baseline: 批次A-D 成果 + membership 半成品（测试红）
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"""AI 经营问答（批次 B3）：白名单工具取数 → LLM 组织语言。
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安全设计（计划要求"只读、不给 LLM 写权限"）：
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- 取数完全由本模块的**白名单工具**完成，LLM 只拿到聚合后的数字，不能生成查询；
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- 所有工具都是只读 ORM，且强制 `tenant=tenant`（越权查他租户不可能）；
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- 无 LLM KEY 时返回结构化数据 + `llm_enhanced=False`（前端可隐藏入口）。
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"""
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from __future__ import annotations
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from datetime import date, timedelta
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from . import llm
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# 意图 → 工具名（关键词命中即取该工具数据）
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INTENT_KEYWORDS = [
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("sales", ["销售", "卖了", "营收", "营业额", "出货"]),
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("receivable", ["应收", "欠款", "回款", "催收", "未收", "账款"]),
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("inventory", ["库存", "存货", "积压", "周转", "缺货"]),
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("purchase", ["采购", "进货", "买入"]),
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("profit", ["利润", "毛利", "赚", "成本", "盈利"]),
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("ranking", ["排行", "最好卖", "畅销", "大客户", "top", "TOP"]),
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]
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def detect_intents(question: str) -> list:
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"""按关键词命中意图；都没命中则给一个"全局概览"。"""
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q = question or ""
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hits = [name for name, kws in INTENT_KEYWORDS if any(k in q for k in kws)]
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return hits or ["overview"]
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# ------------------------------------------------------------
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# 白名单工具（全部只读 + 租户隔离）
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# ------------------------------------------------------------
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def tool_sales(tenant) -> dict:
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from apps.report.services import get_dashboard_summary
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s = get_dashboard_summary(tenant)
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return {"本月销售额": float(s["month_sales"]["amount"]),
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"本月销售单数": s["month_sales"]["count"]}
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def tool_purchase(tenant) -> dict:
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from apps.report.services import get_dashboard_summary
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s = get_dashboard_summary(tenant)
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return {"本月采购额": float(s["month_purchase"]["amount"]),
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"本月进货单数": s["month_purchase"]["count"]}
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def tool_inventory(tenant) -> dict:
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from apps.report.services import get_dashboard_summary
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s = get_dashboard_summary(tenant)
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return {"库存估值": float(s["inventory"]["valuation"]),
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"SKU 数": s["inventory"]["sku_count"],
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"库存件数": float(s["inventory"]["total_quantity"])}
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def tool_receivable(tenant) -> dict:
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from decimal import Decimal
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from apps.finance.models import Receivable
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from apps.finance.services import receivable_aging
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aging = receivable_aging(tenant)
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overdue_amount = Decimal("0")
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for b in aging["buckets"]:
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if b["bucket"] not in ("0-30",):
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overdue_amount += Decimal(str(b["amount"]))
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return {
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"应收未结合计": float(aging["total"]),
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"其中 30 天以上": float(overdue_amount),
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"账龄分桶": {b["bucket"]: float(b["amount"]) for b in aging["buckets"]},
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}
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def tool_profit(tenant) -> dict:
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from apps.finance import services as fin_services
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period = fin_services.current_period(tenant)
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if period is None:
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return {"本月营业收入": 0.0, "本月营业成本": 0.0,
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"本月毛利": 0.0, "本月净利润": 0.0}
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data = fin_services.income_statement(tenant, period)
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return {
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"本月营业收入": float(data.get("total_revenue") or 0),
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"本月营业成本": float(data.get("cogs") or 0),
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"本月毛利": float(data.get("gross_profit") or 0),
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"本月净利润": float(data.get("net_profit") or 0),
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}
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def tool_ranking(tenant) -> dict:
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from apps.report.services import get_sales_rank
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today = date.today()
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start = today - timedelta(days=30)
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prods = get_sales_rank(tenant, start_date=start, rank_by="product", top_n=5)
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custs = get_sales_rank(tenant, start_date=start, rank_by="customer", top_n=5)
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return {
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"近30天商品排行": [
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{"商品": p["product_name"], "销售额": float(p["total_amount"])} for p in prods
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],
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"近30天客户排行": [
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{"客户": c["customer_name"], "销售额": float(c["total_amount"])} for c in custs
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],
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}
