Merge branch 'main' of https://github.com/HPCL-EI/RoboWaiter
This commit is contained in:
Caiyishuai
commit
c4dd4f4378
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@ -1,3 +0,0 @@
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from . import navigate
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from . import dstar_lite
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@ -7,7 +7,6 @@ import pickle
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import matplotlib.pyplot as plt
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import numpy as np
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from robowaiter.scene import scene
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from robowaiter.algos.navigator.dstar_lite import DStarLite, euclidean_distance
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@ -94,6 +93,7 @@ class Navigator:
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if __name__ == '__main__':
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# 根据map计算并保存cost_map
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from robowaiter.scene import scene
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file_name = 'map_4.pkl'
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if os.path.exists(file_name):
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@ -81,9 +81,10 @@ class Bahavior(ptree.behaviour.Behaviour):
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# let behavior node interact with the scene
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def set_scene(self, scene):
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self.scene = scene
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self.robot = scene.robot
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def set_scene(self, scene=None):
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if scene:
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self.scene = scene
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self.robot = scene.robot
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def setup(self, **kwargs: Any) -> None:
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return super().setup(**kwargs)
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@ -3,6 +3,7 @@ from typing import Any
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class Selector(ptree.composites.Selector):
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print_name = "Selector"
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ins_name = "Selector"
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type = "Selector"
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def __init__(self,*args,**kwargs):
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@ -3,6 +3,7 @@ from typing import Any
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class Sequence(ptree.composites.Sequence):
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print_name = "Sequence"
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ins_name = "Selector"
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type = "Sequence"
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def __init__(self,*args,**kwargs):
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@ -1,7 +1,13 @@
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import py_trees as ptree
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from robowaiter.behavior_lib._base.Act import Act
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from robowaiter.llm_client.multi_rounds import ask_llm,new_history
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from robowaiter.llm_client.multi_rounds import ask_llm, new_history
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import random
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# import spacy
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# nlp = spacy.load('en_core_web_lg')
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class DealChat(Act):
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def __init__(self):
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@ -10,13 +16,14 @@ class DealChat(Act):
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self.function_success = False
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self.func_map = {
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"create_sub_task": self.create_sub_task,
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"get_object_info": self.get_object_info,
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"stop_serve": self.stop_serve
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"stop_serve": self.stop_serve,
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# "get_object_info": self.get_object_info,
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# "find_location": self.find_location
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}
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def _update(self) -> ptree.common.Status:
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# if self.scene.status?
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name,sentence = self.scene.state['chat_list'].pop(0)
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name, sentence = self.scene.state['chat_list'].pop(0)
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if name == "Goal":
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self.create_sub_task(goal=sentence)
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@ -39,14 +46,14 @@ class DealChat(Act):
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return ptree.common.Status.RUNNING
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def create_sub_task(self,**args):
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def create_sub_task(self, **args):
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try:
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goal = args['goal']
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w = goal.split(")")
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goal_set = set()
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goal_set.add(w[0] + ")")
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if len(w)>1:
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if len(w) > 1:
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for x in w[1:]:
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if x != "":
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goal_set.add(x[1:] + ")")
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@ -56,25 +63,73 @@ class DealChat(Act):
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self.scene.robot.expand_sub_task_tree(goal_set)
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def get_object_info(self,**args):
