DeepSeek Harness vs langgraph
Side-by-side comparison of two AI agent tools
Short answer
- DeepSeek Harness is growing faster: +16,095 GitHub stars in the last 30 days vs +99 for langgraph.
- Pick DeepSeek Harness for: deepSeek Harness: Everything is a Plugin. Pick langgraph for: framework to build resilient language agents as graphs.
From GitHub data refreshed daily.
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DeepSeek Harnessopen-source
DeepSeek Harness: Everything is a Plugin.
langgraphopen-source
Framework to build resilient language agents as graphs.
Metrics
| DeepSeek Harness | langgraph | |
|---|---|---|
| Stars | 242.1k | 3.3k |
| Star velocity /mo | 16.1k | 98.88888888888889 |
| Commits (90d) | 19.6k | 135 |
| Releases (6m) | 10 | 10 |
| Overall score | 0.9504253212996784 | 0.6740823209830771 |
Pros
- +提供可视化的图形控制流,让智能体行为更加透明和可调试,相比黑盒式的自主智能体更易于理解和维护
- +内置人机协作机制和长期记忆支持,适合处理需要人工介入或持续状态的复杂业务流程
- +CLI 工具和预构建智能体模板显著降低了入门门槛,支持从概念验证到生产部署的快速迭代
Cons
- -作为低级框架需要更多的架构设计工作,学习曲线相对陡峭,不如高级抽象框架那样开箱即用
- -主要依赖 LangChain 生态系统,在非 LangChain 技术栈中的集成可能需要额外的适配工作
Use Cases
- •构建需要人工审核和批准的自动化工作流,如内容审核、财务审批或合规检查流程
- •开发具有长期记忆的客服或助理智能体,能够跨会话保持上下文和用户偏好
- •创建复杂的数据处理管道,需要在多个 AI 模型和外部 API 之间协调执行任务
FAQ
- Which is more popular, DeepSeek Harness or langgraph?
- DeepSeek Harness has more GitHub stars (242,104 vs 3,332).
- Which is more actively developed, DeepSeek Harness or langgraph?
- DeepSeek Harness had more commits in the last 90 days (19,632 vs 135).
- Should I use DeepSeek Harness or langgraph?
- 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.