kiwi-pdf-chunker 0.2.5

A tool for parsing PDF document layouts and chunking content

PDF Parser

A Python package for parsing PDF document layouts using YOLO models, chunking content based on layout, and optionally performing OCR.

Features

• Convert PDF documents to images for processing.
• Detect document layout elements (e.g., paragraphs, tables, figures) using YOLO.
• Process and refine bounding boxes.
• Chunk document content based on detected layout.
• (Optional) Perform OCR on detected elements using Azure Document Intelligence.
• Save structured document data (layouts, chunks, OCR text) in JSON format.
• Get paragraph embeddings using OpenAI embedder

Installation

Prerequisites

• Python 3.10+
• Pip package manager
• (Optional but Recommended) CUDA-capable GPU for YOLO model inference acceleration.

Steps

1. Install the Package:

   # pip install kiwi-pdf-chunker
   

User-Provided Data

This package requires the user to provide certain data externally:

1. Input Directory (input/): Place the PDF documents you want to process in a directory (e.g., input/). You will need to provide the path to your input file(s) when using the package.
2. Models Directory (models/): Download the necessary YOLO model(s) (e.g., doclayout_yolo_docstructbench_imgsz1024.pt) and place them in a dedicated directory (e.g., models/). The path to this directory (or the specific model file) will be needed by the parser.