Langchain-Chatchat vs RAGFlow

Langchain-Chatchat

RAG

RAGFlow

RAG

Tagline

Langchain-Chatchat

Self-hostable RAG and agent framework that wires LangChain to any local open-source LLM and a knowledge base.

RAGFlow

Open-source RAG engine with deep document parsing, hybrid search, and visual agent orchestration.

Pricing

Langchain-Chatchat

Free· Apache-2.0 open source; self-hosted, infra costs only

RAGFlow

Freemium· Free tier; Starter $29/mo; Pro $129/mo; Enterprise custom

Free trial

Langchain-Chatchat

Yes

RAGFlow

Yes

API

Langchain-Chatchat

Yes

RAGFlow

Yes

Platforms

Langchain-Chatchat

api

RAGFlow

api

Open source

Langchain-Chatchat

Yes · Apache-2.0

RAGFlow

Yes · Apache-2.0

GitHub stars

Langchain-Chatchat

38,666

checked 2026-09-29

RAGFlow

91,511

checked 2026-09-29

Last GitHub push

Langchain-Chatchat

2025-11-10

RAGFlow

2026-09-29

First commit

Langchain-Chatchat

2023-03

RAGFlow

2023-12

Model used

Langchain-Chatchat

Multi-model (GLM-4, Qwen2, Llama 3, etc. via Xinference/Ollama/LocalAI/FastChat)

RAGFlow

Multi-model

Best for

Langchain-Chatchat

Pick Langchain-Chatchat if you need an open-source, on-prem RAG and agent scaffold that can drive local Qwen, GLM or Llama models against a private knowledge base.

RAGFlow

Pick RAGFlow if you need a self-hostable, citation-grounded RAG stack that can actually digest gnarly enterprise documents and feed agents.

Not for

Langchain-Chatchat

Skip it if you want a hosted, turnkey RAG product or a polished consumer chatbot without managing Python, GPUs and a vector store yourself.

RAGFlow

Skip it if you just want a hosted chat-with-PDF widget or you're allergic to running your own infrastructure.

Editorial score

Langchain-Chatchat

7.4 / 10

RAGFlow

8.1 / 10

Use cases

Langchain-Chatchat

private-knowledge-baseoffline-ragdocument-qalocal-llm-agentsenterprise-chatbot

RAGFlow

document-qaenterprise-searchagent-orchestrationknowledge-basehybrid-retrieval

Pros

Langchain-Chatchat

• Fully offline, self-hosted RAG stack with Apache-2.0 license
• Framework-agnostic: plugs into Xinference, Ollama, LocalAI, FastChat, One API
• Ships both Streamlit UI and FastAPI service with OpenAI-compatible endpoints
• Built-in agent tools (SQL chat, arXiv, Wolfram, text-to-image)
• Large community (~38k stars) and broad model coverage

RAGFlow

• Strong deep-document parsing for messy PDFs, tables, and scans
• Hybrid vector + BM25 retrieval with citation-grounded answers
• Fully open-source with active GitHub repo and self-host option
• Visual agent builder plus MCP integration for tool-calling clients
• Model-agnostic; works with most major LLM providers

Cons

Langchain-Chatchat

• Dependency and GPU setup is non-trivial; not a one-click install
• Documentation is Chinese-first; English coverage lags
• Release cadence has slowed since the v0.3 peak
• You still pick and operate your own vector DB and model server

RAGFlow

• Free tier blocks API access, pushing real use to paid plans
• Self-hosting is non-trivial and resource-hungry
• Documentation and UI lag behind the engine's capabilities

Website

Langchain-Chatchat

github.com

RAGFlow

ragflow.io

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.