AI产品PRD：对话流(Bot Flow)设计与异常分支设计

class EvalCase:    """评估集用例：输入对话序列 + 期望最终状态"""    def __init__(self, name, inputs, expected_state):        self.name = name        self.inputs = inputs        self.expected_state = expected_state  class OrderBot:    """点餐机器人：对话流主流程与异常分支的状态机实现"""    DISHES = ["麻婆豆腐", "宫保鸡丁", "酸辣汤"]    COUNT_MAP = {"一": 1, "两": 2, "三": 3}     def __init__(self, threshold=0.5, max_fallback=2):        self.state = "opening"        self.slots = {}        self.fallback_count = 0        self.threshold = threshold        self.max_fallback = max_fallback        self.required_slots = ["菜品", "数量"]     def recognize(self, text):        """意图识别：命中词表返回高置信度，否则返回低置信度"""        for dish in self.DISHES:            if dish in text:                return "dish", 0.85        for word in self.COUNT_MAP:            if word in text:                return "count", 0.85        for kw in ["人工", "客服", "投诉"]:            if kw in text:                return "human", 0.85        return "unknown", 0.2     def extract(self, text):        """槽位抽取：从一句话中抓取菜品与数量"""        for dish in self.DISHES:            if dish in text:                self.slots["菜品"] = dish        for word, num in self.COUNT_MAP.items():            if word in text:                self.slots["数量"] = num     def collect(self, text):        """槽位收集：补全必填槽位，齐了则进入确认"""        self.fallback_count = 0        self.extract(text)        need = [s for s in self.required_slots if s not in self.slots]        if not need:            self.state = "confirm"            return "您确认点%s%s份吗？" % (self.slots["菜品"], self.slots["数量"])        return "还需要告诉我%s。" % "、".join(need)     def step(self, text):        """状态转移：一个用户输入对应一次状态流转"""        intent, conf = self.recognize(text)        if intent == "human":            self.state = "human"            return "已为您转接人工客服，请稍候。"        if self.state == "opening":            self.state = "collect_slot"            if intent in ("dish", "count"):                return self.collect(text)            return "您好，请问您要点什么？"        if self.state == "collect_slot":            if conf < self.threshold:                self.fallback_count += 1                if self.fallback_count >= self.max_fallback:                    self.state = "human"                    return "多次未识别，转接人工客服。"                return "没听清，请再说一次。"            return self.collect(text)        if self.state == "confirm":            if "确认" in text or "对" in text:                self.state = "done"                return "好的，订单已下达，感谢惠顾。"            self.state = "collect_slot"            return "请重新告诉我需求，我来重新下单。"        return "您的订单已完成，还有别的需要吗？"     def run(self, inputs):        """跑一段对话，返回每一步后的状态与回复"""        logs = []        for text in inputs:            reply = self.step(text)            logs.append((self.state, reply))        return logs  def run_eval(cases):    """用评估集验收：逐条断言最终状态是否符合预期"""    passed = 0    for case in cases:        bot = OrderBot()        logs = bot.run(case.inputs)        final_state = logs[-1][0] if logs else "opening"        ok = final_state == case.expected_state        passed += 1 if ok else 0        mark = "通过" if ok else "失败"        print("[%s] %s -> %s (期望 %s)" % (mark, case.name, final_state, case.expected_state))    return passed / len(cases)  if __name__ == "__main__":    cases = [        EvalCase("主流程-完整点单", ["我要点麻婆豆腐", "两", "确认"], "done"),        EvalCase("异常-两次未识别转人工", ["你好", "嗯", "人工"], "human"),        EvalCase("异常-直接要求转人工", ["转人工"], "human"),        EvalCase("边界-分批补齐槽位", ["宫保鸡丁", "三", "确认"], "done"),    ]    rate = run_eval(cases)    print("评估集通过率: %.0f%%" % (rate * 100))