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try:
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obj = args['obj']
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self.function_success = True
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except:
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obj = None
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print("参数解析错误")
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near_object = "None"
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if obj == "洗手间":
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near_object = "大门"
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return near_object
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# def get_object_info(self,**args):
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# try:
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# obj = args['obj']
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#
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# self.function_success = True
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# except:
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# obj = None
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# print("参数解析错误")
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#
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# near_object = "None"
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#
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# max_similarity = 0.02
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# similar_word = None
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#
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# # 场景中现有物品
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# cur_things = set()
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# for item in self.scene.status.objects:
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# cur_things.add(item.name)
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# # obj与现有物品进行相似度匹配
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# query_token = nlp(obj)
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# for w in cur_things:
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# word_token = nlp(w)
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# similarity = query_token.similarity(word_token)
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# if similarity > max_similarity:
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# max_similarity = similarity
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# similar_word = w
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# if similar_word:
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# print("max_similarity:",max_similarity,"similar_word:",similar_word)
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#
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# if similar_word: # 存在同义词说明场景中存在该物品
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# near_object = random.choices(list(cur_things), k=5) # 返回场景中的5个物品
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#
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# if obj == "洗手间":
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# near_object = "Door"
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#
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# return near_object
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#
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# def find_location(self, **args):
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# try:
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# location = args['obj']
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# self.function_success = True
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# except:
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# obj = None
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# print("参数解析错误")
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#
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# near_location = None
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# # 用户咨询的地点
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# query_token = nlp(location)
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# max_similarity = 0
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# similar_word = None
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# # 到自己维护的地点列表中找同义词
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# for w in self.scene.all_loc_en:
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# word_token = nlp(w)
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# similarity = query_token.similarity(word_token)
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# if similarity > max_similarity:
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# max_similarity = similarity
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# similar_word = w
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# print("similarity:", max_similarity, "similar_word:", similar_word)
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# # 存在同义词说明客户咨询的地点有效
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# if similar_word:
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# mp = list(self.scene.loc_map_en[similar_word])
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# near_location = random.choice(mp)
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# return near_location
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def stop_serve(self,**args):
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return "好的"
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return "好的"
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@ -0,0 +1,135 @@
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import py_trees as ptree
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from robowaiter.behavior_lib._base.Act import Act
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from robowaiter.llm_client.multi_rounds import ask_llm, new_history
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import random
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import spacy
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nlp = spacy.load('en_core_web_lg')
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class DealChat(Act):
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def __init__(self):
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super().__init__()
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self.chat_history = ""
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self.function_success = False
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self.func_map = {
