完整消费明细，仅用于测试/审计参考
_MAX_PROMPT_LEN = 4000


async def build_prompt(
    context: dict,
    cache_svc: AICacheService | None = None,
) -> str:
    """构建 App3 prompt 字符串。

    Args:
        context: site_id, member_id
        cache_svc: 缓存服务，用于读取 reference 历史数据

    Returns:
        JSON 序列化后的 prompt 字符串
    """
    site_id = context["site_id"]
    member_id = context["member_id"]

    # 数据获取（失败降级）
    fetch_failed = False
    try:
        member_data = await fetch_member_consumption_data(site_id, member_id)
    except Exception:
        logger.warning(
            "App3 消费数据获取失败: site_id=%s member_id=%s",
            site_id, member_id, exc_info=True,
        )
        member_data = _default_member_data()
        fetch_failed = True

    consumption_records = member_data.get("consumption_records") or []
    if not consumption_records:
        consumption_records = (
            "⚠ 消费数据获取失败，该客户暂无消费记录可供分析"
            if fetch_failed else "该客户暂无消费记录"
        )

    payload: dict[str, Any] = {
        "current_time": as_runtime_business_now_str(site_id, fmt="%Y-%m-%d %H:%M"),
        "member_id": member_id,
        "member_nickname": member_data.get("member_nickname", ""),
        "main_data": {
            "consumption_records": consumption_records,
            "member_cards": member_data.get("member_cards", []),
            "card_balance_total": member_data.get("card_balance_total", 0),
            "stored_value_balance_total": member_data.get("stored_value_balance_total", 0),
            "expected_visit_date": member_data.get("expected_visit_date"),
            "days_since_last_visit": member_data.get("days_since_last_visit"),
        },
        "reference": _build_reference(site_id, member_id, cache_svc),
    }

    # 完整明细策略：App3 需要尽量保留消费行为模式，不在本地裁剪消费记录。
    # 真实 App3 完整 100 条明细调用已验证可在 180s 单步超时内返回。
    text = json.dumps(payload, ensure_ascii=False, default=str)
    return text


def _default_member_data() -> dict:
    return {
        "member_nickname": "",
        "consumption_records": [],
        "member_cards": [],
        "card_balance_total": 0,
        "stored_value_balance_total": 0,
        "expected_visit_date": None,
        "days_since_last_visit": None,
    }


def _build_reference(
    site_id: int,
    member_id: int,
    cache_svc: AICacheService | None,
) -> dict:
    """组装参考字段：App6 备注线索最新 + App8 历史最近 2 条。"""
    if cache_svc is None:
        return {}

    ref: dict = {}
    target_id = str(member_id)

    app6_latest = cache_svc.get_latest(
        CacheTypeEnum.APP6_NOTE_ANALYSIS.value, site_id, target_id,
    )
    if app6_latest:
        ref["app6_note_clues"] = {
            "result_json": app6_latest.get("result_json"),
            "generated_at": app6_latest.get("created_at"),
        }

    app8_history = cache_svc.get_history(
        CacheTypeEnum.APP8_CLUE_CONSOLIDATED.value, site_id, target_id, limit=2,
    )
    if app8_history:
        ref["app8_history"] = [
            {
                "result_json": h.get("result_json"),
                "generated_at": h.get("created_at"),
            }
            for h in app8_history
        ]

    return ref