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import gradio as gr | |
from transformers import pipeline | |
import pandas as pd | |
import time # Import time to measure duration | |
# Load the text summarization pipeline | |
summarizer = pipeline("summarization", model="astro21/bart-cls_n") | |
chunk_counter = 0 | |
def summarize_text(input_text): | |
global chunk_counter | |
start_time = time.time() # Start timer | |
chunk_counter = 0 | |
max_chunk_size = 1024 | |
chunks = [input_text[i:i + max_chunk_size] for i in range(0, len(input_text), max_chunk_size)] | |
summarized_chunks = [] | |
chunk_lengths = [] | |
summarized_chunks_only = [] | |
for chunk in chunks: | |
chunk_counter += 1 | |
summarized_chunk = summarizer(chunk, max_length=128, min_length=64, do_sample=False)[0]['summary_text'] | |
summarized_chunks.append(f"Chunk {chunk_counter}:\n{summarized_chunk}") | |
summarized_chunks_only.append(summarized_chunk) | |
chunk_lengths.append(len(chunk)) | |
summarized_text = "\n".join(summarized_chunks) | |
summarized_text_only = "\n".join(summarized_chunks_only) | |
# Save the merged summary to a file | |
with open("summarized.txt", "w") as output_file: | |
output_file.write(summarized_text_only) | |
end_time = time.time() # End timer | |
duration = end_time - start_time | |
result = f"Summarized in {duration:.2f} seconds:\n{summarized_text}" | |
return result | |
# Define the Gradio interface | |
demo = gr.Interface(fn=summarize_text, | |
inputs=gr.Textbox(label="Enter Text", placeholder="Paste your text here.", lines=10), | |
outputs=gr.Textbox(label="Summarized Text"), | |
title="Text Summarization", | |
description="Paste text and click 'Summarize' to see a summarized version using BART.", | |
theme="huggingface", | |
allow_flagging="never") | |
demo.launch(share=True, debug=True) | |