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Free, open-source file converter. Convert 263 formats offline by drag & drop — images, PDF, Word, Excel, PowerPoint, HWP/HWPX, video, audio, e-books and archives. No upload, no Office needed.

  • audio-converter
  • avalonia
  • batch-conversion
  • converter

LLM Wiki is a cross-platform desktop application that turns your documents into an organized, interlinked knowledge base — automatically. Instead of traditional RAG (retrieve-and-answer from scratch every time), the LLM incrementally builds and maintains a persistent wiki from your sources。

PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.

  • mupdf
  • xps
  • pdf-documents
  • epub

Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.

  • pdf
  • pdf-parsing
  • table-extraction

A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files

  • pypdf2
  • pdf
  • python
  • pdf-parser

A simple, semantic and developer-friendly time package for golang

  • carbon
  • date
  • datetime
  • time

CommonMark/Markdown Java parser with source level AST. CommonMark 0.28, emulation of: pegdown, kramdown, markdown.pl, MultiMarkdown. With HTML to MD, MD to PDF, MD to DOCX conversion modules.

This repository is outdated and no longer maintained. A new version of massCode is available! https://github.com/massCodeIO/massCode. A free and open source code snippets manager for developers.

iText for .NET is the .NET version of the iText library, formerly known as iTextSharp, which it replaces. iText represents the next level of SDKs for developers that want to take advantage of the benefits PDF can bring. Equipped with a better document engine, high and low-level programming capabilities and the ability to create, edit and enha

The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.