camofox-browser vs RasaGPT

Side-by-side comparison of two AI agent tools

Short answer

  • RasaGPT has had no commit in 41 months; camofox-browser is actively maintained (178 commits in the last 90 days).
  • camofox-browser is growing faster: +450 GitHub stars in the last 30 days vs +0 for RasaGPT.
  • Pick camofox-browser for: stealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Pick RasaGPT for: headless LLM chatbot platform built on Rasa and LangChain for indexing, retrieval, and context injection.

From GitHub data refreshed daily.

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camofox-browseropen-source

Stealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Drop-in Puppeteer/Playwright replacement.

RasaGPTopen-source

Headless LLM chatbot platform built on Rasa and LangChain for indexing, retrieval, and context injection

Metrics

camofox-browserRasaGPT
Stars11.3k2.5k
Star velocity /mo4500.47619047619047616
Commits (90d)1780
Releases (6m)100
Overall score0.76875727726194090.15359045579284894

Pros

    • +开箱即用的完整解决方案，解决了 Rasa 与 LLM 集成的所有技术痛点，包括库冲突、元数据传递等问题
    • +提供完整的技术栈集成，包括 FastAPI 后端、文档上传训练管道、Docker 支持和多平台部署能力
    • +实现了自定义 pgvector 集成和多租户架构，比使用 Langchain 原生方案更加灵活可控

    Cons

      • -作者明确表示这不是生产级代码，存在 prompt injection 和多种安全漏洞风险
      • -作为概念验证项目，缺乏企业级的安全性、稳定性和性能优化
      • -学习成本较高，需要同时掌握 Rasa、Langchain 和 FastAPI 等多个框架

      Use Cases

        • •企业内部知识库问答系统，需要结合传统规则对话和 LLM 生成能力的客服场景
        • •多渠道聊天机器人部署，特别是需要同时支持 Telegram、Slack 等平台的应用
        • •需要文档索引和检索功能的智能助手，如技术文档查询、产品说明书问答等场景
        View camofox-browser DetailsView RasaGPT Details

        FAQ

        Which is more popular, camofox-browser or RasaGPT?
        camofox-browser has more GitHub stars (11,315 vs 2,464).
        Which is more actively developed, camofox-browser or RasaGPT?
        camofox-browser had more commits in the last 90 days (178 vs 0).
        Should I use camofox-browser or RasaGPT?
        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.