app.py

import torch
import gradio as gr
# from gradio.themes.builder_app import output_code

# Use a pipeline as a high-level helper
from transformers import pipeline

text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)

# model_path = ("../Models/models--sshleifer--distilbart-cnn-12-6/snapshots/a4f8f3ea906ed274767e9906dbaede7531d660ff")
# text_summary = pipeline("summarization", model=model_path, torch_dtype=torch.bfloat16)

# text = '''Elon Reeve Musk (/ˈiːlɒn/ EE-lon; born June 28, 1971) is a businessman known for his leadership of Tesla, SpaceX, and X (formerly Twitter). Since 2025, he has been a senior advisor to United States President Donald Trump and the de facto head of the Department of Government Efficiency (DOGE). Musk is the wealthiest person in the world; as of March 2025, Forbes estimates his net worth to be US$345 billion. He was named Time magazine's Person of the Year in 2021.'''
# print(text_summary(text))

def summary (input):
    output = text_summary(input)
    return output[0]['summary_text']

gr.close_all()

# demo = gr.Interface(fn=summary, inputs="text", outputs="text")
demo = gr.Interface(fn=summary,
             inputs=[gr.Textbox(label="Input text to summarize", lines=6)],
             outputs=[gr.Textbox(label="Summarized text", lines=4)],
             title="@GenAILearniverse Project 1: Text Summarizer",
             description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")

demo.launch()