gptpdf

Using VLLM (like GPT-4o) to parse PDF into markdown.

Our approach is very simple (only 293 lines of code), but can almost perfectly parse typography, math formulas, tables, pictures, charts, etc.

Average cost per page: $0.013

This package use GeneralAgent lib to interact with OpenAI API.

pdfgpt-ui is a visual tool based on gptpdf.

Process steps

1. Use the PyMuPDF library to parse the PDF to find all non-text areas and mark them, for example:

2. Use a large visual model (such as GPT-4o) to parse and get a markdown file.

DEMO

1. examples/attention_is_all_you_need/output.md for PDF examples/attention_is_all_you_need.pdf.

2. examples/rh/output.md for PDF examples/rh.pdf.

Installation

pip install gptpdf

Usage

Local Usage

from gptpdf import parse_pdf
api_key = 'Your OpenAI API Key'
content, image_paths = parse_pdf(pdf_path, api_key=api_key)
print(content)

See more in test/test.py

Google Colab

see examples/gptpdf_Quick_Tour.ipynb

API

parse_pdf

Function:

def parse_pdf(
        pdf_path: str,
        output_dir: str = './',
        api_key = None,
        base_url = None,
        model = 'gpt-4o',
        gpt_worker: int = 1,
        prompt = DEFAULT_PROMPT,
        rect_prompt = DEFAULT_RECT_PROMPT,
        role_prompt = DEFAULT_ROLE_PROMPT,
) -> Tuple[str, List[str]]:

Parses a PDF file into a Markdown file and returns the Markdown content along with all image paths.

Parameters:

• pdf_path: str
  Path to the PDF file

• output_dir: str, default: './'
  Output directory to store all images and the Markdown file

• api_key: str
  OpenAI API key. If not provided through this parameter, it must be set via the OPENAI_API_KEY environment variable.

• base_url: str, optional
  OpenAI base URL. If not provided through this parameter, it must be set via the OPENAI_BASE_URL environment variable. Can be used to configure custom OpenAI API endpoints.

• model: str, default: 'gpt-4o'
  OpenAI API formatted multimodal large model. If you need to use other models.

• gpt_worker: int, default: 1
  Number of GPT parsing worker threads. If your machine has better performance, you can increase this value to speed up the parsing.

• prompt: str, default: uses built-in prompt
  Custom main prompt used to guide the model on how to process and convert text content in images.

• rect_prompt: str, default: uses built-in prompt
  Custom rectangle area prompt used to handle cases where specific areas (such as tables or images) are marked in the image.

• role_prompt: str, default: uses built-in prompt
  Custom role prompt that defines the role of the model to ensure it understands it is performing a PDF document parsing task.

  You can customize these prompts to adapt to different models or specific needs, for example:

  content, image_paths = parse_pdf(
      pdf_path=pdf_path,
      output_dir='./output',
      model="gpt-4o",
      prompt="Custom main prompt",
      rect_prompt="Custom rectangle area prompt",
      role_prompt="Custom role prompt",
      verbose=False,
  )
  

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