function

from pytube import YouTube
import whisper
import openai
openai.api_key = YOUROPENAIKEY
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN)

def createarticle_from_video(url):
    output = ''
    video = YouTube(url).streams.filter(only_audio=True).first()
    video.download('',"audio.mp4")
pipe = pipe.to("gpu")
    model = whisper.load_model("base")
    result = model.transcribe("audio.mp4")
    newstext = result["text"]
    
    prompt = "Newstext:\n" + newstext + "\nTitle:\n *"
    response = openai.Completion.create(
            engine="text-davinci-002",
            prompt=str(prompt),
            temperature=0,
            max_tokens=25,
            top_p=1,
            frequency_penalty=0,
            presence_penalty=0
        )
    titeltext = response["choices"][0]["text"]
    
    prompt = "Newstext:\n" + newstext + "\nMain facts:\n *"
    response = openai.Completion.create(
            engine="text-davinci-002",
            prompt=str(prompt),
            temperature=0,
            max_tokens=100,
            top_p=1,
            frequency_penalty=0,
            presence_penalty=0
        )

    resulttext = "*" + response["choices"][0]["text"]
    
    resultlist = resulttext.strip().split('*')

    image = pipe(titeltext).images[0]
    image.save("news.jpg")
    
    output = output + "#" + titeltext + "\n"
    
    output = output + "![" + titeltext + "](news.jpg?modified=1234567)"
    
    for i, res in enumerate(resultlist):
        output = output + res.strip() + "\n\n"
    
    return output