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import gradio as gr
from PyPDF2 import PdfReader
from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
from gtts import gTTS
from io import BytesIO
import re
# Load the LED-large model for summarization
model_name = "pszemraj/led-large-book-summary"
summarizer = pipeline("summarization", model=model_name, tokenizer=model_name)
def extract_abstract_and_summarize(pdf_file):
try:
if pdf_file is None:
raise ValueError("PDF file is not provided.")
with open(pdf_file, "rb") as file:
pdf_reader = PdfReader(file)
abstract_text = ""
for page_num in range(len(pdf_reader.pages)):
page = pdf_reader.pages[page_num]
text = page.extract_text()
abstract_match = re.search(r"\bAbstract\b", text, re.IGNORECASE)
if abstract_match:
start_index = abstract_match.end()
introduction_match = re.search(r"\bIntroduction\b", text[start_index:], re.IGNORECASE)
if introduction_match:
end_index = start_index + introduction_match.start()
else:
end_index = None
abstract_text = text[start_index:end_index]
break
# Summarize the extracted abstract using the LED-large model with a specific max_length
result = summarizer(abstract_text, max_length=81)
# Extract only the first sentence from the summary
if result and isinstance(result, list) and len(result) > 0:
summary = result[0].get('summary_text', 'Summary not available.')
# Extracting the first sentence
first_sentence = summary.split('.')[0] + '.'
else:
first_sentence = "Summary not available."
# Generate audio
speech = gTTS(text=first_sentence, lang="en")
speech_bytes = BytesIO()
speech.write_to_fp(speech_bytes)
# Return individual output values
return first_sentence, speech_bytes.getvalue(), abstract_text.strip()
except Exception as e:
raise Exception(str(e))
interface = gr.Interface(
fn=extract_abstract_and_summarize,
inputs=[gr.File(label="Upload PDF")],
outputs=[gr.Textbox(label="Summary"), gr.Audio()],
title="PDF Summarization & Audio Tool",
description="""PDF Summarization App. This app extracts the abstract from a PDF, summarizes it using the 'pszemraj/led-large-book-summary' model, and generates an audio of it. Only upload PDFs with abstracts. Please read the README.MD for information about the app and sample PDFs.""",
examples=[[os.path.join(os.path.dirname(__file__), "Article 11 Hidden Technical Debt in Machine Learning Systems.pdf")],[os.path.join(os.path.dirname(__file__), "Article 4 Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence.pdf")]],cache_examples=True,
)
interface.launch()
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