353 lines
12 KiB
Python
353 lines
12 KiB
Python
"""
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报价工作表映射 mode：上传时用千问产出 mappingJson。
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本文件职责：加载映射分析提示词、拼用户消息、调千问、剥 Markdown、校验 JSON、
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对照单元格清单做缺项检测，必要时再补跑一轮。
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禁止：发明运价；在企微回调线程同步调用；出单阶段再调本 mode。
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"""
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from __future__ import annotations
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import json
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import logging
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import re
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from pathlib import Path
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from typing import Any, Optional
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from agent.llm.modes import LlmMode
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logger = logging.getLogger(__name__)
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MODE = LlmMode.SHEET_MAP
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_PROMPT_CACHE: str | None = None
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# 清单原文片段 → 白名单 code（用于缺项检测；不要求全覆盖词典）
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_LABEL_TO_CODE: list[tuple[tuple[str, ...], str]] = [
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(("提货地址", "Place of Receipt", "place of receipt"), "pickup_address"),
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(("送货地址", "派送地址", "Place of Delivery", "place of delivery"), "delivery_address"),
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(("货值", "Cargo Value", "cargo value"), "cargo_value"),
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(("海关编码", "HS Code", "HS编码", "hs code"), "hs_code"),
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(("油、电、磁", "油,电,磁", "油电磁", "IL, ELEC", "L,ELEC", "oil"), "oil_elec_mag"),
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(("特殊说明", "特别说明", "Special Remarks"), "special_remarks"),
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(("要求货物到达", "Requested Arriv", "抵达时间"), "eta_request"),
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(("运输时效", "Transit Time", "航程时间", "Navigation time"), "transit_time"),
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(("船期", "Sailing", "Requested Sh"), "sailing_schedule"),
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(("开船日", "On Board"), "on_board_date"),
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(("船公司", "Shipping Line", "Shipping Co"), "shipping_line"),
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(("货好时间", "Cargo Ready"), "cargo_ready_date"),
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(("贸易条款", "Terms"), "trade_terms"),
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(("整柜或散货", "整柜或拼柜", "FCL or LCL"), "fcl_or_lcl"),
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(("箱型", "柜量", "Type & Qty", "Cont."), "container_type_qty"),
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(("起运港", "POL"), "pol"),
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(("目的港", "POD"), "pod"),
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(("品名", "Commodity"), "commodity"),
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(("货物数量", "Quantity"), "quantity"),
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(("询价日期", "Inquiry Date", "报价日期"), "quote_date"),
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(("RFQ", "询价单号", "报价单编号"), "quote_no"),
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(("有效期", "period"), "valid_until"),
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]
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_SEA_FEE_MARKERS: list[tuple[tuple[str, ...], tuple[str, ...]]] = [
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# (清单关键词, 可匹配的 feeRegion id/title/tmsSource 子串)
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(
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("始发港费用", "Origin Charges"),
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("origin_charges", "polcost", "始发港", "origin"),
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),
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(
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("海运费用", "Ocean Freight"),
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("ocean_freight", "oceancost", "海运费用", "ocean"),
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),
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(
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("目的港费用", "Destination Charges"),
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("destination_charges", "podcost", "目的港", "destination"),
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),
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]
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def mode_meta() -> dict[str, Any]:
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return {
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"mode": MODE.value,
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"provider": "qwen",
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"purpose": "sheet_map",
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"implemented": True,
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}
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def _prompt_path() -> Path:
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return Path(__file__).resolve().parents[1] / "quote_templates" / "prompts" / "mapping_analyzer.txt"
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def load_system_prompt() -> str:
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"""加载映射分析器系统提示词（仓库内只读资源）。"""
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global _PROMPT_CACHE
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if _PROMPT_CACHE is not None:
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return _PROMPT_CACHE
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path = _prompt_path()
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text = path.read_text(encoding="utf-8")
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_PROMPT_CACHE = text
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return text
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def _inventory_lines(payload: dict[str, Any]) -> list[str]:
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inventory = payload.get("cellInventory") or payload.get("cell_inventory") or []
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if isinstance(inventory, list):
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return [str(x) for x in inventory]
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return [str(inventory)]
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def _inventory_blob(payload: dict[str, Any]) -> str:
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return "\n".join(_inventory_lines(payload))
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def build_user_message(payload: dict[str, Any], *, gaps: list[str] | None = None) -> str:
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"""
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组装用户消息：运输方式 + 文件名 + 工作表 + 单元格清单。
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gaps 非空时追加补全指令（第二轮）。
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"""
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mode = str(payload.get("transportMode") or payload.get("transport_mode") or "sea").strip()
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mode_cn = {"sea": "海运", "air": "空运", "land": "陆运"}.get(mode, mode)
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file_name = str(payload.get("fileName") or payload.get("file_name") or "")
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sheet = str(payload.get("sheet") or "")
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lines = _inventory_lines(payload)
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max_lines = 2200
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truncated_note = ""
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if len(lines) > max_lines:
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lines = lines[:max_lines]
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truncated_note = f"\n（单元格清单已截断至前 {max_lines} 行）\n"
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body = "\n".join(lines)
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gap_block = ""
