AgentIndex icon
AgentIndex
ragflow logo
ragflow
★ 92.7k
vs
knowledge-rag logo
knowledge-rag
★ 300

ragflow vs knowledge-rag

ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that integrates RAG with Agent capabilities. It provides a superior context layer for LLMs and offers a streamlined RAG workflow adaptable to enterprises of any scale.; knowledge-rag: Knowledge RAG is a fully local, zero-cloud document retrieval system that lets Claude Code search your PDFs, markdown, code, and notebooks natively. It indexes up to 1800+ files in under 3 minutes, using hybrid search (BM25 + semantic vectors + cross-encoder reranking) via 12 MCP tools. Everything runs locally via ONNX, no Docker, Ollama, or API keys required.

01

TL;DR

ragflow logo
ragflowRAG / Knowledge Base · ★ 92.7k
When to choose:
  • Your documents have complex layouts (PDFs, scanned files, tables, slides) and you need layout analysis, OCR, and traceable citations.
  • You want an Apache-2.0 all-in-one RAG platform where you can inspect and hand-tune template-based chunks in a web UI.
When to skip:
  • Your server has less than 4 CPU cores and 16 GB RAM; RAGFlow's multi-service stack is heavy.
  • You want an autonomous web research agent that writes 2,000-word reports from live search rather than indexing a local document corpus; GPT Researcher fits better.
Read ragflow full review →
knowledge-rag logo
knowledge-ragRAG / Knowledge Base · ★ 300

Personal document retrieval and knowledge base for developers

Read knowledge-rag full review →
02

Side-by-Side Comparison

Field
ragflow logoragflow
knowledge-rag logoknowledge-rag
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 92.7k
★ 300
License
Apache-2.0
MIT
Install Command
docker compose -f docker-compose.yml up -d
pip install knowledge-rag
Updated
1d ago
1w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
RAG, AI Agent, LLM
bm25, chromadb, claude
03

Features

ragflow logoragflow
01Deep document understanding for knowledge extraction from unstructured data.
02Intelligent and template-based chunking with explainable options.
03Grounded citations with reduced hallucinations and traceable references.
04Compatibility with heterogeneous data sources including documents, images, and web pages.
05Automated and effortless RAG workflow orchestration with configurable models and fused re-ranking.
knowledge-rag logoknowledge-rag
01Hybrid Search with BM25 + semantic vectors + cross-encoder reranking
02Optional GPU acceleration for 5-10x faster indexing
0320 format parsers (MD, PDF, DOCX, code, etc.)
04YAML configuration with domain-specific presets
0512 MCP tools for full CRUD, search, and evaluation
04

Use Cases

ragflow logoragflow
↳Building high-fidelity, production-ready AI systems with complex data.
↳Developing enterprise-scale knowledge base and intelligent Q&A chatbots.
↳Facilitating intelligent document processing and advanced information retrieval.
knowledge-rag logoknowledge-rag
↳Personal document retrieval and knowledge base for developers
↳Security research document indexing and querying
↳Offline documentation assistant for sensitive environments
05

Best For

ragflow logoragflow
Most PopularEssentialTrending
knowledge-rag logoknowledge-rag
—
FAQ

FAQ

What is the difference between ragflow and knowledge-rag?
Both ragflow and knowledge-rag are in the RAG / Knowledge Base category. ragflow has 92.7k stars, while knowledge-rag has 300 stars.
Which is better, ragflow or knowledge-rag?
The best choice depends on your use case. Choose ragflow if Building high-fidelity, production-ready AI systems with complex data., and knowledge-rag if Personal document retrieval and knowledge base for developers.
Is ragflow free or open source?
Yes, ragflow is open source on GitHub (Apache-2.0).
Is knowledge-rag free or open source?
Yes, knowledge-rag is open source on GitHub (MIT).
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