https://github.com/trending The most popular GitHub repositories today for rust. Sat, 07 Feb 2026 00:08:00 GMT https://validator.w3.org/feed/docs/rss2.html GitHub Trending RSS Generator en All rights reserved 2026, GitHub https://github.com/ZeroTworu/anet https://github.com/ZeroTworu/anet Sat, 07 Feb 2026 00:08:00 GMT ZeroTworu/anet

Simple Rust VPN Client / Server

Language: Rust

Stars: 528

Forks: 46

Stars today: 193 stars today

README

# ANet: Сеть Друзей

![Build Status](https://img.shields.io/badge/build-passing-brightgreen)
![Language](https://img.shields.io/badge/rust-1.84%2B-orange)
![Protocol](https://img.shields.io/badge/protocol-ASTP_v1.0-blue)

**ANet** — это инструмент для организации приватного, защищенного информационного пространства между близкими людьми. Мы строим цифровые мосты там, где обычные пути недоступны.

Это не сервис. Это технология для связи тех, кто доверяет друг другу.

## Особенности

В основе проекта лежит собственный транспортный протокол **ASTP (ANet Secure Transport Protocol)**, разработанный с фокусом на:

*   **Приватность:** Полное сквозное шифрование (ChaCha20Poly1305 / X25519).
*   **Устойчивость:** Стабильная работа в сетях с высокими потерями пакетов и нестабильным соединением.
*   **Мимикрия:** Транспортный уровень неотличим от случайного шума (High-entropy UDP stream).
*   **Кроссплатформенность:** Клиенты для Linux, Windows и Android.

## Структура проекта

Проект написан на Rust и разделен на модули:

*   `anet-server` — Узел координации.
*   `anet-client-cli` — Консольный клиент для Linux/Headless систем.
*   `anet-client-gui` — Графический клиент (Windows/Linux) с минималистичным интерфейсом.
*   `anet-mobile` — Библиотека и JNI-биндинги для Android.
*   `anet-common` — Реализация протокола ASTP и криптографии.
*   `anet-keygen` — Утилита для генерации ключей доступа.

## Сборка

Требуется установленный Rust (cargo).

```bash
# Сборка всех компонентов
cargo build --release
```

Support the Chaos / Поддержать Хаос

Разработка ведется в условиях повышенной радиации (Черниковка), под пристальным взглядом Ханюши и с использованием альтернативных источников энергии (C2H5OH).

Если ANet помог тебе пробить стену цензуры — налей автору.

    На водку разрабу (чтобы код компилился): 2202 2084 3646 6800

    На булочки для Ханю (чтобы не кусалась): 2202 2084 3646 6800

    На J7 (для выхода из штопора): 2202 2084 3646 6800

]]> Rust https://github.com/Zackriya-Solutions/meeting-minutes https://github.com/Zackriya-Solutions/meeting-minutes Sat, 07 Feb 2026 00:07:59 GMT Zackriya-Solutions/meeting-minutes

Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper live transcription, speaker diarization, and Ollama summarization built on Rust. 100% local processing. no cloud required. Meetily (Meetly Ai - https://meetily.ai) is the #1 Self-hosted, Open-source Ai meeting note taker for macOS & Windows.

Language: Rust

Stars: 9,662

Forks: 848

Stars today: 29 stars today

README

<div align="center" style="border-bottom: none">
    <h1>
        <img src="docs/Meetily-6.png" style="border-radius: 10px;" />
        <br>
        Privacy-First AI Meeting Assistant
    </h1>
    <a href="https://trendshift.io/repositories/13272" target="_blank"><img src="https://trendshift.io/api/badge/repositories/13272" alt="Zackriya-Solutions%2Fmeeting-minutes | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
    <br>
    <br>
    <a href="https://github.com/Zackriya-Solutions/meeting-minutes/releases/"><img src="https://img.shields.io/badge/Pre_Release-Link-brightgreen" alt="Pre-Release"></a>
    <a href="https://github.com/Zackriya-Solutions/meeting-minutes/releases"><img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/zackriya-solutions/meeting-minutes?style=flat">
</a>
 <a href="https://github.com/Zackriya-Solutions/meeting-minutes/releases"> <img alt="GitHub Downloads (all assets, all releases)" src="https://img.shields.io/github/downloads/zackriya-solutions/meeting-minutes/total?style=plastic"> </a>
    <a href="https://github.com/Zackriya-Solutions/meeting-minutes/releases"><img src="https://img.shields.io/badge/License-MIT-blue" alt="License"></a>
    <a href="https://github.com/Zackriya-Solutions/meeting-minutes/releases"><img src="https://img.shields.io/badge/Supported_OS-macOS,_Windows-white" alt="Supported OS"></a>
    <a href="https://github.com/Zackriya-Solutions/meeting-minutes/releases"><img alt="GitHub Tag" src="https://img.shields.io/github/v/tag/zackriya-solutions/meeting-minutes?include_prereleases&color=yellow">
</a>
    <br>
    <h3>
    <br>
    Open Source • Privacy-First • Enterprise-Ready
    </h3>
    <p align="center">
    Get latest <a href="https://www.zackriya.com/meetily-subscribe/"><b>Product updates</b></a> <br><br>
    <a href="https://meetily.ai"><b>Website</b></a> •
    <a href="https://www.linkedin.com/company/106363062/"><b>LinkedIn</b></a> •
    <a href="https://discord.gg/crRymMQBFH"><b>Meetily Discord</b></a> •
    <a href="https://discord.com/invite/vCFJvN4BwJ"><b>Privacy-First AI</b></a> •
    <a href="https://www.reddit.com/r/meetily/"><b>Reddit</b></a>
</p>
    <p align="center">

A privacy-first AI meeting assistant that captures, transcribes, and summarizes meetings entirely on your infrastructure. Built by expert AI engineers passionate about data sovereignty and open source solutions. Perfect for enterprises that need advanced meeting intelligence without compromising on privacy, compliance, or control.

</p>

<p align="center">
    <img src="docs/meetily_demo.gif" width="650" alt="Meetily Demo" />
    <br>
    <a href="https://youtu.be/6FnhSC_eSz8">View full Demo Video</a>
</p>

</div>

---

> **🎉 New: Meetily PRO Available** - Looking for enhanced accuracy and advanced features? Check out our professional-grade solution with custom summary templates, advanced exports (PDF, DOCX), auto-meeting detection, built-in GDPR compliance, and many more. **This Community Edition remains forever free & open source**. [Learn more about PRO →](https://meetily.ai/pro/)

---

<details>
<summary>Table of Contents</summary>

- [Introduction](#introduction)
- [Why Meetily?](#why-meetily)
- [Features](#features)
- [Installation](#installation)
- [Key Features in Action](#key-features-in-action)
- [System Architecture](#system-architecture)
- [For Developers](#for-developers)
- [Meetily PRO](#meetily-pro)
- [Contributing](#contributing)
- [License](#license)

</details>

## Introduction

Meetily is a privacy-first AI meeting assistant that runs entirely on your local machine. It captures your meetings, transcribes them in real-time, and generates summaries, all without sending any data to the cloud. This makes it the perfect solution for professionals and enterprises who need to maintain complete control over their sensitive information.

## Why Meetily?

While there are many meeting transcription tools available, this solution stands out by offering:

- **Privacy First:** All processing happens locally on your device.
- **Cost-Effective:** Uses open-source AI models instead of expensive APIs.
- **Flexible:** Works offline and supports multiple meeting platforms.
- **Customizable:** Self-host and modify for your specific needs.

<details>
<summary>The Privacy Problem</summary>

Meeting AI tools create significant privacy and compliance risks across all sectors:

- **$4.4M average cost per data breach** (IBM 2024)
- **€5.88 billion in GDPR fines** issued by 2025
- **400+ unlawful recording cases** filed in California this year

Whether you're a defense consultant, enterprise executive, legal professional, or healthcare provider, your sensitive discussions shouldn't live on servers you don't control. Cloud meeting tools promise convenience but deliver privacy nightmares with unclear data storage practices and potential unauthorized access.

**Meetily solves this:** Complete data sovereignty on your infrastructure, zero vendor lock-in, and full control over your sensitive conversations.

</details>

## Features

- **Local First:** All processing is done on your machine. No data ever leaves your computer.
- **Real-time Transcription:** Get a live transcript of your meeting as it happens.
- **AI-Powered Summaries:** Generate summaries of your meetings using powerful language models.
- **Multi-Platform:** Works on macOS, Windows, and Linux.
- **Open Source:** Meetily is open source and free to use.
- **Flexible AI Provider Support:** Choose from Ollama (local), Claude, Groq, OpenRouter, or use your own OpenAI-compatible endpoint.

## Installation

### 🪟 **Windows**

1. Download the latest `x64-setup.exe` from [Releases](https://github.com/Zackriya-Solutions/meeting-minutes/releases/latest)
2. Right-click the downloaded file → **Properties** → Check **Unblock** → Click **OK**
3. Run the installer (if Windows shows a security warning: Click **More info** → **Run anyway**)

### 🍎 **macOS**

1. Download `meetily_0.2.0_aarch64.dmg` from [Releases](https://github.com/Zackriya-Solutions/meeting-minutes/releases/latest)
2. Open the downloaded `.dmg` file
3. Drag **Meetily** to your Applications folder
4. Open **Meetily** from Applications folder

### 🐧 **Linux**

Build from source following our detailed guides:

- [Building on Linux](docs/building_in_linux.md)
- [General Build Instructions](docs/BUILDING.md)

**Quick start:**

```bash
git clone https://github.com/Zackriya-Solutions/meeting-minutes
cd meeting-minutes/frontend
pnpm install
./build-gpu.sh
```

## Key Features in Action

### 🎯 Local Transcription

Transcribe meetings entirely on your device using **Whisper** or **Parakeet** models. No cloud required.

<p align="center">
    <img src="docs/home.png" width="650" style="border-radius: 10px;" alt="Meetily Demo" />
</p>

### 🤖 AI-Powered Summaries

Generate meeting summaries with your choice of AI provider. **Ollama** (local) is recommended, with support for Claude, Groq, OpenRouter, and OpenAI.

<p align="center">
    <img src="docs/summary.png" width="650" style="border-radius: 10px;" alt="Summary generation" />
</p>

<p align="center">
    <img src="docs/editor1.png" width="650" style="border-radius: 10px;" alt="Editor Summary generation" />
</p>

### 🔒 Privacy-First Design

All data stays on your machine. Transcription models, recordings, and transcripts are stored locally.

<p align="center">
    <img src="docs/settings.png" width="650" style="border-radius: 10px;" alt="Local Transcription and storage" />
</p>

### 🌐 Custom OpenAI Endpoint Support

Use your own OpenAI-compatible endpoint for AI summaries. Perfect for organizations with custom AI infrastructure or preferred providers.

<p align="center">
    <img src="docs/custom.png" width="650" style="border-radius: 10px;" alt="Custom OpenAI Endpoint Configuration" />
</p>

### 🎙️ Professional Audio Mixing

Capture microphone and system audio simultaneously with intelligent ducking and clipping prevention.

<p align="center">
    <img src="docs/audio.png" width="650" style="border-radius: 10px;" alt="Device selection" />
</p>

### ⚡ GPU Acceleration

Built-in support for hardware acceleration across platforms:

- **macOS**: Apple Silicon (Metal) + CoreML
- **Windows/Linux**: NVIDIA (CUDA), AMD/Intel (Vulkan)

Automatically enabled at build time - no configuration needed.

## System Architecture

Meetily is a single, self-contained application built with [Tauri](https://tauri.app/). It uses a Rust-based backend to handle all the core logic, and a Next.js frontend for the user interface.

For more details, see the [Architecture documentation](docs/architecture.md).

## For Developers

If you want to contribute to Meetily or build it from source, you'll need to have Rust and Node.js installed. For detailed build instructions, please see the [Building from Source guide](docs/BUILDING.md).

## Meetily Pro

<p align="center">
    <img src="docs/pv2.1.png" width="650" style="border-radius: 10px;" alt="Upcoming version" />
</p>

**Meetily PRO** is a professional-grade solution with enhanced accuracy and advanced features for serious users and teams. Built on a different codebase with superior transcription models and enterprise-ready capabilities.

### Key Advantages Over Community Edition:

- **Enhanced Accuracy**: Superior transcription models for professional-grade accuracy
- **Custom Summary Templates**: Tailor summaries to your specific workflow and needs
- **Advanced Export Options**: PDF, DOCX, and Markdown exports with formatting
- **Auto-detect and Join Meetings**: Automatic meeting detection and joining
- **Speaker Identification**: Distinguish between speakers automatically *(Coming Soon)*
- **Chat with Meetings**: AI-powered meeting insights and queries *(Coming Soon)*
- **Calendar Integration**: Seamless integration with your calendar *(Coming Soon)*
- **Self-Hosted Deployment**: Deploy on your own infrastructure for teams
- **GDPR Compliance Built-In**: Privacy by design architecture with complete audit trails
- **Priority Support**: Dedicated support for PRO users

### Who is PRO for?

- **Professionals** who need the highest accuracy for critical meetings
- **Teams and organizations** (2-100 users) requiring self-hosted deployment
- **Power users** who need advanced export formats and custom workflows
- **Compliance-focused organizations** requiring GDPR readiness

> **Note:** Meetily Community Edition remains **free & open source forever** with local transcription, AI summaries, and core features. PRO is a separate professional solution for users who need enhanced accuracy and advanced capabilities.

For organizations needing 100+ users or managed compliance solutions, explore [Meetily Enterprise](https://meetily.ai/enterprise/).

**Learn more about pricing and features:** [https://meetily.ai/pro/](https://meetily.ai/pro/)

## Contributing

We welcome contributions from the community! If you have any questions or suggestions, please open an issue or submit a pull request. Please follow the established project structure and guidelines. For more details, refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file.

Thanks for all the contributions. Our community is what makes this project possible.

## License

MIT License - Feel free to use this project for your own purposes.

## Acknowledgments

- We borrowed some code from [Whisper.cpp](https://github.com/ggerganov/whisper.cpp).
- We borrowed some code from [Screenpipe](https://github.com/mediar-ai/screenpipe).
- We borrowed some code from [transcribe-rs](https://crates.io/crates/transcribe-rs).
- Thanks to **NVIDIA** for developing the **Parakeet** model.
- Thanks to [istupakov](https://huggingface.co/istupakov/parakeet-tdt-0.6b-v3-onnx) for providing the **ONNX conversion** of the Parakeet model.

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=Zackriya-Solutions/meeting-minutes&type=Date)](https://star-history.com/#Zackriya-Solutions/meeting-minutes&Date)

]]> Rust https://github.com/storytold/artcraft https://github.com/storytold/artcraft Sat, 07 Feb 2026 00:07:58 GMT storytold/artcraft

ArtCraft is an intentional crafting engine for artists, designers, and filmmakers

Language: Rust

Stars: 673

Forks: 40

Stars today: 41 stars today

README

<p align="center">
  <video src="https://github.com/user-attachments/assets/b4e24c27-d87d-4fd1-8599-dc0d0b8af48d" width="100%" autoplay="true" loop controls>
</p>

<p align="center">The IDE for artists.</p>
<p align="center">
  <a href="https://discord.gg/artcraft"><img alt="Discord" src="https://img.shields.io/discord/1359579021108842617?style=for-the-badge&label=discord&color=ffffff&logo=discord&logoColor=ffffff" /></a>
  <a href="https://www.youtube.com/@OfficialArtCraftStudios"><img alt="YouTube" src="https://img.shields.io/youtube/channel/subscribers/UCdjY4VG0ntoGwFsKZO4sVWA?style=for-the-badge&logo=YouTube" /></a>
  <a href="https://x.com/intent/follow?screen_name=get_artcraft"><img alt="X" src="https://img.shields.io/twitter/follow/get_artcraft?style=for-the-badge&label=follow&logo=x&logoColor=ffffff&color=ffffff" /></a>
  <a href="https://www.linkedin.com/company/artcraft-ai"><img alt="LinkedIn" src="https://img.shields.io/badge/linkedin--0A66C2?style=for-the-badge"></a>
</p>

---

ArtCraft
========
ArtCraft is the IDE for interactive AI image and video creation.
We turn prompting into *crafting*, so your ideas become a form of tangible expression and computing.
This is Adobe Photoshop for everyone, and we're giving away the source code!

## Show, Don't Tell: Advanced Crafting Features

Text-to-image is great, but artists *need control*. It's important to know what your image will look like before you generate it, and it's vitally important to achieve consistency and repeatability.

| Feature                           | Demo + Explanation                                                                                                                                                                                                                                                      
|-----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **Image to Location**             | ![Video](https://github.com/user-attachments/assets/21f103e3-cc19-4882-a630-9caa1b76ae31) Placing virtual actors into physical environments establishes single-location consistency. You can film multiple shots within a room without having things disappear.         |
| **3D Image Compositing**          | ![Video](https://github.com/user-attachments/assets/f93a616f-571d-474e-bcc0-53736de7303d) Use images (backdrops, foreground elements, props, etc.) in scenes with depth and blend them naturally together. Just a couple of images usually leads to great compositions. |
| **2D Image Compositing**          | ![Video](https://github.com/user-attachments/assets/d6f99391-e496-4c62-9e37-29734ba5f899) Use images, background removal, layers, and simple drawing tools to precisely compose a scene.                                                                                |
| **Image to 3D Mesh**              | ![Video](https://github.com/user-attachments/assets/600a405c-e360-48c1-9b42-6e657ae6243b) It's almost impossible to lay out complicated objects or block complicated scenes; turning images into 3D helps position elements exactingly and intentionally.               |
| **Character Posing**              | ![Video](https://github.com/user-attachments/assets/52a8e983-7c8f-42d2-be8b-25296ab9ed57) You can dynamically pose your characters to achieve the precise character, scene, and camera blocking before calling "action".                                                |
| **Scene Blocking w/ Kit Bashing** | ![Video](https://github.com/user-attachments/assets/eef025ac-0346-4a46-a023-d48e23629eb5) Use 3D asset kits to precisely block out your scene: get the correct angles, object positions, and rich depth layering you can't with text prompting.                         |
| **Character Identity Transfer**   | ![Video](https://github.com/user-attachments/assets/629119ee-8c76-4a83-9827-8c6c995a3ec1) Use mannequins as simple 3D ControlNets for posing any character.                                                                                                             |
| **Background Removal**            | ![Video](https://github.com/user-attachments/assets/90c65057-5531-404f-83af-b34e66e24ec1) Remove backgrounds from images to make them useful in 2D or 3D compositing. They can be props, layers, or backdrops.                                                          |
| **Mixed Asset Crafting**          | ![Video](https://raw.githubusercontent.com/storytold/github-media/main/ship-editing.gif) You can use image cutouts, worlds, and simple 3D meshes all together to precisely and intentionally lay out your scenes.                                                       |
| **Scene Blocking**                | (preview coming soon)                                                                                                                                                                                                                                                   |
| **Canvas Editing**                | (preview coming soon)                                                                                                                                                                                                                                                   |
| **Scene Relighting**              | (preview coming soon)                                                                                                                                                                                                                                                   |

Note: all of the above videos were generated for free with Grok Video; the cost to build this README was negligible.

## Quick and Easy Prompting
We haven't abandoned text-to-asset generation for quick prototyping and ideation. We support every popular workflow in a first class fashion.

| Feature               | Demo + Explanation                                                                                                                                    
|-----------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------|
| **Text to Image**     | ![Video](https://github.com/user-attachments/assets/9cc289cd-faf4-4eaf-aed2-21134cce127c) Text prompt over a dozen different image models.            |
| **Image Editing**     | ![Video](https://github.com/user-attachments/assets/a06fa6ad-936c-42d0-8767-48fdbb8ff141) Edit with Nano Banana Pro and GPT Image 1.5.                |
| **Image Editing**     | ![Video](https://github.com/user-attachments/assets/f036e08a-f3a6-417a-98ee-ec7f04b2b5ff) Use inpainting, drawing, masking, etc. to edit images.      |
| **Image to Video**    | ![Video](https://github.com/user-attachments/assets/2bc6c592-511e-4fba-b40f-03c96699b7f7) Image to video with lots of different options and controls. |
| **Image Inpainting**  | (preview coming soon)                                                                                                                                 |
| **Image Ingredients** | (preview coming soon)                                                                                                                                 |

## Models and Providers Supported within Artcraft

| Provider   | Features                                                                                                                                                                |
|------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Artcraft   | Nano Banana, Nano Banana Pro, GPT-Image-1 / 1.5, Seedream 4 / 4.5, Flux 1.1 / Kontext, Veo 2 / 3 / 3.1, Kling 1.6 / 2.1 / 2.5 / 2.6, Seedance, Sora 2 / Pro, Hunyuan 3d 2 / 3 |
| Grok       | Grok Imagine, Grok Video                                                                                                                                                |
| Midjourney | Image Gen (all versions)                                                                                                                                                |
| Sora       | Sora 1, Sora 2, GPT-Image-1                                                                                                                                             |
| WorldLabs  | Marble (Gaussian Splat World Generation)                                                                                                                                |

We're going to be adding the following providers soon: Kling (via Kling website accounts), Google (via API keys), 
Runway (via website account), Luma (via website account).

