import os
import io
#from IPython.display import Image, display, HTML
from PIL import Image
import base64 
#from dotenv import load_dotenv, find_dotenv
#_ = load_dotenv(find_dotenv()) # read local .env file
#hf_api_key = os.environ['HF_API_KEY']

# Helper function
import requests, json


from transformers import pipeline

get_completion = pipeline("summarization", model="shleifer/distilbart-cnn-12-6")

import gradio as gr

def summarize(input):
    output = get_completion(input)
    return output[0]['summary_text']

gr.close_all()
demo = gr.Interface(fn=summarize, 
                    inputs=[gr.Textbox(label="Text to summarize", lines=6)],
                    outputs=[gr.Textbox(label="Result", lines=3)],
                    title="Text summarization with distilbart-cnn",
                    description="Summarize any text using the `shleifer/distilbart-cnn-12-6` model under the hood!"
                   )
demo.launch(share=True, server_port=int(os.environ['PORT2']))