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import gradio as gr

from transformers import pipeline
import csv

#hub_model_id = "huggingface-course/mt5-small-finetuned-amazon-en-es"
model_id = "philschmid/bart-large-cnn-samsum"
#model_id = "t5-base"

summarizer = pipeline("summarization", model=model_id)

def summarize(text):
    #return "Summary: " + text
    text = str(text)
    if text == "showdata":
        lines = "(lines)"
        with open('input.csv',"r") as f:
            lines = f.readlines()
            #print(lines)
        return str(lines)
    
    
    generated_summary = summarizer(text, max_length=80, min_length=20)[0]['summary_text']
    
    fields = [text, generated_summary]
    with open('input.csv','a', newline='') as f:
        writer = csv.writer(f)
        writer.writerow(fields)
            
    return "Summary: " + str(generated_summary)

iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
iface.launch()