204 lines
6.8 KiB
Python
204 lines
6.8 KiB
Python
import inspect
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import traceback
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from copy import deepcopy
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from pprint import pformat
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from types import GenericAlias
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from typing import get_origin, Annotated
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import robowaiter.llm_client.find_obj_utils as find_obj_utils
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import random
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# import spacy
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_TOOL_HOOKS = {}
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_TOOL_DESCRIPTIONS = {}
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# nlp = spacy.load('en_core_web_lg')
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def register_tool(func: callable):
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tool_name = func.__name__
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tool_description = inspect.getdoc(func).strip()
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python_params = inspect.signature(func).parameters
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tool_params = []
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for name, param in python_params.items():
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annotation = param.annotation
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if annotation is inspect.Parameter.empty:
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raise TypeError(f"Parameter `{name}` missing type annotation")
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if get_origin(annotation) != Annotated:
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raise TypeError(f"Annotation type for `{name}` must be typing.Annotated")
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typ, (description, required) = annotation.__origin__, annotation.__metadata__
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typ: str = str(typ) if isinstance(typ, GenericAlias) else typ.__name__
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if not isinstance(description, str):
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raise TypeError(f"Description for `{name}` must be a string")
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if not isinstance(required, bool):
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raise TypeError(f"Required for `{name}` must be a bool")
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tool_params.append({
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"name": name,
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"description": description,
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"type": typ,
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"required": required
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})
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tool_def = {
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"name": tool_name,
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"description": tool_description,
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"params": tool_params
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}
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# print("[registered tool] " + pformat(tool_def))
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_TOOL_HOOKS[tool_name] = func
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_TOOL_DESCRIPTIONS[tool_name] = tool_def
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return func
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def dispatch_tool(tool_name: str, tool_params: dict) -> str:
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if tool_name not in _TOOL_HOOKS:
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return f"Tool `{tool_name}` not found. Please use a provided tool."
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tool_call = _TOOL_HOOKS[tool_name]
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try:
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ret = tool_call(**tool_params)
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except:
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ret = traceback.format_exc()
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return str(ret)
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def get_tools() -> dict:
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return deepcopy(_TOOL_DESCRIPTIONS)
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# Tool Definitions
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# @register_tool
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# def random_number_generator(
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# seed: Annotated[int, 'The random seed used by the generator', True],
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# range: Annotated[tuple[int, int], 'The range of the generated numbers', True],
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# ) -> int:
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# """
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# Generates a random number x, s.t. range[0] <= x < range[1]
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# """
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# if not isinstance(seed, int):
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# raise TypeError("Seed must be an integer")
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# if not isinstance(range, tuple):
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# raise TypeError("Range must be a tuple")
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# if not isinstance(range[0], int) or not isinstance(range[1], int):
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# raise TypeError("Range must be a tuple of integers")
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#
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# import random
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# return random.Random(seed).randint(*range)
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# @register_tool
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# def get_weather(
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# city_name: Annotated[str, 'The name of the city to be queried', True],
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# ) -> str:
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# """
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# Get the current weather for `city_name`
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# """
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#
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# if not isinstance(city_name, str):
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# raise TypeError("City name must be a string")
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#
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# key_selection = {
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# "current_condition": ["temp_C", "FeelsLikeC", "humidity", "weatherDesc", "observation_time"],
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# }
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# import requests
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# try:
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# resp = requests.get(f"https://wttr.in/{city_name}?format=j1")
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# resp.raise_for_status()
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# resp = resp.json()
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# ret = {k: {_v: resp[k][0][_v] for _v in v} for k, v in key_selection.items()}
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# except:
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# import traceback
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# ret = "Error encountered while fetching weather data!\n" + traceback.format_exc()
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#
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# return str(ret)
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# @register_tool
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# def add(
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# a: Annotated[int, '需要相加的第1个数', True],
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# b: Annotated[int, '需要相加的第2个数', True]
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# ) -> int:
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# """
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# 获取 `a` + `b` 的值
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# """
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#
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# if (not isinstance(a, int)) or (not isinstance(b, int)):
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# raise TypeError("相加的数必须为整数")
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#
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# return int(a+b)
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@register_tool
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def create_sub_task(
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goal: Annotated[str, '子任务需要达到的目标条件集合，例如{On(Coffee,Bar)}，{At(Robot,Table1)}，{Is(AC,Off)}', True]
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) -> str:
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"""
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当需要完成具身任务（如做咖啡，拿放物体，扫地，前往某位置）时，调用该函数，根据用户的提示进行意图理解，生成子任务的目标状态集合 `goal`（以一阶逻辑的形式表示），用户意图
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做一杯咖啡,则该函数的参数为 "On(Coffee,Bar)",
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前往一号桌,则该函数的参数为 "At(Robot,Table1)",
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前往二号桌,则该函数的参数为 "At(Robot,Table2)",
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打开空调,则该函数的参数为 "Is(AC,On)",
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关空调,则该函数的参数为 "Is(AC,Off)",
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打开窗帘,则该函数的参数为 "Is(Curtain,On)",
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关闭窗帘,则该函数的参数为 "Is(Curtain,Off)",
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拖地,则该函数的参数为 "Is(Floor,Clean)",
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打开大厅灯,则该函数的参数为 "Is(HallLight,On)",
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"""
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return goal
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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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# ) -> str:
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# """
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# 获取场景中指定物体 `object` 在哪里，不涉及到具体的执行任务
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# 如果`object` 是一个地点，例如洗手间，则输出大门。
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# 如果`object`是咖啡，则输出桌子，咖啡在桌子上。
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# 如果`object` 是空桌子，则输出一号桌
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# """
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# near_object = None
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# # if obj == "Table":
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# # near_object = "Bar"
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# # if obj == "洗手间":
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# # near_object = "大门"
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# # if obj == "空桌子":
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# # near_object = "一号桌"
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# if obj in find_obj_utils.all_loc: # object是一个地点
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# mp = list(find_obj_utils.loc_map[obj])
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# # near_object = random.choice(mp)
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# near_object = mp
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# if obj in find_obj_utils.all_obj: # object是一个物品
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# near_ls = find_obj_utils.all_loc + find_obj_utils.all_obj
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# near_object = random.choices(near_ls,k=5)
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# return near_object
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# @register_tool
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# def find_location(
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# location: Annotated[str, '客人咨询的地点', True]
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# ) -> str:
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# """"
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# 获取的location为英文
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# 用户想找某个地点
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# """
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# near_location = None
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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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# for w in find_obj_utils.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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#
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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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# if similar_word:
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# mp = list(find_obj_utils.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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if __name__ == "__main__":
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print(dispatch_tool("get_weather", {"city_name": "beijing"}))
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print(get_tools())
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