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134 lines
5.1 KiB
Python
134 lines
5.1 KiB
Python
import re
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from dataclasses import dataclass
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IMAGE_URL_RE = re.compile(r"https?://[^\s]+(?:\.jpg|\.jpeg|\.png|\.webp|\.bmp|\.gif)(?:\?[^\s]*)?", re.I)
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SIZE_RE = re.compile(r"(\d+(?:\.\d+)?)\s*(米|m|M)\s*[xX*乘]\s*(\d+(?:\.\d+)?)\s*(米|m|M)")
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MAP_POLITICAL_KWS = ["地图", "国界", "边界", "南海", "台湾", "香港", "澳门", "西藏", "新疆", "政治"]
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PORN_RISK_KWS = ["裸", "成人视频", "成人视频", "性爱", "激情", "成人视频"]
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EXTERNAL_CONTACT_KWS = ["微信", "vx", "vx", "qq", "手机号", "电话", "加我", "私下"]
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PRICE_KWS = ["多少钱", "怎么收费", "报价", "价格", "多少米", "多少"]
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GREETING_KWS = ["你好", "您好", "在吗", "在不在", "hello", "hi"]
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FINISH_KWS = ["发完了", "没了", "就这些", "报价吧", "可以报价", "先这样"]
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NONSENSE_KWS = ["嗯", "哦", "好的", "ok", "1", "收到"]
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@dataclass
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class RuleResult:
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ignore: bool = False
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normalized_msg: str = ""
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reason: str = ""
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def extract_customer_text_from_shop_card(msg: str) -> str:
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if "[进店卡片]" not in (msg or ""):
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return ""
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prefix = msg.split("#*#[进店卡片]", 1)[0].strip()
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if prefix and prefix not in {"你好", "您好", "在吗"}:
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return prefix
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return prefix
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def detect_order_status(order_text: str) -> str:
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t = (order_text or "")
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if "买家已付款" in t:
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return "paid"
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if "等待买家付款" in t or "待付款" in t:
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return "pending_payment"
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if "已退款" in t or "退款" in t:
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return "refund"
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return "unknown"
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def extract_size_pairs_m(msg: str) -> list[tuple[float, float]]:
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out: list[tuple[float, float]] = []
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for m in SIZE_RE.finditer(msg or ""):
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w = float(m.group(1))
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h = float(m.group(3))
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out.append((w, h))
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return out
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def has_map_or_political_risk(msg: str, goods_name: str = "") -> bool:
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t = f"{msg or ''} {goods_name or ''}".lower()
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return any(k.lower() in t for k in MAP_POLITICAL_KWS)
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def has_porn_risk(msg: str) -> bool:
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t = (msg or "").lower()
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return any(k.lower() in t for k in PORN_RISK_KWS)
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def requests_external_contact(msg: str) -> bool:
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t = (msg or "").lower()
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return any(k.lower() in t for k in EXTERNAL_CONTACT_KWS)
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def is_meaningless_short(msg: str) -> bool:
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t = (msg or "").strip().lower()
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if len(t) <= 2:
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return True
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return t in NONSENSE_KWS
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def prefilter_message(msg: str, msg_type: int) -> RuleResult:
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m = (msg or "").strip()
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if not m:
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return RuleResult(ignore=True, reason="empty")
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if msg_type not in (0, 1):
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return RuleResult(ignore=True, reason="unsupported_msg_type")
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if "由 " in m and " 转交给 " in m:
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return RuleResult(ignore=True, reason="transfer_notice")
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if "Gemini 店铺消息,跳过" in m:
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return RuleResult(ignore=True, reason="system_echo")
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if "[进店卡片]" in m:
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t = extract_customer_text_from_shop_card(m)
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if t:
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return RuleResult(ignore=False, normalized_msg=t, reason="shop_card_with_text")
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return RuleResult(ignore=True, reason="pure_shop_card")
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return RuleResult(ignore=False, normalized_msg=m, reason="normal")
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def detect_intent(msg: str) -> str:
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m = (msg or "").lower()
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if IMAGE_URL_RE.search(m):
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return "image"
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if any(k in m for k in FINISH_KWS):
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return "finish_or_quote_trigger"
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if any(k in m for k in PRICE_KWS):
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return "pricing"
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if any(k in m for k in GREETING_KWS):
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return "greeting"
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if requests_external_contact(m):
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return "external_contact"
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if is_meaningless_short(m):
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return "nonsense"
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return "unknown"
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def extract_image_urls(msg: str) -> list[str]:
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return IMAGE_URL_RE.findall(msg or "")
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def rules_prompt() -> str:
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return (
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"你是淘宝客服主决策。只输出JSON动作,不要解释。\n"
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"动作 action 只能是: reply / quote / transfer / noop。\n"
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"规则提炼(严格执行):\n"
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"1) 客户发图: 先承接, 允许继续收图。\n"
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"2) 询价且有图(当前/待处理): 优先 quote。\n"
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"3) 无图询价: reply 承接并引导发图。\n"
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"4) 客户说发完了/报价吧/没图: 若有待处理图则 quote。\n"
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"5) 外部联系方式请求: reply 站内引导, 不给微信QQ手机号。\n"
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"6) 地图/政治/黄暴风险: transfer 或拒绝性 reply。\n"
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"7) 仅无意义短句(嗯/哦/ok): 给简短自然承接, 不要长回复。\n"
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"8) 避免重复同一句; 若上句语义相同则换表达。\n"
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"9) 订单已付款: 可回复已安排; 待付款: 提示先付款。\n"
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"10) 尺寸明显超大(如>=2m*2m): 提示需补图/重做边缘, 不要直接承诺一模一样。\n"
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"11) 店铺差异化: 按 acc_id/persona 口吻回复, 保持真人聊天。\n"
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"12) 最终输出只允许一个动作, 不能混合。\n"
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"13) reply 必须很短: 1句为主, 不超过20字, 口语化, 不要客服官话和AI腔。\n"
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"输出格式:\n"
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'{"action":"reply|quote|transfer|noop","reply":"","transfer_msg":"","quote_mode":"flush_pending|analyze_current_or_recent|collect_only","reason":""}'
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)
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