修改固定组合
This commit is contained in:
ChenXL97
parent
7e63d9658b
commit
f8e4f0053c
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@ -1,51 +1,55 @@
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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.ask_llm import ask_llm
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from robowaiter.llm_client.multi_rounds import ask_llm,new_history
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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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}
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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(sentence)
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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.chat_history += sentence + '\n'
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res_dict = ask_llm(sentence)
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answer = res_dict["Answer"]
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self.scene.chat_bubble(answer) # 机器人输出对话
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self.chat_history += answer + '\n'
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goal = res_dict["Goal"]
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if goal:
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if "{" not in goal:
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goal = {str(goal)}
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else:
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goal=eval(goal)
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if goal is not None:
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print(f'goal：{goal}')
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self.create_sub_task(goal)
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if self.scene.show_bubble:
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self.scene.chat_bubble(f"{answer}")
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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,goal):
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self.scene.robot.expand_sub_task_tree(goal)
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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[0] + ")")
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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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@ -0,0 +1,17 @@
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你好
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您好，我是这家咖啡厅的服务员，请问您要点什么？
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做一杯咖啡
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好的，我马上做咖啡
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create_sub_task
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{"goal":"On(Coffee,CoffeeTable)"}
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不用了
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好的，您有需要再跟我说
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stop_serve
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{}
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来一号桌
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好的，我马上来一号桌
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create_sub_task
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{"goal":"At(Robot,Table1)"}
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@ -1,29 +1,162 @@
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import json
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import openai
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from colorama import init, Fore
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from loguru import logger
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import json
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from robowaiter.llm_client.tool_register import get_tools, dispatch_tool
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import requests
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import json
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from collections import deque
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import urllib3
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from robowaiter.llm_client.tool_api import run_conversation
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import copy
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init(autoreset=True)
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from robowaiter.utils import get_root_path
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import os
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import re
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from robowaiter.llm_client.single_round import single_round
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########################################
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# 该文件实现了与大模型的简单通信、多轮对话，输入end表示对话结束
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# 该文件实现了与大模型的通信以及工具调用
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########################################
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# 忽略https的安全性警告
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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url = "https://45.125.46.134:25344/v1/chat/completions"
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headers = {"Content-Type": "application/json"}
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base_url = "https://45.125.46.134:25344" # 本地部署的地址,或者使用你访问模型的API地址
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#在这里输入你的问题
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k=input()
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data_memory=[]
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n=1
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while k!='end':
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question_now=k
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user_dict={"role": "user","content":question_now}
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data_memory.append(user_dict)
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#print(data_memory)
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response = run_conversation(str(data_memory))
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answer=str(response)
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print(answer)
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assistant_dict={"role": "assistant","content":answer}
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data_memory.append(assistant_dict)
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n=n+2
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k=input()
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root_path = get_root_path()
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# load test questions
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file_path = os.path.join(root_path,"robowaiter/llm_client/data/fix_questions.txt")
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fix_questions_dict = {}
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with open(file_path,'r',encoding="utf-8") as f:
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#读取所有行
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lines = f.read().strip()
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sections = re.split(r'\n\s*\n', lines)
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for s in sections:
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x = s.split()
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fix_questions_dict[x[0]] = x[1:]
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functions = get_tools()
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role_system = [{
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"role": "system",
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"content": "你是RoboWaiter,一个由HPCL团队开发的机器人服务员，你在咖啡厅工作。接受顾客的指令并调用工具函数来完成各种服务任务。如果顾客问你们这里有什么，或者想要点单，你说我们咖啡厅提供咖啡，水，点心，酸奶等食物。如果顾客不需要你了，你就回到吧台招待。如果顾客叫你去做某事，你回复：好的，我马上去做这件事。",
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}]
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def new_history(max_length=7):
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history = deque(maxlen=max_length)
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return history
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def new_response():
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return {'choices': [{'index': 0, 'message':{} }]}
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def parse_fix_question(question):
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response = new_response()
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fix_ans = fix_questions_dict[question]
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if len(fix_ans)<=1: #简单对话
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message = {'role': 'assistant', 'content': fix_ans, 'name': None,
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'function_call': None}
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else:
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reply, func,args = fix_ans
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# tool_response = dispatch_tool(function_call["name"], json.loads(args))
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# logger.info(f"Tool Call Response: {tool_response}")
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message = {'role': 'assistant',
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'content': f"\n <|assistant|> {func}({args})\n ```python\ntool_call(goal={args})\n```",
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'name': None,
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'function_call': {'name': func, 'arguments': args}}
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response["choices"][0]["message"] = message
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return response
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def get_response(sentence, history, allow_function_call = True):
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if sentence:
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history.append({"role": "user", "content": sentence})
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if sentence in fix_questions_dict:
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return parse_fix_question(sentence)
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params = dict(model="RoboWaiter")
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params['messages'] = role_system + list(history)
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if allow_function_call:
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params["functions"] = functions
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response = requests.post(f"{base_url}/v1/chat/completions", json=params, stream=False, verify=False)
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decoded_line = response.json()
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return decoded_line
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def deal_response(response, history, func_map=None ):
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if response["choices"][0]["message"].get("function_call"):
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function_call = response["choices"][0]["message"]["function_call"]
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logger.info(f"Function Call Response: {function_call}")
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function_name = function_call["name"]
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function_args = json.loads(function_call["arguments"])
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if func_map:
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tool_response = func_map[function_name](**function_args)
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else:
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try:
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tool_response = dispatch_tool(function_call["name"], function_args)
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logger.info(f"Tool Call Response: {tool_response}")
