llama-cpp-agent vs OpenHuman

Side-by-side comparison of two AI agent tools

Short answer

  • llama-cpp-agent has had no commit in 6 months; OpenHuman is actively maintained (22,774 commits in the last 90 days).
  • OpenHuman is growing faster: +2,510 GitHub stars in the last 30 days vs +6 for llama-cpp-agent.
  • Pick llama-cpp-agent for: python framework for LLM chat, structured output, function calling, RAG, and agent chains. Pick OpenHuman for: openHuman is the fastest, cheapest, most efficient open-source agent harness.

From GitHub data refreshed daily.

Python framework for LLM chat, structured output, function calling, RAG, and agent chains

O
OpenHumanopen-source

OpenHuman is the fastest, cheapest, most efficient open-source agent harness. Written in Rust

Metrics

llama-cpp-agentOpenHuman
Stars65940.5k
Star velocity /mo5.6842105263157892.5k
Commits (90d)022.8k
Releases (6m)010
Downloads (30d, npm + PyPI)603—
Overall score0.185810447531319280.9308227395695856

Pros

  • +引导采样技术让未微调模型也能进行函数调用和结构化输出
  • +支持多种后端提供商(llama-cpp-python、TGI、vllm等)提供良好兼容性
  • +功能全面涵盖聊天、函数调用、RAG和代理链等核心能力

    Cons

    • -项目已不再维护,官方建议迁移到其他框架
    • -对于简单用例可能存在过度设计的复杂性

      Use Cases

      • •构建具有函数调用能力的对话代理系统
      • •实现带文档检索的RAG应用程序
      • •从LLM中提取结构化数据和执行复杂的代理链工作流

        FAQ

        Which is more popular, llama-cpp-agent or OpenHuman?
        OpenHuman has more GitHub stars (40,486 vs 659).
        Which is more actively developed, llama-cpp-agent or OpenHuman?
        OpenHuman had more commits in the last 90 days (22,774 vs 0).
        Should I use llama-cpp-agent or OpenHuman?
        Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.