jillion886andCursor
cfbce2fd69
必填核对后再建单；多条线路走 H5 点选；费用只展示该线路 TMS 回包，不套用整单空运费。 Co-authored-by: Cursor <cursoragent@cursor.com>
467 lines
16 KiB
Python
467 lines
16 KiB
Python
"""
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文字询价字段抽取入口。
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本文件职责：生产走 DeepSeek B；单测可注入 facts；无网时只认「键：值」结构化行，不猜港口。
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禁止：用正则把「上海到洛杉矶」拆成起运目的；禁止改六态。
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"""
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from __future__ import annotations
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import logging
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import re
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from typing import Any, Optional
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logger = logging.getLogger(__name__)
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_MODE_WORDS = (
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("空运", "AIR"),
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("海运", "SEA"),
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("陆运", "LAND"),
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)
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# 仅「键：值」一行一条，键必须是合同字段或展示名
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_LABEL_LINE = re.compile(
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r"^(起运地|起运港|目的地|目的港|品名|件数|毛重|体积|重量|重量\(KG\)|体积\(CBM\)|"
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r"包装方式|包装类型|货量|货物数量|整柜或拼柜|箱型箱量|报价日期|运输分类|车型/数量|车型数量|"
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r"贸易条款|货好时间|货源地|提货地址|收货地址|商品海关编码|海关编码|HS编码|HS|是否含油|是否含电|是否含磁|"
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r"客户名称|货值|是否为危险品|通关口岸（非必填）|通关口岸)\s*[:：]\s*(.+)$"
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)
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_LABEL_INLINE = re.compile(
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r"(起运地|起运港|目的地|目的港|品名|件数|毛重|体积|重量|重量\(KG\)|体积\(CBM\)|"
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r"包装方式|包装类型|货量|货物数量|整柜或拼柜|箱型箱量|报价日期|运输分类|车型/数量|车型数量|"
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r"贸易条款|货好时间|货源地|提货地址|收货地址|商品海关编码|海关编码|HS编码|HS|是否含油|是否含电|是否含磁|"
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r"客户名称|货值|是否为危险品|通关口岸（非必填）|通关口岸)\s*[:：]\s*(\S+)"
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)
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# 陆运核对卡非必填：销售可能写「通关口岸皇岗」或照抄「通关口岸（非必填）：皇岗」。长词优先。
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_OPTIONAL_INQUIRY_LABELS = (
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"通关口岸（非必填）",
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"通关口岸",
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"货源地（非必填）",
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"货好时间（非必填）",
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"提货地址（非必填）",
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"收货地址（非必填）",
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"贸易条款（非必填）",
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"起运港（非必填）",
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"货源地",
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"货好时间",
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"提货地址",
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"收货地址",
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"贸易条款",
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"起运港",
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)
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# 群里协同标签，冒号可省略：「客户名称张三」「货值 10万」。长词优先。
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_COLLAB_LABELS = (
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"是否为危险品",
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"商品海关编码",
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"车型/数量",
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"包装方式",
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"客户名称",
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"海关编码",
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"贸易条款",
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"货好时间",
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"是否含油",
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"是否含电",
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"是否含磁",
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"HS编码",
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"货值",
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"HS",
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)
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def detect_transport_mode(text: str) -> str:
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"""
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运输方式：空运/海运/陆运，或空运口语「飞」（南京飞吉隆坡）。
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写了海运/陆运以书面为准。只说飞就是空运，补问件数时不得再问运输方式。
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"""
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raw = text or ""
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found = [code for word, code in _MODE_WORDS if word in raw]
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if len(found) == 1:
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return found[0]
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if len(found) > 1:
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return ""
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if "飞" in raw:
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return "AIR"
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return ""
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def parse_labeled_facts(text: str) -> dict[str, str]:
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"""只采集「字段名：值」，整行优先；同一句里的标签也收。不猜港口。"""
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facts: dict[str, str] = {}
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raw = text or ""
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for line in raw.splitlines():
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m = _LABEL_LINE.match(line.strip())
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if m:
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facts[m.group(1)] = m.group(2).strip()
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if facts:
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return facts
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for m in _LABEL_INLINE.finditer(raw):
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facts[m.group(1)] = m.group(2).strip()
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return facts
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def _merge_spoken_collab(text: str, facts: dict[str, str]) -> dict[str, str]:
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"""
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私聊已经说到的协同项写进事实，进群才能预填。
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不覆盖已有询价键。不拿去补问、不挡查价。
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"""
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from agent.schema.field_validate import harvest_oral_collab, normalize_facts
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merged = dict(facts or {})
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extra = dict(harvest_oral_collab(text))
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extra.update(normalize_facts(harvest_collab_labels(text)))
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for key, val in extra.items():
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if val and not str(merged.get(key) or "").strip():
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merged[key] = val
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return merged
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def extract_inquiry_snapshot(
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text: str,
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*,
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injected_facts: Optional[dict[str, Any]] = None,
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injected_mode: str = "",
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b_result: Optional[dict[str, Any]] = None,
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allow_b: bool = False,
