Parse Multi Format Rag Inputs With Omniparse

---
name: "Parse multi-format RAG inputs with OmniParse"
slug: "parse-multi-format-rag-inputs-with-omniparse"
description: "Run OmniParse locally or as an API service to turn documents, images, audio, video, and web pages into structured Markdown-ready inputs for agent and RAG workflows."
github_stars: 7613
verification: "security_reviewed"
source: "https://github.com/adithya-s-k/omniparse"
author: "adithya-s-k"
publisher_type: "individual"
category: "Data Extraction & Transformation"
framework: "Multi-Framework"
tool_ecosystem:
  github_repo: "adithya-s-k/omniparse"
  github_stars: 7613
---

# Parse multi-format RAG inputs with OmniParse

Run OmniParse locally or as an API service to turn documents, images, audio, video, and web pages into structured Markdown-ready inputs for agent and RAG workflows.

## Prerequisites

Linux, Python 3.10, Conda or virtualenv, Docker optional, GPU recommended for heavier parsing workloads

## Installation

Use the upstream install or setup path that matches your environment:
- git clone https://github.com/adithya-s-k/omniparse
- conda create -n omniparse-venv python=3.10
- conda activate omniparse-venv
- pip install -e .

Requirements and caveats from upstream:
- ✅ Easily deployable using Docker and Skypilot \
- To use OmniParse with Docker, execute the following commands:

Basic usage or getting-started notes:
- [!IMPORTANT]
- The server only works on Linux-based systems. This is due to certain dependencies and system-specific configurations that are not compatible with Windows or macOS.
- cd omniparse

- Source: https://github.com/adithya-s-k/omniparse
- Extracted from upstream docs: https://raw.githubusercontent.com/adithya-s-k/omniparse/HEAD/README.md

## Documentation

- https://omniparse.cognitivelab.in/

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/parse-multi-format-rag-inputs-with-omniparse/)