We're potentially interested in adding other aggregators for those who already have subscriptions and credits at 
those providers, for example: OpenArt, FreePik, etc.

## Downloads

- [Visit our website for the stable Windows and MacOS releases](https://getartcraft.com/)
- Or you can grab a [more recent Windows and MacOS build directly](https://github.com/storytold/artcraft/releases)
- Linux requires building from source for now

## Documentation

- [developer documentation](./_docs)
- [tools, scripts, misc](./script)
- [license](./LICENSE.md)
- [roadmap](./ROADMAP.md)

]]> Rust https://github.com/fish-shell/fish-shell https://github.com/fish-shell/fish-shell Sat, 07 Feb 2026 00:07:57 GMT fish-shell/fish-shell

The user-friendly command line shell.

Language: Rust

Stars: 32,497

Forks: 2,223

Stars today: 193 stars today

README

README not available. Either the repository does not have a README or it could not be accessed.

]]> Rust https://github.com/openai/codex https://github.com/openai/codex Sat, 07 Feb 2026 00:07:56 GMT openai/codex

Lightweight coding agent that runs in your terminal

Language: Rust

Stars: 59,292

Forks: 7,754

Stars today: 210 stars today

README

<p align="center"><code>npm i -g @openai/codex</code><br />or <code>brew install --cask codex</code></p>
<p align="center"><strong>Codex CLI</strong> is a coding agent from OpenAI that runs locally on your computer.
<p align="center">
  <img src="https://github.com/openai/codex/blob/main/.github/codex-cli-splash.png" alt="Codex CLI splash" width="80%" />
</p>
</br>
If you want Codex in your code editor (VS Code, Cursor, Windsurf), <a href="https://developers.openai.com/codex/ide">install in your IDE.</a>
</br>If you are looking for the <em>cloud-based agent</em> from OpenAI, <strong>Codex Web</strong>, go to <a href="https://chatgpt.com/codex">chatgpt.com/codex</a>.</p>

---

## Quickstart

### Installing and running Codex CLI

Install globally with your preferred package manager:

```shell
# Install using npm
npm install -g @openai/codex
```

```shell
# Install using Homebrew
brew install --cask codex
```

Then simply run `codex` to get started.

<details>
<summary>You can also go to the <a href="https://github.com/openai/codex/releases/latest">latest GitHub Release</a> and download the appropriate binary for your platform.</summary>

Each GitHub Release contains many executables, but in practice, you likely want one of these:

- macOS
  - Apple Silicon/arm64: `codex-aarch64-apple-darwin.tar.gz`
  - x86_64 (older Mac hardware): `codex-x86_64-apple-darwin.tar.gz`
- Linux
  - x86_64: `codex-x86_64-unknown-linux-musl.tar.gz`
  - arm64: `codex-aarch64-unknown-linux-musl.tar.gz`

Each archive contains a single entry with the platform baked into the name (e.g., `codex-x86_64-unknown-linux-musl`), so you likely want to rename it to `codex` after extracting it.

</details>

### Using Codex with your ChatGPT plan

Run `codex` and select **Sign in with ChatGPT**. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Team, Edu, or Enterprise plan. [Learn more about what's included in your ChatGPT plan](https://help.openai.com/en/articles/11369540-codex-in-chatgpt).

You can also use Codex with an API key, but this requires [additional setup](https://developers.openai.com/codex/auth#sign-in-with-an-api-key).

## Docs

- [**Codex Documentation**](https://developers.openai.com/codex)
- [**Contributing**](./docs/contributing.md)
- [**Installing & building**](./docs/install.md)
- [**Open source fund**](./docs/open-source-fund.md)

This repository is licensed under the [Apache-2.0 License](LICENSE).

]]> Rust https://github.com/cocoindex-io/cocoindex https://github.com/cocoindex-io/cocoindex Sat, 07 Feb 2026 00:07:55 GMT cocoindex-io/cocoindex

Data transformation framework for AI. Ultra performant, with incremental processing. 🌟 Star if you like it!

Language: Rust

Stars: 6,041

Forks: 445

Stars today: 9 stars today

README

<p align="center">
    <img src="https://cocoindex.io/images/github.svg" alt="CocoIndex">
</p>

<h1 align="center">Data transformation for AI</h1>

<div align="center">

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<div align="center">
    <a href="https://trendshift.io/repositories/13939" target="_blank"><img src="https://trendshift.io/api/badge/repositories/13939" alt="cocoindex-io%2Fcocoindex | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</div>

Ultra performant data transformation framework for AI, with core engine written in Rust. Support incremental processing and data lineage out-of-box.  Exceptional developer velocity. Production-ready at day 0.

⭐ Drop a star to help us grow!

<div align="center">

<!-- Keep these links. Translations will automatically update with the README. -->
[Deutsch](https://readme-i18n.com/cocoindex-io/cocoindex?lang=de) |
[English](https://readme-i18n.com/cocoindex-io/cocoindex?lang=en) |
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</div>

</br>

<p align="center">
    <img src="https://cocoindex.io/images/transformation.svg" alt="CocoIndex Transformation">
</p>

</br>

CocoIndex makes it effortless to transform data with AI, and keep source data and target in sync. Whether you’re building a vector index, creating knowledge graphs for context engineering or performing any custom data transformations — goes beyond SQL.

</br>

<p align="center">
<img alt="CocoIndex Features" src="https://cocoindex.io/images/venn2.svg" />
</p>

</br>

## Exceptional velocity

Just declare transformation in dataflow with ~100 lines of python

```python
# import
data['content'] = flow_builder.add_source(...)

# transform
data['out'] = data['content']
    .transform(...)
    .transform(...)

# collect data
collector.collect(...)

# export to db, vector db, graph db ...
collector.export(...)
```

CocoIndex follows the idea of [Dataflow](https://en.wikipedia.org/wiki/Dataflow_programming) programming model. Each transformation creates a new field solely based on input fields, without hidden states and value mutation. All data before/after each transformation is observable, with lineage out of the box.

**Particularly**, developers don't explicitly mutate data by creating, updating and deleting. They just need to define transformation/formula for a set of source data.

## Plug-and-Play Building Blocks

Native builtins for different source, targets and transformations. Standardize interface, make it 1-line code switch between different components - as easy as assembling building blocks.

<p align="center">
    <img src="https://cocoindex.io/images/components.svg" alt="CocoIndex Features">
</p>

## Data Freshness

CocoIndex keep source data and target in sync effortlessly.

<p align="center">
    <img src="https://github.com/user-attachments/assets/f4eb29b3-84ee-4fa0-a1e2-80eedeeabde6" alt="Incremental Processing" width="700">
</p>

It has out-of-box support for incremental indexing:

- minimal recomputation on source or logic change.
- (re-)processing necessary portions; reuse cache when possible

## Quick Start

If you're new to CocoIndex, we recommend checking out

- 📖 [Documentation](https://cocoindex.io/docs)
- ⚡  [Quick Start Guide](https://cocoindex.io/docs/getting_started/quickstart)
- 🎬 [Quick Start Video Tutorial](https://youtu.be/gv5R8nOXsWU?si=9ioeKYkMEnYevTXT)

### Setup

1. Install CocoIndex Python library

```sh
pip install -U cocoindex
```

2. [Install Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) if you don't have one. CocoIndex uses it for incremental processing.

3. (Optional) Install Claude Code skill for enhanced development experience. Run these commands in [Claude Code](https://claude.com/claude-code):

```
/plugin marketplace add cocoindex-io/cocoindex-claude
/plugin install cocoindex-skills@cocoindex
```

## Define data flow

Follow [Quick Start Guide](https://cocoindex.io/docs/getting_started/quickstart) to define your first indexing flow. An example flow looks like:

```python
@cocoindex.flow_def(name="TextEmbedding")
def text_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.DataScope):
    # Add a data source to read files from a directory
    data_scope["documents"] = flow_builder.add_source(cocoindex.sources.LocalFile(path="markdown_files"))

    # Add a collector for data to be exported to the vector index
    doc_embeddings = data_scope.add_collector()

    # Transform data of each document
    with data_scope["documents"].row() as doc:
        # Split the document into chunks, put into `chunks` field
        doc["chunks"] = doc["content"].transform(
            cocoindex.functions.SplitRecursively(),
            language="markdown", chunk_size=2000, chunk_overlap=500)

        # Transform data of each chunk
        with doc["chunks"].row() as chunk:
            # Embed the chunk, put into `embedding` field
            chunk["embedding"] = chunk["text"].transform(
                cocoindex.functions.SentenceTransformerEmbed(
                    model="sentence-transformers/all-MiniLM-L6-v2"))

            # Collect the chunk into the collector.
            doc_embeddings.collect(filename=doc["filename"], location=chunk["location"],
                                   text=chunk["text"], embedding=chunk["embedding"])

    # Export collected data to a vector index.
    doc_embeddings.export(
        "doc_embeddings",
        cocoindex.targets.Postgres(),
        primary_key_fields=["filename", "location"],
        vector_indexes=[
            cocoindex.VectorIndexDef(
                field_name="embedding",
                metric=cocoindex.VectorSimilarityMetric.COSINE_SIMILARITY)])
```

It defines an index flow like this:

<p align="center">
    <img width="400" alt="Data Flow" src="https://github.com/user-attachments/assets/2ea7be6d-3d94-42b1-b2bd-22515577e463" />
</p>

## 🚀 Examples and demo

| Example | Description |
|---------|-------------|
| [Text Embedding](examples/text_embedding) | Index text documents with embeddings for semantic search |
| [Code Embedding](examples/code_embedding) | Index code embeddings for semantic search |
| [PDF Embedding](examples/pdf_embedding) | Parse PDF and index text embeddings for semantic search |
| [PDF Elements Embedding](examples/pdf_elements_embedding) | Extract text and images from PDFs; embed text with SentenceTransformers and images with CLIP; store in Qdrant for multimodal search |
| [Manuals LLM Extraction](examples/manuals_llm_extraction) | Extract structured information from a manual using LLM |
| [Amazon S3 Embedding](examples/amazon_s3_embedding) | Index text documents from Amazon S3 |
| [Azure Blob Storage Embedding](examples/azure_blob_embedding) | Index text documents from Azure Blob Storage |
| [Google Drive Text Embedding](examples/gdrive_text_embedding) | Index text documents from Google Drive |
| [Meeting Notes to Knowledge Graph](examples/meeting_notes_graph) | Extract structured meeting info from Google Drive and build a knowledge graph |
| [Docs to Knowledge Graph](examples/docs_to_knowledge_graph) | Extract relationships from Markdown documents and build a knowledge graph |
| [Embeddings to Qdrant](examples/text_embedding_qdrant) | Index documents in a Qdrant collection for semantic search |
| [Embeddings to LanceDB](examples/text_embedding_lancedb) | Index documents in a LanceDB collection for semantic search |
| [FastAPI Server with Docker](examples/fastapi_server_docker) | Run the semantic search server in a Dockerized FastAPI setup |
| [Product Recommendation](examples/product_recommendation) | Build real-time product recommendations with LLM and graph database|
| [Image Search with Vision API](examples/image_search) | Generates detailed captions for images using a vision model, embeds them, enables live-updating semantic search via FastAPI and served on a React frontend|
| [Face Recognition](examples/face_recognition) | Recognize faces in images and build embedding index |
| [Paper Metadata](examples/paper_metadata) | Index papers in PDF files, and build metadata tables for each paper |
| [Multi Format Indexing](examples/multi_format_indexing) | Build visual document index from PDFs and images with ColPali for semantic search |
| [Custom Source HackerNews](examples/custom_source_hn) | Index HackerNews threads and comments, using *CocoIndex Custom Source* |
| [Custom Output Files](examples/custom_output_files) | Convert markdown files to HTML files and save them to a local directory, using *CocoIndex Custom Targets* |
| [Patient intake form extraction](examples/patient_intake_extraction) | Use LLM to extract structured data from patient intake forms with different formats |
| [HackerNews Trending Topics](examples/hn_trending_topics) | Extract trending topics from HackerNews threads and comments, using *CocoIndex Custom Source* and LLM |
| [Patient Intake Form Extraction with BAML](examples/patient_intake_extraction_baml) | Extract structured data from patient intake forms using BAML |
| [Patient Intake Form Extraction with DSPy](examples/patient_intake_extraction_dspy) | Extract structured data from patient intake forms using DSPy |

More coming and stay tuned 👀!

## 📖 Documentation

For detailed documentation, visit [CocoIndex Documentation](https://cocoindex.io/docs), including a [Quickstart guide](https://cocoindex.io/docs/getting_started/quickstart).

## 🤝 Contributing

We love contributions from our community ❤️. For details on contributing or running the project for development, check out our [contributing guide](https://cocoindex.io/docs/about/contributing).

## 👥 Community

Welcome with a huge coconut hug 🥥⋆｡˚🤗. We are super excited for community contributions of all kinds - whether it's code improvements, documentation updates, issue reports, feature requests, and discussions in our Discord.

Join our community here:

- 🌟 [Star us on GitHub](https://github.com/cocoindex-io/cocoindex)
- 👋 [Join our Discord community](https://discord.com/invite/zpA9S2DR7s)
- ▶️ [Subscribe to our YouTube channel](https://www.youtube.com/@cocoindex-io)
- 📜 [Read our blog posts](https://cocoindex.io/blogs/)

## Support us

We are constantly improving, and more features and examples are coming soon. If you love this project, please drop us a star ⭐ at GitHub repo [![GitHub](https://img.shields.io/github/stars/cocoindex-io/cocoindex?color=5B5BD6)](https://github.com/cocoindex-io/cocoindex) to stay tuned and help us grow.

## License

CocoIndex is Apache 2.0 licensed.

]]> Rust https://github.com/sinelaw/fresh https://github.com/sinelaw/fresh Sat, 07 Feb 2026 00:07:54 GMT sinelaw/fresh

Terminal based IDE & text editor: easy, powerful and fast

Language: Rust

Stars: 5,736

Forks: 201

Stars today: 50 stars today

README

# Fresh

A terminal-based text editor. [Official Website →](https://sinelaw.github.io/fresh/)

**[📦 Installation Instructions](#installation)**

**[Contributing](#contributing)**

## Why?

Why another text editor? Fresh brings the intuitive, conventional UX of editors like VS Code and Sublime Text to the terminal.

While veterans like Emacs and Vim - and newer editors like Neovim and Helix - are excellent for power users who prefer modal, highly specialized workflows, they often present a steep learning curve for those used to standard GUI interactions. Fresh is built for the developer who wants a familiar, non-modal experience out-of-the-box, without sacrificing the speed and portability of the command line. Keyboard bindings, mouse support, menus, command palette etc. are all designed to be familiar to most modern users.

Architecturally, Fresh is built to handle multi-gigabyte files or slow network streams efficiently, maintaining a negligible memory overhead regardless of file size. While traditional editors struggle with latency and RAM bloat on large files, Fresh delivers consistent, high-speed performance on any scale.

The goal for Fresh is to be an intuitive and accessible, high-performance terminal-based editor that "just works" on any hardware, for everyone.

## Discovery & Ease of Use

Fresh is designed for discovery. It features native UIs, a full Menu system, and a powerful Command Palette. With full mouse support, transitioning from graphical editors is seamless.

## Modern Extensibility

Extend Fresh easily using modern tools. Plugins are written in TypeScript and run securely in a sandboxed Deno environment, providing access to a modern JavaScript ecosystem without compromising stability.

## Low-Latency Performance

Fresh is engineered for speed. It delivers a low-latency experience, with text appearing instantly. The editor is designed to be light and fast, reliably opening and editing [huge files up to multi-gigabyte sizes](https://noamlewis.com/blog/2025/12/09/how-fresh-loads-huge-files-fast) without slowdown.

## Comprehensive Feature Set

- **File Management**: open/save/new/close, file explorer, tabs, auto-revert, git file finder
- **Editing**: undo/redo, multi-cursor, block selection, smart indent, comments, clipboard
- **Search & Replace**: incremental search, find in selection, query replace, git grep
- **Navigation**: go to line/bracket, word movement, position history, bookmarks, error navigation
- **Views & Layout**: split panes, line numbers, line wrap, backgrounds, markdown preview
- **Language Server (LSP)**: go to definition, references, hover, code actions, rename, diagnostics, autocompletion
- **Productivity**: command palette, menu bar, keyboard macros, git log, diagnostics panel
- **Plugins & Extensibility**: TypeScript plugins, color highlighter, TODO highlighter, merge conflicts, path complete, keymaps
- **Internationalization**: Multiple language support (see [`locales/`](locales/) for available languages), plugin translation system

![Fresh Demo](docs/fresh-demo2.gif)
![Fresh Screenshot](docs/public/images/screenshot1.png)
![Fresh Screenshot](docs/public/images/screenshot2.png)
![Fresh Screenshot](docs/public/images/screenshot3.png)

## Installation

Quick install (autodetect best method):

`curl https://raw.githubusercontent.com/sinelaw/fresh/refs/heads/master/scripts/install.sh | sh`

Or, pick your preferred method:

| Platform | Method |
|----------|--------|
| macOS | [brew](#brew) |
| Bazzite/Bluefin/Aurora Linux | [brew](#brew) |
| Arch Linux | [AUR](#arch-linux-aur) |
| Debian/Ubuntu | [.deb](#debianubuntu-deb) |
| Fedora/RHEL | [.rpm](#fedorarhelopensuse-rpm), [Terra](https://terra.fyralabs.com/) |
| FreeBSD | [ports / pkg](https://www.freshports.org/editors/fresh) |
| Linux (any distro) | [AppImage](#appimage), [Flatpak](#flatpak) |
| All platforms | [Pre-built binaries](#pre-built-binaries) |
| npm | [npm / npx](#npm) |
| Rust users (Fast) | [cargo-binstall](#using-cargo-binstall) |
| Rust users | [crates.io](#from-cratesio) |
| Nix | [Nix flakes](#nix-flakes) |
| Developers | [From source](#from-source) |

### Brew

On macOS and some linux distros (Bazzite/Bluefin/Aurora):

> **Note:** On macOS, see [macOS Terminal Tips](https://getfresh.dev/docs/configuration/keyboard#macos-terminal-tips) for recommended terminal configuration.

```bash
brew tap sinelaw/fresh
brew install fresh-editor
```

### Arch Linux ([AUR](https://aur.archlinux.org/packages/fresh-editor-bin))

**Binary package (recommended, faster install):**

```bash
git clone https://aur.archlinux.org/fresh-editor-bin.git
cd fresh-editor-bin
makepkg --syncdeps --install
```

**Build from source:**

```bash
git clone https://aur.archlinux.org/fresh-editor.git
cd fresh-editor
makepkg --syncdeps --install
```

**Using an AUR helper (such as `yay` or `paru`):**

```bash
# Binary package (recommended, faster install)
yay -S fresh-editor-bin

# Or build from source
yay -S fresh-editor
```

### Debian/Ubuntu (.deb)

Download and install the latest release:

```bash
curl -sL $(curl -s https://api.github.com/repos/sinelaw/fresh/releases/latest | grep "browser_download_url.*_$(dpkg --print-architecture)\.deb" | cut -d '"' -f 4) -o fresh-editor.deb && sudo dpkg -i fresh-editor.deb
```

Or download the `.deb` file manually from the [releases page](https://github.com/sinelaw/fresh/releases).

### Fedora/RHEL/openSUSE (.rpm)

Download and install the latest release:

```bash
curl -sL $(curl -s https://api.github.com/repos/sinelaw/fresh/releases/latest | grep "browser_download_url.*\.$(uname -m)\.rpm" | cut -d '"' -f 4) -o fresh-editor.rpm && sudo rpm -U fresh-editor.rpm
```

Or download the `.rpm` file manually from the [releases page](https://github.com/sinelaw/fresh/releases).

### AppImage

Download the `.AppImage` file from the [releases page](https://github.com/sinelaw/fresh/releases) and run:

```bash
chmod +x fresh-editor-VERSION-x86_64.AppImage
./fresh-editor-VERSION-x86_64.AppImage
```

**For faster startup** (recommended): Extract the AppImage instead of running it directly. This avoids the FUSE mount overhead on each launch (~10x faster):

```bash
./fresh-editor-VERSION-x86_64.AppImage --appimage-extract
mkdir -p ~/.local/share/fresh-editor ~/.local/bin
mv squashfs-root/* ~/.local/share/fresh-editor/
ln -sf ~/.local/share/fresh-editor/usr/bin/fresh ~/.local/bin/fresh
```

Ensure `~/.local/bin` is in your PATH. Available for x86_64 and aarch64 architectures.

