RAGFlow

RAG frameworks Intermediate Open source Open core

An open-source RAG engine built around deep document understanding. It parses complex, messy documents (PDFs with tables, scans, varied layouts) with OCR and structure-aware chunking, then serves retrieval and a chat interface over them. The emphasis is on getting good text out of hard documents, which is where many RAG systems quietly fail.

Strengths

Strong parsing of complex documents (Word, Excel, PDF, scans, images)
Explainable, template-based chunking with traceable citations
Configurable LLMs, embeddings, and reranking

Weaknesses

Heavy resource needs and many service dependencies
Docker images are x86-only, so ARM64 needs a manual build
Requires understanding of RAG concepts to configure well

At a glance

Licence: Apache-2.0
Pricing: Open core
Platforms: Linux, Docker
GPU required: No

Works with

BGE-M3
Qwen3-Reranker 0.6B

Related guides

Building a local RAG system
Improving RAG retrieval quality

Glossary

RAG
Embedding
Vector database
Reranker

Entry last verified 18 August 2026.