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-distil",use_auth_token=auth_token)
pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-qa-detector-chinese",use_auth_token=auth_token)



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_en({"text":q, "text_pair":a})
    return res['label'],res['score']




with gr.Blocks() as demo:
    gr.Markdown("""
                ## ChatGPT Detector 🔬 (QA version)
                Visit our project on Github: [chatgpt-comparison-detection project](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection)<br>
                欢迎在 Github 上关注我们的 [ChatGPT 对比与检测项目](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection)
                
                This is the **QA version** detector, to detect whether an **answer** is generated by ChatGPT for certain **question**, using PLM-based classifiers.<br>
                您现在使用的是**问答版**的检测器，用来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。
                
                We also provide other two versions / 我们还提供了另外两种版本:
                - [Sinlge-text version / 独立文本版](https://huggingface.co/spaces/Hello-SimpleAI/chatgpt-detector-single): 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](https://huggingface.co/spaces/Hello-SimpleAI/chatgpt-detector-ling): 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"):
        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"):
        q2 = gr.Textbox(lines=2, label='问题',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.")
        a2 = gr.Textbox(lines=5, label='回答',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.")
        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')

    button1.click(predict_en, inputs=[q1,a1], outputs=[label1,score1])
    button1.click(predict_zh, inputs=[q2,a2], outputs=[label2,score2])


demo.launch()