lazyFrogLOL/llmdocparser
A package for parsing PDFs and analyzing their content using LLMs.
Need to extract specific information from complex PDF documents like research papers or financial reports? This tool accurately parses your PDF files, identifying distinct regions such as text, titles, figures, tables, and equations. It then uses advanced AI models to extract content from these regions, providing structured text blocks optimized for further analysis or integration into systems like Retrieval-Augmented Generation (RAG). This is ideal for researchers, analysts, or anyone who regularly needs to pull detailed, categorized content from a large volume of PDFs.
269 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to precisely extract and categorize content from PDFs, separating out elements like figures, tables, and references into distinct text blocks.
Not ideal if you only need a simple, raw text dump from a PDF without detailed structural analysis or content categorization.
Stars
269
Forks
8
Language
Python
License
MIT
Category
Last pushed
Aug 06, 2024
Commits (30d)
0
Dependencies
13
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/lazyFrogLOL/llmdocparser"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kreuzberg-dev/kreuzberg
A polyglot document intelligence framework with a Rust core. Extract text, metadata, and...
PaddlePaddle/PaddleOCR
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR...
yfedoseev/pdf_oxide
The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown...
opendataloader-project/opendataloader-pdf
PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.
AKSarav/pdfstract
PDFStract - The Extraction and Chunking Layer in Your RAG Pipeline - Available as CLI - WEBUI - API