在真实工程项目中，不使用 LangChain、LangGraph、CrewAI 等框架，纯用 Python + LLM API 手动实现 AI Agent 不仅完全可行，而且在许多场景下是更优选择。 Anthropic 官方明确建议开发者”从直接使用 ...

A new around of vulnerabilities in the popular AI automation platform could let attackers hijack servers and steal ...

While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...

摘要 随着 Anthropic 开源 skills 仓库，"Code Interpreter"（代码解释器）模式成为 Agent 开发的热门方向。许多开发者试图采取激进路线：赋予 LLM 联网和 Python 执行权限，让其现场编写代码来解决一切问题 ...

A step-by-step guide to installing the tools, creating an application, and getting up to speed with Angular components, ...

At Slash’s request, the Lil’ Viper was kitted out with a speaker-emulated 1/4” headphone output to mimic the internal speaker ...

Many developers share their LeetCode solutions on GitHub. Look for repositories that are well-organized by topic or problem number, have clear explanations, and show good code quality. Some popular ...

自2025年初DeepSeek R1模型发布以来，强化学习（RL）在大型语言模型（LLM）的后训练范式中受到越来越多的关注，R1的突破性在于引入了可验证奖励强化学习（RLVR），通过构建数学题、代码谜题等自动验证环境，使模型在客观奖励信号的驱动下，自发地演化出与人类推理策略高度相似的思维方式。