adithya-s-k/omniparse Alternatives

choose it for an Apache-2.0 document ETL library with a large connector ecosystem; it lacks OmniParse's audio/video/web support.

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

choose it for a widely-adopted MIT-licensed document parser with excellent PDF/Office fidelity, if you don't need multimedia.

Get your documents ready for gen AI

choose it for a focused, high-quality PDF/Office-to-markdown converter under Apache-2.0 when you don't need audio/video.

Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.

choose it for a lightweight OCR-free document-to-markdown toolkit under Apache-2.0, if you don't need multimedia.

An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/)

choose it for a flexible MIT-licensed document parser with multiple output formats (markdown/JSON/CSV) and URL support.

Extract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.

choose it for a Rust-core parser that is faster and Apache-2.0 licensed, at the cost of less multi-modal coverage.

A fast, helpful, and open-source document parser

choose it for a minimal vision-model OCR-to-markdown pipeline when you want simplicity over a full ingestion platform.

OCR & Document Extraction using vision models

choose it for production-grade OCR in 100+ languages with strong on-prem performance, if you are willing to build the parsing pipeline yourself.

Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.

choose it for a Rust-native parser covering 106 formats including code, under MIT, if you don't need GenAI-specific structured markdown.

A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured data from 101 formats (115 file extensions) plus code intelligence for 371 code languages. 15 language bindings — Rust, Python, Ruby, Java, Go, PHP, Elixir, C#, TypeScript — plus CLI, REST API, and MCP server.

choose it for a Node.js-based document-to-structured-data server with Apache-2.0, if you prefer a JavaScript stack.

Transforms PDF, Documents and Images into Enriched Structured Data

choose it for a lightweight, widely-used file-to-markdown converter when you don't need OCR or AI-based layout analysis.

Python tool for converting files and office documents to Markdown.

choose it for a fast Rust-based converter for Office/PDF to markdown, with bindings for Node/Python, when you don't need OCR.

Convert Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, and PDF to clean Markdown. Built in Rust, with Node.js and Python bindings.

choose it if you need a Java-native PDF parser for AI data extraction; it only handles PDFs.

PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.

choose it for experimenting with the ACL 2025 document image parsing model if you want SOTA research code, not a production tool.

The official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025.

choose it for a simple LLM-focused Office document parser, but it is less maintained and does not cover images/audio.

File Parser optimised for LLM Ingestion with no loss 🧠 Parse PDFs, Docx, PPTx in a format that is ideal for LLMs.

choose it for a lightweight LMM-based document parsing model if you want to integrate a model rather than a full platform.

A lightweight LMM-based Document Parsing Model

choose it for a specialized, high-quality PDF-to-markdown converter with complex layout/table support, if PDFs are your only need.

OCRFlux is a lightweight yet powerful multimodal toolkit that significantly advances PDF-to-Markdown conversion, excelling in complex layout handling, complicated table parsing and cross-page content merging.

choose it for Baidu's long-horizon parsing model for whole-document OCR, if you want research code over a production platform.

Unlimited OCR Works: Welcome the Era of One-shot Long-horizon Parsing.

choose it for a specialized high-quality PDF extraction toolkit if you accept AGPL and need fine-grained control; it is unmaintained and PDF-only.

A Comprehensive Toolkit for High-Quality PDF Content Extraction

choose it if you need a historic OCR-free document understanding model for research; it is not a production-ready replacement.

Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022