import gradio as gr
from transformers import pipeline

def summarize_aritcle(Article, model_selector, min_length, max_length):
    summarizer = pipeline("summarization", model=model_selector)
    return f"{model_selector}: \n {summarizer(Article, max_length=max_length, min_length=min_length, do_sample=False)[0]['summary_text']}"

# gradio_app = gr.Interface(fn=greet, inputs="text", outputs="text")
model_list = ["facebook/bart-large-cnn", "facebook/bart-large-xsum"]

with gr.Blocks() as demo:
    model_selector = gr.Dropdown(model_list, label="model selection", value=0, show_label=True)    

    article = gr.TextArea(label="Article Text")
    min_length=gr.Number(label="min summary length", value=30)
    max_length=gr.Number(label="max summary length", value=100)
    
    summary_text = gr.TextArea(label="Summary Text")
    run_btn = gr.Button("Do Summarize")
    run_btn.click(fn=summarize_aritcle, inputs=[article, model_selector, min_length, max_length], outputs=summary_text)

if __name__ == "__main__":
    demo.launch()