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if gaps:
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gap_lines = "\n".join(f"- {g}" for g in gaps)
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gap_block = (
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"\n【补跑缺口】上一轮 mapping 缺少以下项，请输出完整 mappingJson（不要只回增量）：\n"
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f"{gap_lines}\n"
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)
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return (
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f"运输方式：{mode_cn}\n"
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f"模板文件名：{file_name}\n"
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f"工作表名：{sheet}\n"
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f"单元格清单：地址 | 原文 | 合并范围 | 填充色\n"
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f"{body}"
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f"{truncated_note}"
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f"{gap_block}\n"
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"输出前自检 fields 与 feeRegions/routeRegions 是否覆盖清单中的可见业务标签，"
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"再只输出 mappingJson。"
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)
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def strip_json_fence(raw: str) -> str:
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"""去掉模型可能包的 Markdown 代码围栏。"""
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text = (raw or "").strip()
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if not text:
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return ""
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fence = re.match(r"^```(?:json)?\s*([\s\S]*?)\s*```$", text, re.IGNORECASE)
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if fence:
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return fence.group(1).strip()
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# 偶发前后解释：取第一个 { 到最后一个 }
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start = text.find("{")
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end = text.rfind("}")
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if start >= 0 and end > start:
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return text[start : end + 1]
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return text
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def parse_mapping_json(raw: str) -> dict[str, Any]:
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"""
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解析模型正文为 mapping 对象。
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成功：{ok:True, mapping:dict}
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失败：{ok:False, error:str}
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"""
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cleaned = strip_json_fence(raw)
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if not cleaned:
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return {"ok": False, "error": "模型返回空内容"}
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try:
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data = json.loads(cleaned)
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except json.JSONDecodeError as exc:
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return {"ok": False, "error": f"mappingJson 不是合法 JSON: {exc}"}
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if not isinstance(data, dict):
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return {"ok": False, "error": "mappingJson 不是对象"}
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if not isinstance(data.get("fields"), dict):
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data["fields"] = data.get("fields") if isinstance(data.get("fields"), dict) else {}
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data.setdefault("schemaVersion", "quote-template-mapping-v1")
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return {"ok": True, "mapping": data}
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def assess_mapping_gaps(payload: dict[str, Any], mapping: dict[str, Any] | None) -> list[str]:
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"""
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对照单元格清单，列出 mapping 明显缺口（中文说明，供补跑用户消息）。
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不打外网。海运：费用段标题出现则要求对应 feeRegion；常见业务标签出现则要求 fields code。
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"""
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blob = _inventory_blob(payload)
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if not blob.strip():
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return []
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mapping = mapping or {}
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fields = mapping.get("fields") if isinstance(mapping.get("fields"), dict) else {}
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field_codes = {str(k) for k in fields.keys()}
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fee_regions = mapping.get("feeRegions") if isinstance(mapping.get("feeRegions"), list) else []
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fee_blob = " ".join(
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str(r.get("id") or "")
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+ " "
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+ str(r.get("title") or "")
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+ " "
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+ str(r.get("tmsSource") or "")
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for r in fee_regions
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if isinstance(r, dict)
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).lower()
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gaps: list[str] = []
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mode = str(payload.get("transportMode") or payload.get("transport_mode") or "sea").strip().lower()
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if mode in ("sea", "海运"):
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for markers, matchers in _SEA_FEE_MARKERS:
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if not any(m in blob for m in markers):
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continue
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if not any(x in fee_blob for x in matchers):
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gaps.append(f"费用区缺失：清单有「{markers[0]}」，须建对应 feeRegion")
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for labels, code in _LABEL_TO_CODE:
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if code in field_codes:
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continue
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if any(lab in blob for lab in labels):
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gaps.append(f"字段缺失：清单有「{labels[0]}」→ 应映射 {code}")
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return gaps
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def invoke_shell(*, payload: dict[str, Any]) -> dict[str, Any]:
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"""
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无网/单测入口：若带 assistant_json 则直接解析；否则返回未实现。
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"""
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raw = payload.get("assistant_json") or payload.get("content")
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if raw is not None:
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parsed = parse_mapping_json(str(raw))
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parsed["stub"] = True
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parsed["mode"] = MODE.value
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return parsed
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return {
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"ok": False,
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"stub": True,
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"mode": MODE.value,
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"error": "sheet_map_shell_needs_assistant_json_or_network",
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"echo_keys": sorted(payload.keys()),
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}
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def _chat_once(
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*,
