Best pdf document summarizer to generate accurate summary from PDF

To get the best PDF document summarizer for large PDF files? Using Python for summarizing large PDF files is a powerful and flexible approach, especially if you're comfortable with programming. It allows you to process large documents efficiently by splitting them into manageable chunks and applying NLP (Natural Language Processing) models to generate summaries.

Here's a step-by-step guide to help you set up a best PDF document summarizer using Python:
1. Python installed on your system (version 3.6+ recommended)
2. Basic knowledge of Python scripting
3. Open your command prompt or terminal and install the following libraries:

pip install PyMuPDF transformers nltk

4. PyMuPDF (also known as fitz) for extracting text from PDFs
transformers for accessing pre-trained NLP models (like BART or T5)
nltk for optional text processing
5. Here's a sample code to extract text from your PDF:

import fitz  # PyMuPDF

def extract_text_from_pdf(pdf_path):
    doc = fitz.open(pdf_path)
    text = ""
    for page_num in range(len(doc)):
        page = doc.load_page(page_num)
        text += page.get_text()
    return text

pdf_path = "your_large_pdf.pdf"
full_text = extract_text_from_pdf(pdf_path)