refactor: remove hardcoded routing rules and centralize AI master rules

qingjian_cs/app/agents.py

@@ -115,7 +115,9 @@ class RouterAgent(_AgentRuntime):
     def __init__(self) -> None:
         super().__init__(
             "RouterAgent",
-            "你是客服路由Agent。只输出路由，不回复客户。必须先调用工具读取意图/风险/订单后再路由。",
+            rules_prompt()
+            + "\n你是路由Agent。只输出路由 pre_sales/quote/after_sales/risk，不直接回复客户。"
+            + " 你必须基于上下文语义路由，禁止关键词硬匹配。",
         )
 
     async def route(self, context: dict[str, Any]) -> tuple[str, str]:
@@ -132,7 +134,7 @@ class QuoteAgent(_AgentRuntime):
     def __init__(self) -> None:
         super().__init__(
             "QuoteAgent",
-            rules_prompt() + "\n你是报价专家Agent。必须结合图片数量、尺寸和订单状态给出报价动作。",
+            rules_prompt() + "\n你是报价Agent。负责收图、报价触发、报价回复和报价阶段状态更新。",
         )
 
     async def decide(self, context: dict[str, Any]) -> Decision:
@@ -144,7 +146,7 @@ class AfterSalesAgent(_AgentRuntime):
     def __init__(self) -> None:
         super().__init__(
             "AfterSalesAgent",
-            rules_prompt() + "\n你是售后专家Agent。优先维护售后状态并给出下一步动作。",
+            rules_prompt() + "\n你是售后Agent。负责退款/重发/不满意等售后处理与状态推进。",
         )
 
     async def decide(self, context: dict[str, Any]) -> Decision:
@@ -156,7 +158,7 @@ class RiskAgent(_AgentRuntime):
     def __init__(self) -> None:
         super().__init__(
             "RiskAgent",
-            "你是风控Agent。遇到地图政治/黄暴/外联高风险优先给 transfer 或拒绝性 reply。",
+            rules_prompt() + "\n你是风控Agent。专注风险识别与风险动作决策。",
         )
 
     async def decide(self, context: dict[str, Any]) -> Decision:
@@ -168,7 +170,7 @@ class PreSalesAgent(_AgentRuntime):
     def __init__(self) -> None:
         super().__init__(
             "PreSalesAgent",
-            rules_prompt() + "\n你是售前专家Agent。处理打招呼、询价前引导、收图承接。",
+            rules_prompt() + "\n你是售前Agent。处理咨询承接、收图、澄清需求与转报价前动作。",
         )
 
     async def decide(self, context: dict[str, Any]) -> Decision:

qingjian_cs/app/client.py

@@ -16,7 +16,7 @@ from .config import (
 from .logger import setup_logger
 from .observability import activity_event, build_trace_id
 from .orchestrator import Orchestrator
-from .rules import detect_intent, extract_image_urls, prefilter_message
+from .rules import extract_image_urls, prefilter_message
 
 
 class QingjianClient:
@@ -44,13 +44,8 @@ class QingjianClient:
         return str(data.get("msg", "") or "").strip()
 
     def _debounce_seconds(self, msg: str) -> float:
-        intent = detect_intent(msg)
-        if intent == "image":
+        if extract_image_urls(msg):
             return 2.5
-        if intent in {"pricing", "finish_or_quote_trigger"}:
-            return 2.0
-        if intent == "greeting":
-            return 1.5
         return float(MESSAGE_DEBOUNCE_SECONDS)
 
     async def send_message(self, message: dict) -> None:
@@ -103,22 +98,6 @@ class QingjianClient:
     @staticmethod
     def _humanize_reply(text: str) -> str:
         t = str(text or "").strip()
-        replacements = {
-            "您好呀": "在的",
-            "您好，": "在的，",
-            "您好": "在的",
-            "很高兴为您服务": "我在呢",
-            "请问您有什么需求": "你要做啥图",
-            "请问有什么可以帮您": "你要做啥",
-            "可以把要做的图发我": "图发我就行",
-            "请您先完成订单付款": "先拍下付款哈",
-            "麻烦您先完成付款": "先拍下付款哈",
-            "我们马上为您处理": "我马上处理",
-            "我这边": "我这",
-        }
-        for k, v in replacements.items():
-            t = t.replace(k, v)
-        t = t.replace("~~", "~")
         return t
 
