OmniParse
OSS platform for Structuring Any Unstructured 📄🌄🎥🕸️ Data
Listed in categories:
Developer ToolsGitHubArtificial Intelligence
Description
OmniParse is a platform that ingests and parses any unstructured data into structured actionable data optimized for GenAI LLM applications. Whether working with documents, tables, images, videos, audio files, or web pages, OmniParse prepares your data to be clean, structured, and ready for AI applications such as RAG fine-tuning and more.
How to use OmniParse?
To use OmniParse, you can install it on a Linux-based system using pip. It supports various data types such as documents, images, audio, video, and web content. You can deploy it using Docker and access an interactive UI powered by Gradio.
Core features of OmniParse:
1️⃣
Completely local, no external APIs
2️⃣
Fits in a T4 GPU
3️⃣
Supports 20 file types
4️⃣
Converts documents, multimedia, and web pages to high-quality structured markdown
5️⃣
Table extraction, image extraction/captioning, audio/video transcription, web page crawling
Why could be used OmniParse?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Data preparation for AI applications | ✅ | |
| # 2 | Structured data extraction from unstructured sources | ✅ | |
| # 3 | Multimedia content processing | ✅ | |
Who developed OmniParse?
OmniParse is created by Adithya S. K. The project builds upon the Marker project created by Vik Paruchuri and utilizes models like Surya OCR, Florence2, and Whisper for data processing.