### Flatpak

Download the `.flatpak` bundle from the [releases page](https://github.com/sinelaw/fresh/releases) and install:

```bash
flatpak install --user fresh-editor-VERSION-x86_64.flatpak
flatpak run io.github.sinelaw.fresh
```

See [flatpak/README.md](flatpak/README.md) for building from source.

### Pre-built binaries

Download the latest release for your platform from the [releases page](https://github.com/sinelaw/fresh/releases).

### npm

```bash
npm install -g @fresh-editor/fresh-editor
```

Or try it without installing:

```bash
npx @fresh-editor/fresh-editor
```

### Using cargo-binstall

To install the binary directly without compiling (much faster than crates.io):

First, install cargo-binstall if you haven't already

```bash
cargo install cargo-binstall
```

Then install fresh

```bash
cargo binstall fresh-editor
```

### Nix flakes

Run without installing:
```bash
nix run github:sinelaw/fresh
```

Or install to your profile:
```bash
nix profile add github:sinelaw/fresh
```

### From crates.io

```bash
cargo install fresh-editor
```

### From source

```bash
git clone https://github.com/sinelaw/fresh.git
cd fresh
cargo build --release
./target/release/fresh [file]
```

## Documentation

- [User Guide](https://getfresh.dev/docs)
- [macOS Tips](https://getfresh.dev/docs/configuration/keyboard#macos-terminal-tips) - Terminal configuration, keyboard shortcuts, and troubleshooting for Mac users
- [Plugin Development](https://getfresh.dev/docs/plugins/development)

## Contributing

Thanks for contributing!

1. **Reproduce Before Fixing**: Always include a test case that reproduces the bug (fails) without the fix, and passes with the fix. This ensures the issue is verified and prevents future regressions.

2. **E2E Tests for New Flows**: Any new user flow or feature must include an end-to-end (e2e) test. E2E tests send keyboard/mouse events and examines the final rendered output, do not examine internal state.

3. **No timeouts or time-sensitive tests**: Use "semantic waiting" (waiting for specific state changes/events) instead of fixed timers to ensure test stability. Wait indefinitely, don't put timeouts inside tests (cargo nextest will timeout externally).

4. **Test isolation**: Tests should run in parallel. Use the internal clipboard mode in tests to isolate them from the host system and prevent flakiness in CI. Same for other external resources (temp files, etc. should all be isolated between tests, under a per-test temporary workdir).

5. **Required Formatting**: All code must be formatted with `cargo fmt` before submission. PRs that fail formatting checks will not be merged.

6. **Cross-Platform Consistency**: Avoid hard-coding newline or CRLF related logic, consider the buffer mode.

7. **LSP**: Ensure LSP interactions follow the correct lifecycle (e.g., `didOpen` must always precede other requests to avoid server-side errors). Use the appropriate existing helpers for this pattern.

8. **Regenerate plugin types and schemas**: After modifying the plugin API or config types:
   - **TypeScript definitions** (`plugins/lib/fresh.d.ts`): Auto-generated from Rust types with `#[derive(TS)]`. Run: `cargo test -p fresh-plugin-runtime write_fresh_dts_file -- --ignored`
   - **JSON schemas** (`plugins/config-schema.json`, `plugins/schemas/theme.schema.json`): Auto-generated from Rust types with `#[derive(JsonSchema)]`. Run: `./scripts/gen_schema.sh`
   - **Package schema** (`plugins/schemas/package.schema.json`): Manually maintained - edit directly when adding new language pack fields

9. **Type check plugins**: Run `crates/fresh-editor/plugins/check-types.sh` (requires `tsc`)

**Tip**: You can use tmux + send-keys + render-pane to script ad-hoc tests on the UI, for example when trying to reproduce an issue.

## Privacy

Fresh checks for new versions daily to notify you of available upgrades. Alongside this, it sends basic anonymous telemetry (version, OS/architecture, terminal type) to help understand usage patterns. No personal data or file contents are collected.

To disable both upgrade checks and telemetry, use `--no-upgrade-check` or set `check_for_updates: false` in your config.

## License

Copyright (c) Noam Lewis

This project is licensed under the GNU General Public License v2.0 (GPL-2.0).

]]> Rust https://github.com/lance-format/lance https://github.com/lance-format/lance Sat, 07 Feb 2026 00:07:53 GMT lance-format/lance

Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

Language: Rust

Stars: 6,021

Forks: 544

Stars today: 7 stars today

README

<div align="center">
<p align="center">

<img width="257" alt="Lance Logo" src="https://user-images.githubusercontent.com/917119/199353423-d3e202f7-0269-411d-8ff2-e747e419e492.png">

**The Open Lakehouse Format for Multimodal AI**<br/>
**High-performance vector search, full-text search, random access, and feature engineering capabilities for the lakehouse.**<br/>
**Compatible with Pandas, DuckDB, Polars, PyArrow, Ray, Spark, and more integrations on the way.**

<a href="https://lance.org">Documentation</a> •
<a href="https://lance.org/community">Community</a> •
<a href="https://discord.gg/lance">Discord</a>

[CI]: https://github.com/lance-format/lance/actions/workflows/rust.yml
[CI Badge]: https://github.com/lance-format/lance/actions/workflows/rust.yml/badge.svg
[Docs]: https://lance.org
[Docs Badge]: https://img.shields.io/badge/docs-passing-brightgreen
[crates.io]: https://crates.io/crates/lance
[crates.io badge]: https://img.shields.io/crates/v/lance.svg
[Python versions]: https://pypi.org/project/pylance/
[Python versions badge]: https://img.shields.io/pypi/pyversions/pylance

[![CI Badge]][CI]
[![Docs Badge]][Docs]
[![crates.io badge]][crates.io]
[![Python versions badge]][Python versions]

</p>
</div>

<hr />

Lance is an open lakehouse format for multimodal AI. It contains a file format, table format, and catalog spec that allows you to build a complete lakehouse on top of object storage to power your AI workflows. Lance is perfect for:

1. Building search engines and feature stores with hybrid search capabilities.
2. Large-scale ML training requiring high performance IO and random access.
3. Storing, querying, and managing multimodal data including images, videos, audio, text, and embeddings.

The key features of Lance include:

* **Expressive hybrid search:** Combine vector similarity search, full-text search (BM25), and SQL analytics on the same dataset with accelerated secondary indices.

* **Lightning-fast random access:** 100x faster than Parquet or Iceberg for random access without sacrificing scan performance.

* **Native multimodal data support:** Store images, videos, audio, text, and embeddings in a single unified format with efficient blob encoding and lazy loading.

* **Data evolution:** Efficiently add columns with backfilled values without full table rewrites, perfect for ML feature engineering.

* **Zero-copy versioning:** ACID transactions, time travel, and automatic versioning without needing extra infrastructure.

* **Rich ecosystem integrations:** Apache Arrow, Pandas, Polars, DuckDB, Apache Spark, Ray, Trino, Apache Flink, and open catalogs (Apache Polaris, Unity Catalog, Apache Gravitino).

For more details, see the full [Lance format specification](https://lance.org/format).

> [!TIP]
> Lance is in active development and we welcome contributions. Please see our [contributing guide](https://lance.org/community/contributing/) for more information.

## Quick Start

**Installation**

```shell
pip install pylance
```

To install a preview release:

```shell
pip install --pre --extra-index-url https://pypi.fury.io/lance-format/pylance
```

> [!NOTE]
> For versions prior to 1.0.0-beta.4, you can find them at https://pypi.fury.io/lancedb/pylance

> [!TIP]
> Preview releases are released more often than full releases and contain the
> latest features and bug fixes. They receive the same level of testing as full releases.
> We guarantee they will remain published and available for download for at
> least 6 months. When you want to pin to a specific version, prefer a stable release.

**Converting to Lance**

```python
import lance

import pandas as pd
import pyarrow as pa
import pyarrow.dataset

df = pd.DataFrame({"a": [5], "b": [10]})
uri = "/tmp/test.parquet"
tbl = pa.Table.from_pandas(df)
pa.dataset.write_dataset(tbl, uri, format='parquet')

parquet = pa.dataset.dataset(uri, format='parquet')
lance.write_dataset(parquet, "/tmp/test.lance")
```

**Reading Lance data**
```python
dataset = lance.dataset("/tmp/test.lance")
assert isinstance(dataset, pa.dataset.Dataset)
```

**Pandas**
```python
df = dataset.to_table().to_pandas()
df
```

**DuckDB**
```python
import duckdb

# If this segfaults, make sure you have duckdb v0.7+ installed
duckdb.query("SELECT * FROM dataset LIMIT 10").to_df()
```

**Vector search**

Download the sift1m subset

```shell
wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
tar -xzf sift.tar.gz
```

Convert it to Lance

```python
import lance
from lance.vector import vec_to_table
import numpy as np
import struct

nvecs = 1000000
ndims = 128
with open("sift/sift_base.fvecs", mode="rb") as fobj:
    buf = fobj.read()
    data = np.array(struct.unpack("<128000000f", buf[4 : 4 + 4 * nvecs * ndims])).reshape((nvecs, ndims))
    dd = dict(zip(range(nvecs), data))

table = vec_to_table(dd)
uri = "vec_data.lance"
sift1m = lance.write_dataset(table, uri, max_rows_per_group=8192, max_rows_per_file=1024*1024)
```

Build the index

```python
sift1m.create_index("vector",
                    index_type="IVF_PQ",
                    num_partitions=256,  # IVF
                    num_sub_vectors=16)  # PQ
```

Search the dataset

```python
# Get top 10 similar vectors
import duckdb

dataset = lance.dataset(uri)

# Sample 100 query vectors. If this segfaults, make sure you have duckdb v0.7+ installed
sample = duckdb.query("SELECT vector FROM dataset USING SAMPLE 100").to_df()
query_vectors = np.array([np.array(x) for x in sample.vector])

# Get nearest neighbors for all of them
rs = [dataset.to_table(nearest={"column": "vector", "k": 10, "q": q})
      for q in query_vectors]
```

## Directory structure

| Directory          | Description              |
|--------------------|--------------------------|
| [rust](./rust)     | Core Rust implementation |
| [python](./python) | Python bindings (PyO3)   |
| [java](./java)     | Java bindings (JNI)      |
| [docs](./docs)     | Documentation source     |

## Benchmarks

### Vector search

We used the SIFT dataset to benchmark our results with 1M vectors of 128D

1. For 100 randomly sampled query vectors, we get <1ms average response time (on a 2023 m2 MacBook Air)

![avg_latency.png](docs/src/images/avg_latency.png)

2. ANNs are always a trade-off between recall and performance

![avg_latency.png](docs/src/images/recall_vs_latency.png)

### Vs. parquet

We create a Lance dataset using the Oxford Pet dataset to do some preliminary performance testing of Lance as compared to Parquet and raw image/XMLs. For analytics queries, Lance is 50-100x better than reading the raw metadata. For batched random access, Lance is 100x better than both parquet and raw files.

![](docs/src/images/lance_perf.png)

## Why Lance for AI/ML workflows?

The machine learning development cycle involves multiple stages:

```mermaid
graph LR
    A[Collection] --> B[Exploration];
    B --> C[Analytics];
    C --> D[Feature Engineer];
    D --> E[Training];
    E --> F[Evaluation];
    F --> C;
    E --> G[Deployment];
    G --> H[Monitoring];
    H --> A;
```

Traditional lakehouse formats were designed for SQL analytics and struggle with AI/ML workloads that require:
- **Vector search** for similarity and semantic retrieval
- **Fast random access** for sampling and interactive exploration
- **Multimodal data** storage (images, videos, audio alongside embeddings)
- **Data evolution** for feature engineering without full table rewrites
- **Hybrid search** combining vectors, full-text, and SQL predicates

While existing formats (Parquet, Iceberg, Delta Lake) excel at SQL analytics, they require additional specialized systems for AI capabilities. Lance brings these AI-first features directly into the lakehouse format.

A comparison of different formats across ML development stages:

|                     | Lance | Parquet & ORC | JSON & XML | TFRecord | Database | Warehouse |
|---------------------|-------|---------------|------------|----------|----------|-----------|
| Analytics           | Fast  | Fast          | Slow       | Slow     | Decent   | Fast      |
| Feature Engineering | Fast  | Fast          | Decent     | Slow     | Decent   | Good      |
| Training            | Fast  | Decent        | Slow       | Fast     | N/A      | N/A       |
| Exploration         | Fast  | Slow          | Fast       | Slow     | Fast     | Decent    |
| Infra Support       | Rich  | Rich          | Decent     | Limited  | Rich     | Rich      |

]]> Rust https://github.com/risingwavelabs/risingwave https://github.com/risingwavelabs/risingwave Sat, 07 Feb 2026 00:07:52 GMT risingwavelabs/risingwave

Event streaming platform for agents, apps, and analytics. Continuously ingest, transform, and serve event data in real time, at scale.

Language: Rust

Stars: 8,772

Forks: 732

Stars today: 4 stars today

README

<p align="center">
  <picture>
    <source srcset=".github/RisingWave-logo-dark.svg" width="500px" media="(prefers-color-scheme: dark)">
    <img src=".github/RisingWave-logo-light.svg" width="500px">
  </picture>
</p>


<div align="center">

### 🌊 Ride the wave of event streaming

</div>
<p align="center">
  <a href="https://docs.risingwave.com/">Docs</a> | <a href="https://docs.risingwave.com/get-started/rw-benchmarks-stream-processing">Benchmarks</a> | <a href="https://docs.risingwave.com/demos/overview">Demos</a>
</p>

<p align="center">

<div align="center">
  <a
    href="https://github.com/risingwavelabs/risingwave/releases/latest"
    target="_blank"
  >
    <img alt="Release" src="https://img.shields.io/github/v/release/risingwavelabs/risingwave.svg?sort=semver" />
  </a>
  <a
    href="https://go.risingwave.com/slack"
    target="_blank"
  >
    <img alt="Slack" src="https://badgen.net/badge/Slack/Join%20RisingWave/0abd59?icon=slack" />
  </a>
  <a
    href="https://x.com/risingwavelabs"
    target="_blank"
  >
    <img alt="X" src="https://img.shields.io/twitter/follow/risingwavelabs" />
  </a>
  <a
    href="https://www.youtube.com/@risingwave-labs"
    target="_blank"
  >
    <img alt="YouTube" src="https://img.shields.io/youtube/channel/views/UCsHwdyBRxBpmkA5RRd0YNEA" />
  </a>
</div>

RisingWave is an enterprise-grade event streaming platform designed to offer the <i><b>simplest</b></i> and <i><b>most cost-effective</b></i> way to <b>ingest</b>, <b>process</b>, and <b>manage</b> real-time event data — with built-in support for the [Apache Iceberg™](https://iceberg.apache.org/) open table format. It provides both a Postgres-compatible [SQL interface](https://docs.risingwave.com/sql/overview) and a DataFrame-style [Python interface](https://docs.risingwave.com/python-sdk/intro).

RisingWave can <b>ingest</b> millions of events per second, continuously <b>join and analyze</b> live streams with historical data, <b>serve</b> ad-hoc queries at low latency, and <b>manage</b> data reliably in Apache Iceberg™ tables.

![RisingWave](./docs/dev/src/images/architecture_20250609.jpg)

## Try it out in 60 seconds

Install RisingWave standalone mode:
```shell
curl -L https://risingwave.com/sh | sh
```

To learn about other installation options, such as using a Docker image, see the [quick start guide](https://docs.risingwave.com/get-started/quickstart).

## Unified platform for streaming data

RisingWave delivers a unified streaming data platform that combines **ultra-low-latency stream processing** and **Iceberg-native data management**.

### Low-latency streaming ingestion and processing
RisingWave integrates real-time streaming ingestion, stream processing and low-latency serving in a single system. It continuously ingests data from streaming and batch sources, performs incremental computations across streams and tables with end-to-end freshness under 100 ms. Materialized views can be served directly within RisingWave with 10–20 ms p99 query latency, or delivered to downstream systems.

### Iceberg lakehouse ingestion, transformation, and management
RisingWave treats Apache Iceberg™ as a first-class citizen. It directly hosts and manages the Iceberg REST catalog, allowing users to create and operate Iceberg tables through a PostgreSQL-compatible interface. RisingWave supports two write modes: Merge-on-Read (MoR) and Copy-on-Write (CoW), to suit different ingestion and query patterns. It also provides built-in table maintenance capabilities, including compaction, small-file optimization, vacuum, and snapshot cleanup, ensuring efficient and consistent data management without external tools or pipelines.

_Plug: [Nimtable](https://github.com/nimtable/nimtable) is an observability tool developed by RisingWave for easily exploring and managing Iceberg tables._



## Key design decisions

RisingWave is designed to be easier to use and more cost-efficient:

### PostgreSQL compatibility

* **Seamless integration:** Connects via the PostgreSQL wire protocol, working with psql, JDBC, and any Postgres tool.
* **Expressive SQL:** Supports structured, semi-structured, and unstructured data with a familiar SQL dialect.
* **No manual state tuning:** Eliminates complex state management configurations.

### S3 as primary storage

RisingWave stores tables, materialized views, and internal states of stream processing jobs in S3 (or equivalent object storage), providing:
- **High performance:** Optimized for complex queries, including joins and time windowing.
- **Fast recovery:** Restores from system failures within seconds.
- **[Dynamic scaling](https://docs.risingwave.com/deploy/k8s-cluster-scaling):** Instantly adjusts resources to handle workload spikes.

Beyond caching hot data in memory, RisingWave supports [**elastic disk cache**](https://docs.risingwave.com/get-started/disk-cache), a powerful performance optimization that uses local disks or EBS for efficient data caching. This minimizes access to S3, lowering processing latency and cutting S3 access costs.

### Apache Iceberg™ native support
RisingWave [**natively integrates with Apache Iceberg™**](https://docs.risingwave.com/iceberg/overview), enabling continuous ingestion of streaming data into Iceberg tables. It can also read directly from Iceberg, perform automatic compaction, and maintain table health over time. Since Iceberg is an open table format, results are accessible by other query engines — making storage not only cost-efficient, but interoperable by design.

## In what use cases does RisingWave excel?
RisingWave is particularly effective for the following use cases:

* **Live dashboards**: Achieve sub-second data freshness in live dashboards, ideal for high-stakes scenarios like stock trading, sports betting, and IoT monitoring.
* **Monitoring and alerting**: Develop sophisticated monitoring and alerting systems for critical applications such as fraud and anomaly detection.
* **Real-time data enrichment**: Continuously ingest data from diverse sources, conduct real-time data enrichment, and efficiently deliver the results to downstream systems.
* **Feature engineering**: Transform batch and streaming data into features in your machine learning models using a unified codebase, ensuring seamless integration and consistency.
* **Iceberg-based lakehouses**: Power real-time lakehouse architectures where streaming data is continuously written to Apache Iceberg™ tables for unified analytics, governance, and long-term retention in open formats.

## Production deployments

[**RisingWave Cloud**](https://cloud.risingwave.com) offers the easiest way to run RisingWave in production.

For **Docker deployment**, please refer to [Docker Compose](https://docs.risingwave.com/deploy/risingwave-docker-compose/).

For **Kubernetes deployment**, please refer to [Kubernetes with Helm](https://docs.risingwave.com/deploy/risingwave-k8s-helm/) or [Kubernetes with Operator](https://docs.risingwave.com/deploy/risingwave-kubernetes/).

## Community

Looking for help, discussions, collaboration opportunities, or a casual afternoon chat with our fellow engineers and community members? Join our [Slack workspace](https://risingwave.com/slack)!

## Notes on telemetry


RisingWave uses [Scarf](https://scarf.sh/) to collect anonymized installation analytics. These analytics help support us understand and improve the distribution of our package. The privacy policy of Scarf is available at [https://about.scarf.sh/privacy-policy](https://about.scarf.sh/privacy-policy).

RisingWave also collects anonymous usage statistics to better understand how the community is using RisingWave. The sole intention of this exercise is to help improve the product. Users may opt out easily at any time. Please refer to the [user documentation](https://docs.risingwave.com/operate/telemetry/) for more details.

## License

RisingWave is distributed under the Apache License (Version 2.0). Please refer to [LICENSE](LICENSE) for more information.

## Contributing

Thanks for your interest in contributing to the project! Please refer to [RisingWave Developer Guide](https://risingwavelabs.github.io/risingwave/) for more information.

]]> Rust https://github.com/mainmatter/100-exercises-to-learn-rust https://github.com/mainmatter/100-exercises-to-learn-rust Sat, 07 Feb 2026 00:07:51 GMT mainmatter/100-exercises-to-learn-rust

A self-paced course to learn Rust, one exercise at a time.

Language: Rust

Stars: 9,015

Forks: 1,939

Stars today: 234 stars today

README

# Learn Rust, one exercise at a time

You've heard about Rust, but you never had the chance to try it out?\
This course is for you!

You'll learn Rust by solving 100 exercises.\
You'll go from knowing nothing about Rust to being able to start
writing your own programs, one exercise at a time.

