这是一个股票智能分析系统仓库：Python 后端 + FastAPI API + 多数据源行情抓取 + LLM 分析报告 + 通知推送，另外有 React Web 工作台和 Electron 桌面端。覆盖 A ...

Supported Releases: These releases have been certified by Bloomberg’s Enterprise Products team for use by Bloomberg customers. Experimental Releases: These releases have not yet been certified for use ...

About the RoleA well-established, data-driven organisation is seeking an experienced Python Developer to join its growing technical team. The successful candidate will play a key role in designing, ...

You'll work alongside software engineers, data scientists, domain experts, and product owners, with a culture of continuous improvement and daily deployments. Our technology stack consists of ...

GitHub 账号 pewdiepie-archdaemon 开源了自托管 AI 工作台 Odysseus——外界普遍将其与坐拥超 1 亿粉丝的 YouTuber PewDiePie 关联。上线一周 Star 数突破六万五，把 ChatGPT ...

Ongoing research into AI agent framework security identified an exploit chain in AutoGen Studio (AutoGen’s open-source prototyping user interface) that allows untrusted web content rendered by a ...

Tbilisi, Georgia, June 22nd, 2026, FinanceWireAs artificial intelligence reshapes global industries, the demand for ...

有道的 AI 现在现在越来越有一种「闷声干大事」的感觉了。不搞发布会刷存在感，就是一个接一个往外丢开源项目，TTS、Agent 框架、多模态，全都 Apache 2.0，拿来就能用。

整套架构本来是给程序员写代码用的，意外地特别适合当业务系统的多智能体后端。今天就把整个流程分享给大家。 做 AI 多智能体业务后端，开源框架满地都是。LangChain、LangGraph、AutoGen、CrewAI 我都试过。 结果这次我用一个"写代码用的 CLI"反而搭得最快。

Agent 先看到轻量的技能列表，再按需加载 SKILL.md，必要时继续加载外部资源。它避免把所有知识都塞进系统提示，也让每个 Skill 可以被单独设计、测试和迭代。下面这 5 种模式，可以当作写 Skill 时的基本分类。 之前 Google Cloud Tech 传播了一篇文章：5 Agent Skill ...