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"create_sub_task": self.create_sub_task,
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"stop_serve": self.stop_serve,
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"get_object_info": self.get_object_info,
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"find_location": self.find_location
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}
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def _update(self) -> ptree.common.Status:
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# if self.scene.status?
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name, sentence = self.scene.state['chat_list'].pop(0)
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if name == "Goal":
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self.create_sub_task(goal=sentence)
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return ptree.common.Status.RUNNING
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if name not in self.scene.state["chat_history"]:
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self.scene.state["chat_history"][name] = new_history()
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history = self.scene.state["chat_history"][name]
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self.scene.state["attention"]["customer"] = name
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self.scene.state["serve_state"] = {
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"last_chat_time": self.scene.time,
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}
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function_call, response = ask_llm(sentence,history,func_map=self.func_map)
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self.scene.chat_bubble(response) # 机器人输出对话
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return ptree.common.Status.RUNNING
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def create_sub_task(self, **args):
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try:
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goal = args['goal']
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w = goal.split(")")
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goal_set = set()
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goal_set.add(w[0] + ")")
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if len(w) > 1:
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for x in w[1:]:
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if x != "":
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goal_set.add(x[1:] + ")")
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self.function_success = True
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except:
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print("参数解析错误")
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self.scene.robot.expand_sub_task_tree(goal_set)
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def get_object_info(self,**args):
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try:
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obj = args['obj']
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self.function_success = True
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except:
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obj = None
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print("参数解析错误")
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near_object = "None"
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max_similarity = 0.02
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similar_word = None
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# 场景中现有物品
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cur_things = set()
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for item in self.scene.status.objects:
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cur_things.add(item.name)
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# obj与现有物品进行相似度匹配
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query_token = nlp(obj)
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for w in cur_things:
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word_token = nlp(w)
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similarity = query_token.similarity(word_token)
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if similarity > max_similarity:
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max_similarity = similarity
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similar_word = w
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if similar_word:
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print("max_similarity:",max_similarity,"similar_word:",similar_word)
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if similar_word: # 存在同义词说明场景中存在该物品
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near_object = random.choices(list(cur_things), k=5) # 返回场景中的5个物品
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if obj == "洗手间":
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near_object = "Door"
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return near_object
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def find_location(self, **args):
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try:
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location = args['obj']
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self.function_success = True
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except:
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obj = None
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print("参数解析错误")
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near_location = None
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# 用户咨询的地点
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query_token = nlp(location)
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max_similarity = 0
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similar_word = None
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# 到自己维护的地点列表中找同义词
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for w in self.scene.all_loc_en:
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word_token = nlp(w)
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similarity = query_token.similarity(word_token)
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if similarity > max_similarity:
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max_similarity = similarity
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similar_word = w
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print("similarity:", max_similarity, "similar_word:", similar_word)
