工具调用
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ChenXL97
parent
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@ -5,16 +5,14 @@ from colorama import init, Fore
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from loguru import logger
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from tool_register import get_tools, dispatch_tool
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init(autoreset=True)
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# 使用Python代码测返回
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import requests
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import json
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import urllib3
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init(autoreset=True)
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########################################
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# 该文件实现了与大模型的简单通信
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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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@ -77,10 +75,10 @@ if __name__ == "__main__":
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query = "你是谁"
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run_conversation(query, stream=False)
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# query = "你是谁"
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# run_conversation(query, stream=False)
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#
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# logger.info("\n=========== next conversation ===========")
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logger.info("\n=========== next conversation ===========")
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query = "帮我查询北京的天气怎么样"
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query = "洗手间在哪儿"
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run_conversation(query, functions=functions, stream=False)
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@ -1,67 +0,0 @@
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# 使用curl命令测试返回
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# curl -X POST "http://127.0.0.1:8000/v1/chat/completions" \
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# -H "Content-Type: application/json" \
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# -d "{\"model\": \"chatglm3-6b\", \"messages\": [{\"role\": \"system\", \"content\": \"You are ChatGLM3, a large language model trained by Zhipu.AI. Follow the user's instructions carefully. Respond using markdown.\"}, {\"role\": \"user\", \"content\": \"你好，给我讲一个故事，大概100字\"}], \"stream\": false, \"max_tokens\": 100, \"temperature\": 0.8, \"top_p\": 0.8}"
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# 使用Python代码测返回
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import requests
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import json
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import urllib3
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########################################
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# 该文件实现了与大模型的简单通信
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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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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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def create_chat_completion(model, messages, use_stream=False):
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data = {
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"model": model, # 模型名称
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"messages": messages, # 会话历史
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"stream": use_stream, # 是否流式响应
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"max_tokens": 100, # 最多生成字数
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"temperature": 0.8, # 温度
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"top_p": 0.8, # 采样概率
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}
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response = requests.post(f"{base_url}/v1/chat/completions", json=data, stream=use_stream, verify=False)
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if response.status_code == 200:
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if use_stream:
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# 处理流式响应
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for line in response.iter_lines():
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if line:
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decoded_line = line.decode('utf-8')[6:]
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try:
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response_json = json.loads(decoded_line)
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content = response_json.get("choices", [{}])[0].get("delta", {}).get("content", "")
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print(content)
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except:
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print("Special Token:", decoded_line)
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else:
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# 处理非流式响应
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decoded_line = response.json()
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print(decoded_line)
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content = decoded_line.get("choices", [{}])[0].get("message", "").get("content", "")
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print(content)
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else:
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print("Error:", response.status_code)
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return None
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if __name__ == "__main__":
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chat_messages = [
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{
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"role": "system",
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"content": "You are ChatGLM3, a large language model trained by Zhipu.AI. Follow the user's instructions carefully. Respond using markdown.",
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},
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{
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"role": "user",
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"content": "你好，给我讲一个故事，大概100字"
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}
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]
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create_chat_completion("chatglm3-6b", chat_messages, use_stream=False)
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@ -64,50 +64,91 @@ def get_tools() -> dict:
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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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# @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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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 get_weather(
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city_name: Annotated[str, 'The name of the city to be queried', True],
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def create_sub_task(
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goal: Annotated[str, '用于子任务的目标状态集合', 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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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，以一阶逻辑的形式来表示，例如：前往桌子的目标状态为{At(Robot,Table)}，做咖啡的目标状态为{On(Coffee,Bar)}等
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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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return goal
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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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@register_tool
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def find_near_object(
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object: Annotated[str, '需要判断所在位置的物体', True]
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) -> str:
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"""
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在场景中找到相邻的物体，并说出 `object` 在输出物体的附近
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"""
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near_object = None
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if object == "Table":
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near_object = "Bar"
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if object == "洗手间":
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near_object = "大门"
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return near_object
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return str(ret)
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if __name__ == "__main__":
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