     @staticmethod
@@ -133,11 +112,9 @@ class QingjianClient:
         return False
 
     def _fallback_reply(self, action: str) -> str:
-        if action == "quote":
-            return "我先看下，马上给你报价。"
         if action == "transfer":
-            return "我给你转人工处理哈。"
-        return "收到，我先看一下哈。"
+            return "我先给你转人工处理。"
+        return "收到，我先处理一下。"
 
     def _is_outbound_echo(self, data: dict, msg: str) -> bool:
         """
@@ -177,7 +154,7 @@ class QingjianClient:
             "goods_name": data.get("goods_name", ""),
             "goods_order": data.get("goods_order", ""),
             "msg": merged_msg,
-            "intent": detect_intent(merged_msg),
+            "intent": "unknown",
             "pending_images": len(self.pending_images[key]),
             "auto_quote_trigger": auto_quote,
             "last_reply": self.last_reply_key.get(key, ""),
@@ -238,7 +215,7 @@ class QingjianClient:
         try:
             await asyncio.sleep(AUTO_QUOTE_WAIT_SECONDS)
             if self.pending_images.get(key):
-                await self._handle_decision(data, "发完了，报价吧", auto_quote=True)
+                await self._handle_decision(data, "", auto_quote=True)
         finally:
             self.auto_quote_tasks.pop(key, None)
 

qingjian_cs/app/orchestrator.py

@@ -3,15 +3,7 @@ from __future__ import annotations
 from typing import Any
 
 from .agents import AfterSalesAgent, PreSalesAgent, QuoteAgent, RiskAgent, RouterAgent
-from .config import FAST_ROUTE_ENABLED
 from .models import Decision
-from .rules import (
-    detect_intent,
-    detect_order_status,
-    has_map_or_political_risk,
-    has_porn_risk,
-    requests_external_contact,
-)
 from .state_machine import evolve_after_sales_state, migrate_state_schema
 from .store import ConversationStore
 
@@ -31,8 +23,9 @@ class Orchestrator:
         prev_state = migrate_state_schema(session.get("state", {}))
         prev_route = session.get("route", "pre_sales")
 
-        intent = detect_intent(str(context.get("msg", "") or ""))
-        order_status = detect_order_status(str(context.get("goods_order", "") or ""))
+        # 统一改为语义决策：不走关键词意图/订单硬判定。
+        intent = "unknown"
+        order_status = "unknown"
 
         merged_ctx = {
             **context,
@@ -42,43 +35,7 @@ class Orchestrator:
             "order_status": order_status,
         }
 
-        msg = str(context.get("msg", "") or "")
-        goods_name = str(context.get("goods_name", "") or "")
-        risk_hit = has_map_or_political_risk(msg, goods_name) or has_porn_risk(msg) or requests_external_contact(msg)
-
-        # 命中硬风控才调用 RiskAgent，避免每条消息都先走一轮模型。
-        if risk_hit:
-            risk_decision = await self.risk.decide(merged_ctx)
-            route = "risk"
-            new_state = evolve_after_sales_state(
-                {**prev_state, **(risk_decision.state_patch or {})},
-                route=route,
-                action=risk_decision.action,
-                intent=intent,
-                order_status=order_status,
-                msg=str(context.get("msg", "") or ""),
-            )
-            self.store.upsert_session(customer_key, context.get("acc_id", ""), context.get("customer_id", ""), route, new_state)
-            self.store.append_event(customer_key, "decision", {"route": route, "action": risk_decision.action, "reason": risk_decision.reason})
-            return route, risk_decision, new_state
-
-        route = ""
-        route_reason = ""
-        if FAST_ROUTE_ENABLED:
-            pending_images = int(context.get("pending_images", 0) or 0)
-            auto_quote_trigger = bool(context.get("auto_quote_trigger", False))
-            if intent in {"pricing", "finish_or_quote_trigger"} and (pending_images > 0 or auto_quote_trigger):
-                route = "quote"
-                route_reason = "fast_route_quote_with_pending_images"
-            elif order_status == "refund":
-                route = "after_sales"
-                route_reason = "fast_route_refund"
-            elif intent in {"image", "greeting", "nonsense", "pricing", "finish_or_quote_trigger", "unknown"}:
-                route = "pre_sales"
-                route_reason = "fast_route_common_presales"
-
-        if not route:
-            route, route_reason = await self.router.route(merged_ctx)
+        route, route_reason = await self.router.route(merged_ctx)
 
