import openai
import gradio as gr
import random


openai.api_key = random.choice(['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',
              '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',
              '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',
              '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',
              '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',
              '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',
              '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',
              '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',
              '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',
              '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',
              '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'])

def completion(prompt):
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=prompt,
        max_tokens=1024,
        n=1,
        stop=None,
        temperature=0.5
        )
    return response.choices[0].text[2:]

def greet(question):
    return completion('Please translate this passage into German and then into Chinese.\n'+question)


demo = gr.Interface(fn=greet, inputs=gr.Textbox(lines=20, placeholder='Please enter the text to be weighted down'), outputs=gr.Textbox(lines=20, placeholder='It will take some time to reduce the weight, please wait...'))

if __name__ == "__main__":
    # demo.launch(share='True')
    demo.launch()