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xbrain专注于构建一款可解释的AI开发框架

Project description

🤔解决了什么问题

如果你用LangChain开发Agent应用,需要以下四步:

  1. 基础组件设置
  2. 定义工具集
  3. 定义Prompt模板
  4. 定义输出解析器

如果你用swarm开发Agent应用,需要以下四步:

  1. 基础组件设置
  2. Agent角色定义
  3. 任务协调系统
  4. 工作流程实现

但是,如果你用xbrain开发Agent应用,一切将变得非常美好,只需要两步:

  1. 编写工具
  2. 与AI聊天部署运行

👥用户故事

  • AI 接口封装: 独立 AI 函数快速封装为 HTTP 服务,便于集成到其他系统中;
  • 功能验证: 早期开发阶段原型设计与测试,无需搭建复杂后端;
  • 轻量化微服务改造: 适合将 Python 脚本微服务化,轻松满足小规模、灵活部署需求。

✨特点

  • 一键安装,开箱即用: 命令行一键启动,简单易用;
  • 无提示词设计: 摒弃提示词书写,用户专注于业务开发;
  • 将python函数接入Tools Call: 将本地 Python 代码直接接入大模型的工具调用。

📄文档

几个有意思的例子

智能客服系统

使用 NLP 模型构建智能应答机器人,优化客服效率。 Todo 待完善。

🤝 如何贡献

你可以通过 Fork 项目、提交 PR 或在 Issue 中提出你的想法和建议。具体操作可参考贡献指南

强烈推荐阅读 《提问的智慧》《如何向开源社区提问题》《如何有效地报告 Bug》《如何向开源项目提交无法解答的问题》,更好的问题更容易获得帮助。

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