> [!NOTE]
> This course has been written by [Mainmatter](https://mainmatter.com/rust-consulting/).\
> It's one of the trainings in [our portfolio of Rust workshops](https://mainmatter.com/services/workshops/rust/).\
> Check out our [landing page](https://mainmatter.com/rust-consulting/) if you're looking for Rust consulting or
> training!

## Getting started

Go to [rust-exercises.com](https://rust-exercises.com) and follow the instructions there
to get started with the course.

## Requirements

- **Rust** (follow instructions [here](https://www.rust-lang.org/tools/install)).\
  If `rustup` is already installed on your system, run `rustup update` (or another appropriate command depending on how
  you installed Rust on your system)
  to make sure you're running on the latest stable version.
- _(Optional but recommended)_ An IDE with Rust autocompletion support.
  We recommend one of the following:
  - [RustRover](https://www.jetbrains.com/rust/);
  - [Visual Studio Code](https://code.visualstudio.com) with
    the [`rust-analyzer`](https://marketplace.visualstudio.com/items?itemName=matklad.rust-analyzer) extension.

## Solutions

You can find the solutions to the exercises in
the [`solutions` branch](https://github.com/mainmatter/100-exercises-to-learn-rust/tree/solutions) of this repository.

# License

Copyright © 2024- Mainmatter GmbH (https://mainmatter.com), released under the
[Creative Commons Attribution-NonCommercial 4.0 International license](https://creativecommons.org/licenses/by-nc/4.0/).

]]> Rust https://github.com/iced-rs/iced https://github.com/iced-rs/iced Sat, 07 Feb 2026 00:07:50 GMT iced-rs/iced

A cross-platform GUI library for Rust, inspired by Elm

Language: Rust

Stars: 29,394

Forks: 1,483

Stars today: 14 stars today

README

<div align="center">

<img src="docs/logo.svg" width="140px" />

# Iced

[![Documentation](https://docs.rs/iced/badge.svg)][documentation]
[![Crates.io](https://img.shields.io/crates/v/iced.svg)](https://crates.io/crates/iced)
[![License](https://img.shields.io/crates/l/iced.svg)](https://github.com/iced-rs/iced/blob/master/LICENSE)
[![Downloads](https://img.shields.io/crates/d/iced.svg)](https://crates.io/crates/iced)
[![Test Status](https://img.shields.io/github/actions/workflow/status/iced-rs/iced/test.yml?branch=master&event=push&label=test)](https://github.com/iced-rs/iced/actions)
[![Discourse](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscourse.iced.rs%2Fsite%2Fstatistics.json&query=%24.users_count&suffix=%20users&label=discourse&color=5e7ce2)](https://discourse.iced.rs/)
[![Discord Server](https://img.shields.io/discord/628993209984614400?label=&labelColor=6A7EC2&logo=discord&logoColor=ffffff&color=7389D8)](https://discord.gg/3xZJ65GAhd)

A cross-platform GUI library for Rust focused on simplicity and type-safety.
Inspired by [Elm].

<a href="https://github.com/squidowl/halloy">
  <img src="https://iced.rs/showcase/halloy.gif" width="460px">
</a>
<a href="https://github.com/hecrj/icebreaker">
  <img src="https://iced.rs/showcase/icebreaker.gif" width="360px">
</a>

</div>

## Features

* Simple, easy-to-use, batteries-included API
* Type-safe, reactive programming model
* [Cross-platform support] (Windows, macOS, Linux, and the Web)
* Responsive layout
* Built-in widgets (including [text inputs], [scrollables], and more!)
* Custom widget support (create your own!)
* [Debug tooling with performance metrics and time traveling]
* First-class support for async actions (use futures!)
* Modular ecosystem split into reusable parts:
  * A [renderer-agnostic native runtime] enabling integration with existing systems
  * Two built-in renderers leveraging [`wgpu`] and [`tiny-skia`]
    * [`iced_wgpu`] supporting Vulkan, Metal and DX12
    * [`iced_tiny_skia`] offering a software alternative as a fallback
  * A [windowing shell]

__Iced is currently experimental software.__ [Take a look at the roadmap] and
[check out the issues].

[Cross-platform support]: https://raw.githubusercontent.com/iced-rs/iced/master/docs/images/todos_desktop.jpg
[text inputs]: https://iced.rs/examples/text_input.mp4
[scrollables]: https://iced.rs/examples/scrollable.mp4
[Debug tooling with performance metrics and time traveling]: https://github.com/user-attachments/assets/2e49695c-0261-4b43-ac2e-8d7da5454c4b
[renderer-agnostic native runtime]: runtime/
[`wgpu`]: https://github.com/gfx-rs/wgpu
[`tiny-skia`]: https://github.com/RazrFalcon/tiny-skia
[`iced_wgpu`]: wgpu/
[`iced_tiny_skia`]: tiny_skia/
[windowing shell]: winit/
[Take a look at the roadmap]: ROADMAP.md
[check out the issues]: https://github.com/iced-rs/iced/issues

## Overview

Inspired by [The Elm Architecture], Iced expects you to split user interfaces
into four different concepts:

* __State__ — the state of your application
* __Messages__ — user interactions or meaningful events that you care
  about
* __View logic__ — a way to display your __state__ as widgets that
  may produce __messages__ on user interaction
* __Update logic__ — a way to react to __messages__ and update your
  __state__

We can build something to see how this works! Let's say we want a simple counter
that can be incremented and decremented using two buttons.

We start by modelling the __state__ of our application:

```rust
#[derive(Default)]
struct Counter {
    value: i32,
}
```

Next, we need to define the possible user interactions of our counter:
the button presses. These interactions are our __messages__:

```rust
#[derive(Debug, Clone, Copy)]
pub enum Message {
    Increment,
    Decrement,
}
```

Now, let's show the actual counter by putting it all together in our
__view logic__:

```rust
use iced::widget::{button, column, text, Column};

impl Counter {
    pub fn view(&self) -> Column<Message> {
        // We use a column: a simple vertical layout
        column![
            // The increment button. We tell it to produce an
            // `Increment` message when pressed
            button("+").on_press(Message::Increment),

            // We show the value of the counter here
            text(self.value).size(50),

            // The decrement button. We tell it to produce a
            // `Decrement` message when pressed
            button("-").on_press(Message::Decrement),
        ]
    }
}
```

Finally, we need to be able to react to any produced __messages__ and change our
__state__ accordingly in our __update logic__:

```rust
impl Counter {
    // ...

    pub fn update(&mut self, message: Message) {
        match message {
            Message::Increment => {
                self.value += 1;
            }
            Message::Decrement => {
                self.value -= 1;
            }
        }
    }
}
```

And that's everything! We just wrote a whole user interface. Let's run it:

```rust
fn main() -> iced::Result {
    iced::run(Counter::update, Counter::view)
}
```

Iced will automatically:

  1. Take the result of our __view logic__ and layout its widgets.
  1. Process events from our system and produce __messages__ for our
     __update logic__.
  1. Draw the resulting user interface.

Read the [book], the [documentation], and the [examples] to learn more!

## Implementation details

Iced was originally born as an attempt at bringing the simplicity of [Elm] and
[The Elm Architecture] into [Coffee], a 2D game library I am working on.

The core of the library was implemented during May 2019 in [this pull request].
[The first alpha version] was eventually released as
[a renderer-agnostic GUI library]. The library did not provide a renderer and
implemented the current [tour example] on top of [`ggez`], a game library.

Since then, the focus has shifted towards providing a batteries-included,
end-user-oriented GUI library, while keeping the ecosystem modular.

[this pull request]: https://github.com/hecrj/coffee/pull/35
[The first alpha version]: https://github.com/iced-rs/iced/tree/0.1.0-alpha
[a renderer-agnostic GUI library]: https://www.reddit.com/r/rust/comments/czzjnv/iced_a_rendereragnostic_gui_library_focused_on/
[tour example]: examples/README.md#tour
[`ggez`]: https://github.com/ggez/ggez

## Contributing / Feedback

If you want to contribute, please read our [contributing guidelines] for more details.

Feedback is also welcome! You can create a new topic in [our Discourse forum] or
come chat to [our Discord server].

## Sponsors

The development of Iced is sponsored by the [Cryptowatch] team at [Kraken.com]

[book]: https://book.iced.rs/
[documentation]: https://docs.rs/iced/
[examples]: https://github.com/iced-rs/iced/tree/master/examples#examples
[Coffee]: https://github.com/hecrj/coffee
[Elm]: https://elm-lang.org/
[The Elm Architecture]: https://guide.elm-lang.org/architecture/
[the current issues]: https://github.com/iced-rs/iced/issues
[contributing guidelines]: https://github.com/iced-rs/iced/blob/master/CONTRIBUTING.md
[our Discourse forum]: https://discourse.iced.rs/
[our Discord server]: https://discord.gg/3xZJ65GAhd
[Cryptowatch]: https://cryptowat.ch/charts
[Kraken.com]: https://kraken.com/

]]> Rust https://github.com/microsoft/litebox https://github.com/microsoft/litebox Sat, 07 Feb 2026 00:07:49 GMT microsoft/litebox

A security-focused library OS supporting kernel- and user-mode execution

Language: Rust

Stars: 705

Forks: 30

Stars today: 208 stars today

README

# LiteBox

> A security-focused library OS

> [!NOTE]  
> This project is currently actively evolving and improving. While we are
> working toward a stable release, some APIs and interfaces may change as the
> design continues to mature. You are welcome to explore and experiment, but if
> you need long-term stability, it may be best to wait for a stable release, or
> be prepared to adapt to updates along the way.

LiteBox is a sandboxing library OS that drastically cuts down the interface to the host, thereby reducing attack surface.  It focuses on easy interop of various "North" shims and "South" platforms.  LiteBox is designed for usage in both kernel and non-kernel scenarios.

LiteBox exposes a Rust-y [`nix`](https://docs.rs/nix)/[`rustix`](https://docs.rs/rustix)-inspired "North" interface when it is provided a `Platform` interface at its "South".  These interfaces allow for a wide variety of use-cases, easily allowing for connection between any of the North--South pairs.

Example use cases include:
- Running unmodified Linux programs on Windows
- Sandboxing Linux applications on Linux
- Run programs on top of SEV SNP
- Running OP-TEE programs on Linux
- Running on LVBS

![LiteBox and related projects](./.figures/litebox.svg)

## Contributing

See the following files for details:

- [CONTRIBUTING.md](./CONTRIBUTING.md)
- [CODE_OF_CONDUCT.md](./CODE_OF_CONDUCT.md)
- [SECURITY.md](./SECURITY.md)
- [SUPPORT.md](./SUPPORT.md)

## License

MIT License.  See [./LICENSE](./LICENSE) for details.

## Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft 
trademarks or logos is subject to and must follow 
[Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
Any use of third-party trademarks or logos are subject to those third-party's policies.

]]> Rust https://github.com/j178/prek https://github.com/j178/prek Sat, 07 Feb 2026 00:07:48 GMT j178/prek

⚡ Better `pre-commit`, re-engineered in Rust

Language: Rust

Stars: 5,713

Forks: 152

Stars today: 329 stars today

README

<div align="center">

<h1>
  <img width="180" alt="prek" src="https://raw.githubusercontent.com/j178/prek/master/docs/assets/logo.webp" />
  <br/>prek
</h1>

[![prek](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/j178/prek/master/docs/assets/badge-v0.json)](https://github.com/j178/prek)
[![codecov](https://codecov.io/github/j178/prek/graph/badge.svg?token=MP6TY24F43)](https://codecov.io/github/j178/prek)
[![GitHub Downloads](https://img.shields.io/github/downloads/j178/prek/total?logo=github)](https://github.com/j178/prek/releases)
[![PyPI Downloads](https://img.shields.io/pypi/dm/prek?logo=python)](https://pepy.tech/projects/prek)
[![Discord](https://img.shields.io/discord/1403581202102878289?logo=discord)](https://discord.gg/3NRJUqJz86)

</div>

<!-- --8<-- [start: description] -->

[pre-commit](https://pre-commit.com/) is a framework to run hooks written in many languages, and it manages the
language toolchain and dependencies for running the hooks.

*prek* is a reimagined version of pre-commit, built in Rust.
It is designed to be a faster, dependency-free and drop-in alternative for it,
while also providing some additional long-requested features.

<!-- --8<-- [end: description] -->

> [!NOTE]
> Although prek is pretty new, it’s already powering real‑world projects like [CPython](https://github.com/python/cpython), [Apache Airflow](https://github.com/apache/airflow), [FastAPI](https://github.com/fastapi/fastapi), and more projects are picking it up—see [Who is using prek?](#who-is-using-prek). If you’re looking for an alternative to `pre-commit`, please give it a try—we’d love your feedback!
>
> Please note that some languages are not yet supported for full drop‑in parity with `pre-commit`. See [Language Support](https://prek.j178.dev/languages/) for current status.

<!-- --8<-- [start:features] -->

## Features

- A single binary with no dependencies, does not require Python or any other runtime.
- [Faster](https://prek.j178.dev/benchmark/) than `pre-commit` and more efficient in disk space usage.
- Fully compatible with the original pre-commit configurations and hooks.
- Built-in support for monorepos (i.e. [workspace mode](https://prek.j178.dev/workspace/)).
- Integration with [`uv`](https://github.com/astral-sh/uv) for managing Python virtual environments and dependencies.
- Improved toolchain installations for Python, Node.js, Bun, Go, Rust and Ruby, shared between hooks.
- [Built-in](https://prek.j178.dev/builtin/) Rust-native implementation of some common hooks.

<!-- --8<-- [end:features] -->

## Table of contents

- [Installation](#installation)
- [Quick start](#quick-start)
- [Why prek?](#why-prek)
- [Who is using prek?](#who-is-using-prek)
- [Acknowledgements](#acknowledgements)

## Installation

<details>
<summary>Standalone installer</summary>

prek provides a standalone installer script to download and install the tool,

On Linux and macOS:

<!-- --8<-- [start: linux-standalone-install] -->

```bash
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/j178/prek/releases/download/v0.3.2/prek-installer.sh | sh
```

<!-- --8<-- [end: linux-standalone-install] -->

On Windows:

<!-- --8<-- [start: windows-standalone-install] -->

```powershell
powershell -ExecutionPolicy ByPass -c "irm https://github.com/j178/prek/releases/download/v0.3.2/prek-installer.ps1 | iex"
```

<!-- --8<-- [end: windows-standalone-install] -->

</details>

<details>
<summary>PyPI</summary>

<!-- --8<-- [start: pypi-install] -->

prek is published as Python binary wheel to PyPI, you can install it using `pip`, `uv` (recommended), or `pipx`:

```bash
# Using uv (recommended)
uv tool install prek

# Using uvx (install and run in one command)
uvx prek

# Adding prek to the project dev-dependencies
uv add --dev prek

# Using pip
pip install prek

# Using pipx
pipx install prek
```

<!-- --8<-- [end: pypi-install] -->

</details>

<details>
<summary>Homebrew</summary>

<!-- --8<-- [start: homebrew-install] -->

```bash
brew install prek
```

<!-- --8<-- [end: homebrew-install] -->

</details>

<details>
<summary>mise</summary>

<!-- --8<-- [start: mise-install] -->

To use prek with [mise](https://mise.jdx.dev) ([v2025.8.11](https://github.com/jdx/mise/releases/tag/v2025.8.11) or later):

```bash
mise use prek
```

<!-- --8<-- [end: mise-install] -->

</details>

<details>
<summary>Cargo binstall</summary>

<!-- --8<-- [start: cargo-binstall] -->

Install pre-compiled binaries from GitHub using [cargo-binstall](https://github.com/cargo-bins/cargo-binstall):

```bash
cargo binstall prek
```

<!-- --8<-- [end: cargo-binstall] -->

</details>

<details>
<summary>Cargo</summary>

<!-- --8<-- [start: cargo-install] -->

Build from source using Cargo (Rust 1.89+ is required):

```bash
cargo install --locked prek
```

<!-- --8<-- [end: cargo-install] -->

</details>

<details>
<summary>npmjs</summary>

<!-- --8<-- [start: npmjs-install] -->

prek is published as a [Node.js package](https://www.npmjs.com/package/@j178/prek)
and can be installed with any npm-compatible package manager:

```bash
# As a dev dependency
npm add -D @j178/prek
pnpm add -D @j178/prek
bun add -D @j178/prek

# Or install globally
npm install -g @j178/prek
pnpm add -g @j178/prek
bun install -g @j178/prek

# Or run directly without installing
npx @j178/prek --version
bunx @j178/prek --version
```

<!-- --8<-- [end: npmjs-install] -->

</details>

<details>
<summary>Nix</summary>

<!-- --8<-- [start: nix-install] -->

prek is available via [Nixpkgs](https://search.nixos.org/packages?channel=unstable&show=prek&query=prek).

```shell
# Choose what's appropriate for your use case.
# One-off in a shell:
nix-shell -p prek

# NixOS or non-NixOS without flakes:
nix-env -iA nixos.prek

# Non-NixOS with flakes:
nix profile install nixpkgs#prek
```

<!-- --8<-- [end: nix-install] -->

</details>

<details>
<summary>Conda</summary>

<!-- --8<-- [start: conda-forge-install] -->

prek is available as `prek` via [conda-forge](https://anaconda.org/conda-forge/prek).

```shell
conda install conda-forge::prek
```

<!-- --8<-- [end: conda-forge-install] -->

</details>

<details>
<summary>Scoop (Windows)</summary>

<!-- --8<-- [start: scoop-install] -->

prek is available via [Scoop](https://scoop.sh/#/apps?q=prek).

```powershell
scoop install main/prek
```

<!-- --8<-- [end: scoop-install] -->

</details>

<details>
<summary>MacPorts</summary>

<!-- --8<-- [start: macports-install] -->

prek is available via [MacPorts](https://ports.macports.org/port/prek/).

```bash
sudo port install prek
```

<!-- --8<-- [end: macports-install] -->

</details>

<details>
<summary>GitHub Releases</summary>

<!-- --8<-- [start: pre-built-binaries] -->

Pre-built binaries are available for download from the [GitHub releases](https://github.com/j178/prek/releases) page.

<!-- --8<-- [end: pre-built-binaries] -->

</details>

<details>
<summary>GitHub Actions</summary>

<!-- --8<-- [start: github-actions] -->

prek can be used in GitHub Actions via the [j178/prek-action](https://github.com/j178/prek-action) repository.

Example workflow:

```yaml
name: Prek checks
on: [push, pull_request]

jobs:
  prek:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
      - uses: j178/prek-action@v1
```

This action installs prek and runs `prek run --all-files` on your repository.

prek is also available via [`taiki-e/install-action`](https://github.com/taiki-e/install-action) for installing various tools.

<!-- --8<-- [end: github-actions] -->

</details>

<!-- --8<-- [start: self-update] -->

If installed via the standalone installer, prek can update itself to the latest version:

```bash
prek self update
```

<!-- --8<-- [end: self-update] -->

## Quick start

- **I already use pre-commit:** follow the short migration checklist in the [quickstart guide](https://prek.j178.dev/quickstart/#already-using-pre-commit) to swap in `prek` safely.
- **I'm new to pre-commit-style tools:** learn the basics—creating a config, running hooks, and installing git hooks—in the [beginner quickstart walkthrough](https://prek.j178.dev/quickstart/#new-to-pre-commit-style-workflows).

<!-- --8<-- [start: why] -->

## Why prek?

### prek is faster

- It is [multiple times faster](https://prek.j178.dev/benchmark/) than `pre-commit` and takes up half the disk space.
- It redesigned how hook environments and toolchains are managed, they are all shared between hooks, which reduces the disk space usage and speeds up the installation process.
- Repositories are cloned in parallel, and hooks are installed in parallel if their dependencies are disjoint.
- Hooks can run in parallel by priority (hooks with the same [`priority`](https://prek.j178.dev/configuration/#priority) may run concurrently), reducing end-to-end runtime.
- It uses [`uv`](https://github.com/astral-sh/uv) for creating Python virtualenvs and installing dependencies, which is known for its speed and efficiency.
- It implements some common hooks in Rust, [built in prek](https://prek.j178.dev/builtin/), which are faster than their Python counterparts.
- It supports `repo: builtin` for offline, zero-setup hooks, which is not available in `pre-commit`.

### prek provides a better user experience

- No need to install Python or any other runtime, just download a single binary.
- No hassle with your Python version or virtual environments, prek automatically installs the required Python version and creates a virtual environment for you.
- Built-in support for [workspaces](https://prek.j178.dev/workspace/) (or monorepos), each subproject can have its own `.pre-commit-config.yaml` file.
- [`prek run`](https://prek.j178.dev/cli/#prek-run) has some nifty improvements over `pre-commit run`, such as:
    - `prek run --directory <dir>` runs hooks for files in the specified directory, no need to use `git ls-files -- <dir> | xargs pre-commit run --files` anymore.
    - `prek run --last-commit` runs hooks for files changed in the last commit.
    - `prek run [HOOK] [HOOK]` selects and runs multiple hooks.
- [`prek list`](https://prek.j178.dev/cli/#prek-list) command lists all available hooks, their ids, and descriptions, providing a better overview of the configured hooks.
- [`prek auto-update`](https://prek.j178.dev/cli/#prek-auto-update) supports `--cooldown-days` to mitigate open source supply chain attacks.
- prek provides shell completions for `prek run <hook_id>` command, making it easier to run specific hooks without remembering their ids.