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def tool_risk(tenant) -> dict:
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from . import risk as ai_risk
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top = ai_risk.risk_ranking(tenant, top_n=5)
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return {
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"风险客户TOP5": [
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{"客户": r["customer_name"], "风险分": r["score"],
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"档位": r["level"], "未结": r["outstanding"]}
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for r in top
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]
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}
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TOOLS = {
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"sales": tool_sales,
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"purchase": tool_purchase,
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"inventory": tool_inventory,
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"receivable": tool_receivable,
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"profit": tool_profit,
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"ranking": tool_ranking,
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"risk": tool_risk,
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}
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def gather(tenant, question: str) -> dict:
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"""按意图取数：返回 {intents, data}。'overview' 时给全景四项。"""
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intents = detect_intents(question)
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if intents == ["overview"]:
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intents = ["sales", "receivable", "inventory", "profit"]
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data = {}
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for name in intents:
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fn = TOOLS.get(name)
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if fn is None:
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continue
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try:
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data[name] = fn(tenant)
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except Exception as exc: # 单个工具失败不影响整体问答
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data[name] = {"error": str(exc)}
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return {"intents": intents, "data": data}
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ASK_PROMPT = """你是经销商进销存系统的"老板参谋"。下面是系统实时取到的经营数据（JSON），
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请用中文回答老板的问题：先给结论，再给 1-2 条可执行建议。总长不超过 120 字。
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问题：{question}
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数据：{data}
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"""
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def answer(tenant, question: str) -> dict:
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"""问答主入口：取数 →（有 LLM 则）组织语言。"""
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gathered = gather(tenant, question)
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payload = {
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"question": question,
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"intents": gathered["intents"],
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"data": gathered["data"],
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"llm_enhanced": False,
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"answer": None,
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}
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if llm.available():
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import json
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text = llm.collect_advice(
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ASK_PROMPT.format(question=question,
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data=json.dumps(gathered["data"], ensure_ascii=False))
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)
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if text:
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payload["answer"] = text
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payload["llm_enhanced"] = True
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if not payload["answer"]:
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payload["answer"] = _stat_answer(gathered)
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return payload
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def _stat_answer(gathered: dict) -> str:
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"""无 LLM 时的统计口径回答（结构化文本，保证功能不空转）。"""
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parts = []
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d = gathered["data"]
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if "sales" in d and "error" not in d["sales"]:
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parts.append(f"本月销售额 ¥{d['sales'].get('本月销售额', 0):,.2f}"
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f"（{d['sales'].get('本月销售单数', 0)} 单）")
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if "purchase" in d and "error" not in d["purchase"]:
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parts.append(f"本月采购额 ¥{d['purchase'].get('本月采购额', 0):,.2f}")
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if "receivable" in d and "error" not in d["receivable"]:
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parts.append(f"应收未结 ¥{d['receivable'].get('应收未结合计', 0):,.2f}"
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f"，其中 30 天以上 ¥{d['receivable'].get('其中 30 天以上', 0):,.2f}")
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if "inventory" in d and "error" not in d["inventory"]:
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parts.append(f"库存估值 ¥{d['inventory'].get('库存估值', 0):,.2f}"
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f"（{d['inventory'].get('SKU 数', 0)} 个 SKU）")
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if "profit" in d and "error" not in d["profit"]:
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parts.append(f"本月净利润 ¥{d['profit'].get('本月净利润', 0):,.2f}")
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if "ranking" in d and "error" not in d["ranking"]:
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top = (d["ranking"].get("近30天商品排行") or [{}])[0]
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if top.get("商品"):
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parts.append(f"近 30 天最畅销：{top['商品']}（¥{top.get('销售额', 0):,.2f}）")
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if "risk" in d and "error" not in d["risk"]:
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risk_top = (d["risk"].get("风险客户TOP5") or [{}])[0]
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if risk_top.get("客户"):
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parts.append(f"应收风险最高：{risk_top['客户']}"
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f"（{risk_top.get('风险分', 0):.0f} 分 / {risk_top.get('档位')}）")
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return "；".join(parts) + "。" if parts else "暂无相关经营数据。"
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