         if route == "quote":
             decision = await self.quote.decide(merged_ctx)

qingjian_cs/app/rules.py

@@ -4,15 +4,6 @@ from dataclasses import dataclass
 IMAGE_URL_RE = re.compile(r"https?://[^\s]+(?:\.jpg|\.jpeg|\.png|\.webp|\.bmp|\.gif)(?:\?[^\s]*)?", re.I)
 SIZE_RE = re.compile(r"(\d+(?:\.\d+)?)\s*(米|m|M)\s*[xX*乘]\s*(\d+(?:\.\d+)?)\s*(米|m|M)")
 
-MAP_POLITICAL_KWS = ["地图", "国界", "边界", "南海", "台湾", "香港", "澳门", "西藏", "新疆", "政治"]
-PORN_RISK_KWS = ["裸", "成人视频", "成人视频", "性爱", "激情", "成人视频"]
-EXTERNAL_CONTACT_KWS = ["微信", "vx", "vx", "qq", "手机号", "电话", "加我", "私下"]
-PRICE_KWS = ["多少钱", "怎么收费", "报价", "价格", "多少米", "多少"]
-GREETING_KWS = ["你好", "您好", "在吗", "在不在", "hello", "hi"]
-FINISH_KWS = ["发完了", "没了", "就这些", "报价吧", "可以报价", "先这样"]
-NONSENSE_KWS = ["嗯", "哦", "好的", "ok", "1", "收到"]
-
-
 @dataclass
 class RuleResult:
     ignore: bool = False
@@ -30,13 +21,7 @@ def extract_customer_text_from_shop_card(msg: str) -> str:
 
 
 def detect_order_status(order_text: str) -> str:
-    t = (order_text or "")
-    if "买家已付款" in t:
-        return "paid"
-    if "等待买家付款" in t or "待付款" in t:
-        return "pending_payment"
-    if "已退款" in t or "退款" in t:
-        return "refund"
+    # 订单状态交给主决策 AI 从上下文语义判断。
     return "unknown"
 
 
@@ -50,25 +35,23 @@ def extract_size_pairs_m(msg: str) -> list[tuple[float, float]]:
 
 
 def has_map_or_political_risk(msg: str, goods_name: str = "") -> bool:
-    t = f"{msg or ''} {goods_name or ''}".lower()
-    return any(k.lower() in t for k in MAP_POLITICAL_KWS)
+    # 风险由 RiskAgent 语义判断。
+    return False
 
 
 def has_porn_risk(msg: str) -> bool:
-    t = (msg or "").lower()
-    return any(k.lower() in t for k in PORN_RISK_KWS)
+    # 风险由 RiskAgent 语义判断。
+    return False
 
 
 def requests_external_contact(msg: str) -> bool:
-    t = (msg or "").lower()
-    return any(k.lower() in t for k in EXTERNAL_CONTACT_KWS)
+    # 外联风险由 RiskAgent 语义判断。
+    return False
 
 
 def is_meaningless_short(msg: str) -> bool:
-    t = (msg or "").strip().lower()
-    if len(t) <= 2:
-        return True
-    return t in NONSENSE_KWS
+    # 无意义短句由主决策 AI 语义判断。
+    return False
 
 
 def prefilter_message(msg: str, msg_type: int) -> RuleResult:
@@ -93,16 +76,7 @@ def detect_intent(msg: str) -> str:
     m = (msg or "").lower()
     if IMAGE_URL_RE.search(m):
         return "image"
-    if any(k in m for k in FINISH_KWS):
-        return "finish_or_quote_trigger"
-    if any(k in m for k in PRICE_KWS):
-        return "pricing"
-    if any(k in m for k in GREETING_KWS):
-        return "greeting"
-    if requests_external_contact(m):
-        return "external_contact"
-    if is_meaningless_short(m):
-        return "nonsense"
+    # 其余意图交给 AI 语义判断。
     return "unknown"
 
