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import torch
import gradio as gr
from transformers import pipeline
import logging
# Set up logging
logging.basicConfig(level=logging.INFO)
# Use a pipeline as a high-level helper
device = 0 if torch.cuda.is_available() else -1
text_summary = pipeline("summarization", model="facebook/bart-large-cnn", device=device, torch_dtype=torch.bfloat16)
# Function for summarization with enhancements
def summary(input, summary_type="medium"):
# Check for empty input
if not input.strip():
return "Error: Please provide some text to summarize."
# Calculate input length
input_length = len(input.split())
logging.info(f"Input length: {input_length} words")
# Handle input that's too short
if input_length < 10:
return "Error: Input is too short. Please provide at least 10 words."
# Handle input that's too long for the model
if input_length > 512:
return "Warning: Input exceeds the model's limit of 512 tokens. Please shorten the input text."
# Adjust max/min lengths based on the summary type
if summary_type == "short":
max_output_tokens = max(10, input_length // 4)
elif summary_type == "medium":
max_output_tokens = max(20, input_length // 2)
elif summary_type == "long":
max_output_tokens = max(30, (3 * input_length) // 4)
min_output_tokens = max(10, input_length // 6)
# Generate summary
output = text_summary(input, max_length=max_output_tokens, min_length=min_output_tokens, truncation=True)
return output[0]['summary_text']
# Gradio interface
def save_output(summary_text):
"""Save the summarized text to a file."""
with open("summary_output.txt", "w") as file:
file.write(summary_text)
return "Summary saved to 'summary_output.txt'."
gr.close_all()
# Create the Gradio interface
demo = gr.Interface(
fn=summary,
inputs=[
gr.Textbox(label="INPUT THE PASSAGE TO SUMMARIZE", lines=15, placeholder="Paste your text here."),
gr.Dropdown(["short", "medium", "long"], label="SUMMARY LENGTH", value="medium")
],
outputs=[
gr.Textbox(label="SUMMARIZED TEXT", lines=10, placeholder="Your summarized text will appear here."),
gr.Button("Download Summary")
],
title="PAVISHINI @ GenAI Project 1: Text Summarizer",
description=(
"This application summarizes input text. "
"The output length can be short, medium, or long based on your selection."
),
live=True
)
demo.launch()
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