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# 存在同义词说明客户咨询的地点有效
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if similar_word:
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mp = list(self.scene.loc_map_en[similar_word])
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near_location = random.choice(mp)
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return near_location
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def stop_serve(self,**args):
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return "好的"
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@ -107,9 +107,12 @@ def format_trans_to_bracket(file_path: str) -> str:
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for i in range(level):
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ptml_new += '}'
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import re
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new_path = re.sub('\\\[a-zA-Z0-9_]*\.ptml', '/bracket_ptml.ptml', file_path)
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with open(new_path, 'w+') as file:
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file_name = os.path.basename(file_path).split(".")[0]
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dir_path = os.path.dirname(file_path)
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# import re
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# new_path = re.sub('\\\[a-zA-Z0-9_]*\.ptml', '/bracket_ptml.ptml', file_path)
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new_path = os.path.join(dir_path,file_name+"_bracket.ptml")
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with open(new_path, 'w') as file:
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file.write(ptml_new)
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return new_path
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|
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@ -30,9 +30,8 @@ all_obj = ['马克杯', '香蕉', '牙膏', '面包', '软饮料', '酸奶', 'AD
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all_loc = ['吧台', '餐桌', '沙发', '灶台', '大门', '灯开关', '空调开关', '橱柜', '卫生间', '窗户', '音响', '休闲区', '工作台', '服务台', '收银台', '墙角',
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'蛋糕柜', '充电处', '冰箱', '书架']
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all_loc_en = ['bar', 'Table', 'sofa', 'stove', 'Gate', 'light switch', 'airconditioner switch', 'cabinet', 'bathroom', 'window',
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'audio', 'lounge area', 'workstation', 'service counter', 'cashier counter', 'corner',
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'cake display', 'ChargingStations', 'refrigerator', 'bookshelf']
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all_loc_en = ['bar', 'Table', 'sofa', 'stove', 'Gate', 'light switch', 'airconditioner switch', 'cabinet', 'bathroom', 'window','audio', 'lounge area',
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'workstation', 'service counter', 'cashier counter', 'corner','cake display', 'ChargingStations', 'refrigerator', 'bookshelf']
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loc_map_en = {'bar': {'工作台', '服务台', '收银台', '蛋糕柜'},
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'Table': {'大门', '休闲区', '墙角'},
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|
|
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@ -154,7 +154,7 @@ def ask_llm(question,history, func_map=None, retry=3):
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"你是机器人服务员，请把以下句子换一种表述方式对顾客说，但是意思不变，尽量简短：\n")
|
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else:
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reply = fix_questions_dict[question]["answer"]
|
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result = single_round(f"你是机器人服务员，顾客想知道{question}, 你的具身场景查询返回的是{result},请把按照以下句子对顾客说，{reply}, 尽量简短。\n")
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result = single_round(f"你是机器人服务员，顾客想知道{question}, 你的具身场景查询返回的是{result},把返回的英文名词翻译成中文,请把按照以下句子对顾客说，{reply}, 尽量简短。\n")
|
||||
|
||||
message = {'role': 'assistant', 'content': result, 'name': None,
|
||||
'function_call': None}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,32 @@
|
|||
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()
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -35,7 +35,7 @@ class Robot(object):
|
|||
self.action_list = None
|
||||
|
||||
|
||||
def set_scene(self,scene):
|
||||
def set_scene(self,scene=None):
|
||||
self.scene = scene
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -132,6 +132,25 @@ class Scene:
|
|||
with open(self.filename, 'rb') as file:
|
||||
self.map_file = pickle.load(file)
|
||||
|
||||
# tool register
|
||||
self.all_loc_en = ['bar', 'Table', 'sofa', 'stove', 'Gate', 'light switch', 'airconditioner switch', 'cabinet', 'bathroom', 'window', 'audio',
|
||||
'lounge area', 'workstation', 'service counter', 'cashier counter', 'corner', 'cake display', 'ChargingStations',
|
||||
'refrigerator', 'bookshelf']
|
||||
|
||||
self.loc_map_en = {'bar': {'工作台', '服务台', '收银台', '蛋糕柜'}, 'Table': {'大门', '休闲区', '墙角'},
|
||||
'sofa': {'餐桌', '窗户', '音响', '休闲区', '墙角', '书架'},
|
||||
'stove': {'吧台', '橱柜', '工作台', '服务台', '收银台', '蛋糕柜', '冰箱'},
|
||||
'Gate': {'吧台', '灯开关', '空调开关', '卫生间', '墙角'}, 'light switch': {'大门', '空调开关', '卫生间', '墙角'},
|
||||
'airconditioner switch': {'大门', '灯开关', '卫生间', '墙角'},
|
||||
'cabinet': {'灶台', '吧台', '工作台', '服务台', '收银台', '蛋糕柜', '充电处', '冰箱'}, 'bathroom': {'大门', '墙角'},
|
||||
'window': {'餐桌', '沙发', '休闲区'}, 'audio': {'餐桌', '沙发', '休闲区', '墙角', '书架'},
|
||||
'lounge area': {'沙发', '餐桌', '墙角', '书架', '音响'}, 'workstation': {'吧台', '服务台', '收银台'},
|
||||
'service counter': {'吧台', '工作台', '收银台'}, 'cashier counter': {'吧台', '工作台', '服务台'},
|
||||
'corner': {'卫生间', '沙发', '灯开关', '空调开关', '音响', '休闲区', '书架'},
|
||||
'cake display': {'吧台', '橱柜', '服务台', '收银台', '冰箱'},
|
||||
'ChargingStations': {'吧台', '餐桌', '沙发', '休闲区', '工作台', '服务台', '收银台', '墙角', '书架'},
|
||||
'refrigerator': {'吧台', '服务台', '蛋糕柜'}, 'bookshelf': {'餐桌', '沙发', '窗户', '休闲区', '墙角'}}
|
||||
|
||||
|
||||
def reset(self):
|
||||
# 基类reset，默认执行仿真器初始化操作
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ class SceneGQA(Scene):
|
|||
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","请问洗手间在哪里？"))
|
||||
(3, self.customer_say, ("System","哪里有蛋糕"))
|
||||
]
|
||||
|
||||
def _reset(self):
|
||||
|
|
|
|||
|
|
@ -0,0 +1,47 @@
|
|||
"""
|
||||
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()
|
||||
|
|
@ -111,10 +111,10 @@ def dot_tree(
|
|||
if with_qualified_names:
|
||||
node_label += f"\n({utilities.get_fully_qualified_name(behaviour)})"
|
||||
'''
|
||||
if node_name == "Sequence":
|
||||
node_name = ">"
|
||||
if node_name == "Selector":
|
||||
node_name = "?"
