hermes-agent vs langgraph

Side-by-side comparison of two AI agent tools

Short answer

  • hermes-agent is growing faster: +5,760 GitHub stars in the last 30 days vs +99 for langgraph.
  • Pick hermes-agent for: the agent that grows with you. Pick langgraph for: framework to build resilient language agents as graphs.

From GitHub data refreshed daily.

h
hermes-agentopen-source

The agent that grows with you

langgraphopen-source

Framework to build resilient language agents as graphs.

Metrics

hermes-agentlanggraph
Stars250.7k3.3k
Star velocity /mo5.8k98.88888888888889
Commits (90d)32.9k135
Releases (6m)1010
Overall score0.95017616633487660.6740823209830771

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, hermes-agent or langgraph?
        hermes-agent has more GitHub stars (250,690 vs 3,332).
        Which is more actively developed, hermes-agent or langgraph?
        hermes-agent had more commits in the last 90 days (32,889 vs 135).
        Should I use hermes-agent 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.