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chat_fn: Optional[Any] = None,
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) -> dict[str, Any]:
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"""
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抽出业务线 + 字段快照。
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优先 injected_*（单测）；其次合并标签行与 DeepSeek B（口语）。
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标签行覆盖 B 的同名字段。B 未出现的字段保持空，不本地猜港口。
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件数/毛重/体积若原话已带 TMS 单位（件/KGS/CBM），空字段可机读补上。
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"""
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from agent.schema.field_validate import harvest_oral_collab, harvest_oral_measures, normalize_facts
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if injected_facts is not None:
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mode = (injected_mode or detect_transport_mode(text) or "").upper()
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facts = harvest_oral_measures(text, normalize_facts(dict(injected_facts)))
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facts = _merge_spoken_collab(text, facts)
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facts = _merge_optional_inquiry_labels(text, facts)
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subtype = str(facts.get("运输类型") or "").strip()
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return {
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"business_line": mode,
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"land_subtype": subtype,
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"facts": facts,
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"source": "injected",
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}
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mode = detect_transport_mode(text)
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facts = parse_labeled_facts(text)
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source = "labeled_or_mode"
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b_payload = b_result
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if b_payload is None and (allow_b or chat_fn is not None):
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from agent.llm.mode_extract_fields import invoke_extract_fields
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b_payload = invoke_extract_fields(
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text, allow_network=allow_b, chat_fn=chat_fn
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)
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if isinstance(b_payload, dict) and not b_payload.get("ok"):
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err = str(b_payload.get("error") or "").strip()
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if err not in {"b_network_disabled", "extract_fields_shell_not_implemented"} and (
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allow_b or chat_fn is not None
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):
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return {
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"business_line": mode,
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"land_subtype": "",
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"facts": {},
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"source": "llm_tech_fail",
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"tech_fail": True,
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"tech_error": err or "LLM_FAIL",
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}
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if b_payload and b_payload.get("ok"):
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merged = dict(b_payload.get("facts") or {})
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merged.update(facts)
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facts = merged
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mode = mode or str(b_payload.get("business_line") or "")
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source = "deepseek_b"
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facts = harvest_oral_measures(text, normalize_facts(facts))
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facts = _merge_spoken_collab(text, facts)
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facts = _merge_optional_inquiry_labels(text, facts)
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land_subtype = str((b_payload or {}).get("land_subtype") or facts.get("运输类型") or "").strip()
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if land_subtype and not str(facts.get("运输类型") or "").strip():
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facts["运输类型"] = land_subtype
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if not mode and facts.get("起运港") and facts.get("目的港") and "飞" in (text or ""):
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mode = "AIR"
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logger.info("extract.snapshot mode=%s keys=%s src=%s", mode or "-", sorted(facts), source)
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return {
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"business_line": mode,
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"land_subtype": land_subtype,
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"facts": facts,
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"source": source,
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}
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def harvest_collab_labels(text: str) -> dict[str, str]:
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"""
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群里协同标签：有无冒号都收。
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「客户名称张三 包装方式编织袋 货值 10万」切成三项。
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只说「纸箱」没有标签则不收。值取到下一个标签之前。
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"""
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return _harvest_labels(text, _COLLAB_LABELS)
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def harvest_inquiry_optional_labels(text: str) -> dict[str, str]:
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"""
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陆运询价非必填标签：通关口岸。
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核对卡写「通关口岸（非必填）：」，销售可能照抄或只写「通关口岸皇岗」。
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有无冒号都收。不猜口岸名。
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"""
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return _harvest_labels(text, _OPTIONAL_INQUIRY_LABELS)
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def _merge_optional_inquiry_labels(text: str, facts: dict[str, str]) -> dict[str, str]:
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"""把原话里的通关口岸写进询价事实。有值才覆盖。"""
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from agent.schema.field_validate import normalize_facts
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merged = dict(facts or {})
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extra = normalize_facts(harvest_inquiry_optional_labels(text))
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for key, val in extra.items():
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if val:
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merged[key] = val
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return merged
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def _harvest_labels(text: str, labels: tuple[str, ...]) -> dict[str, str]:
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"""按标签切原话。同一起点只留最长标签。"""
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raw = text or ""
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hits: list[tuple[int, str]] = []
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for label in labels:
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start = 0
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while True:
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pos = raw.find(label, start)
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if pos < 0:
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break
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hits.append((pos, label))
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start = pos + len(label)
