方便NLP的测试

robowaiter/robot/DefaultNLP.ptml

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+selector
+{
+    sequence
+    {
+        cond CustomerChatting()
+        act DealChatNLP()
+    }
+    sequence
+    {
+        cond HasSubTask()
+        sequence
+        {
+            act SubTaskPlaceHolder()
+        }
+    }
+    sequence
+    {
+        cond FocusingCustomer()
+        act ServeCustomer()
+    }
+    sequence
+    {
+        cond NewCustomerComing()
+        selector
+        {
+            cond At(Robot,Bar)
+            act MoveTo(Bar)
+        }
+        act GreetCustomer()
+    }
+
+}

robowaiter/scene/tasks/GQA/GQA_NLP.py

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+"""
+具身多轮对话 GQA
+点餐（order）的对话，咖啡厅服务员可以为客人（NPC）完成点餐基本对话
+场景对话（GQA）结合场景：询问卫生间、附近娱乐场所（数据来源自主定义）
+开始条件：顾客NPC发出点餐指令
+结束条件：顾客NPC发出指令，表示不再需要服务
+"""
+
+# todo: 使用大模型进行对话，获得指令信息，适时结束对话
+# order = {...}
+
+from robowaiter.scene.scene import Scene
+
+class SceneGQA(Scene):
+    def __init__(self, robot):
+        super().__init__(robot)
+        # 在这里加入场景中发生的事件， (事件发生的时间，事件函数)
+        self.new_event_list = [
+            (3, self.customer_say, ("System","哪里有蛋糕"))
+        ]
+
+    def _reset(self):
+        # self.clean_walker()
+        # self.add_walkers([[50, 500,90]])
+        pass
+
+        # self.walker_bubble("洗手间在哪里")
+        # self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])
+
+
+    def _run(self):
+        pass
+
+
+if __name__ == '__main__':
+    import os
+    from robowaiter.robot.robot import Robot
+    from robowaiter.utils.basic import get_root_path
+    root_path = get_root_path()
+    ptml_path = os.path.join(root_path, 'robowaiter/robot/DefaultNLP.ptml')
+
+    robot = Robot(ptml_path=ptml_path)
+
+    # create task
+    task = SceneGQA(robot)
+    task.reset()
+    task.run()