For more detailed improvements prek offers, take a look at [Difference from pre-commit](https://prek.j178.dev/diff/).

## Who is using prek?

prek is pretty new, but it is already being used or recommend by some projects and organizations:

- [apache/airflow](https://github.com/apache/airflow/issues/44995)
- [python/cpython](https://github.com/python/cpython/issues/143148)
- [pdm-project/pdm](https://github.com/pdm-project/pdm/pull/3593)
- [fastapi/fastapi](https://github.com/fastapi/fastapi/pull/14572)
- [fastapi/typer](https://github.com/fastapi/typer/pull/1453)
- [fastapi/asyncer](https://github.com/fastapi/asyncer/pull/437)
- [astral-sh/ruff](https://github.com/astral-sh/ruff/pull/22505)
- [astral-sh/ty](https://github.com/astral-sh/ty/pull/2469)
- [openclaw/openclaw](https://github.com/openclaw/openclaw/pull/1720)
- [home-assistant/core](https://github.com/home-assistant/core/pull/160427)
- [DetachHead/basedpyright](https://github.com/DetachHead/basedpyright/pull/1413)
- [OpenLineage/OpenLineage](https://github.com/OpenLineage/OpenLineage/pull/3965)
- [authlib/authlib](https://github.com/authlib/authlib/pull/804)
- [django/djangoproject.com](https://github.com/django/djangoproject.com/pull/2252)
- [Future-House/paper-qa](https://github.com/Future-House/paper-qa/pull/1098)
- [requests-cache/requests-cache](https://github.com/requests-cache/requests-cache/pull/1116)
- [Goldziher/kreuzberg](https://github.com/Goldziher/kreuzberg/pull/142)
- [python-attrs/attrs](https://github.com/python-attrs/attrs/commit/c95b177682e76a63478d29d040f9cb36a8d31915)
- [jlowin/fastmcp](https://github.com/jlowin/fastmcp/pull/2309)
- [apache/iceberg-python](https://github.com/apache/iceberg-python/pull/2533)
- [apache/lucene](https://github.com/apache/lucene/pull/15629)
- [jcrist/msgspec](https://github.com/jcrist/msgspec/pull/918)
- [python-humanize/humanize](https://github.com/python-humanize/humanize/pull/276)
- [MoonshotAI/kimi-cli](https://github.com/MoonshotAI/kimi-cli/pull/535)
- [simple-icons/simple-icons](https://github.com/simple-icons/simple-icons/pull/14245)
- [ast-grep/ast-grep](https://github.com/ast-grep/ast-grep.github.io/commit/e30818144b2967a7f9172c8cf2f4596bba219bf5)
- [commitizen-tools/commitizen](https://github.com/commitizen-tools/commitizen)
- [cocoindex-io/cocoindex](https://github.com/cocoindex-io/cocoindex/pull/1564)
- [cachix/devenv](https://github.com/cachix/devenv/pull/2304)
- [copper-project/copper-rs](https://github.com/copper-project/copper-rs/pull/783)

<!-- --8<-- [end: why] -->

## Acknowledgements

This project is heavily inspired by the original [pre-commit](https://pre-commit.com/) tool, and it wouldn't be possible without the hard work
of the maintainers and contributors of that project.

And a special thanks to the [Astral](https://github.com/astral-sh) team for their remarkable projects, particularly [uv](https://github.com/astral-sh/uv),
from which I've learned a lot on how to write efficient and idiomatic Rust code.

]]> Rust https://github.com/block/goose https://github.com/block/goose Sat, 07 Feb 2026 00:07:47 GMT block/goose

an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM

Language: Rust

Stars: 30,018

Forks: 2,714

Stars today: 54 stars today

README

<div align="center">

# goose

_a local, extensible, open source AI agent that automates engineering tasks_

<p align="center">
  <a href="https://opensource.org/licenses/Apache-2.0">
    <img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg">
  </a>
  <a href="https://discord.gg/goose-oss">
    <img src="https://img.shields.io/discord/1287729918100246654?logo=discord&logoColor=white&label=Join+Us&color=blueviolet" alt="Discord">
  </a>
  <a href="https://github.com/block/goose/actions/workflows/ci.yml">
     <img src="https://img.shields.io/github/actions/workflow/status/block/goose/ci.yml?branch=main" alt="CI">
  </a>
</p>
</div>

goose is your on-machine AI agent, capable of automating complex development tasks from start to finish. More than just code suggestions, goose can build entire projects from scratch, write and execute code, debug failures, orchestrate workflows, and interact with external APIs - _autonomously_.

Whether you're prototyping an idea, refining existing code, or managing intricate engineering pipelines, goose adapts to your workflow and executes tasks with precision.

Designed for maximum flexibility, goose works with any LLM and supports multi-model configuration to optimize performance and cost, seamlessly integrates with MCP servers, and is available as both a desktop app as well as CLI - making it the ultimate AI assistant for developers who want to move faster and focus on innovation.

[![Watch the video](https://github.com/user-attachments/assets/ddc71240-3928-41b5-8210-626dfb28af7a)](https://youtu.be/D-DpDunrbpo)

# Quick Links
- [Quickstart](https://block.github.io/goose/docs/quickstart)
- [Installation](https://block.github.io/goose/docs/getting-started/installation)
- [Tutorials](https://block.github.io/goose/docs/category/tutorials)
- [Documentation](https://block.github.io/goose/docs/category/getting-started)
- [Responsible AI-Assisted Coding Guide](https://github.com/block/goose/blob/main/HOWTOAI.md)
- [Governance](https://github.com/block/goose/blob/main/GOVERNANCE.md)

## Need Help?
- [Diagnostics & Reporting](https://block.github.io/goose/docs/troubleshooting/diagnostics-and-reporting)
- [Known Issues](https://block.github.io/goose/docs/troubleshooting/known-issues)

# a little goose humor 🦢

> Why did the developer choose goose as their AI agent?
> 
> Because it always helps them "migrate" their code to production! 🚀

# goose around with us  
- [Discord](https://discord.gg/goose-oss)
- [YouTube](https://www.youtube.com/@goose-oss)
- [LinkedIn](https://www.linkedin.com/company/goose-oss)
- [Twitter/X](https://x.com/goose_oss)
- [Bluesky](https://bsky.app/profile/opensource.block.xyz)
- [Nostr](https://njump.me/opensource@block.xyz)

]]> Rust https://github.com/ajeetdsouza/zoxide https://github.com/ajeetdsouza/zoxide Sat, 07 Feb 2026 00:07:46 GMT ajeetdsouza/zoxide

A smarter cd command. Supports all major shells.

Language: Rust

Stars: 33,200

Forks: 729

Stars today: 31 stars today

README

<!-- markdownlint-configure-file {
  "MD013": {
    "code_blocks": false,
    "tables": false
  },
  "MD033": false,
  "MD041": false
} -->

<div align="center">

<sup>Special thanks to:</sup>

<!-- markdownlint-disable-next-line MD013 -->
<div><a href="https://go.warp.dev/zoxide"><img alt="Sponsored by Warp" width="230" src="https://raw.githubusercontent.com/warpdotdev/brand-assets/refs/heads/main/Github/Sponsor/Warp-Github-LG-03.png" /></a></div>
<div><sup><b>Warp, built for coding with multiple AI agents.</b></sup></div>
<div><sup>Available for macOS, Linux, and Windows.</sup></div>
<div><sup>
  Visit
  <a href="https://go.warp.dev/zoxide"><u>warp.dev</u></a>
  to learn more.
</sup></div>

<hr />

# zoxide

[![crates.io][crates.io-badge]][crates.io]
[![Downloads][downloads-badge]][releases]
[![Built with Nix][builtwithnix-badge]][builtwithnix]

zoxide is a **smarter cd command**, inspired by z and autojump.

It remembers which directories you use most frequently, so you can "jump" to
them in just a few keystrokes.<br />
zoxide works on all major shells.

[Getting started](#getting-started) •
[Installation](#installation) •
[Configuration](#configuration) •
[Integrations](#third-party-integrations)

</div>

## Getting started

![Tutorial][tutorial]

```sh
z foo              # cd into highest ranked directory matching foo
z foo bar          # cd into highest ranked directory matching foo and bar
z foo /            # cd into a subdirectory starting with foo

z ~/foo            # z also works like a regular cd command
z foo/             # cd into relative path
z ..               # cd one level up
z -                # cd into previous directory

zi foo             # cd with interactive selection (using fzf)

z foo<SPACE><TAB>  # show interactive completions (zoxide v0.8.0+, bash 4.4+/fish/zsh only)
```

Read more about the matching algorithm [here][algorithm-matching].

## Installation

zoxide can be installed in 4 easy steps:

1. **Install binary**

   zoxide runs on most major platforms. If your platform isn't listed below,
   please [open an issue][issues].

   <details>
   <summary>Linux / WSL</summary>

   > The recommended way to install zoxide is via the install script:
   >
   > ```sh
   > curl -sSfL https://raw.githubusercontent.com/ajeetdsouza/zoxide/main/install.sh | sh
   > ```
   >
   > Or, you can use a package manager:
   >
   > | Distribution        | Repository                  | Instructions                                                                                          |
   > | ------------------- | --------------------------- | ----------------------------------------------------------------------------------------------------- |
   > | **_Any_**           | **[crates.io]**             | `cargo install zoxide --locked`                                                                       |
   > | _Any_               | [asdf]                      | `asdf plugin add zoxide https://github.com/nyrst/asdf-zoxide.git` <br /> `asdf install zoxide latest` |
   > | _Any_               | [conda-forge]               | `conda install -c conda-forge zoxide`                                                                 |
   > | _Any_               | [guix]                      | `guix install zoxide`                                                                                 |
   > | _Any_               | [Linuxbrew]                 | `brew install zoxide`                                                                                 |
   > | _Any_               | [nixpkgs]                   | `nix-env -iA nixpkgs.zoxide`                                                                          |
   > | Alpine Linux 3.13+  | [Alpine Linux Packages]     | `apk add zoxide`                                                                                      |
   > | Arch Linux          | [Arch Linux Extra]          | `pacman -S zoxide`                                                                                    |
   > | ~Debian~[^1]    | ~[Debian Packages]~         | ~`apt install zoxide`~                                                                                    |
   > | Devuan 4.0+         | [Devuan Packages]           | `apt install zoxide`                                                                                  |
   > | Exherbo Linux       | [Exherbo packages]          | `cave resolve -x repository/rust` <br /> `cave resolve -x zoxide`                                     |
   > | Fedora 32+          | [Fedora Packages]           | `dnf install zoxide`                                                                                  |
   > | Gentoo              | [Gentoo Packages]           | `emerge app-shells/zoxide`                                                                            |
   > | Manjaro             |                             | `pacman -S zoxide`                                                                                    |
   > | openSUSE Tumbleweed | [openSUSE Factory]          | `zypper install zoxide`                                                                               |
   > | ~Parrot OS~[^1]     |                             | ~`apt install zoxide`~                                                                                |
   > | ~Raspbian~[^1]  | ~[Raspbian Packages]~       | ~`apt install zoxide`~                                                                                    |
   > | Rhino Linux         | [Pacstall Packages]         | `pacstall -I zoxide-deb`                                                                              |
   > | Slackware 15.0+     | [SlackBuilds]               | [Instructions][slackbuilds-howto]                                                                     |
   > | Solus               | [Solus Packages]            | `eopkg install zoxide`                                                                                |
   > | ~Ubuntu~[^1]        | ~[Ubuntu Packages]~         | ~`apt install zoxide`~                                                                                |
   > | Void Linux          | [Void Linux Packages]       | `xbps-install -S zoxide`                                                                              |

   </details>

   <details>
   <summary>macOS</summary>

   > To install zoxide, use a package manager:
   >
   > | Repository      | Instructions                                                                                          |
   > | --------------- | ----------------------------------------------------------------------------------------------------- |
   > | **[crates.io]** | `cargo install zoxide --locked`                                                                       |
   > | **[Homebrew]**  | `brew install zoxide`                                                                                 |
   > | [asdf]          | `asdf plugin add zoxide https://github.com/nyrst/asdf-zoxide.git` <br /> `asdf install zoxide latest` |
   > | [conda-forge]   | `conda install -c conda-forge zoxide`                                                                 |
   > | [MacPorts]      | `port install zoxide`                                                                                 |
   > | [nixpkgs]       | `nix-env -iA nixpkgs.zoxide`                                                                          |
   >
   > Or, run this command in your terminal:
   >
   > ```sh
   > curl -sSfL https://raw.githubusercontent.com/ajeetdsouza/zoxide/main/install.sh | sh
   > ```

   </details>

   <details>
   <summary>Windows</summary>

   > zoxide works with PowerShell, as well as shells running in Cygwin, Git
   > Bash, and MSYS2.
   >
   > The recommended way to install zoxide is via `winget`:
   >
   > ```sh
   > winget install ajeetdsouza.zoxide
   > ```
   >
   > Or, you can use an alternative package manager:
   >
   > | Repository      | Instructions                          |
   > | --------------- | ------------------------------------- |
   > | **[crates.io]** | `cargo install zoxide --locked`       |
   > | [Chocolatey]    | `choco install zoxide`                |
   > | [conda-forge]   | `conda install -c conda-forge zoxide` |
   > | [Scoop]         | `scoop install zoxide`                |
   >
   > If you're using Cygwin, Git Bash, or MSYS2, you can also use the install script:
   >
   > ```sh
   > curl -sSfL https://raw.githubusercontent.com/ajeetdsouza/zoxide/main/install.sh | sh
   > ```

   </details>

   <details>
   <summary>BSD</summary>

   > To install zoxide, use a package manager:
   >
   > | Distribution  | Repository      | Instructions                    |
   > | ------------- | --------------- | ------------------------------- |
   > | **_Any_**     | **[crates.io]** | `cargo install zoxide --locked` |
   > | DragonFly BSD | [DPorts]        | `pkg install zoxide`            |
   > | FreeBSD       | [FreshPorts]    | `pkg install zoxide`            |
   > | NetBSD        | [pkgsrc]        | `pkgin install zoxide`          |
   >
   > Or, run this command in your terminal:
   >
   > ```sh
   > curl -sS https://raw.githubusercontent.com/ajeetdsouza/zoxide/main/install.sh | bash
   > ```

   </details>

   <details>
   <summary>Android</summary>

   > To install zoxide, use a package manager:
   >
   > | Repository | Instructions         |
   > | ---------- | -------------------- |
   > | [Termux]   | `pkg install zoxide` |
   >
   > Or, run this command in your terminal:
   >
   > ```sh
   > curl -sS https://raw.githubusercontent.com/ajeetdsouza/zoxide/main/install.sh | bash
   > ```

   </details>

2. **Setup zoxide on your shell**

   To start using zoxide, add it to your shell.

   <details>
   <summary>Bash</summary>

   > Add this to the <ins>**end**</ins> of your config file (usually `~/.bashrc`):
   >
   > ```sh
   > eval "$(zoxide init bash)"
   > ```

   </details>

   <details>
   <summary>Elvish</summary>

   > Add this to the <ins>**end**</ins> of your config file (usually `~/.elvish/rc.elv`):
   >
   > ```sh
   > eval (zoxide init elvish | slurp)
   > ```
   >
   > **Note**
   > zoxide only supports elvish v0.18.0 and above.

   </details>

   <details>
   <summary>Fish</summary>

   > Add this to the <ins>**end**</ins> of your config file (usually
   > `~/.config/fish/config.fish`):
   >
   > ```sh
   > zoxide init fish | source
   > ```

   </details>

   <details>
   <summary>Nushell</summary>

   > Add this to the <ins>**end**</ins> of your env file (find it by running `$nu.env-path`
   > in Nushell):
   >
   > ```sh
   > zoxide init nushell | save -f ~/.zoxide.nu
   > ```
   >
   > Now, add this to the <ins>**end**</ins> of your config file (find it by running
   > `$nu.config-path` in Nushell):
   >
   > ```sh
   > source ~/.zoxide.nu
   > ```
   >
   > **Note**
   > zoxide only supports Nushell v0.89.0+.

   </details>

   <details>
   <summary>PowerShell</summary>

   > Add this to the <ins>**end**</ins> of your config file (find it by running
   > `echo $profile` in PowerShell):
   >
   > ```powershell
   > Invoke-Expression (& { (zoxide init powershell | Out-String) })
   > ```

   </details>

   <details>
   <summary>Tcsh</summary>

   > Add this to the <ins>**end**</ins> of your config file (usually `~/.tcshrc`):
   >
   > ```sh
   > zoxide init tcsh > ~/.zoxide.tcsh
   > source ~/.zoxide.tcsh
   > ```

   </details>

   <details>
   <summary>Xonsh</summary>

   > Add this to the <ins>**end**</ins> of your config file (usually `~/.xonshrc`):
   >
   > ```python
   > execx($(zoxide init xonsh), 'exec', __xonsh__.ctx, filename='zoxide')
   > ```

   </details>

   <details>
   <summary>Zsh</summary>

   > Add this to the <ins>**end**</ins> of your config file (usually `~/.zshrc`):
   >
   > ```sh
   > eval "$(zoxide init zsh)"
   > ```
   >
   > For completions to work, the above line must be added _after_ `compinit` is
   > called. You may have to rebuild your completions cache by running
   > `rm ~/.zcompdump*; compinit`.

   </details>

   <details>
   <summary>Any POSIX shell</summary>

   > Add this to the <ins>**end**</ins> of your config file:
   >
   > ```sh
   > eval "$(zoxide init posix --hook prompt)"
   > ```

   </details>

3. **Install fzf** <sup>(optional)</sup>

   [fzf] is a command-line fuzzy finder, used by zoxide for completions /
   interactive selection. It can be installed from [here][fzf-installation].

   > **Note**
   > The minimum supported fzf version is v0.51.0.

4. **Import your data** <sup>(optional)</sup>

   If you currently use any of these plugins, you may want to import your data
   into zoxide:

   <details>
   <summary>autojump</summary>

   > Run this command in your terminal:
   >
   > ```sh
   > zoxide import --from=autojump "/path/to/autojump/db"
   > ```
   >
   > The path usually varies according to your system:
   >
   > | OS      | Path                                                                                 | Example                                                |
   > | ------- | ------------------------------------------------------------------------------------ | ------------------------------------------------------ |
   > | Linux   | `$XDG_DATA_HOME/autojump/autojump.txt` or `$HOME/.local/share/autojump/autojump.txt` | `/home/alice/.local/share/autojump/autojump.txt`       |
   > | macOS   | `$HOME/Library/autojump/autojump.txt`                                                | `/Users/Alice/Library/autojump/autojump.txt`           |
   > | Windows | `%APPDATA%\autojump\autojump.txt`                                                    | `C:\Users\Alice\AppData\Roaming\autojump\autojump.txt` |

   </details>

   <details>
   <summary>fasd, z, z.lua, zsh-z</summary>

   > Run this command in your terminal:
   >
   > ```sh
   > zoxide import --from=z "path/to/z/db"
   > ```
   >
   > The path usually varies according to your system:
   >
   > | Plugin           | Path                                                                                |
   > | ---------------- | ----------------------------------------------------------------------------------- |
   > | fasd             | `$_FASD_DATA` or `$HOME/.fasd`                                                      |
   > | z (bash/zsh)     | `$_Z_DATA` or `$HOME/.z`                                                            |
   > | z (fish)         | `$Z_DATA` or `$XDG_DATA_HOME/z/data` or `$HOME/.local/share/z/data`                 |
   > | z.lua (bash/zsh) | `$_ZL_DATA` or `$HOME/.zlua`                                                        |
   > | z.lua (fish)     | `$XDG_DATA_HOME/zlua/zlua.txt` or `$HOME/.local/share/zlua/zlua.txt` or `$_ZL_DATA` |
   > | zsh-z            | `$ZSHZ_DATA` or `$_Z_DATA` or `$HOME/.z`                                            |

   </details>

   <details>
   <summary>ZLocation</summary>

   > Run this command in PowerShell:
   >
   > ```powershell
   > $db = New-TemporaryFile
   > (Get-ZLocation).GetEnumerator() | ForEach-Object { Write-Output ($_.Name+'|'+$_.Value+'|0') } | Out-File $db
   > zoxide import --from=z $db
   > ```

   </details>

## Configuration

### Flags

When calling `zoxide init`, the following flags are available:

- `--cmd`
  - Changes the prefix of the `z` and `zi` commands.
  - `--cmd j` would change the commands to (`j`, `ji`).
  - `--cmd cd` would replace the `cd` command.
- `--hook <HOOK>`
  - Changes how often zoxide increments a directory's score:

    | Hook            | Description                       |
    | --------------- | --------------------------------- |
    | `none`          | Never                             |
    | `prompt`        | At every shell prompt             |
    | `pwd` (default) | Whenever the directory is changed |

- `--no-cmd`
  - Prevents zoxide from defining the `z` and `zi` commands.
  - These functions will still be available in your shell as `__zoxide_z` and
    `__zoxide_zi`, should you choose to redefine them.