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except:
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logger.info(f"重试工具调用")
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# tool_response = dispatch_tool(function_call["name"], function_args)
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return function_name,None
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return_message = response["choices"][0]["message"]
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history.append(return_message)
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t = {
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"role": "function",
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"name": function_call["name"],
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"content": str(tool_response), # 调用函数返回结果
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}
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history.append(t)
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return function_call["name"], return_message
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else:
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return_message = response["choices"][0]["message"]
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reply = return_message["content"]
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history.append(return_message)
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logger.info(f"Final Reply: \n{reply}")
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return False, reply
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def ask_llm(question,history, func_map=None, retry=3):
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response = get_response(question, history)
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function_call,result = deal_response(response, history, func_map)
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if function_call:
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if question in fix_questions_dict:
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reply = fix_questions_dict[question][0]
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result = single_round(reply,"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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message = {'role': 'assistant', 'content': result, 'name': None,
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'function_call': None}
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history.append(message)
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else:
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response = get_response(None, history,allow_function_call=False)
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_,result = deal_response(response, history, func_map)
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print(f'{len(history)}条历史记录:')
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for x in history:
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print(x)
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return function_call, result
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if __name__ == "__main__":
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question = input("\n顾客：")
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history = new_history()
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n = 1
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max_retry = 2
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while question != 'end':
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function_call, return_message = ask_llm(question,history)
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question = input("\n顾客：")
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@ -9,7 +9,7 @@ import urllib3
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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def single_round(question):
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def single_round(question,prefix=""):
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url = "https://45.125.46.134:25344/v1/chat/completions"
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headers = {"Content-Type": "application/json"}
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data = {
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@ -21,7 +21,7 @@ def single_round(question):
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},
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{
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"role": "user",
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"content": question
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"content": prefix + question
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}
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]
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}
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@ -147,6 +147,17 @@ def create_sub_task(
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return goal
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@register_tool
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def stop_serve(
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) -> bool:
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"""
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当顾客通过任何形式表示不再需要服务时，调用该函数
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"""
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return True
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# @register_tool
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# def get_object_info(
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# obj: Annotated[str, '需要获取信息的物体名称', True]
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@ -71,6 +71,7 @@ class Scene:
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"greeted_customers":set(),
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"attention":{},
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"serve_state":{},
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"chat_history":{}
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}
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"""
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status:
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@ -439,7 +440,7 @@ class Scene:
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def chat_bubble(self, message):
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stub.ControlRobot(
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GrabSim_pb2.ControlInfo(
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scene=self.sceneID, type=0, action=1, content=message
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scene=self.sceneID, type=0, action=1, content=message.strip()
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)
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)
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@ -18,28 +18,14 @@ class SceneOT(Scene):
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super().__init__(robot)
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# 在这里加入场景中发生的事件
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self.new_event_list = [
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# (9,self.add_walkers,([[0, 880]],)),
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# (10,self.walker_walk_to,(2,50,500))
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# (5, self.set_goal("On(Yogurt,Table4)"))
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(3, self.customer_say, ("System","来一号桌"))
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# (5, self.set_goal("At(Robot,BrightTable4)"))
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]
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def _reset(self):
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# self.add_walkers([[0, 880], [250, 1200]])
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pass
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# 展示顾客，前8个id是小孩，后面都是大人
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for i in range(4):
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self.add_walker(i,50,300 + i * 50)
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name1 = self.walker_index2mem(1)
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name2 = self.walker_index2mem(3)
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self.remove_walker(0,2)
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index1 = self.state["customer_mem"][name1]
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index2 = self.state["customer_mem"][name2]
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self.walker_bubble(name1,f"我是第{index1}个")
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self.walker_bubble(name2,f"我是第{index2}个")
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def _run(self):
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pass
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@ -0,0 +1,57 @@
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"""
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人提出请求，机器人完成任务
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1. 做咖啡（固定动画）：接收到做咖啡指令、走到咖啡机、拿杯子、操作咖啡机、取杯子、送到客人桌子上
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2. 倒水
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3. 夹点心
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具体描述：设计一套点单规则（如菜单包含咖啡、水、点心等），按照规则拟造随机的订单。在收到订单后，通过大模型让机器人输出合理的备餐计划，并尝试在模拟环境中按照这个规划实现任务。
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"""
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# todo: 接收点单信息，大模型生成任务规划
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from robowaiter.scene.scene import Scene
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class SceneOT(Scene):
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def __init__(self, robot):
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super().__init__(robot)
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# 在这里加入场景中发生的事件
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self.new_event_list = [
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# (9,self.add_walkers,([[0, 880]],)),
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# (10,self.walker_walk_to,(2,50,500))
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# (5, self.set_goal("On(Yogurt,Table4)"))
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# (5, self.set_goal("At(Robot,BrightTable4)"))
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]
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def _reset(self):
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# self.add_walkers([[0, 880], [250, 1200]])
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# 展示顾客，前8个id是小孩，后面都是大人
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for i in range(4):
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self.add_walker(i,50,300 + i * 50)
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name1 = self.walker_index2mem(1)
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name2 = self.walker_index2mem(3)
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self.remove_walker(0,2)
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index1 = self.state["customer_mem"][name1]
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index2 = self.state["customer_mem"][name2]
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self.walker_bubble(name1,f"我是第{index1}个")
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self.walker_bubble(name2,f"我是第{index2}个")
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def _run(self):
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pass
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if __name__ == '__main__':
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import os
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from robowaiter.robot.robot import Robot
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robot = Robot()
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# create task
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task = SceneOT(robot)
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task.reset()
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task.run()
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