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if not hits:
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return {}
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hits.sort()
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# 同一起点只留最长标签，避免 HS 抢 HS编码、通关口岸抢「通关口岸（非必填）」。
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kept: list[tuple[int, str]] = []
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for pos, label in hits:
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if kept and kept[-1][0] == pos and len(label) <= len(kept[-1][1]):
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continue
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if kept and kept[-1][0] == pos:
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kept[-1] = (pos, label)
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continue
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kept.append((pos, label))
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out: dict[str, str] = {}
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for i, (pos, label) in enumerate(kept):
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begin = pos + len(label)
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end = kept[i + 1][0] if i + 1 < len(kept) else len(raw)
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chunk = raw[begin:end]
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chunk = re.sub(r"^[\s:：,，、]+", "", chunk)
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chunk = re.sub(r"[\s,，、]+$", "", chunk)
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if chunk:
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out[label] = chunk
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return out
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def extract_collab_fields(
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text: str,
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*,
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allow_b: bool = False,
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injected: Optional[dict[str, str]] = None,
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allowed_keys: Optional[tuple[str, ...]] = None,
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) -> dict[str, str]:
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"""
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群里协同字段：标签（冒号可省）+ 口语含油/含电/含磁/危险品、货好时间。
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allowed_keys 传入则只返回本单该有的项。不传则海运协同五项 ∪ 贸易条款（陆运跨境仍要）∪ 陆运协同键，给意图分类。
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闲聊、只说「纸箱」不进这里。商品海关编码 / HS 折成 HS编码。
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"""
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from agent.schema.field_validate import (
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ALL_COLLAB_KEYS,
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harvest_oral_collab,
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normalize_facts,
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)
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del allow_b
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keys = tuple(allowed_keys) if allowed_keys is not None else ALL_COLLAB_KEYS
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if injected:
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return {
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k: str(v).strip()
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for k, v in normalize_facts(dict(injected)).items()
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if k in keys and str(v or "").strip()
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}
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labeled = normalize_facts(parse_labeled_facts(text))
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labeled.update(normalize_facts(harvest_collab_labels(text)))
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oral = harvest_oral_collab(text)
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if "是否为危险品" in oral:
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if allowed_keys is not None and "是否为危险品" not in keys:
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oral.pop("是否为危险品", None)
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elif allowed_keys is None:
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raw = text or ""
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if "普货" in raw and not any(
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w in raw for w in ("危险", "非危", "有危", "含危", "是否为危险品")
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):
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oral.pop("是否为危险品", None)
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merged = dict(oral)
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merged.update({k: v for k, v in labeled.items() if v})
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out: dict[str, str] = {}
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for key in keys:
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val = (merged.get(key) or "").strip()
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if val:
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out[key] = val
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return out
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def extract_air_collab_fields(
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text: str,
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*,
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allow_b: bool = False,
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injected: Optional[dict[str, str]] = None,
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) -> dict[str, str]:
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"""
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空运群只认是否含电、是否含磁。
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复用海运口语收割，再滤成这两项。
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"""
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keys = ("是否含电", "是否含磁")
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if injected:
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return {
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k: str(v).strip()
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for k, v in (injected or {}).items()
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if k in keys and str(v or "").strip()
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}
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got = extract_collab_fields(text, allow_b=allow_b)
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return {k: got[k] for k in keys if str(got.get(k) or "").strip()}
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_RE_MONEY = re.compile(
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r"(?:USD|CNY|RMB|美金|美元|人民币)?\s*(\d+(?:\.\d+)?)\s*(?:USD|CNY|RMB|美金|美元|人民币|元)?"
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r"|(?:USD|CNY|RMB|美金|美元)\s*(\d+(?:\.\d+)?)",
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re.I,
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)
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_RE_FEE_LINE = re.compile(
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r"(?P<name>[\u4e00-\u9fffA-Za-z][\u4e00-\u9fffA-Za-z0-9/()（）+＋\-－]{0,24}费|[A-Za-z]{2,10})"
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r"\s*(?:改为|改成|调整为|调整成)?"
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r"\s*[:：=]?"
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r"\s*(?:(?P<ccy1>USD|CNY|RMB|美金|美元|人民币)\s+)?"
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r"(?P<amount>\d+(?:\.\d+)?)"
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r"\s*(?P<ccy2>USD|CNY|RMB|美金|美元|人民币|元)?",
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re.I,
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)
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# 「文件发改为：500」漏了「费」、中间还有冒号，不能丢掉。
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_RE_FEE_CHANGE = re.compile(
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r"(?P<name>[\u4e00-\u9fff]{2,16}?)"
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r"\s*(?:改为|改成|调整为|调整成)"
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r"\s*[:：=]?"