### Environment variables

Environment variables[^2] can be used for configuration. They must be set before
`zoxide init` is called.

- `_ZO_DATA_DIR`
  - Specifies the directory in which the database is stored.
  - The default value varies across OSes:

    | OS          | Path                                     | Example                                    |
    | ----------- | ---------------------------------------- | ------------------------------------------ |
    | Linux / BSD | `$XDG_DATA_HOME` or `$HOME/.local/share` | `/home/alice/.local/share`                 |
    | macOS       | `$HOME/Library/Application Support`      | `/Users/Alice/Library/Application Support` |
    | Windows     | `%LOCALAPPDATA%`                         | `C:\Users\Alice\AppData\Local`             |

- `_ZO_ECHO`
  - When set to 1, `z` will print the matched directory before navigating to
    it.
- `_ZO_EXCLUDE_DIRS`
  - Excludes the specified directories from the database.
  - This is provided as a list of [globs][glob], separated by OS-specific
    characters:

    | OS                  | Separator | Example                 |
    | ------------------- | --------- | ----------------------- |
    | Linux / macOS / BSD | `:`       | `$HOME:$HOME/private/*` |
    | Windows             | `;`       | `$HOME;$HOME/private/*` |

  - By default, this is set to `"$HOME"`.
- `_ZO_FZF_OPTS`
  - Custom options to pass to [fzf] during interactive selection. See
    [`man fzf`][fzf-man] for the list of options.
- `_ZO_MAXAGE`
  - Configures the [aging algorithm][algorithm-aging], which limits the maximum
    number of entries in the database.
  - By default, this is set to 10000.
- `_ZO_RESOLVE_SYMLINKS`
  - When set to 1, `z` will resolve symlinks before adding directories to the
    database.

## Third-party integrations

| Application           | Description                                  | Plugin                     |
| --------------------- | -------------------------------------------- | -------------------------- |
| [aerc]                | Email client                                 | Natively supported         |
| [alfred]              | macOS launcher                               | [alfred-zoxide]            |
| [clink]               | Improved cmd.exe for Windows                 | [clink-zoxide]             |
| [emacs]               | Text editor                                  | [zoxide.el]                |
| [felix]               | File manager                                 | Natively supported         |
| [joshuto]             | File manager                                 | Natively supported         |
| [lf]                  | File manager                                 | See the [wiki][lf-wiki]    |
| [nnn]                 | File manager                                 | [nnn-autojump]             |
| [ranger]              | File manager                                 | [ranger-zoxide]            |
| [raycast]             | macOS launcher                               | [raycast-zoxide]           |
| [rfm]                 | File manager                                 | Natively supported         |
| [sesh]                | `tmux` session manager                       | Natively supported         |
| [telescope.nvim]      | Fuzzy finder for Neovim                      | [telescope-zoxide]         |
| [tmux-session-wizard] | `tmux` session manager                       | Natively supported         |
| [tmux-sessionx]       | `tmux` session manager                       | Natively supported         |
| [vim] / [neovim]      | Text editor                                  | [zoxide.vim]               |
| [xplr]                | File manager                                 | [zoxide.xplr]              |
| [xxh]                 | Transports shell configuration over SSH      | [xxh-plugin-prerun-zoxide] |
| [yazi]                | File manager                                 | Natively

... [README content truncated due to size. Visit the repository for the complete README] ...

]]> Rust https://github.com/gitbutlerapp/gitbutler https://github.com/gitbutlerapp/gitbutler Sat, 07 Feb 2026 00:07:45 GMT gitbutlerapp/gitbutler

The GitButler version control client, backed by Git, powered by Tauri/Rust/Svelte

Language: Rust

Stars: 17,698

Forks: 768

Stars today: 66 stars today

README

<div align="center">
  <img align="center" width="100%" src="./readme-preview.webp" />

  <br />
  <br />

  <p align="center" >
    Version Control tool built from the ground up for modern, AI-powered workflows.
    <br />
    <br />
    <a href="https://gitbutler.com">Website</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href="https://blog.gitbutler.com/">Blog</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href="https://docs.gitbutler.com/">Docs</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href="https://gitbutler.com/downloads">Downloads</a>
  </p>

[![TWEET][s1]][l1] [
![BLUESKY][s8]][l8 ] [![DISCORD][s2]][l2]

[![CI][s0]][l0] [![INSTA][s3]][l3] [![YOUTUBE][s5]][l5] [![DEEPWIKI][s7]][l7]

[s0]: https://github.com/gitbutlerapp/gitbutler/actions/workflows/push.yaml/badge.svg
[l0]: https://github.com/gitbutlerapp/gitbutler/actions/workflows/push.yaml
[s1]: https://img.shields.io/badge/Twitter-black?logo=x&logoColor=white
[l1]: https://twitter.com/intent/follow?screen_name=gitbutler
[s2]: https://img.shields.io/discord/1060193121130000425?label=Discord&color=5865F2
[l2]: https://discord.gg/MmFkmaJ42D
[s3]: https://img.shields.io/badge/Instagram-E4405F?logo=instagram&logoColor=white
[l3]: https://www.instagram.com/gitbutler/
[s5]: https://img.shields.io/youtube/channel/subscribers/UCEwkZIHGqsTGYvX8wgD0LoQ
[l5]: https://www.youtube.com/@gitbutlerapp
[s7]: https://deepwiki.com/badge.svg
[l7]: https://deepwiki.com/gitbutlerapp/gitbutler
[s8]: https://img.shields.io/badge/Bluesky-0285FF?logo=bluesky&logoColor=fff
[l8]: https://bsky.app/profile/gitbutler.com

</div>

<br/>

![Alt](https://repobeats.axiom.co/api/embed/fb23382bcf57c609832661874d3019a43555d6ae.svg 'Repobeats analytics for GitButler')

GitButler is a git client that lets you work on multiple branches at the same time.
It allows you to quickly organize file changes into separate branches while still having them applied to your working directory.
You can then push branches individually to your remote, or directly create pull requests.

In a nutshell, it's a more flexible version of `git add -p` and `git rebase -i`, allowing you to efficiently multitask across branches.

## How Does It Work?

GitButler keeps track of uncommitted changes in a layer on top of Git. Changes to files or parts of files can be grouped into what we call virtual branches. Whenever you are happy with the contents of a virtual branch, you can push it to a remote. GitButler makes sure that the state of other virtual branches is kept separate.

## How Do GB's Virtual Branches Differ From Git Branches?

The branches that we know and love in Git are separate universes, and switching between them is a full context switch. GitButler allows you to work with multiple branches in parallel in the same working directory. This effectively means having the content of multiple branches available at the same time.

GitButler is aware of changes before they are committed. This allows it to keep a record of which virtual branch each individual diff belongs to. Effectively, this means that you can separate out individual branches with their content at any time to push them to a remote or to unapply them from your working directory.

And finally, while in Git it is preferable that you create your desired branch ahead of time, using GitButler you can move changes between virtual branches at any point during development.

## Why GitButler?

We love Git. Our own [@schacon](https://github.com/schacon) has even published the [Pro Git](https://git-scm.com/book/en/v2) book. At the same time, Git's user interface hasn't been fundamentally changed for 15 years. While it was written for Linux kernel devs sending patches to each other over mailing lists, most developers today have different workflows and needs.

Instead of trying to fit the semantics of the Git CLI into a graphical interface, we are starting with the developer workflow and mapping it back to Git.

## Tech

GitButler is a [Tauri](https://tauri.app/)-based application. Its UI is written in [Svelte](https://svelte.dev/) using [TypeScript](https://www.typescriptlang.org) and its backend is written in [Rust](https://www.rust-lang.org/).

## Main Features

- **Virtual Branches**
  - Organize work on multiple branches simultaneously, rather than constantly switching branches
  - Automatically create new branches when needed
- **Easy Commit Management**
  - Undo, Amend and Squash commits by dragging and dropping
- **Undo Timeline**
  - Logs all operations and changes and allows you to easily undo or revert any operation
- **GitHub Integration**
  - Authenticate to GitHub to open Pull Requests, list branches and statuses and more
- **Easy SSH Key Management**
  - GitButler can generate an SSH key to upload to GitHub automatically
- **AI Tooling**
  - Automatically write commit messages based on your work in progress
  - Automatically create descriptive branch names
- **Commit Signing**
  - Easy commit signing with GPG or SSH

## Example Uses

### Fixing a Bug While Working on a Feature

> Say that while developing a feature, you encounter a bug that you wish to fix. It's often desirable that you ship the fix as a separate contribution (Pull request).

Using Git you can stash your changes and switch to another branch, where you can commit, and push your fix.

_With GitButler_ you simply assign your fix to a separate virtual branch, which you can individually push (or directly create a PR). An additional benefit is that you can retain the fix in your working directory while waiting for CI and/or code review.

### Trying Someone Else's Branch Together With My Work in Progress

> Say you want to test a branch from someone else for the purpose of code review.

Using Git trying out someone else's branch is a full context switch away from your own work.
_With GitButler_ you can apply and unapply (add / remove) any remote branch directly into your working directory.

## Documentation

You can find our end user documentation at: <https://docs.gitbutler.com>

## Bugs and Feature Requests

If you have a bug or feature request, feel free to open an [issue](https://github.com/gitbutlerapp/gitbutler/issues/new),
or [join our Discord server](https://discord.gg/MmFkmaJ42D).

## AI Commit Message Generation

Commit message generation is an opt-in feature. You can enable it while adding your repository for the first time or later in the project settings.

Currently, GitButler uses OpenAI's API for diff summarization, which means that if enabled, code diffs would be sent to OpenAI's servers.

Our goal is to make this feature more modular such that in the future you can modify the prompt as well as plug a different LLM endpoints (including local ones).

## Contributing

So you want to help out? Please check out the [CONTRIBUTING.md](CONTRIBUTING.md)
document.

If you want to skip right to getting the code to actually compile, take a look
at the [DEVELOPMENT.md](DEVELOPMENT.md) file.

### Contributors

<a href="https://github.com/gitbutlerapp/gitbutler/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=gitbutlerapp/gitbutler" />
</a>

]]> Rust https://github.com/cloud-hypervisor/cloud-hypervisor https://github.com/cloud-hypervisor/cloud-hypervisor Sat, 07 Feb 2026 00:07:44 GMT cloud-hypervisor/cloud-hypervisor

A Virtual Machine Monitor for modern Cloud workloads. Features include CPU, memory and device hotplug, support for running Windows and Linux guests, device offload with vhost-user and a minimal compact footprint. Written in Rust with a strong focus on security.

Language: Rust

Stars: 5,244

Forks: 580

Stars today: 5 stars today

README

- [1. What is Cloud Hypervisor?](#1-what-is-cloud-hypervisor)
  - [Objectives](#objectives)
    - [High Level](#high-level)
    - [Architectures](#architectures)
    - [Guest OS](#guest-os)
- [2. Getting Started](#2-getting-started)
  - [Host OS](#host-os)
  - [Use Pre-built Binaries](#use-pre-built-binaries)
  - [Packages](#packages)
  - [Building from Source](#building-from-source)
  - [Booting Linux](#booting-linux)
    - [Firmware Booting](#firmware-booting)
    - [Custom Kernel and Disk Image](#custom-kernel-and-disk-image)
      - [Building your Kernel](#building-your-kernel)
      - [Disk image](#disk-image)
      - [Booting the guest VM](#booting-the-guest-vm)
- [3. Status](#3-status)
  - [Hot Plug](#hot-plug)
  - [Device Model](#device-model)
  - [Roadmap](#roadmap)
- [4. Relationship with _Rust VMM_ Project](#4-relationship-with-rust-vmm-project)
  - [Differences with Firecracker and crosvm](#differences-with-firecracker-and-crosvm)
- [5. Community](#5-community)
  - [Contribute](#contribute)
  - [Slack](#slack)
  - [Mailing list](#mailing-list)
  - [Security issues](#security-issues)

# 1. What is Cloud Hypervisor?

Cloud Hypervisor is an open source Virtual Machine Monitor (VMM) that runs on
top of the [KVM](https://www.kernel.org/doc/Documentation/virtual/kvm/api.txt)
hypervisor and the Microsoft Hypervisor (MSHV).

The project focuses on running modern, _Cloud Workloads_, on specific, common,
hardware architectures. In this case _Cloud Workloads_ refers to those that are
run by customers inside a Cloud Service Provider. This means modern operating
systems with most I/O handled by
paravirtualised devices (e.g. _virtio_), no requirement for legacy devices, and
64-bit CPUs.

Cloud Hypervisor is implemented in [Rust](https://www.rust-lang.org/) and is
based on the [Rust VMM](https://github.com/rust-vmm) crates.

## Objectives

### High Level

- Runs on KVM or MSHV
- Minimal emulation
- Low latency
- Low memory footprint
- Low complexity
- High performance
- Small attack surface
- 64-bit support only
- CPU, memory, PCI hotplug
- Machine to machine migration

### Architectures

Cloud Hypervisor supports the `x86-64`, `AArch64` and `riscv64`
architectures, with functionality varying across these platforms. The
functionality differences between `x86-64` and `AArch64` are documented
in [#1125](https://github.com/cloud-hypervisor/cloud-hypervisor/issues/1125).
The `riscv64` architecture support is experimental and offers limited
functionality. For more details and instructions, please refer to [riscv
documentation](docs/riscv.md).

### Guest OS

Cloud Hypervisor supports `64-bit Linux` and Windows 10/Windows Server 2019.

# 2. Getting Started

The following sections describe how to build and run Cloud Hypervisor.

## Prerequisites for AArch64

- AArch64 servers (recommended) or development boards equipped with the GICv3
  interrupt controller.

## Host OS

For required KVM functionality and adequate performance the recommended host
kernel version is 5.13. The majority of the CI currently tests with kernel
version 5.15.

## Use Pre-built Binaries

The recommended approach to getting started with Cloud Hypervisor is by using a
pre-built binary. Binaries are available for the [latest
release](https://github.com/cloud-hypervisor/cloud-hypervisor/releases/latest).
Use `cloud-hypervisor-static` for `x86-64` or `cloud-hypervisor-static-aarch64`
for `AArch64` platform.

## Packages

For convenience, packages are also available targeting some popular Linux
distributions. This is thanks to the [Open Build
Service](https://build.opensuse.org). The [OBS
README](https://github.com/cloud-hypervisor/obs-packaging) explains how to
enable the repository in a supported Linux distribution and install Cloud Hypervisor
and accompanying packages. Please report any packaging issues in the
[obs-packaging](https://github.com/cloud-hypervisor/obs-packaging) repository.

## Building from Source

Please see the [instructions for building from source](docs/building.md) if you
do not wish to use the pre-built binaries.

## Booting Linux

Cloud Hypervisor supports direct kernel boot (the x86-64 kernel requires the kernel
built with PVH support or a bzImage) or booting via a firmware (either [Rust Hypervisor
Firmware](https://github.com/cloud-hypervisor/rust-hypervisor-firmware) or an
edk2 UEFI firmware called `CLOUDHV` / `CLOUDHV_EFI`.)

Binary builds of the firmware files are available for the latest release of
[Rust Hypervisor
Firmware](https://github.com/cloud-hypervisor/rust-hypervisor-firmware/releases/latest)
and [our edk2
repository](https://github.com/cloud-hypervisor/edk2/releases/latest)

The choice of firmware depends on your guest OS choice; some experimentation
may be required.

### Firmware Booting

Cloud Hypervisor supports booting disk images containing all needed components
to run cloud workloads, a.k.a. cloud images.

The following sample commands will download an Ubuntu Cloud image, converting
it into a format that Cloud Hypervisor can use and a firmware to boot the image
with.

```shell
$ wget https://cloud-images.ubuntu.com/focal/current/focal-server-cloudimg-amd64.img
$ qemu-img convert -p -f qcow2 -O raw focal-server-cloudimg-amd64.img focal-server-cloudimg-amd64.raw
$ wget https://github.com/cloud-hypervisor/rust-hypervisor-firmware/releases/download/0.4.2/hypervisor-fw
```

The Ubuntu cloud images do not ship with a default password so it necessary to
use a `cloud-init` disk image to customise the image on the first boot. A basic
`cloud-init` image is generated by this [script](scripts/create-cloud-init.sh).
This seeds the image with a default username/password of `cloud/cloud123`. It
is only necessary to add this disk image on the first boot. Script also assigns
default IP address using `test_data/cloud-init/ubuntu/local/network-config` details
with `--net "mac=12:34:56:78:90:ab,tap="` option. Then the matching mac address
interface will be enabled as per `network-config` details.

```shell
$ sudo setcap cap_net_admin+ep ./cloud-hypervisor
$ ./create-cloud-init.sh
$ ./cloud-hypervisor \
	--firmware ./hypervisor-fw \
	--disk path=focal-server-cloudimg-amd64.raw path=/tmp/ubuntu-cloudinit.img \
	--cpus boot=4 \
	--memory size=1024M \
	--net "tap=,mac=,ip=,mask="
```

If access to the firmware messages or interaction with the boot loader (e.g.
GRUB) is required then it necessary to switch to the serial console instead of
`virtio-console`.

```shell
$ ./cloud-hypervisor \
	--kernel ./hypervisor-fw \
	--disk path=focal-server-cloudimg-amd64.raw path=/tmp/ubuntu-cloudinit.img \
	--cpus boot=4 \
	--memory size=1024M \
	--net "tap=,mac=,ip=,mask=" \
	--serial tty \
	--console off
```

## Booting: `--firmware` vs `--kernel`

The following scenarios are supported by Cloud Hypervisor to bootstrap a VM, i.e.,
to load a payload/bootitem(s):

- Provide firmware
- Provide kernel \[+ cmdline\]\ [+ initrd\]

Please note that our Cloud Hypervisor firmware (`hypervisor-fw`) has a Xen PVH
boot entry, therefore it can also be booted via the `--kernel` parameter, as 
seen in some examples.

### Custom Kernel and Disk Image

#### Building your Kernel

Cloud Hypervisor also supports direct kernel boot. For x86-64, a `vmlinux` ELF kernel (compiled with PVH support) or a regular bzImage are supported. In order to support development there is a custom branch; however provided the required options are enabled any recent kernel will suffice.

To build the kernel:

```shell
# Clone the Cloud Hypervisor Linux branch
$ git clone --depth 1 https://github.com/cloud-hypervisor/linux.git -b ch-6.12.8 linux-cloud-hypervisor
$ pushd linux-cloud-hypervisor
$ make ch_defconfig
# Do native build of the x86-64 kernel
$ KCFLAGS="-Wa,-mx86-used-note=no" make bzImage -j `nproc`
# Do native build of the AArch64 kernel
$ make -j `nproc`
$ popd
```

For x86-64, the `vmlinux` kernel image will then be located at
`linux-cloud-hypervisor/arch/x86/boot/compressed/vmlinux.bin`.
For AArch64, the `Image` kernel image will then be located at
`linux-cloud-hypervisor/arch/arm64/boot/Image`.

#### Disk image

For the disk image the same Ubuntu image as before can be used. This contains
an `ext4` root filesystem.

```shell
$ wget https://cloud-images.ubuntu.com/focal/current/focal-server-cloudimg-amd64.img # x86-64
$ wget https://cloud-images.ubuntu.com/focal/current/focal-server-cloudimg-arm64.img # AArch64
$ qemu-img convert -p -f qcow2 -O raw focal-server-cloudimg-amd64.img focal-server-cloudimg-amd64.raw # x86-64
$ qemu-img convert -p -f qcow2 -O raw focal-server-cloudimg-arm64.img focal-server-cloudimg-arm64.raw # AArch64
```

#### Booting the guest VM

These sample commands boot the disk image using the custom kernel whilst also
supplying the desired kernel command line.

- x86-64

```shell
$ sudo setcap cap_net_admin+ep ./cloud-hypervisor
$ ./create-cloud-init.sh
$ ./cloud-hypervisor \
	--kernel ./linux-cloud-hypervisor/arch/x86/boot/compressed/vmlinux.bin \
	--disk path=focal-server-cloudimg-amd64.raw path=/tmp/ubuntu-cloudinit.img \
	--cmdline "console=hvc0 root=/dev/vda1 rw" \
	--cpus boot=4 \
	--memory size=1024M \
	--net "tap=,mac=,ip=,mask="
```

- AArch64

```shell
$ sudo setcap cap_net_admin+ep ./cloud-hypervisor
$ ./create-cloud-init.sh
$ ./cloud-hypervisor \
	--kernel ./linux-cloud-hypervisor/arch/arm64/boot/Image \
	--disk path=focal-server-cloudimg-arm64.raw path=/tmp/ubuntu-cloudinit.img \
	--cmdline "console=hvc0 root=/dev/vda1 rw" \
	--cpus boot=4 \
	--memory size=1024M \
	--net "tap=,mac=,ip=,mask="
```

If earlier kernel messages are required the serial console should be used instead of `virtio-console`.

