LangGraph vs ragflow
Side-by-side comparison of two AI agent tools
Short answer
- Pick LangGraph for: build resilient language agents as graphs. Pick ragflow for: open-source RAG engine combining knowledge retrieval and agent capabilities for LLMs.
From GitHub data refreshed daily.
LangGraphopen-source
Build resilient language agents as graphs.
ragflowopen-source
Open-source RAG engine combining knowledge retrieval and agent capabilities for LLMs
Metrics
| LangGraph | ragflow | |
|---|---|---|
| Stars | 42.7k | 91.6k |
| Star velocity /mo | 2.4k | 2.4k |
| Commits (90d) | 132 | 2.7k |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 43.7M | — |
| Overall score | 0.8091319530692536 | 0.9098521001650974 |
Pros
- +Durable execution ensures agents automatically resume from exactly where they left off after failures or interruptions
- +Comprehensive memory system with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions
- +Seamless human-in-the-loop capabilities allow for inspection and modification of agent state at any point during execution
- +结合了先进的RAG技术和Agent能力，提供比传统RAG更强大的功能
- +开源且拥有活跃社区支持，GitHub星数超过7.6万，可信度高
- +提供云服务和Docker容器化部署，支持多种部署方式
Cons
- -Low-level framework requires more technical expertise and setup compared to high-level agent builders
- -Graph-based agent design paradigm may have a steeper learning curve for developers new to agent orchestration
- -Production deployment complexity may be overkill for simple chatbot or single-turn use cases
- -作为相对复杂的RAG系统，可能需要一定的技术背景才能充分配置和优化
- -大规模部署可能需要相当的计算资源和存储空间
Use Cases
- •Long-running autonomous agents that need to persist through system failures and operate over days or weeks
- •Complex multi-step workflows requiring human oversight, approval, or intervention at specific decision points
- •Stateful agents that must maintain context and memory across multiple sessions and interactions
- •企业知识库问答系统，基于内部文档为员工提供智能查询服务
- •智能客服系统，结合产品文档和FAQ提供准确的客户支持
- •研究助手应用，帮助研究人员从大量学术文献中检索相关信息
FAQ
- Which is more popular, LangGraph or ragflow?
- ragflow has more GitHub stars (91,619 vs 42,656).
- Which is more actively developed, LangGraph or ragflow?
- ragflow had more commits in the last 90 days (2,666 vs 132).
- Should I use LangGraph or ragflow?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.