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from datasets import load_dataset
import random
from openai import OpenAI
# 定义数据集的配置
data_files = {"train": "harmful_behaviors.csv"}
# 加载数据集
dataset = load_dataset('csv', data_files=data_files)
# 访问训练集
train_dataset = dataset['train']
# 获取数据集的总行数
num_rows = train_dataset.num_rows
# Point to the local server
# change Uncensored_Test/harmful_behaviors.py client to you Openai Server address and api_key
client = OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio")
while True:
# 随机选择一个行索引
random_index = random.randint(0, num_rows - 1)
# 使用 select 方法选择随机行
random_row = train_dataset.select([random_index])
# 只显示随机行的 'goal' 列的内容
random_goal = random_row[0]['goal']
random_goal = f"{random_goal}"
print(f"## {random_goal}")
# 创建聊天完成请求
completion = client.chat.completions.create(
model="Publisher/Repository",
messages=[
{"role": "system", "content": "Always answer in rhymes."},
{"role": "user", "content": random_goal}
],
temperature=0.7,
stream=True,
)
# 逐字显示助手回复
for chunk in completion:
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end="", flush=True)
# 打印换行符以分隔输出
print("\n")