- x86-64

```shell
$ ./cloud-hypervisor \
	--kernel ./linux-cloud-hypervisor/arch/x86/boot/compressed/vmlinux.bin \
	--console off \
	--serial tty \
	--disk path=focal-server-cloudimg-amd64.raw \
	--cmdline "console=ttyS0 root=/dev/vda1 rw" \
	--cpus boot=4 \
	--memory size=1024M \
	--net "tap=,mac=,ip=,mask="
```

- AArch64

```shell
$ ./cloud-hypervisor \
	--kernel ./linux-cloud-hypervisor/arch/arm64/boot/Image \
	--console off \
	--serial tty \
	--disk path=focal-server-cloudimg-arm64.raw \
	--cmdline "console=ttyAMA0 root=/dev/vda1 rw" \
	--cpus boot=4 \
	--memory size=1024M \
	--net "tap=,mac=,ip=,mask="
```

# 3. Status

Cloud Hypervisor is under active development. The following stability
guarantees are currently made:

* The API (including command line options) will not be removed or changed in a
  breaking way without a minimum of 2 major releases notice. Where possible
  warnings will be given about the use of deprecated functionality and the
  deprecations will be documented in the release notes.

* Point releases will be made between individual releases where there are
  substantial bug fixes or security issues that need to be fixed. These point
  releases will only include bug fixes.

Currently the following items are **not** guaranteed across updates:

* Snapshot/restore is not supported across different versions
* Live migration is not supported across different versions
* The following features are considered experimental and may change
  substantially between releases: TDX, vfio-user, vDPA.

Further details can be found in the [release documentation](docs/releases.md).

As of 2023-01-03, the following cloud images are supported:

- [Ubuntu Focal](https://cloud-images.ubuntu.com/focal/current/) (focal-server-cloudimg-{amd64,arm64}.img)
- [Ubuntu Jammy](https://cloud-images.ubuntu.com/jammy/current/) (jammy-server-cloudimg-{amd64,arm64}.img)
- [Ubuntu Noble](https://cloud-images.ubuntu.com/noble/current/) (noble-server-cloudimg-{amd64,arm64}.img)
- [Fedora 36](https://archives.fedoraproject.org/pub/archive/fedora/linux/releases/36/Cloud/) ([Fedora-Cloud-Base-36-1.5.x86_64.raw.xz](https://archives.fedoraproject.org/pub/archive/fedora/linux/releases/36/Cloud/x86_64/images/) / [Fedora-Cloud-Base-36-1.5.aarch64.raw.xz](https://archives.fedoraproject.org/pub/archive/fedora/linux/releases/36/Cloud/aarch64/images/))

Direct kernel boot to userspace should work with a rootfs from most
distributions although you may need to enable exotic filesystem types in the
reference kernel configuration (e.g. XFS or btrfs.)

## Hot Plug

Cloud Hypervisor supports hotplug of CPUs, passthrough devices (VFIO),
`virtio-{net,block,pmem,fs,vsock}` and memory resizing. This
[document](docs/hotplug.md) details how to add devices to a running VM.

## Device Model

Details of the device model can be found in this
[documentation](docs/device_model.md).

## Roadmap

The project roadmap is tracked through a [GitHub
project](https://github.com/orgs/cloud-hypervisor/projects/6).

# 4. Relationship with _Rust VMM_ Project

In order to satisfy the design goal of having a high-performance,
security-focused hypervisor the decision was made to use the
[Rust](https://www.rust-lang.org/) programming language. The language's strong
focus on memory and thread safety makes it an ideal candidate for implementing
VMMs.

Instead of implementing the VMM components from scratch, Cloud Hypervisor is
importing the [Rust VMM](https://github.com/rust-vmm) crates, and sharing code
and architecture together with other VMMs like e.g. Amazon's
[Firecracker](https://firecracker-microvm.github.io/) and Google's
[crosvm](https://chromium.googlesource.com/chromiumos/platform/crosvm/).

Cloud Hypervisor embraces the _Rust VMM_ project's goals, which is to be able
to share and re-use as many virtualization crates as possible.

## Differences with Firecracker and crosvm

A large part of the Cloud Hypervisor code is based on either the Firecracker or
the crosvm project's implementations. Both of these are VMMs written in Rust
with a focus on safety and security, like Cloud Hypervisor.

The goal of the Cloud Hypervisor project differs from the aforementioned
projects in that it aims to be a general purpose VMM for _Cloud Workloads_ and
not limited to container/serverless or client workloads.

The Cloud Hypervisor community thanks the communities of both the Firecracker
and crosvm projects for their excellent work.

# 5. Community

The Cloud Hypervisor project follows the governance, and community guidelines
described in the [Community](https://github.com/cloud-hypervisor/community)
repository.

## Contribute

The project strongly believes in building a global, diverse and collaborative
community around the Cloud Hypervisor project. Anyone who is interested in
[contributing](CONTRIBUTING.md) to the project is welcome to participate.

Contributing to a open source project like Cloud Hypervisor covers a lot more
than just sending code. Testing, documentation, pull request
reviews, bug reports, feature requests, project improvement suggestions, etc,
are all equal and welcome means of contribution. See the
[CONTRIBUTING](CONTRIBUTING.md) document for more details.

## Slack

Get an [invite to our Slack channel](https://join.slack.com/t/cloud-hypervisor/shared_invite/enQtNjY3MTE3MDkwNDQ4LWQ1MTA1ZDVmODkwMWQ1MTRhYzk4ZGNlN2UwNTI3ZmFlODU0OTcwOWZjMTkwZDExYWE3YjFmNzgzY2FmNDAyMjI),
 [join us on Slack](https://cloud-hypervisor.slack.com/), and [participate in our community activities](https://cloud-hypervisor.slack.com/archives/C04R5DUQVBN).

## Mailing list

Please report bugs using the [GitHub issue
tracker](https://github.com/cloud-hypervisor/cloud-hypervisor/issues) but for
broader community discussions you may use our [mailing
list](https://lists.cloudhypervisor.org/g/dev/).

## Security issues

Please contact the maintainers listed in the MAINTAINERS.md file with security issues.

]]> Rust https://github.com/lbjlaq/Antigravity-Manager https://github.com/lbjlaq/Antigravity-Manager Sat, 07 Feb 2026 00:07:43 GMT lbjlaq/Antigravity-Manager

Professional Antigravity Account Manager & Switcher. One-click seamless account switching for Antigravity Tools. Built with Tauri v2 + React (Rust).专业的 Antigravity 账号管理与切换工具。为 Antigravity 提供一键无缝账号切换功能。

Language: Rust

Stars: 21,686

Forks: 2,458

Stars today: 292 stars today

README

# Antigravity Tools 🚀
> 专业的 AI 账号管理与协议反代系统 (v4.1.7)
<div align="center">
  <img src="public/icon.png" alt="Antigravity Logo" width="120" height="120" style="border-radius: 24px; box-shadow: 0 10px 30px rgba(0,0,0,0.15);">

  <h3>您的个人高性能 AI 调度网关</h3>
  <p>不仅仅是账号管理，更是打破 API 调用壁垒的终极解决方案。</p>
  
  <p>
    <a href="https://github.com/lbjlaq/Antigravity-Manager">
      <img src="https://img.shields.io/badge/Version-4.1.7-blue?style=flat-square" alt="Version">
    </a>
    <img src="https://img.shields.io/badge/Tauri-v2-orange?style=flat-square" alt="Tauri">
    <img src="https://img.shields.io/badge/Backend-Rust-red?style=flat-square" alt="Rust">
    <img src="https://img.shields.io/badge/Frontend-React-61DAFB?style=flat-square" alt="React">
    <img src="https://img.shields.io/badge/License-CC--BY--NC--SA--4.0-lightgrey?style=flat-square" alt="License">
  </p>

  <p>
    <a href="#-核心功能">核心功能</a> • 
    <a href="#-界面导览">界面导览</a> • 
    <a href="#-技术架构">技术架构</a> • 
    <a href="#-安装指南">安装指南</a> • 
    <a href="#-快速接入">快速接入</a>
  </p>

  <p>
    <strong>简体中文</strong> | 
    <a href="./README_EN.md">English</a>
  </p>
</div>

---

**Antigravity Tools** 是一个专为开发者和 AI 爱好者设计的全功能桌面应用。它将多账号管理、协议转换和智能请求调度完美结合，为您提供一个稳定、极速且成本低廉的 **本地 AI 中转站**。

通过本应用，您可以将常见的 Web 端 Session (Google/Anthropic) 转化为标准化的 API 接口，消除不同厂商间的协议鸿沟。

## 💖 赞助商 (Sponsors)

| 赞助商 (Sponsor) | 简介 (Description) |
| :---: | :--- |
| <img src="docs/images/packycode_logo.png" width="200" alt="PackyCode Logo"> | 感谢 **PackyCode** 对本项目的赞助！PackyCode 是一家可靠高效的 API 中转服务商，提供 Claude Code、Codex、Gemini 等多种服务的中转。PackyCode 为本项目的用户提供了特别优惠：使用[此链接](https://www.packyapi.com/register?aff=Ctrler)注册，并在充值时输入 **“Ctrler”** 优惠码即可享受 **九折优惠**。 |
| <img src="docs/images/AICodeMirror.jpg" width="200" alt="AICodeMirror Logo"> | 感谢 AICodeMirror 赞助了本项目！AICodeMirror 提供 Claude Code / Codex / Gemini CLI 官方高稳定中转服务，支持企业级高并发、极速开票、7×24 专属技术支持。 Claude Code / Codex / Gemini 官方渠道低至 3.8 / 0.2 / 0.9 折，充值更有折上折！AICodeMirror 为 Antigravity-Manager 的用户提供了特别福利，通过[此链接](https://www.aicodemirror.com/register?invitecode=MV5XUM)注册的用户，可享受首充8折，企业客户最高可享 7.5 折！ |

### ☕ 支持项目 (Support)

如果您觉得本项目对您有所帮助，欢迎打赏作者！

<a href="https://www.buymeacoffee.com/Ctrler" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-green.png" alt="请我喝杯咖啡" style="height: 60px !important; width: 217px !important;"></a>

| 支付宝 (Alipay) | 微信支付 (WeChat) | Buy Me a Coffee |
| :---: | :---: | :---: |
| ![Alipay](./docs/images/donate_alipay.png) | ![WeChat](./docs/images/donate_wechat.png) | ![Coffee](./docs/images/donate_coffee.png) |

## 🌟 深度功能解析 (Detailed Features)

### 1. 🎛️ 智能账号仪表盘 (Smart Dashboard)
*   **全局实时监控**: 一眼洞察所有账号的健康状况，包括 Gemini Pro、Gemini Flash、Claude 以及 Gemini 绘图的 **平均剩余配额**。
*   **最佳账号推荐 (Smart Recommendation)**: 系统会根据当前所有账号的配额冗余度，实时算法筛选并推荐“最佳账号”，支持 **一键切换**。
*   **活跃账号快照**: 直观显示当前活跃账号的具体配额百分比及最后同步时间。

### 2. 🔐 强大的账号管家 (Account Management)
*   **OAuth 2.0 授权（自动/手动）**: 添加账号时会提前生成可复制的授权链接，支持在任意浏览器完成授权；回调成功后应用会自动完成并保存（必要时可点击“我已授权，继续”手动收尾）。
*   **多维度导入**: 支持单条 Token 录入、JSON 批量导入（如来自其他工具的备份），以及从 V1 旧版本数据库自动热迁移。
*   **网关级视图**: 支持“列表”与“网格”双视图切换。提供 403 封禁检测，自动标注并跳过权限异常的账号。

### 3. 🔌 协议转换与中继 (API Proxy)
*   **全协议适配 (Multi-Sink)**:
    *   **OpenAI 格式**: 提供 `/v1/chat/completions` 端点，兼容 99% 的现有 AI 应用。
    *   **Anthropic 格式**: 提供原生 `/v1/messages` 接口，支持 **Claude Code CLI** 的全功能（如思思维链、系统提示词）。
    *   **Gemini 格式**: 支持 Google 官方 SDK 直接调用。
*   **智能状态自愈**: 当请求遇到 `429 (Too Many Requests)` 或 `401 (Expire)` 时，后端会毫秒级触发 **自动重试与静默轮换**，确保业务不中断。

### 4. 🔀 模型路由中心 (Model Router)
*   **系列化映射**: 您可以将复杂的原始模型 ID 归类到“规格家族”（如将所有 GPT-4 请求统一路由到 `gemini-3-pro-high`）。
*   **专家级重定向**: 支持自定义正则表达式级模型映射，精准控制每一个请求的落地模型。
*   **智能分级路由 (Tiered Routing)**: [新] 系统根据账号类型（Ultra/Pro/Free）和配额重置频率自动优先级排序，优先消耗高速重置账号，确保高频调用下的服务稳定性。
*   **后台任务静默降级**: [新] 自动识别 Claude CLI 等工具生成的后台请求（如标题生成），智能重定向至 Flash 模型，保护高级模型配额不被浪费。

### 5. 🎨 多模态与 Imagen 3 支持
*   **高级画质控制**: 支持通过 OpenAI `size` (如 `1024x1024`, `16:9`) 参数自动映射到 Imagen 3 的相应规格。
*   **超强 Body 支持**: 后端支持高达 **100MB** (可配置) 的 Payload，处理 4K 高清图识别绰绰有余。

## 📸 界面导览 (GUI Overview)

| | |
| :---: | :---: |
| ![仪表盘 - 全局配额监控与一键切换](docs/images/dashboard-light.png) <br> 仪表盘 | ![账号列表 - 高密度配额展示与 403 智能标注](docs/images/accounts-light.png) <br> 账号列表 |
| ![关于页面 - 关于 Antigravity Tools](docs/images/about-dark.png) <br> 关于页面 | ![API 反代 - 服务控制](docs/images/v3/proxy-settings.png) <br> API 反代 |
| ![系统设置 - 通用配置](docs/images/settings-dark.png) <br> 系统设置 | |

### 💡 使用案例 (Usage Examples)

| | |
| :---: | :---: |
| ![Claude Code 联网搜索 - 结构化来源与引文显示](docs/images/usage/claude-code-search.png) <br> Claude Code 联网搜索 | ![Cherry Studio 深度集成 - 原生回显搜索引文与来源链接](docs/images/usage/cherry-studio-citations.png) <br> Cherry Studio 深度集成 |
| ![Imagen 3 高级绘图 - 完美还原 Prompt 意境与细节](docs/images/usage/image-gen-nebula.png) <br> Imagen 3 高级绘图 | ![Kilo Code 接入 - 多账号极速轮换与模型穿透](docs/images/usage/kilo-code-integration.png) <br> Kilo Code 接入 |

## 🏗️ 技术架构 (Architecture)

```mermaid
graph TD
    Client([外部应用: Claude Code/NextChat]) -->|OpenAI/Anthropic| Gateway[Antigravity Axum Server]
    Gateway --> Middleware[中间件: 鉴权/限流/日志]
    Middleware --> Router[Model Router: ID 映射]
    Router --> Dispatcher[账号分发器: 轮询/权重]
    Dispatcher --> Mapper[协议转换器: Request Mapper]
    Mapper --> Upstream[上游请求: Google/Anthropic API]
    Upstream --> ResponseMapper[响应转换器: Response Mapper]
    ResponseMapper --> Client
```

##  安装指南 (Installation)

### 选项 A: 终端安装 (macOS & Linux 推荐)

#### macOS 
如果您已安装 [Homebrew](https://brew.sh/)，可以通过以下命令快速安装：

```bash
# 1. 订阅本仓库的 Tap
brew tap lbjlaq/antigravity-manager https://github.com/lbjlaq/Antigravity-Manager

# 2. 安装应用
brew install --cask antigravity-tools
```
> **提示**: 如果遇到权限问题，建议添加 `--no-quarantine` 参数。

#### Arch Linux
您可以选择通过一键安装脚本或 Homebrew 进行安装：

**方式 1：一键安装脚本 (推荐)**
```bash
curl -sSL https://raw.githubusercontent.com/lbjlaq/Antigravity-Manager/main/deploy/arch/install.sh | bash
```

**方式 2：通过 Homebrew** (如果您已安装 [Linuxbrew](https://sh.brew.sh/))
```bash
brew tap lbjlaq/antigravity-manager https://github.com/lbjlaq/Antigravity-Manager
brew install --cask antigravity-tools
```

#### 其他 Linux 发行版
安装后会自动将 AppImage 添加到二进制路径并配置可执行权限。

### 选项 B: 手动下载
前往 [GitHub Releases](https://github.com/lbjlaq/Antigravity-Manager/releases) 下载对应系统的包：
*   **macOS**: `.dmg` (支持 Apple Silicon & Intel)
*   **Windows**: `.msi` 或 便携版 `.zip`
*   **Linux**: `.deb` 或 `AppImage`

### 选项 C: Docker 部署 (推荐用于 NAS/服务器)
如果您希望在容器化环境中运行，我们提供了原生的 Docker 镜像。该镜像内置了对 v4.0.2 原生 Headless 架构的支持，可自动托管前端静态资源，并通过浏览器直接进行管理。

```bash
# 方式 1: 直接运行 (推荐)
# - API_KEY: 必填。用于所有协议的 AI 请求鉴定。
# - WEB_PASSWORD: 可选。用于管理后台登录。若不设置则默认使用 API_KEY。
docker run -d --name antigravity-manager \
  -p 8045:8045 \
  -e API_KEY=sk-your-api-key \
  -e WEB_PASSWORD=your-login-password \
  -e ABV_MAX_BODY_SIZE=104857600 \
  -v ~/.antigravity_tools:/root/.antigravity_tools \
  lbjlaq/antigravity-manager:latest

# 忘记密钥？执行 docker logs antigravity-manager 或 grep -E '"api_key"|"admin_password"' ~/.antigravity_tools/gui_config.json

#### 🔐 鉴权逻辑说明
*   **场景 A：仅设置了 `API_KEY`**
    - **Web 登录**：使用 `API_KEY` 进入后台。
    - **API 调用**：使用 `API_KEY` 进行 AI 请求鉴权。
*   **场景 B：同时设置了 `API_KEY` 和 `WEB_PASSWORD` (推荐)**
    - **Web 登录**：**必须**使用 `WEB_PASSWORD`，使用 API Key 将被拒绝（更安全）。
    - **API 调用**：统一使用 `API_KEY`。这样您可以将 API Key 分发给成员，而保留密码仅供管理员使用。

#### 🆙 旧版本升级指引
如果您是从 v4.0.1 及更早版本升级，系统默认未设置 `WEB_PASSWORD`。您可以通过以下任一方式设置：
1.  **Web UI 界面 (推荐)**：使用原有 `API_KEY` 登录后，在 **API 反代设置** 页面手动设置并保存。新密码将持久化存储在 `gui_config.json` 中。
2.  **环境变量 (Docker)**：在启动容器时增加 `-e WEB_PASSWORD=您的新密码`。**注意：环境变量具有最高优先级，将覆盖 UI 中的任何修改。**
3.  **配置文件 (持久化)**：直接修改 `~/.antigravity_tools/gui_config.json`，在 `proxy` 对象中修改或添加 `"admin_password": "您的新密码"` 字段。
    - *注：`WEB_PASSWORD` 是环境变量名，`admin_password` 是配置文件中的 JSON 键名。*

> [!TIP]
> **密码优先级逻辑 (Priority)**:
> - **第一优先级 (环境变量)**: `ABV_WEB_PASSWORD` 或 `WEB_PASSWORD`。只要设置了环境变量，系统将始终使用它。
> - **第二优先级 (配置文件)**: `gui_config.json` 中的 `admin_password` 字段。UI 的“保存”操作会更新此值。
> - **保底回退 (向后兼容)**: 若上述均未设置，则回退使用 `API_KEY` 作为登录密码。

# 方式 2: 使用 Docker Compose
# 1. 进入项目的 docker 目录
cd docker
# 2. 启动服务
docker compose up -d
```
> **访问地址**: `http://localhost:8045` (管理后台) | `http://localhost:8045/v1` (API Base)
> **系统要求**:
> - **内存**: 建议 **1GB** (最小 256MB)。
> - **持久化**: 需挂载 `/root/.antigravity_tools` 以保存数据。
> - **架构**: 支持 x86_64 和 ARM64。
> **详情见**: [Docker 部署指南 (docker)](./docker/README.md)

---

Copyright © 2024-2026 [lbjlaq](https://github.com/lbjlaq)