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r"\s*(?P<amount>\d+(?:\.\d+)?)"
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r"\s*(?P<ccy>USD|CNY|RMB|美金|美元|人民币|元)?",
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re.I,
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)
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_SKIP_FEE_NAMES = frozenset({"usd", "cny", "rmb", "美金", "美元", "人民币", "元"})
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_FULLWIDTH_NUM = str.maketrans("０１２３４５６７８９．", "0123456789.")
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def _ascii_amount(raw: str) -> str:
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"""全角数字折成半角，方便和模板金额列对齐。"""
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return (raw or "").translate(_FULLWIDTH_NUM).strip()
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def _currency_of(text: str, hint: str = "") -> str:
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blob = f"{hint} {text}".upper()
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if any(x in blob for x in ("CNY", "RMB", "人民币", "元")):
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return "CNY"
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if any(x in blob for x in ("USD", "美金", "美元")):
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return "USD"
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return hint or "USD"
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def _parse_fee_rows(text: str) -> list[dict[str, str]]:
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"""
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按行抽费用：码头操作费100CNY、报关费改为300CNY。
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只认带「费」的中文名或短英文费用码，避免把工单号当金额。
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"""
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raw = _ascii_amount(text or "")
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rows: list[dict[str, str]] = []
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seen: set[str] = set()
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def _add(name: str, amount: str, ccy: str) -> None:
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if not name or not amount or name.lower() in _SKIP_FEE_NAMES:
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return
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||
# 「WO202609160001」会被 [A-Za-z]{2,10}+数字 抽成费用名 WO，群里发工单号不能当报价。
|
||
if name.upper() == "WO":
|
||
return
|
||
if name in seen:
|
||
return
|
||
seen.add(name)
|
||
rows.append(
|
||
{
|
||
"name": name,
|
||
"amount": amount,
|
||
"currency": _currency_of(raw, ccy),
|
||
}
|
||
)
|
||
|
||
for hit in _RE_FEE_LINE.finditer(raw):
|
||
_add(
|
||
(hit.group("name") or "").strip(),
|
||
_ascii_amount(hit.group("amount") or ""),
|
||
hit.group("ccy1") or hit.group("ccy2") or "",
|
||
)
|
||
for hit in _RE_FEE_CHANGE.finditer(raw):
|
||
_add(
|
||
(hit.group("name") or "").strip(),
|
||
_ascii_amount(hit.group("amount") or ""),
|
||
hit.group("ccy") or "",
|
||
)
|
||
return rows
|
||
|
||
|
||
def extract_product_quote(text: str, *, injected: Optional[dict[str, Any]] = None) -> dict[str, Any]:
|
||
"""
|
||
产品文字报价：先按费用行抽，再退回合计/币别。注入优先。
|
||
|
||
认不出价格返回空 dict，调用方回「没有识别到报价」。
|
||
群里常见「码头操作费100CNY / 报关费改为300CNY」，不能只把第一笔数当成海运费。
|
||
"""
|
||
if isinstance(injected, dict) and (injected.get("total") or injected.get("fee_rows")):
|
||
out = dict(injected)
|
||
out.setdefault("source_label", "产品报价")
|
||
return out
|
||
raw = (text or "").strip()
|
||
if not raw:
|
||
return {}
|
||
compact = raw.replace(" ", "").replace(" ", "")
|
||
if re.fullmatch(r"WO\d{12}", compact, re.I):
|
||
return {}
|
||
rows = _parse_fee_rows(raw)
|
||
if rows:
|
||
ccy = rows[0].get("currency") or _currency_of(raw)
|
||
total = rows[0]["amount"]
|
||
if len({x.get("currency") for x in rows}) == 1:
|
||
try:
|
||
total = str(sum(float(x["amount"]) for x in rows))
|
||
except ValueError:
|
||
total = rows[0]["amount"]
|
||
return {
|
||
"total": total,
|
||
"currency": ccy,
|
||
"source_label": "产品报价",
|
||
"raw_text": raw,
|
||
"fee_rows": rows,
|
||
"fee_lines": list(rows),
|
||
}
|
||
hit = _RE_MONEY.search(_ascii_amount(raw))
|
||
if not hit:
|
||
return {}
|
||
amount = _ascii_amount(hit.group(1) or hit.group(2) or "")
|
||
if not amount:
|
||
return {}
|
||
ccy = _currency_of(raw)
|
||
return {
|
||
"total": amount,
|
||
"currency": ccy,
|
||
"source_label": "产品报价",
|
||
"raw_text": raw,
|
||
"fee_rows": [{"name": "海运费", "amount": amount, "currency": ccy}],
|
||
"fee_lines": [{"name": "海运费", "amount": amount, "currency": ccy}],
|
||
}
|