app.py

import newspaper
from newspaper import*
import gradio as gr
import openai
openai.api_key = "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"
import validators
def predict(model, url_or_text, prompt, temperature, max_tokens):
  text = url_or_text
  if validators.url(url_or_text):
    article = Article(url="%s" % (url_or_text), language='en')
    article.download()
    article.parse()
    text = article.text
  response = openai.Completion.create(
    model=model,
    prompt = text + "\n"+ prompt,
    temperature=int(temperature),
    max_tokens=int(max_tokens),
    top_p=1,
    frequency_penalty=0.0,
    presence_penalty=1
  )
  return response.choices[0].text
intr = gr.Interface(predict, [gr.Dropdown(["text-curie-001", "text-davinci-003"], value = "text-curie-001"), gr.Textbox(value="https://www.datasciencecentral.com/will-chatgpt-make-fraud-easier/"),gr.Textbox(value="tl:dr"),gr.Number(value=0.7), gr.Number(value=100)], 
                    "text", title = "Summmarizer", description = "For default summarizer give prompt as tl:dr, and temprature 0-1, higher the value, the more random will be the output. "
                    ,examples=[["text-curie-001",'https://www.datasciencecentral.com/will-chatgpt-make-fraud-easier/', 'Get the gist of the article',0.7, 100],
                               ["text-curie-001","A neutron star is the collapsed core of a massive supergiant star, which had a total mass of between 10 and 25 solar masses, possibly more if the star was especially metal-rich.[1] Neutron stars are the smallest and densest stellar objects, excluding black holes and hypothetical white holes, quark stars, and strange stars.[2] Neutron stars have a radius on the order of 10 kilometres (6.2 mi) and a mass of about 1.4 solar masses.[3] They result from the supernova explosion of a massive star, combined with gravitational collapse, that compresses the core past white dwarf star density to that of atomic nuclei."
                                ,"tl:dr",0.5, 50],
                               ["text-davinci-003",'https://www.datasciencecentral.com/enriching-customer-service-using-sentiment-analysis/','Summerize the crux of the above article for a linkedin post', 0.3,100]])
intr.launch(inline = False)