|
||||
# if node_name == "Sequence":
|
||||
# node_name = ">"
|
||||
# if node_name == "Selector":
|
||||
# node_name = "?"
|
||||
return node_name
|
||||
|
||||
fontsize = 20
|
||||
|
|
|
|||
|
|
@ -0,0 +1,17 @@
|
|||
selector
|
||||
sequence
|
||||
cond CustomerChatting()
|
||||
act DealChat()
|
||||
sequence
|
||||
cond HasSubTask()
|
||||
sequence
|
||||
act SubTaskPlaceHolder()
|
||||
sequence
|
||||
cond FocusingCustomer()
|
||||
act ServeCustomer()
|
||||
sequence
|
||||
cond NewCustomerComing()
|
||||
selector
|
||||
cond At(Robot,Bar)
|
||||
act MoveTo(Bar)
|
||||
act GreetCustomer()
|
||||
|
|
@ -0,0 +1,28 @@
|
|||
selector
|
||||
{
|
||||
sequence
|
||||
{
|
||||
cond CustomerChatting()
|
||||
act DealChat()
|
||||
|
||||
} sequence
|
||||
{
|
||||
cond HasSubTask()
|
||||
sequence
|
||||
{
|
||||
act SubTaskPlaceHolder()
|
||||
|
||||
} sequence
|
||||
cond FocusingCustomer()
|
||||
act ServeCustomer()
|
||||
|
||||
} sequence
|
||||
{
|
||||
cond NewCustomerComing()
|
||||
selector
|
||||
{
|
||||
cond At(Robot,Bar)
|
||||
act MoveTo(Bar)
|
||||
|
||||
} act GreetCustomer()
|
||||
}}
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
# from robowaiter.scene.scene import Scene
|
||||
# from robowaiter.behavior_tree.ptml.ptmlCompiler import load
|
||||
|
||||
import os
|
||||
from robowaiter.robot.robot import Robot
|
||||
from robowaiter.utils.bt.draw import render_dot_tree
|
||||
from robowaiter.utils.basic import get_root_path
|
||||
from robowaiter.utils.bt.load import load_bt_from_ptml
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
# create robot
|
||||
root_path = get_root_path()
|
||||
ptml_path = os.path.join(root_path, 'robowaiter/utils/draw_bt/Default.ptml')
|
||||
behavior_lib_path = os.path.join(root_path, 'robowaiter/behavior_lib')
|
||||
bt = load_bt_from_ptml(None, ptml_path, behavior_lib_path)
|
||||
|
||||
|
||||
|
||||
render_dot_tree(bt.root,name="test")
|
||||
# build and tick
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
digraph pastafarianism {
|
||||
ordering=out;
|
||||
graph [fontname="times-roman"];
|
||||
node [fontname="times-roman"];
|
||||
edge [fontname="times-roman"];
|
||||
"a3ac082f-ad46-4cc9-86b4-3e76c3c564d3" [fillcolor=cyan, fontcolor=black, fontsize=20, height=0.01, label=Selector, shape=diamond, style=filled, width=0.01];
|
||||
"717a1290-56bc-41e1-9b4b-e6df93d40e64" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01];
|
||||
"a3ac082f-ad46-4cc9-86b4-3e76c3c564d3" -> "717a1290-56bc-41e1-9b4b-e6df93d40e64";
|
||||
"b3236b13-d5f2-4643-ae7c-6f27bd4ab6f2" [fillcolor=yellow, fontcolor=black, fontsize=20, label="CustomerChatting()", shape=ellipse, style=filled];
|
||||
"717a1290-56bc-41e1-9b4b-e6df93d40e64" -> "b3236b13-d5f2-4643-ae7c-6f27bd4ab6f2";
|
||||
"28015225-b7a4-4f38-b26f-4dbe5eea4154" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="DealChat()", shape=box, style=filled];
|
||||
"717a1290-56bc-41e1-9b4b-e6df93d40e64" -> "28015225-b7a4-4f38-b26f-4dbe5eea4154";
|
||||
"ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01];
|
||||
"a3ac082f-ad46-4cc9-86b4-3e76c3c564d3" -> "ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e";
|
||||
"2f77f976-499c-4601-9d8c-86dd80d66dfa" [fillcolor=yellow, fontcolor=black, fontsize=20, label="HasSubTask()", shape=ellipse, style=filled];
|
||||
"ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e" -> "2f77f976-499c-4601-9d8c-86dd80d66dfa";
|
||||
"2428792c-3896-443d-8744-f5e286644fad" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01];
|
||||
"ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e" -> "2428792c-3896-443d-8744-f5e286644fad";
|
||||
"4bb7a9c3-521b-408f-b403-1fd25d54b192" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="SubTaskPlaceHolder()", shape=box, style=filled];
|
||||
"2428792c-3896-443d-8744-f5e286644fad" -> "4bb7a9c3-521b-408f-b403-1fd25d54b192";
|
||||
"64b2362a-d99e-4e99-8772-ad1419e53a2e" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01];
|
||||
"ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e" -> "64b2362a-d99e-4e99-8772-ad1419e53a2e";
|
||||
"fd7124ba-c9d1-4fde-8063-e8337d335121" [fillcolor=yellow, fontcolor=black, fontsize=20, label="FocusingCustomer()", shape=ellipse, style=filled];
|
||||
"64b2362a-d99e-4e99-8772-ad1419e53a2e" -> "fd7124ba-c9d1-4fde-8063-e8337d335121";
|
||||
