RAGFlow
Open-source RAG engine for document understanding and Q&A with LLMs.
Pricing
Free tier
Flat rate
Adoption
↗RisingLicense
Open Source
Data freshness
Verified · Jul 16, 2026Overview
What is RAGFlow?
RAGFlow is an open-source Retrieval-Augmented Generation (RAG) framework designed to help developers build applications that understand documents and answer questions using Large Language Models (LLMs). It simplifies the process of integrating document retrieval and question answering capabilities into your projects.
Key differentiator
“RAGFlow stands out as a fully open-source, self-hosted RAG framework, offering developers the flexibility to integrate document understanding and question answering capabilities into their projects without cloud dependency.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development and maintenance focus is on Python, other languages have limited or no official support
Retrieval process can become slow and resource-intensive when handling extensive document collections
Fit analysis
Who is it for?
✓ Best for
Teams building applications that require integration of document retrieval and question answering with LLMs.
Projects needing a self-hosted RAG solution without cloud dependency.
Developers looking for an open-source alternative to proprietary RAG frameworks.
✕ Not a fit for
Applications requiring real-time streaming capabilities (RAGFlow is designed for batch processing).
Teams that prefer managed services over self-hosting solutions.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Integrations
Next step
Get Started with RAGFlow
Step-by-step setup guide with code examples and common gotchas.