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chat: Any,
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payload: dict[str, Any],
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gaps: list[str] | None = None,
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) -> dict[str, Any]:
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messages = [
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{"role": "system", "content": load_system_prompt()},
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{"role": "user", "content": build_user_message(payload, gaps=gaps)},
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]
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result = chat(mode=MODE, messages=messages, temperature=0.0)
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if not getattr(result, "ok", False):
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err = str(getattr(result, "error", "") or "qwen_failed")
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logger.warning("sheet_map 失败 versionId=%s err=%s", payload.get("versionId"), err)
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return {
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"ok": False,
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"error": _humanize_llm_error(err),
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"mapping": None,
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"provider": getattr(result, "provider", "qwen"),
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}
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parsed = parse_mapping_json(str(result.content or ""))
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if not parsed.get("ok"):
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return {
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"ok": False,
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"error": str(parsed.get("error") or "解析 mapping 失败"),
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"mapping": None,
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"raw_preview": str(result.content or "")[:240],
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}
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return {
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"ok": True,
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"mapping": parsed["mapping"],
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"provider": getattr(result, "provider", "qwen"),
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}
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def invoke_sheet_map(
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payload: dict[str, Any],
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*,
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allow_network: bool = False,
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chat_fn: Optional[Any] = None,
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timeout_seconds: float = 180.0,
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) -> dict[str, Any]:
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"""
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调用千问产出 mappingJson；若对照清单有明显缺口，再补跑一轮（最多 2 次 chat）。
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allow_network=False 且无 chat_fn：不打外网。
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副作用：可能出站 HTTPS；应在 Worker HTTP 槽内调用。
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"""
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if chat_fn is None and not allow_network:
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return {"ok": False, "error": "sheet_map_network_disabled", "mapping": None}
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from agent.llm.http_client import LlmHttpClient
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if chat_fn is None:
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client = LlmHttpClient.from_settings()
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client.timeout_seconds = float(timeout_seconds)
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chat = client.chat
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else:
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chat = chat_fn
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first = _chat_once(chat=chat, payload=payload, gaps=None)
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if not first.get("ok"):
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return first
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mapping = first["mapping"]
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gaps = assess_mapping_gaps(payload, mapping)
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rounds = 1
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if gaps:
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logger.info(
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"sheet_map gaps versionId=%s n=%s sample=%s",
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payload.get("versionId"),
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len(gaps),
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gaps[:5],
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)
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second = _chat_once(chat=chat, payload=payload, gaps=gaps)
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rounds = 2
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if second.get("ok") and second.get("mapping"):
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mapping = second["mapping"]
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# 第二轮仍失败结构时保留第一轮
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elif not second.get("ok"):
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logger.warning(
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"sheet_map 补跑失败，保留第一轮 versionId=%s err=%s",
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payload.get("versionId"),
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second.get("error"),
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)
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remaining = assess_mapping_gaps(payload, mapping)
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# 缺口落进 mappingJson，主账/后台可直接展示「表上有、未映射上」
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if isinstance(mapping, dict):
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mapping["mappingGaps"] = list(remaining)
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logger.info(
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"sheet_map ok versionId=%s rounds=%s fields=%s feeRegions=%s routeRegions=%s remain_gaps=%s",
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payload.get("versionId"),
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rounds,
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len((mapping or {}).get("fields") or {}),
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len((mapping or {}).get("feeRegions") or []),
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len((mapping or {}).get("routeRegions") or []),
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len(remaining),
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)
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return {
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"ok": True,
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"mapping": mapping,
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"provider": first.get("provider", "qwen"),
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"rounds": rounds,
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"gaps_after": remaining,
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}
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def _humanize_llm_error(err: str) -> str:
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e = (err or "").strip()
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if e == "llm_data_usage_not_confirmed":
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return "未确认 LLM 数据用途（LLM_DATA_USAGE_CONFIRMED），无法调用千问"
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if e == "qwen_not_configured":
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return "千问未配置（QWEN_API_KEY / QWEN_BASE_URL）"
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if e.startswith("http_"):
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return f"千问 HTTP 失败: {e}"
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return f"千问调用失败: {e[:180]}"
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