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import gradio as gr
from transformers import BartForConditionalGeneration, BartTokenizer
from PyPDF2 import PdfFileReader
import torch
# Loading BART
model_name = "facebook/bart-large-cnn"
tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = BartForConditionalGeneration.from_pretrained(model_name).to(device)
# Function to Calculate summary lengths
def calc_summary_lengths(text_length):
short_min = int(0.10 * text_length)
medium_min = short_max_ = int(0.15 * text_length)
medium_max = long_min = int(0.20 * text_length)
long_max = int(0.30 * text_length)
return {
"Short": (short_min, short_max_),
"Medium": (medium_min, medium_max),
"Long": (long_min, long_max)
}
# Function to summarize text
def summarize_text(pdf_file, summary_length):
try:
text = ""
with open(pdf_file.name, "rb") as f:
reader = PdfFileReader(f)
for page in range(reader.numPages):
text += reader.getPage(page).extractText()
text = " ".join(text.split())
text_length = len(text.split())
summary_range = calc_summary_lengths(text_length)
min_length, max_length = summary_range[summary_length]
# Summary Generation
inputs = tokenizer.encode(text, max_length=1024, return_tensors='pt', truncation=True).to(device)
summary_ids = model.generate(inputs, num_beams=4, min_length=min_length, max_length=max_length, early_stopping=True)
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
return summary
except Exception as e:
return f"Error: {str(e)} \nPlease check file size and type!"
input_component = gr.File(label="Upload PDF file")
output_component = gr.Textbox(label="Summarized Text")
summary_length_component = gr.Dropdown(label="Summary Length", choices=["Short", "Medium", "Long"])
title = "PDF Text Summarizer (BART)"
description = "<h2>Upload a PDF file and select the desired summary length.</h2>"
InterFace = gr.Interface(fn=summarize_text, inputs=[input_component, summary_length_component], outputs=output_component, title=title, description=description)
InterFace.launch()
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