Fast Rust library for PDF inspection, classification, and text extraction. Intelligently detects scanned vs text-based PDFs to enable smart routing decisions.
A fast, helpful, and open-source document parser
Polyglot document intelligence with a Rust core: extract text, metadata, images, tables, and structured data from 106 formats across 140 file extensions, plus code intelligence for 371 languages. Fifteen bindings, with CLI, REST API, and MCP server.
Python & Command-line tool to gather text and metadata on the Web: Crawling, scraping, extraction, output as CSV, JSON, HTML, MD, TXT, XML
Module for automatic summarization of text documents and HTML pages.
Golang PDF library for creating and processing PDF files (pure go)
Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.
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.
A general list of resources to image text localization and recognition 场景文本位置感知与识别的论文资源与实现合集 シーンテキストの位置認識と識別のための論文リソースの要約
Zero-copy PDF text extraction library written in Zig. High-performance, memory-mapped parsing with SIMD acceleration.
PDF to markdown using vision LLMs — tables, layouts, and structure preserved
High performance and CommonMark compliant HTML to Markdown converter. Maintained by the Kreuzberg team. Kreuzberg is a fast, polyglot document intelligence engine with a Rust core. It extracts structured data from 98+ document formats using streaming parsers and built-in OCR.
Heuristic based boilerplate removal tool
A self‑hosted search engine for documents
This repository has moved! https://github.com/unidoc/unipdf
Text Extraction, Rendering and Converting of PDF Documents
A simple library and set of tools for parsing, modifying, and composing SRT files.
Parse PDFs into markdown using Vision LLMs
A very simple news crawler with a funny name
[UNMANTEINED] Extract values from strings and fill your structs with nlp.
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