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RAGFlow

Leading open-source RAG engine with deep document understanding and visual RAG

4.5/ 584,954 GitHub starsPython/TypeScriptMIT
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⚡ TL;DR

What
Leading open-source RAG engine with deep document understanding and visual RAG
Who
Enterprises with complex documents, Anyone needing OCR + table extraction + RAG, Teams building document Q&A
Catch
Resource-heavy
Verdict
⭐⭐⭐⭐⭐ Essential

🎯 The Problem It Solves

You need RAG that handles complex documents (PDFs, tables, images) with visual understanding, not just text chunking. RAGFlow provides deep document parsing with OCR, table recognition, and multi-modal RAG.

🔧 How It Works

RAGFlow is a Python/TypeScript RAG engine that parses documents deeply (OCR, table extraction, layout analysis) before indexing. It supports visual RAG (understanding images in documents), multi-turn reasoning, and cite-worthy answers.

🚀 Installation & Quick Start

Installation

docker run -d -p 9380:9380 infiniflow/ragflow:latest

Quick Start

  1. Deploy with Docker
  2. Upload your documents
  3. Create a knowledge base
  4. Start chatting with your data

✅ Pros

  • •Best document understanding
  • •Visual RAG
  • •OCR built-in
  • •100+ file formats
  • •Free core version

❌ Cons

  • •Resource-heavy
  • •Complex setup
  • •Some features require enterprise version

💬 Practitioner Verdict

"RAGFlow is the most advanced open-source RAG engine. The deep document understanding makes it superior for enterprise document processing."
— AI RepoIndex, Security Reviewer

📊 Specifications

Language
Python/TypeScript
License
MIT
Platform
Linux, macOS, Windows
Kill Chain
None

💰 Pricing Reality

Open-source core (MIT). Enterprise version available. Self-hosted or cloud.

👥 Community Health

Stars84,954
Forks10,619
Contributors1699
Health Score8.5/10

🏷️ Tags

Open SourceSelf-HostedRAG

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