"169ebec9-3645-4fbb-a533-5186a8e5967b" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="ServeCustomer()", shape=box, style=filled];
|
||||
"64b2362a-d99e-4e99-8772-ad1419e53a2e" -> "169ebec9-3645-4fbb-a533-5186a8e5967b";
|
||||
"bea12066-ecbd-49b0-8934-efcb2c38b5f5" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01];
|
||||
"ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e" -> "bea12066-ecbd-49b0-8934-efcb2c38b5f5";
|
||||
"a847a0cc-c5af-4757-aa8c-8baef72788dc" [fillcolor=yellow, fontcolor=black, fontsize=20, label="NewCustomerComing()", shape=ellipse, style=filled];
|
||||
"bea12066-ecbd-49b0-8934-efcb2c38b5f5" -> "a847a0cc-c5af-4757-aa8c-8baef72788dc";
|
||||
"99354f05-1716-46b2-9151-d88eac0a5b27" [fillcolor=cyan, fontcolor=black, fontsize=20, height=0.01, label=Selector, shape=diamond, style=filled, width=0.01];
|
||||
"bea12066-ecbd-49b0-8934-efcb2c38b5f5" -> "99354f05-1716-46b2-9151-d88eac0a5b27";
|
||||
"19de10a3-7554-43a3-b892-34cb2e32ab9a" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,Bar)", shape=ellipse, style=filled];
|
||||
"99354f05-1716-46b2-9151-d88eac0a5b27" -> "19de10a3-7554-43a3-b892-34cb2e32ab9a";
|
||||
"4286d652-c4ef-4522-a7f1-b5c865dcc4c9" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(Bar)", shape=box, style=filled];
|
||||
"99354f05-1716-46b2-9151-d88eac0a5b27" -> "4286d652-c4ef-4522-a7f1-b5c865dcc4c9";
|
||||
"a3766a34-5152-4f82-8fba-8bf1f6b3830b" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="GreetCustomer()", shape=box, style=filled];
|
||||
"bea12066-ecbd-49b0-8934-efcb2c38b5f5" -> "a3766a34-5152-4f82-8fba-8bf1f6b3830b";
|
||||
}
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 98 KiB |
|
|
@ -0,0 +1,211 @@
|
|||
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
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<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
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<!-- Generated by graphviz version 9.0.0 (20230911.1827)
|
||||
-->
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||||
<!-- Title: pastafarianism Pages: 1 -->
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<svg width="1699pt" height="417pt"
|
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viewBox="0.00 0.00 1699.49 416.87" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 412.87)">
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<title>pastafarianism</title>
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<polygon fill="white" stroke="none" points="-4,4 -4,-412.87 1695.49,-412.87 1695.49,4 -4,4"/>
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<!-- a3ac082f-ad46-4cc9-86b4-3e76c3c564d3 -->
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<g id="node1" class="node">
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<title>a3ac082f-ad46-4cc9-86b4-3e76c3c564d3</title>
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||||
<text text-anchor="middle" x="495.87" y="-370.24" font-family="Times New Roman,serif" font-size="20.00">Selector</text>
|
||||
</g>
|
||||
<!-- 717a1290-56bc-41e1-9b4b-e6df93d40e64 -->
|
||||
<g id="node2" class="node">
|
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<title>717a1290-56bc-41e1-9b4b-e6df93d40e64</title>
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<polygon fill="orange" stroke="black" points="395.38,-276.54 395.38,-296.35 352.9,-310.37 292.83,-310.37 250.35,-296.35 250.35,-276.54 292.83,-262.53 352.9,-262.53 395.38,-276.54"/>
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<text text-anchor="middle" x="322.87" y="-279.07" font-family="Times New Roman,serif" font-size="20.00">Sequence</text>
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</g>
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<!-- a3ac082f-ad46-4cc9-86b4-3e76c3c564d3->717a1290-56bc-41e1-9b4b-e6df93d40e64 -->
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<g id="edge1" class="edge">
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<title>a3ac082f-ad46-4cc9-86b4-3e76c3c564d3->717a1290-56bc-41e1-9b4b-e6df93d40e64</title>
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<polygon fill="black" stroke="black" points="374.07,-309.9 363.58,-308.43 370.87,-316.13 374.07,-309.9"/>
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</g>
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<!-- ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e -->
