import gradio as gr
from transformers import pipeline

summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
ner = pipeline("ner", aggregation_strategy="simple")

def get_entities(article):
    return ner(article)
    
def make_summary(article, max_length=130, min_length=30, do_sample=False):
    summ = summarizer(article, max_length, min_length, do_sample)[0]
    ents = get_entities(article)
    entslen = len(ents[0].keys())
    return summ.get('summary_text'), entslen, ents



iface = gr.Interface(fn=make_summary, inputs="text", outputs=['text', 'text', 'text'])
iface.launch()