AutoClip : AI-powered video clipping and highlight generation · 一款智能高光提取与剪辑的二创工具 AutoClip 把长视频变成值得分享的精彩片段。 简体中文 · English · 日本語 · 한국어 · Español · Português · Русский · Français 项目网站 · 反馈问题 桌面安装包: macOS · Apple Silicon · Windows · x64 安装与第一次出片 · 完整排错指南 自 v1.3.1 起，产品界面、官网和 README 均支持中、英、日、韩、西、葡、俄、法。顶栏可切换界面语言或跟随系统；用户素材和生成内容保留原文。 AutoClip 用 AI 分析视频字幕、定位高光、生成标题，并自动剪出片段与合集。适合访谈、播客、课程和直播回放，提供桌面应用、Docker Web 界面和 CLI / MCP 三种使用方式。 界面预览 v1.3.0 真实 Web 界面：在文件导入区添加本地视频，可同时提供 SRT 字幕。 社区成就 …
The Generative UI frameworkjson-render The Generative UI framework. Generate dynamic, personalized UIs from prompts without sacrificing reliability. Predefined components and actions for safe, predictable output. # for React npm install @json-render/core @json-render/react # for React with pre-built shadcn/ui components npm install @json-render/shadcn # or for React Native npm install @json-render/core @json-render/react-native # or for video npm install @json-render/core @json-re…
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parametershiggsfield - multi node training without crying Higgsfield is an open-source, fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters, such as Large Language Models (LLMs). Higgsfield serves as a GPU workload manager and machine learning framewor…
Assignments for CS146S: The Modern Software Dev (Stanford University Fall 2026/2025)Assignments for CS146S: The Modern Software Developer This is the home of the assignments for CS146S: The Modern Software Developer, taught at Stanford University fall 2025. Repo Setup These steps work with Python 3.12. Install Anaconda Download and install: Anaconda Individual Edition Open a new terminal so conda is on your PATH. Create and activate a Conda environment (Python 3.12) conda create -n cs146s…
A smarter, self-hosted AI assistant — multi-user, multi-agent. A smarter, self-hosted AI assistant — multi-user, multi-agent. Highlights · Overview · Core Technology · Features · Roadmap · Quick Start · Contents English · 中文 Octop is an open-source, self-hosted AI assistant. It's not just a tool — it's a digital life form that can operate in parallel. Through its multi-agent architecture, it builds an intelligent enviro…
Let AI agents use your real, logged-in browser without interrupting your work. CLI + extension for browser automation across any shell-capable AI agent.BrowserSkill Let AI agents use your browser without interrupting your work. English · 中文 BrowserSkill connects Cursor, Claude Code, Codex, OpenClaw, CodeBuddy, WorkBuddy, Pi, Hermes Agent, DeepSeek Harness, and other AI agents to your already logged-in browser. Need the agent to touch a tab you already have open? It must borrow that…
Tinycast — a tiny, fully native macOS launcher, hotkeys, and clipboard history.Tinycast A tiny, fully native macOS launcher. One hotkey, everything you reach for all day, under 100 MB of RAM. SwiftUI and AppKit, zero third-party dependencies, no Electron and no telemetry. It also runs real Raycast extensions, rendered as native SwiftUI. Free, open source, and staying that way. For anything private, email iabueammar@gmail.com. Support Tinycast…
A coding-agent skill for multi-phase security audits with independently verified, machine-readable findingssecurity-audit A coding-agent skill that turns your agent into a security auditor. It orchestrates isolated agents through reconnaissance, coverage-led hunting, candidate validation, structured output, independent record verification, and target-neutral reporting. This is the skill that seeded Cloudflare's vulnerability discovery harness, described in Build your own vulnerability harne…
ASC is a super FAST Android decompiler front-end designed for Agents/Mobile Researchers.Droid ASC: R8 Compiler Optimization as a DeCompiler Primitive https://blackhat.com/europe/arsenal/schedule/index.html#droid-asc-r8-compiler-optimization-as-a-decompiler-primitive-54834 When decompiling massive Android APKs, the standard procedure is to wait. We wait for tools to eat gigabytes of RAM, fully inflate the artifacts, and spend tens of minutes building heavy global indexes and cross references... …