 
@@ -112,22 +86,40 @@ def extract_image_urls(msg: str) -> list[str]:
 
 def rules_prompt() -> str:
     return (
-        "你是淘宝客服主决策。只输出JSON动作，不要解释。\n"
-        "动作 action 只能是: reply / quote / transfer / noop。\n"
-        "规则提炼(严格执行):\n"
-        "1) 客户发图: 先承接, 允许继续收图。\n"
-        "2) 询价且有图(当前/待处理): 优先 quote。\n"
-        "3) 无图询价: reply 承接并引导发图。\n"
-        "4) 客户说发完了/报价吧/没图: 若有待处理图则 quote。\n"
-        "5) 外部联系方式请求: reply 站内引导, 不给微信QQ手机号。\n"
-        "6) 地图/政治/黄暴风险: transfer 或拒绝性 reply。\n"
-        "7) 仅无意义短句(嗯/哦/ok): 给简短自然承接, 不要长回复。\n"
-        "8) 避免重复同一句; 若上句语义相同则换表达。\n"
-        "9) 订单已付款: 可回复已安排; 待付款: 提示先付款。\n"
-        "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"
-        "11) 店铺差异化: 按 acc_id/persona 口吻回复, 保持真人聊天。\n"
-        "12) 最终输出只允许一个动作, 不能混合。\n"
-        "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"
+        "你是淘宝图像服务客服系统的统一决策AI。必须按以下 MASTER_RULES 执行。\n"
+        "只输出 JSON 决策，不要解释过程。\n"
+        "动作 action 只能是: reply / quote / transfer / noop / update_state。\n\n"
+        "MASTER_RULES:\n"
+        "A. 统一动作语义\n"
+        "1) reply: 直接回复客户。\n"
+        "2) quote: 触发报价或触发看图后报价流程。\n"
+        "3) transfer: 转人工，必须给 transfer_msg。\n"
+        "4) noop: 当前不需要回复。\n"
+        "5) update_state: 仅更新状态，不对外发消息。\n\n"
+        "B. 售前与报价\n"
+        "1) 客户发图: 优先承接，可继续收图；不强行一次报完。\n"
+        "2) 客户询价且已有图(当前图/待处理图/最近图): 优先 action=quote。\n"
+        "3) 客户无图询价: action=reply，引导其先发图。\n"
+        "4) 客户说“发完了/就这些/报价吧”: 若有图则 action=quote。\n"
+        "5) 不能承诺“一模一样原图必找到”，可说先看图评估。\n"
+        "6) 尺寸很大或要求高还原时，不夸张承诺，先说明可评估后给结论。\n\n"
+        "C. 订单阶段\n"
+        "1) 已付款: 可回复“已安排处理/正在处理/完成后发你确认”。\n"
+        "2) 待付款: 可提示付款，但不与客户争执；必要时先给预览再引导付款。\n"
+        "3) 退款/售后诉求: 进入售后语境，保持克制，必要时转人工。\n\n"
+        "D. 风控与合规\n"
+        "1) 涉政治/地图边界/黄暴/违规内容: 优先 transfer 或拒绝性 reply。\n"
+        "2) 客户索要微信/QQ/手机号等站外联系方式: 不外呼，站内引导。\n"
+        "3) 高风险不确定时，不硬答，给保守回复或转人工。\n\n"
+        "E. 对话质量\n"
+        "1) 单次只做一个动作，不混合。\n"
+        "2) 避免重复同一句话；若语义相同，换表达。\n"
+        "3) reply 必须短: 优先 1 句，口语化，避免AI腔。\n"
+        "4) 不要输出思考过程，不要输出 tool_use 文本给客户。\n"
+        "5) 若上下文不足，先澄清 1 个关键问题，不要连续追问。\n\n"
+        "F. 店铺人格\n"
+        "1) 按店铺/账号口吻说话，像真人客服，不要机械模板。\n"
+        "2) 语气友好直接，不啰嗦，不说“作为AI”。\n\n"
         "输出格式:\n"
-        '{"action":"reply|quote|transfer|noop","reply":"","transfer_msg":"","quote_mode":"flush_pending|analyze_current_or_recent|collect_only","reason":""}'
+        '{"action":"reply|quote|transfer|noop|update_state","reply":"","transfer_msg":"","quote_mode":"flush_pending|analyze_current_or_recent|collect_only","state_patch":{},"reason":""}'
     )

qingjian_cs/app/state_machine.py

@@ -38,7 +38,6 @@ def migrate_state_schema(state: dict[str, Any] | None) -> dict[str, Any]:
 def evolve_after_sales_state(prev_state: dict[str, Any], *, route: str, action: str, intent: str, order_status: str, msg: str) -> dict[str, Any]:
     s = migrate_state_schema(prev_state)
     stage = s.get("after_sales_stage", "new")
-    text = (msg or "").lower()
 