### 🛠️ 常见问题排查 (Troubleshooting)

#### macOS 提示“应用已损坏，无法打开”？
由于 macOS 的安全机制，非 App Store 下载的应用可能会触发此提示。您可以按照以下步骤快速修复：

1.  **命令行修复** (推荐):
    打开终端，执行以下命令：
    ```bash
    sudo xattr -rd com.apple.quarantine "/Applications/Antigravity Tools.app"
    ```
2.  **Homebrew 安装技巧**:
    如果您使用 brew 安装，可以添加 `--no-quarantine` 参数来规避此问题：
    ```bash
    brew install --cask --no-quarantine antigravity-tools
    ```

## 🔌 快速接入示例

### 🔐 OAuth 授权流程（添加账号）
1. 打开“Accounts / 账号” → “添加账号” → “OAuth”。
2. 弹窗会在点击按钮前预生成授权链接；点击链接即可复制到系统剪贴板，然后用你希望的浏览器打开并完成授权。
3. 授权完成后浏览器会打开本地回调页并显示“✅ 授权成功!”。
4. 应用会自动继续完成授权并保存账号；如未自动完成，可点击“我已授权，继续”手动完成。

> 提示：授权链接包含一次性回调端口，请始终使用弹窗里生成的最新链接；如果授权时应用未运行或弹窗已关闭，浏览器可能会提示 `localhost refused connection`。

### 如何接入 Claude Code CLI?
1.  启动 Antigravity，并在“API 反代”页面开启服务。
2.  在终端执行：
```bash
export ANTHROPIC_API_KEY="sk-antigravity"
export ANTHROPIC_BASE_URL="http://127.0.0.1:8045"
claude
```

### 如何接入 OpenCode?
1.  进入 **API 反代**页面 → **外部 Providers** → 点击 **OpenCode Sync** 卡片。
2.  点击 **Sync** 按钮，将自动生成 `~/.config/opencode/opencode.json` 配置文件（包含代理 baseURL 与 apiKey，支持 Anthropic/Google 双 Provider）。
3.  可选：勾选 **Sync accounts** 可同时导出 `antigravity-accounts.json` 账号列表，供 OpenCode 插件直接导入使用。
4.  Windows 用户路径为 `C:\Users\<用户名>\.config\opencode\`（与 `~/.config/opencode` 规则一致）。
5.  如需回滚，可点击 **Restore** 按钮从备份恢复之前的配置。

### 如何接入 Kilo Code?
1.  **协议选择**: 建议优先使用 **Gemini 协议**。
2.  **Base URL**: 填写 `http://127.0.0.1:8045`。
3.  **注意**: 
    - **OpenAI 协议限制**: Kilo Code 在使用 OpenAI 模式时，其请求路径会叠加产生 `/v1/chat/completions/responses` 这种非标准路径，导致 Antigravity 返回 404。因此请务必填入 Base URL 后选择 Gemini 模式。
    - **模型映射**: Kilo Code 中的模型名称可能与 Antigravity 默认设置不一致，如遇到无法连接，请在“模型映射”页面设置自定义映射，并查看**日志文件**进行调试。

### 如何在 Python 中使用?
```python
import openai

client = openai.OpenAI(
    api_key="sk-antigravity",
    base_url="http://127.0.0.1:8045/v1"
)

response = client.chat.completions.create(
    model="gemini-3-flash",
    messages=[{"role": "user", "content": "你好，请自我介绍"}]
)
print(response.choices[0].message.content)
```

### 如何使用图片生成 (Imagen 3)?

#### 方式一：OpenAI Images API (推荐)
```python
import openai

client = openai.OpenAI(
    api_key="sk-antigravity",
    base_url="http://127.0.0.1:8045/v1"
)

# 生成图片
response = client.images.generate(
    model="gemini-3-pro-image",
    prompt="一座未来主义风格的城市，赛博朋克，霓虹灯",
    size="1920x1080",      # 支持任意 WIDTHxHEIGHT 格式，自动计算宽高比
    quality="hd",          # "standard" | "hd" | "medium"
    n=1,
    response_format="b64_json"
)

# 保存图片
import base64
image_data = base64.b64decode(response.data[0].b64_json)
with open("output.png", "wb") as f:
    f.write(image_data)
```

**支持的参数**：
- **`size`**: 任意 `WIDTHxHEIGHT` 格式（如 `1280x720`, `1024x1024`, `1920x1080`），自动计算并映射到标准宽高比（21:9, 16:9, 9:16, 4:3, 3:4, 1:1）
- **`quality`**: 
  - `"hd"` → 4K 分辨率（高质量）
  - `"medium"` → 2K 分辨率（中等质量）
  - `"standard"` → 默认分辨率（标准质量）
- **`n`**: 生成图片数量（1-10）
- **`response_format`**: `"b64_json"` 或 `"url"`（Data URI）

#### 方式二：Chat API + 参数设置 (✨ 新增)

**所有协议**（OpenAI、Claude）的 Chat API 现在都支持直接传递 `size` 和 `quality` 参数：

```python
# OpenAI Chat API
response = client.chat.completions.create(
    model="gemini-3-pro-image",
    size="1920x1080",      # ✅ 支持任意 WIDTHxHEIGHT 格式
    quality="hd",          # ✅ "standard" | "hd" | "medium"
    messages=[{"role": "user", "content": "一座未来主义风格的城市"}]
)
```

```bash
# Claude Messages API
curl -X POST http://127.0.0.1:8045/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: sk-antigravity" \
  -d '{
    "model": "gemini-3-pro-image",
    "size": "1280x720",
    "quality": "hd",
    "messages": [{"role": "user", "content": "一只可爱的猫咪"}]
  }'
```

**参数优先级**: 请求体参数 > 模型后缀

#### 方式三：Chat 接口 + 模型后缀
```python
response = client.chat.completions.create(
    model="gemini-3-pro-image-16-9-4k",  # 格式：gemini-3-pro-image-[比例]-[质量]
    messages=[{"role": "user", "content": "一座未来主义风格的城市"}]
)
```

**模型后缀说明**：
- **宽高比**: `-16-9`, `-9-16`, `-4-3`, `-3-4`, `-21-9`, `-1-1`
- **质量**: `-4k` (4K), `-2k` (2K), 不加后缀（标准）
- **示例**: `gemini-3-pro-image-16-9-4k` → 16:9 比例 + 4K 分辨率

#### 方式四：Cherry Studio 等客户端设置
在支持 OpenAI 协议的客户端（如 Cherry Studio）中，可以通过**模型设置**页面配置图片生成参数：

1. **进入模型设置**：选择 `gemini-3-pro-image` 模型
2. **配置参数**：
   - **Size (尺寸)**: 输入任意 `WIDTHxHEIGHT` 格式（如 `1920x1080`, `1024x1024`）
   - **Quality (质量)**: 选择 `standard` / `hd` / `medium`
   - **Number (数量)**: 设置生成图片数量（1-10）
3. **发送请求**：直接在对话框中输入图片描述即可

**参数映射规则**：
- `size: "1920x1080"` → 自动计算为 `16:9` 宽高比
- `quality: "hd"` → 映射为 `4K` 分辨率
- `quality: "medium"` → 映射为 `2K` 分辨率


## 📝 开发者与社区

*   **版本演进 (Changelog)**:
    *   **v4.1.7 (2026-02-06)**:
        -   **[核心修复] 修复图像生成 API (429/500/503) 自动切换账号问题 (Issue #1622)**:
            -   **自动重试**: 为 `images/generations` 和 `images/edits` 引入了与 Chat API 一致的自动重试与账号轮换机制。
            -   **体验一致性**: 确保在某个账号配额耗尽或服务不可用时，请求能自动故障转移到下一个可用账号，不再直接失败。
        -   **[核心功能] 新增账户自定义标签支持 (PR #1620)**:
            -   **标签管理**: 支持为每个账户设置个性化标签，方便在多账户环境下快速识别。
            -   **交互优化**: 账户列表和卡片视图均支持直接查看和内联编辑标签。
            -   **多语言支持**: 完整适配中、英双语显示。
        -   **[核心修复] 修复数据库为空时 `get_stats` 返回 NULL 导致崩溃的问题 (PR #1578)**:
            -   **NULL 值处理**: 在 SQL 查询中使用 `COALESCE(SUM(...), 0)` 确保在没有日志记录时依然返回数值，解决了 `rusqlite` 无法将 `NULL` 转换为 `u64` 的问题。
            -   **性能保留**: 保留了本地分支中通过单次查询获取多项统计数据的性能优化逻辑。

        -   **[核心修复] Claude 403 错误处理与账号轮换优化 (PR #1616)**:
            -   **403 状态映射**: 将 403 (Forbidden) 错误映射为 503 (Service Unavailable)，防止客户端（如 Claude Code）因检测到 403 而自动登出。
            -   **自动禁用逻辑**: 检测到 403 错误时自动将账号标记为 `is_forbidden` 并从活跃池中移除，避免该账号在接下来的请求中被继续选中。
            -   **临时风控识别**: 识别 `VALIDATION_REQUIRED` 错误，并对相关账号执行 10 分钟的临时阻断。
            -   **轮换稳定性**: 修复了在账号额度耗尽 (QUOTA_EXHAUSTED) 时的过早返回问题，确保系统能正确尝试轮换到下一个可用账号。
        -   **[核心功能] OpenCode CLI 配置同步集成 (PR #1614)**:
            -   **一键同步**: 自动生成 `~/.config/opencode/opencode.json`，支持 Anthropic 和 Google 双 Provider 自动配置。
            -   **账号导出**: 可选同步账号列表至 `antigravity-accounts.json`，供 OpenCode 插件直接导入。
            -   **备份与还原**: 同步前自动备份原有配置，支持一键还原。
            -   **跨平台支持**: 统一适配 Windows、macOS 和 Linux 环境。
            -   **体验优化**: 修复了 RPC 参数包装问题，补全了多语言翻译，并优化了配置文件不存在时的视图状态。
        -   **[核心功能] 允许隐藏未使用的菜单项 (PR #1610)**:
            -   **可见性控制**: 在设置页面新增“菜单项显示设置”，允许用户自定义侧边栏显示的导航项。
            -   **界面美化**: 为极简用户提供更清爽的界面，隐藏不常用的功能入口。

        -   **[核心修复] Gemini 原生协议图像生成完全修复 (Issue #1573, #1625)**:
            -   **400 错误修复**: 修复了 Gemini 原生协议生成图片时，因请求体 `contents` 数组缺失 `role: "user"` 字段导致的 `INVALID_ARGUMENT` 错误。
            -   **参数透传支持**: 确保 `generationConfig.imageConfig` (如 `aspectRatio`, `imageSize`) 能正确透传给上游，不再被错误过滤。
            -   **错误码优化**: 优化了图像生成服务的错误映射，确保 429/503 等状态码能正确触发客户端的重试机制。
        -   **[核心增强] 自定义映射支持手动输入任意模型 ID**:
            -   **灵活输入**: 在自定义映射的目标模型选择器中新增手动输入功能，用户现在可以在下拉菜单底部直接输入任意模型 ID。
            -   **未发布模型体验**: 支持体验 Antigravity 尚未正式发布的模型，例如 `claude-opus-4-6`。用户可以通过自定义映射将请求路由到这些实验性模型。
            -   **重要提示**: 并非所有账号都支持调用未发布的模型。如果您的账号无权访问某个模型，请求可能会返回错误。建议先在少量请求中测试，确认账号权限后再大规模使用。
            -   **快捷操作**: 支持 Enter 键快速提交自定义模型 ID，提升输入效率。
    *   **v4.1.6 (2026-02-06)**:
        -   **[核心修复] 深度重构 Claude/Gemini 思考模型中断与工具循环自愈逻辑 (#1575)**:
            -   **思考异常恢复**: 引入了 `thinking_recovery` 机制。当检测到历史消息中包含陈旧思考块或陷入状态循环时，自动进行剥离与引导，提升了在复杂工具调用场景下的稳定性。
            -   **彻底解决签名绑定错误**: 修正了误将缓存签名注入客户端自定义思考内容的逻辑。由于签名与文本强绑定，此举彻底解决了会话中断或重置后常见的 `Invalid signature` (HTTP 400) 报错。
            -   **会话级完全隔离**: 删除了全局签名单例，确保所有思维签名严格在 Session 级别隔离，彻底杜绝了多账号、多会话并发时的签名污染。
        -   **[修复] 彻底解决 Gemini 系列由于 `thinking_budget` 越界导致的 HTTP 400 错误 (#1592, #1602)**:
            -   **全协议路径硬截断**: 修复了 OpenAI 和 Claude 协议映射器在「自定义模式」下缺失限额保护的问题。现在无论选择何种模式（自动/自定义/透传），只要目标模型为 Gemini，后端都会强制执行 24576 的物理上限保护。
            -   **自动适配与前端同步**: 重构了协议转换逻辑，使其基于最终映射的模型型号进行动态限额；同步更新了设置界面的提示文案，明确了 Gemini 协议的物理限制。
        -   **[核心修复] Web Mode 登录验证修复 & 登出按钮 (PR #1603)**:
            -   **登录验证**: 修复了 Web 模式下登录验证逻辑的异常，确保用户身份验证的稳定性。
            -   **登出功能**: 在界面中新增/修复了登出按钮，完善了 Web 模式下的账户管理闭环。
    *   **v4.1.5 (2026-02-05)**:
        -   **[安全修复] 前端 API Key 存储迁移 (LocalStorage -> SessionStorage)**:
            -   **存储机制升级**: 将 Admin API Key 的存储位置从持久化的 `localStorage` 迁移至会话级的 `sessionStorage`，显著降低了在公共设备上的安全风险。
            -   **自动无感迁移**: 实现了自动检测与迁移逻辑。系统会识别旧的 `localStorage` 密钥，将其自动转移到 `sessionStorage` 并彻底清除旧数据，确保现有用户无缝过渡且消除安全隐患。
        -   **[核心修复] 修复 Docker 环境下添加账号失败问题 (Issue #1583)**:
            -   **账号上下文修复**: 修复了在添加新账号时 `account_id` 为 `None` 导致代理选择异常的问题。现在系统会为新账号生成临时 UUID,确保所有 OAuth 请求都有明确的账号上下文。
            -   **日志增强**: 优化了 `refresh_access_token` 和 `get_effective_client` 的日志记录,提供更详细的代理选择信息,帮助诊断 Docker 环境下的网络问题。
            -   **影响范围**: 修复了 Docker 部署环境下通过 Refresh Token 添加账号时可能出现的长时间挂起或失败问题。
        -   **[核心修复] Web Mode 兼容性修复 & 403 账号轮换优化 (PR #1585)**:
            -   **Security API Web Mode 兼容性修复 (Issue: 400/422 错误)**:
                -   为 `IpAccessLogQuery` 添加 `page` 和 `page_size` 的默认值,解决 `/api/security/logs` 返回 400 Bad Request 的问题
                -   移除 `AddBlacklistWrapper` 和 `AddWhitelistWrapper` 结构体,解决 `/api/security/blacklist` 和 `/api/security/whitelist` POST 返回 422 Unprocessable Content 的问题
                -   前端组件参数名修正:`ipPattern` → `ip_pattern`,确保与后端 API 参数一致
            -   **403 账号轮换优化 (Issue: 403 后未正确跳过账号)**:
                -   在 `token_manager.rs` 中添加 `set_forbidden` 方法,支持标记账号为禁用状态
                -   账号选择时检查 `quota.is_forbidden` 状态,自动跳过被禁用的账号
                -   403 时清除该账号的 sticky session 绑定,确保立即切换到其他可用账号
            -   **Web Mode 请求处理优化**:
                -   `request.ts` 修复路径参数替换后从 body 中移除已使用的参数,避免重复传参
                -   支持 PATCH 方法的 body 处理,补全 HTTP 方法支持
                -   自动解包 `request` 字段,简化请求结构
            -   **Debug Console Web Mode 支持**:
                -   `useDebugConsole.ts` 添加 `isTauri` 环境检测,区分 Tauri 和 Web 环境
                -   Web 模式下使用 `request()` 替代 `invoke()`,确保 Web 环境下的正常调用
                -   添加轮询机制,Web 模式下每 2 秒自动刷新日志
            -   **Docker 构建优化**:
                -   添加 `--legacy-peer-deps` 标志,解决前端依赖冲突
                -   启用 BuildKit 缓存加速 Cargo 构建,提升构建速度
                -   补全 `@lobehub/icons` peer dependencies,修复前端依赖缺失导致的构建失败
            -   **影响范围**: 此更新显著提升了 Docker/Web 模式下的稳定性和可用性,解决了 Security API 报错、403 账号轮换失效、Debug Console 不可用等问题,同时优化了 Docker 构建流程。
        -   **[核心修复] 修复 Web/Docker 模式下调试控制台崩溃与日志同步问题 (Issue #1574)**:
            -   **Web 兼容性**: 修复了在非 Tauri 环境下直接调用原生 `invoke` API 导致的 `TypeError` 崩溃。现在通过兼容性请求层进行后端通信。
            -   **指纹绑定修复**: 修复了生成指纹并绑定时,由于前后端参数结构不匹配导致的 `HTTP Error 422` 报错。通过调整后端包装类,使其兼容前端嵌套的 `profile` 对象。
            -   **日志轮询机制**: 为 Web 模式引入了自动日志轮询功能(2秒/次),解决了浏览器端无法接收 Rust 后端事件推送导致调试日志为空的问题。
        -   **[核心优化] 补全 Tauri 命令的 HTTP API 映射**:
            -   **全量适配**: 对齐了 30+ 个原生 Tauri 命令,为缓存管理(清理日志/应用缓存)、系统路径获取、代理池配置、用户令牌管理等核心功能补全了 HTTP 映射,确保 Web/Docker 版本的功能完整性。
        -   **[安全修复] 任意文件读写漏洞加固**:
            -   **API 安全层**: 彻底移除了高危接口 `/api/system/save-file` 及其关联函数,并在数据库导入接口中增加了路径遍历防范 (`..` 校验)。
            -   **Tauri 安全增强**: 为 `save_text_file` 和 `read_text_file` 命令引入了统一的路径校验器,严禁目录遍历并封堵了系统敏感目录的访问权限。
    *   **v4.1.4 (2026-02-05)**:
        -   **[核心功能] 代理池持久化与账号筛选优化 (PR #1565)**:
            -   **持久化增强**: 修复了代理池绑定在反代服务重启或重载时无法正确恢复的问题，确保绑定关系严格持久化。
            -   **智能筛选**: 优化了 `TokenManager` 的账号获取逻辑,在全量加载、同步以及调度路径中增加了对 `disabled` 和 `proxy_disabled` 状态的深度校验，彻底杜绝已禁用账号被误选的问题。
            -   **验证阻止支持**: 引入了 `validation_blocked` 字段体系，专门处理 Google 的 `VALIDATION_REQUIRED` (403 临时风控) 场景，实现了基于截止时间的智能自动绕过。
            -   **状态清理加固**: 账号失效时同步清理内存令牌、限流记录、会话绑定及优先账号标志，保证内部状态机的一致性。
        -   **[核心修复] 修复 Web/Docker 模式下的关键兼容性问题 (Issue #1574)**:
            -   **调试模式修复**: 修正了前端调试控制台 URL 映射错误（移除多余的 `/proxy` 路径），解决了 Web 模式下调试模式无法开启的问题。
            -   **指纹绑定修复**: 为 `admin_bind_device_profile_with_profi

... [README content truncated due to size. Visit the repository for the complete README] ...

]]> Rust https://github.com/rustdesk/rustdesk-server https://github.com/rustdesk/rustdesk-server Sat, 07 Feb 2026 00:07:42 GMT rustdesk/rustdesk-server

RustDesk Server Program

Language: Rust

Stars: 9,317

Forks: 2,190

Stars today: 18 stars today

README

# RustDesk Server Program

[![build](https://github.com/rustdesk/rustdesk-server/actions/workflows/build.yaml/badge.svg)](https://github.com/rustdesk/rustdesk-server/actions/workflows/build.yaml)

[**Download**](https://github.com/rustdesk/rustdesk-server/releases)

[**Manual**](https://rustdesk.com/docs/en/self-host/)

[**FAQ**](https://github.com/rustdesk/rustdesk/wiki/FAQ)

[**How to migrate OSS to Pro**](https://rustdesk.com/docs/en/self-host/rustdesk-server-pro/installscript/#convert-from-open-source)

Self-host your own RustDesk server, it is free and open source.

## How to build manually

```bash
cargo build --release
```

Three executables will be generated in target/release.

- hbbs - RustDesk ID/Rendezvous server
- hbbr - RustDesk relay server
- rustdesk-utils - RustDesk CLI utilities

You can find updated binaries on the [Releases](https://github.com/rustdesk/rustdesk-server/releases) page.

If you want extra features, [RustDesk Server Pro](https://rustdesk.com/pricing.html) might suit you better.

If you want to develop your own server, [rustdesk-server-demo](https://github.com/rustdesk/rustdesk-server-demo) might be a better and simpler start for you than this repo.

## Installation

Please follow this [doc](https://rustdesk.com/docs/en/self-host/rustdesk-server-oss/)

]]> Rust