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<g id="node5" class="node">
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<title>ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e</title>
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<text text-anchor="middle" x="669.87" y="-279.07" font-family="Times New Roman,serif" font-size="20.00">Sequence</text>
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</g>
|
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<!-- a3ac082f-ad46-4cc9-86b4-3e76c3c564d3->ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e -->
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<g id="edge4" class="edge">
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<title>a3ac082f-ad46-4cc9-86b4-3e76c3c564d3->ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e</title>
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<path fill="none" stroke="black" d="M530.24,-359C556.02,-345.79 591.68,-327.51 620.51,-312.74"/>
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<polygon fill="black" stroke="black" points="621.74,-316.04 629.04,-308.37 618.55,-309.81 621.74,-316.04"/>
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</g>
|
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<!-- b3236b13-d5f2-4643-ae7c-6f27bd4ab6f2 -->
|
||||
<g id="node3" class="node">
|
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<title>b3236b13-d5f2-4643-ae7c-6f27bd4ab6f2</title>
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<ellipse fill="yellow" stroke="black" cx="125.87" cy="-202.61" rx="125.87" ry="22.1"/>
|
||||
<text text-anchor="middle" x="125.87" y="-195.24" font-family="Times New Roman,serif" font-size="20.00">CustomerChatting()</text>
|
||||
</g>
|
||||
<!-- 717a1290-56bc-41e1-9b4b-e6df93d40e64->b3236b13-d5f2-4643-ae7c-6f27bd4ab6f2 -->
|
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<g id="edge2" class="edge">
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<title>717a1290-56bc-41e1-9b4b-e6df93d40e64->b3236b13-d5f2-4643-ae7c-6f27bd4ab6f2</title>
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<path fill="none" stroke="black" d="M278.16,-266.88C250.24,-255.28 213.99,-240.22 183.86,-227.7"/>
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<polygon fill="black" stroke="black" points="185.46,-224.58 174.88,-223.97 182.77,-231.04 185.46,-224.58"/>
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</g>
|
||||
<!-- 28015225-b7a4-4f38-b26f-4dbe5eea4154 -->
|
||||
<g id="node4" class="node">
|
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<title>28015225-b7a4-4f38-b26f-4dbe5eea4154</title>
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<polygon fill="lawngreen" stroke="black" points="376.24,-220.61 269.49,-220.61 269.49,-184.61 376.24,-184.61 376.24,-220.61"/>
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||||
<text text-anchor="middle" x="322.87" y="-195.24" font-family="Times New Roman,serif" font-size="20.00">DealChat()</text>
|
||||
</g>
|
||||
<!-- 717a1290-56bc-41e1-9b4b-e6df93d40e64->28015225-b7a4-4f38-b26f-4dbe5eea4154 -->
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<g id="edge3" class="edge">
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<title>717a1290-56bc-41e1-9b4b-e6df93d40e64->28015225-b7a4-4f38-b26f-4dbe5eea4154</title>
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<g id="node6" class="node">
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<title>2f77f976-499c-4601-9d8c-86dd80d66dfa</title>
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<text text-anchor="middle" x="486.87" y="-195.24" font-family="Times New Roman,serif" font-size="20.00">HasSubTask()</text>
|
||||
</g>
|
||||
<!-- ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e->2f77f976-499c-4601-9d8c-86dd80d66dfa -->
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<g id="edge5" class="edge">
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<title>ff83c742-a2ba-4aa5-8b3a-39ecd7c03b0e->2f77f976-499c-4601-9d8c-86dd80d66dfa</title>
|
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<path fill="none" stroke="black" d="M626.96,-266.26C600.92,-254.61 567.48,-239.66 539.8,-227.28"/>
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After Width: | Height: | Size: 15 KiB |
Loading…
Reference in New Issue