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import os
import gradio as gr
from transformers import pipeline
# auth_token = os.environ.get("access_token")
pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-qa-detector-roberta") # use_auth_token=auth_token
pipeline_zh = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-qa-detector-roberta-chinese")
def predict_en(q,a):
res = pipeline_en({"text":q, "text_pair":a})
return res['label'],res['score']
def predict_zh(q,a):
res = pipeline_zh({"text":q, "text_pair":a})
return res['label'],res['score']
with gr.Blocks() as demo:
## ChatGPT Detector 🔬 (QA version)
Visit our project on Github: [chatgpt-comparison-detection project](<br>
欢迎在 Github 上关注我们的 [ChatGPT 对比与检测项目](
We provide three kinds of detectors, all in Bilingual / 我们提供了三个版本的检测器,且都支持中英文:
- [**QA version / 问答版** (👈 Current / 当前使用)](<br>
detect whether an **answer** is generated by ChatGPT for certain **question**, using PLM-based classifiers / 判断某个**问题的回答**是否由ChatGPT生成,使用基于PTM的分类器来开发;
- [Sinlge-text version / 独立文本版](<br>
detect whether a piece of text is ChatGPT generated, using PLM-based classifiers / 判断**单条文本**是否由ChatGPT生成,使用基于PTM的分类器来开发;
- [Linguistic version / 语言学版](<br>
detect whether a piece of text is ChatGPT generated, using linguistic features / 判断**单条文本**是否由ChatGPT生成,使用基于语言学特征的模型来开发;
with gr.Tab("English"):
Note: Providing more text to the `Answer` box can make the prediction more accurate!
q1 = gr.Textbox(lines=2, label='Question',value="What stops a restaurant from noting down my credit card info and using it ? No offense to restaurants . Can be generalized to anyone who I give my credit card info to . Explain like I'm five.")
a1 = gr.Textbox(lines=5, label='Answer',value="There are a few things that can help protect your credit card information from being misused when you give it to a restaurant or any other business:\n\nEncryption: Many businesses use encryption to protect your credit card information when it is being transmitted or stored. This means that the information is transformed into a code that is difficult for anyone to read without the right key.")
button1 = gr.Button("🤖 Predict!")
label1 = gr.Textbox(lines=1, label='Predicted Label 🎃')
score1 = gr.Textbox(lines=1, label='Prob')
with gr.Tab("中文版"):
注意: 在`回答`栏中输入更多的文本,可以让预测更准确哦!
q2 = gr.Textbox(lines=2, label='问题',value="如何评价 OpenAI 的超级对话模型 ChatGPT ?")
a2 = gr.Textbox(lines=5, label='回答',value="对于OpenAI大力出奇迹的工作,自然每个人都有自己的看点。我自己最欣赏的地方是ChatGPT如何解决 “AI校正(Alignment)“这个问题。这个问题也是我们课题组这两年在探索的学术问题之一。")
button2 = gr.Button("🤖 预测!")
label2 = gr.Textbox(lines=1, label='预测结果 🎃')
score2 = gr.Textbox(lines=1, label='模型概率'), inputs=[q1,a1], outputs=[label1,score1]), inputs=[q2,a2], outputs=[label2,score2])
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