     if action == "transfer" or route == "risk":
         stage = "transferred"
@@ -46,22 +45,14 @@ def evolve_after_sales_state(prev_state: dict[str, Any], *, route: str, action:
         stage = "quoted"
         s["quote_count"] = int(s.get("quote_count", 0)) + 1
     elif route == "after_sales":
-        if any(k in text for k in ["退款", "退钱", "退货"]):
-            stage = "refunding"
-        elif any(k in text for k in ["做完", "完成", "好了", "发我"]):
-            stage = "waiting_feedback"
-        elif any(k in text for k in ["补图", "重发", "再发", "原图"]):
-            stage = "waiting_material"
-        elif order_status == "paid":
+        if order_status == "paid":
             stage = "processing"
+        elif stage == "new":
+            stage = "waiting_material"
     elif route == "pre_sales":
         if intent == "image":
             stage = "waiting_material"
 
-    # 终态收敛
-    if stage == "waiting_feedback" and any(k in text for k in ["没问题", "可以", "确认", "好评"]):
-        stage = "done"
-
     s["after_sales_stage"] = stage
     s["last_intent"] = intent
     s["last_order_status"] = order_status or "unknown"

qingjian_cs/scripts/replay_golden.py

@@ -11,35 +11,10 @@ if str(ROOT) not in sys.path:
     sys.path.insert(0, str(ROOT))
 
 from app.orchestrator import Orchestrator
-from app.rules import detect_intent, detect_order_status, has_map_or_political_risk, requests_external_contact
-from app.state_machine import evolve_after_sales_state, migrate_state_schema
 
 CASES_PATH = ROOT / "golden" / "golden_cases.jsonl"
 
 
-def heuristic_decide(msg: str, goods_order: str) -> tuple[str, str, dict]:
-    m = (msg or "")
-    intent = detect_intent(m)
-    order_status = detect_order_status(goods_order or "")
-
-    if has_map_or_political_risk(m) or requests_external_contact(m):
-        route, action = "risk", "transfer"
-    elif "退款" in m:
-        route, action = "after_sales", "reply"
-    elif intent == "image":
-        route, action = "quote", "quote"
-    elif any(k in m for k in ["多少钱", "报价", "价格", "怎么收费"]):
-        route, action = "quote", "reply"
-    elif order_status == "paid":
-        route, action = "after_sales", "reply"
-    else:
-        route, action = "pre_sales", "reply"
-
-    state = migrate_state_schema({})
-    state = evolve_after_sales_state(state, route=route, action=action, intent=intent, order_status=order_status, msg=m)
-    return route, action, state
-
-
 async def full_decide(orch: Orchestrator, cid: str, msg: str, goods_order: str) -> tuple[str, str, dict]:
     context = {
         "customer_key": f"demo_acc:{cid}",
@@ -58,7 +33,7 @@ async def full_decide(orch: Orchestrator, cid: str, msg: str, goods_order: str)
 
 async def main() -> int:
     parser = argparse.ArgumentParser()
-    parser.add_argument("--mode", choices=["heuristic", "full"], default="heuristic")
+    parser.add_argument("--mode", choices=["full"], default="full")
     parser.add_argument("--cases", default=str(CASES_PATH))
     args = parser.parse_args()
 
@@ -69,16 +44,13 @@ async def main() -> int:
 
     cases = [json.loads(line) for line in p.read_text(encoding="utf-8").splitlines() if line.strip()]
 
-    orch = Orchestrator() if args.mode == "full" else None
+    orch = Orchestrator()
 
     passed = 0
     failed = 0
     for i, c in enumerate(cases, 1):
         cid = f"case_{i}"
-        if args.mode == "full":
-            route, action, state = await full_decide(orch, cid, c.get("msg", ""), c.get("goods_order", ""))
-        else:
-            route, action, state = heuristic_decide(c.get("msg", ""), c.get("goods_order", ""))
+        route, action, state = await full_decide(orch, cid, c.get("msg", ""), c.get("goods_order", ""))
 
         ok = route == c.get("expected_route") and action == c.get("expected_action")
         if ok and c.get("expected_stage"):