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Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands. All original source code is the property of Anthropic.

A modern SaaS template/boilerplate built with SvelteKit, Tailwind, and Supabase. Includes marketing page, blog, subscriptions, auth, user dashboard, user settings, pricing page, and more.

Browser-based management platform of machine, database (mysql pgsql oracle sqlserver Gauss sqlite), redis(standalone sentinel cluster), mongo, Es unified management and operation platform. (web版linux(终端 文件 脚本 进程)、数据库(mysql pgsql oracle sqlserver 高斯 达梦 sqlite)、数据同步、redis(单机 哨兵 集群)、mongo、Es统一管理操作平台)

🌀 AI-native framework for building data portals. Scaffold a full portal from a brief and load datasets in minutes with agentic skills — any backend (CKAN, GitHub, Frictionless).

  • data-portal
  • ckan
  • nextjs
  • open-data-portal

一套为研究生和学术研究者设计的完整AI Prompt库 📖 包含内容: ✨ 40+ 精心设计的AI Prompt ✨ 论文选题系统方法(生成、评估、论证) ✨ 论文查找快速方案(8个不同方案) ✨ 文献综述框架和工具 ✨ Excel自动评估表格 ✨ 3个完整的论证模板 🚀 核心优势: ⚡ 节省时间 50-70%(选题3-5天而不是2-3周) 🎯 科学方法(基于系统的5维度评估体系) 💡 即插即用(所有Prompt直接复制可用) 📚 全流程覆盖(从选题到出版的完整方案) 🎓 适用人群: 👨‍🎓 硕士研究生 | 博士研究生 | 本科毕业设计 | 学术研究者 | 内容创作者

  • academic-research
  • ai
  • ai-prompts
  • ailearning

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes