[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-Oxen-AI--Oxen":3,"tool-Oxen-AI--Oxen":61},[4,18,26,36,44,53],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",152630,2,"2026-04-12T23:33:54",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",108322,"2026-04-10T11:39:34",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":32,"last_commit_at":50,"category_tags":51,"status":17},6121,"gemini-cli","google-gemini\u002Fgemini-cli","gemini-cli 是一款由谷歌推出的开源 AI 命令行工具，它将强大的 Gemini 大模型能力直接集成到用户的终端环境中。对于习惯在命令行工作的开发者而言，它提供了一条从输入提示词到获取模型响应的最短路径，无需切换窗口即可享受智能辅助。\n\n这款工具主要解决了开发过程中频繁上下文切换的痛点，让用户能在熟悉的终端界面内直接完成代码理解、生成、调试以及自动化运维任务。无论是查询大型代码库、根据草图生成应用，还是执行复杂的 Git 操作，gemini-cli 都能通过自然语言指令高效处理。\n\n它特别适合广大软件工程师、DevOps 人员及技术研究人员使用。其核心亮点包括支持高达 100 万 token 的超长上下文窗口，具备出色的逻辑推理能力；内置 Google 搜索、文件操作及 Shell 命令执行等实用工具；更独特的是，它支持 MCP（模型上下文协议），允许用户灵活扩展自定义集成，连接如图像生成等外部能力。此外，个人谷歌账号即可享受免费的额度支持，且项目基于 Apache 2.0 协议完全开源，是提升终端工作效率的理想助手。",100752,"2026-04-10T01:20:03",[52,13,15,14],"插件",{"id":54,"name":55,"github_repo":56,"description_zh":57,"stars":58,"difficulty_score":32,"last_commit_at":59,"category_tags":60,"status":17},4721,"markitdown","microsoft\u002Fmarkitdown","MarkItDown 是一款由微软 AutoGen 团队打造的轻量级 Python 工具，专为将各类文件高效转换为 Markdown 格式而设计。它支持 PDF、Word、Excel、PPT、图片（含 OCR）、音频（含语音转录）、HTML 乃至 YouTube 链接等多种格式的解析，能够精准提取文档中的标题、列表、表格和链接等关键结构信息。\n\n在人工智能应用日益普及的今天，大语言模型（LLM）虽擅长处理文本，却难以直接读取复杂的二进制办公文档。MarkItDown 恰好解决了这一痛点，它将非结构化或半结构化的文件转化为模型“原生理解”且 Token 效率极高的 Markdown 格式，成为连接本地文件与 AI 分析 pipeline 的理想桥梁。此外，它还提供了 MCP（模型上下文协议）服务器，可无缝集成到 Claude Desktop 等 LLM 应用中。\n\n这款工具特别适合开发者、数据科学家及 AI 研究人员使用，尤其是那些需要构建文档检索增强生成（RAG）系统、进行批量文本分析或希望让 AI 助手直接“阅读”本地文件的用户。虽然生成的内容也具备一定可读性，但其核心优势在于为机器",93400,"2026-04-06T19:52:38",[52,14],{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":66,"readme_en":67,"readme_zh":68,"quickstart_zh":69,"use_case_zh":70,"hero_image_url":71,"owner_login":72,"owner_name":73,"owner_avatar_url":74,"owner_bio":75,"owner_company":76,"owner_location":76,"owner_email":77,"owner_twitter":78,"owner_website":79,"owner_url":80,"languages":81,"stars":107,"forks":108,"last_commit_at":109,"license":110,"difficulty_score":32,"env_os":111,"env_gpu":112,"env_ram":112,"env_deps":113,"category_tags":127,"github_topics":129,"view_count":32,"oss_zip_url":76,"oss_zip_packed_at":76,"status":17,"created_at":136,"updated_at":137,"faqs":138,"releases":139},6965,"Oxen-AI\u002FOxen","Oxen","Lightning fast data version control system for structured and unstructured machine learning datasets. We aim to make versioning datasets as easy as versioning code.","Oxen 是一款专为机器学习数据集打造的高速数据版本控制系统，旨在让管理数据像使用 Git 管理代码一样简单高效。它主要解决了大型数据集（涵盖图像、音频、视频、文本及 Parquet 等表格数据）在索引、同步和协作过程中面临的性能瓶颈与版本混乱难题。无论是处理百万级文件还是 TB 级数据，Oxen 都能实现秒级索引与快速传输，确保团队能轻松追踪数据随时间的变化，避免状态丢失。\n\n这款工具非常适合 AI 开发者、数据科学家及研究人员使用，尤其是那些需要频繁迭代大规模训练数据集的团队。Oxen 的最大亮点在于其兼容 Git 的操作逻辑，用户无需重新学习即可上手；同时它底层针对大数据进行了深度优化，支持原生 DataFrame 处理与元数据自动提取。此外，Oxen 还提供了独特的“工作区”功能，允许用户在不下载完整数据的情况下直接交互，并配合 OxenHub 平台实现更直观的数据可视化与团队协作。通过命令行、Python 及 Rust 接口，Oxen 能灵活融入各类开发工作流，成为构建可靠数据流水线的得力助手。","\n\n\u003Cdiv align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fdocs.oxen.ai\u002F\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%93%9A-Documentation-245AF0\" alt=\"Oxen.ai Documentation\">\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Foxen.ai\u002F\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%90%82-Oxen%20Hub-245AF0\" alt=\"Oxen.ai\">\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fcrates.io\u002Fcrates\u002Fliboxen\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fcrates\u002Fv\u002Fliboxen.svg?color=245AF0\" alt=\"Oxen.ai Crate\"\u002F>\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Foxenai\u002F\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Foxenai.svg?color=245AF0\" alt=\"PyPi Latest Release\"\u002F>\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fdiscord.com\u002Finvite\u002Fs3tBEn7Ptg\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fjoin-discord-245AF0?logo=discord\" alt =\"Oxen.ai Discord\">\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Ftwitter.com\u002Foxen_ai\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Furl\u002Fhttps\u002Ftwitter.com\u002Foxenai.svg?style=social&label=Follow%20%40Oxen.ai\" alt =\"Oxen.ai Twitter\">\n  \u003C\u002Fa>\n  \u003Cbr\u002F>\n\u003C\u002Fdiv>\n\n#\n\n![Oxen.ai Logo](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_readme_5408eb7a5c90.png)\n![Oxen.ai Logo](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_readme_b4064ba1bed5.png)\n\n## 🐂 What is Oxen?\n\nOxen is a lightning fast data version control system for large datasets. We aim to make versioning data as easy as versioning code.\n\nThe interface mirrors git, but shines in many areas that git or git-lfs fall short. Oxen is built from the ground up for any data type, and is optimized to handle repositories with millions of files and scales to terrabytes of data.\n\n```bash\noxen init\noxen add images\u002F\noxen add annotations\u002F*.parquet\noxen commit \"Adding 200k images and their corresponding annotations\"\noxen push origin main\n```\n\nOxen is comprised of a [command line\ninterface](https:\u002F\u002Fdocs.oxen.ai\u002Fgetting-started\u002Fcli), as well as bindings for\n[Rust](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Ftree\u002Fmain\u002Fcrates) 🦀, [Python](https:\u002F\u002Fdocs.oxen.ai\u002Fgetting-started\u002Fpython) 🐍, and [HTTP interfaces](https:\u002F\u002Fdocs.oxen.ai\u002Fhttp-api) 🌎 to make it easy to integrate into your workflow.\n\n## 🌾 What kind of data?\n\nOxen is designed to efficiently manage large data in any format - including images, audio, video, text or tabular data like parquet files with millions of rows. Behind the scenes Oxen can store any blob type, but has specialized metadata extractors for certain filetypes and caches this information in the merkle tree for fast access later.\n\n## 🚀 Built for speed\n\nOne of the main reasons datasets are hard to maintain is the pure performance of indexing the data and transferring the data over the network. We wanted to be able to index hundreds of thousands of images, videos, audio files, and text files in seconds.\n\nWatch below as we version **hundreds of thousands of images** in seconds 🔥\n\n\u003Cp align=\"center\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_readme_ba7360e5e990.gif\" alt=\"oxen cli demo\" \u002F>\n\u003C\u002Fp>\n\nBut speed is only the beginning.\n\n## ✅ Features\n\nOxen is built around ergonomics, ease of use, and it is easy to learn. If you know how to use git, you know how to use Oxen.\n\n* 🔥 Fast (efficient indexing and syncing of data)\n* 🧠 Easy to learn (same commands as git)\n* 💪 Handles large files (images, videos, audio, text, parquet, arrow, json, models, etc)\n* 🗄️ Index lots of files (millions of images? no problem)\n* 📊 Native DataFrame processing (index, compare and serve up DataFrames)\n* 📈 Tracks changes over time (never worry about losing the state of your data)\n* 🤝 Collaborate with your team (sync to an oxen-server)\n* 🌎 [Workspaces](https:\u002F\u002Fdocs.oxen.ai\u002Fconcepts\u002Fworkspace) to interact with the data without downloading it\n* 👀 Better data visualization on [OxenHub](https:\u002F\u002Foxen.ai)\n\n## 🐮 Learn The Basics\n\nTo learn what everything Oxen can do, the full documentation can be found at [https:\u002F\u002Fdocs.oxen.ai](https:\u002F\u002Fdocs.oxen.ai).\n\n## 🧑‍💻 Getting Started\n\nYou can install through homebrew or pip or from our [releases page](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Freleases).\n\n### 🐂 Install Command Line Tool\n\nInstall via [Homebrew](https:\u002F\u002Fbrew.sh\u002F):\n\n```bash\nbrew install oxen\n```\n\n### 🐍 Install Python Library\n\n```bash\npip install oxenai\n```\n\n### ⬇️ Clone Dataset\n\nClone your first Oxen repository from the [OxenHub](https:\u002F\u002Foxen.ai\u002Fexplore).\n\n\u003CCodeGroup>\n\n```bash\noxen clone https:\u002F\u002Fhub.oxen.ai\u002Fox\u002FCatDogBBox\n```\n\n## 🤝 Support\n\nIf you have any questions, comments, suggestions, or just want to get in contact with the team, feel free to email us at `hello@oxen.ai`\n\n## 👥 Contributing\n\nThis repository contains the Python library that wraps the core Rust codebase. We would love help extending out the python interfaces, the documentation, or the core rust library.\n\nCode bases to contribute to:\n\n* 🦀 [Core Rust Library](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Ftree\u002Fmain\u002Fcrates\u002Flib)\n* 🐍 [Python Interface](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Ftree\u002Fmain\u002Foxen-python)\n* 📚 [Documentation](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002Fdocs)\n\nIf you are building anything with Oxen.ai or have any questions we would love to hear from you in our [discord](https:\u002F\u002Fdiscord.gg\u002Fs3tBEn7Ptg).\n\n## Build 🔨\n\nEach codebase has its own build instructions, please refer to the [Rust build instructions](.\u002Fcrates\u002Flib\u002FREADME.md#-build--run)\nand [`oxen-python`'s build instructions](.\u002Foxen-python\u002FREADME.md#build) for specifics.\n\nHowever, each codebase shares the same pre-requisites and pre-commit hooks.\n\n### Prerequisites\n\n#### Automatic Install\n\nYou should use [`bin\u002Finstall-prereqs`](.\u002Fbin\u002Finstall-prereqs) to automatically install the required development tools and toolchains for Rust and Python. Execute that as:\n\n```bash\nbin\u002Finstall-prereqs\n```\n\nIt supports MacOS and Debian-based Linux distributions. If you have a different OS or distribution, or if you have some error with the install script, you can follow the manual installation steps below.\n\n#### Manual Installation\n\nOxen is purely written in Rust 🦀. You should install the Rust toolchain with [`rustup`](https:\u002F\u002Fwww.rust-lang.org\u002Ftools\u002Finstall).\n\n```bash\ncurl --proto '=https' --tlsv1.2 -sSf https:\u002F\u002Fsh.rustup.rs | sh\n```\n\nOnce you have rust, install the following developer tools:\n- [`bacon`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fbacon): run the server with reload-on-changes\n- [`cargo-machete`](https:\u002F\u002Fgithub.com\u002Fbnjbvr\u002Fcargo-machete): identify and remove unused dependencies\n- [`cargo-llvm-cov`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fcargo-llvm-cov): calculate test code coverage\n- [`cargo-sort`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fcargo-sort): ensure `Cargo.toml` files are organized\n- [`cargo-nextest`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fcargo-nextest): run unit tests\n\nYou can install all of these at once with the following commands:\n\n```bash\ncargo install bacon cargo-machete cargo-llvm-cov cargo-sort\ncargo install --locked cargo-nextest\n```\n\nMake sure [`cmake`](https:\u002F\u002Fcmake.org\u002Fdownload\u002F) is installed. `cmake` can be installed on macOS with:\n\n```bash\nbrew install cmake\n```\n\nThe [Python interface](.\u002Foxen-python\u002FREADME.md) uses [`liboxen`](.\u002Fcrates\u002Flib\u002F) bindings provided by PyO3.\n\nThe `oxen-python` codebase requires installing [`uv`](https:\u002F\u002Fdocs.astral.sh\u002Fuv\u002Fgetting-started\u002Finstallation\u002F):\n\n```bash\ncurl --LsSf https:\u002F\u002Fastral.sh\u002Fuv\u002Finstall.sh | sh\n```\n\nIf you use [`mise`](https:\u002F\u002Fmise.jdx.dev\u002F) to manage your Python installs, you may run into an error where the oxen-py crate can't find the Python dynamic library to link with, e.g., `dyld[31558]: Library not loaded: @rpath\u002Flibpython3.13.dylib`\n\nYou can fix it by adding this to your mise config (`~\u002F.config\u002Fmise\u002Fconfig.toml`)\n\n```toml\n[env]\nDYLD_LIBRARY_PATH = \"{{ exec(command='mise where python') }}\u002Flib\"\n```\n\n### Pre-Commit Hooks\n\nWe use [pre-commit-hooks](https:\u002F\u002Fpre-commit.com\u002F) to check for commit consistency.\n\nInstall with `uv` as a tool:\n\n```bash\nuv tool install pre-commit\n```\n\nInstall `Oxen`'s pre-commit hooks locally using:\n```bash\npre-commit install\n```\n\n### Production Release Build\n\nFor deployment, build with the `production` feature flag and `--release`:\n\n```bash\ncargo build --workspace --release --features production\n```\n\nThis enables:\n- **OpenTelemetry tracing** (`otel`) -- export spans to any OTLP-compatible collector (Jaeger, Tempo, Datadog, etc.). See [OpenTelemetry Tracing](crates\u002Fserver\u002FREADME.md#opentelemetry-tracing) for runtime configuration.\n- **FFmpeg thumbnails** (`ffmpeg`) -- generate video\u002Fimage thumbnails via FFmpeg (requires FFmpeg libraries installed on the host).\n- **Performance logging** (`perf-logging`) -- additional timing instrumentation for internal operations.\n\nWithout `--features production`, the default build excludes OTel dependencies and FFmpeg support, keeping the binary smaller for local development.\n\n## Logging\n\nOxen uses structured logging via the [`tracing`](https:\u002F\u002Fdocs.rs\u002Ftracing) crate. All log output goes to **stderr** by default in a human-readable format. This applies to the CLI (`oxen`), the server (`oxen-server`), and any code using `liboxen` (including the Python bindings).\n\n### Controlling Log Level\n\nSet the `RUST_LOG` environment variable to control verbosity.\n\n```bash\n# Show debug logs from the oxen library\nRUST_LOG=debug oxen push origin main\n\n# Show only warnings and errors\nRUST_LOG=warn oxen-server start\n\n# Fine-grained: debug for liboxen, warn for everything else\nRUST_LOG=warn,liboxen=debug oxen-server start\n```\n\n### File Logging with `OXEN_LOG_DIR`\n\nSet `OXEN_LOG_DIR` to enable file-based logging in addition to stderr. This env var is a directory where rotating log files are written. Log files are written as **newline-delimited JSON** (one JSON object per line), rotated daily. Each line includes the timestamp, level, target, thread ID, source file, and line number.\n\n```bash\nOXEN_LOG_DIR=.\u002Flogs\u002F RUST_LOG=warn oxen clone https:\u002F\u002Fhub.oxen.ai\u002Fox\u002FCatDogBBox\nOXEN_LOG_DIR=\u002Fvar\u002Flog\u002Foxen oxen-server start\n```\n\nLog files are named `{app_name}.{date}` (e.g. `oxen-server.2026-04-06`) inside the configured directory.\n\nTo ingest these logs with standard tooling:\n\n- **Promtail \u002F Grafana Loki** -- point a `file_sd` or static target at the log directory; Loki handles newline-delimited JSON natively.\n- **Filebeat \u002F Elasticsearch** -- configure a `filebeat.inputs` entry with `type: filestream` and `parsers: [{ ndjson: {} }]`.\n- **Vector** -- use a `file` source with `decoding.codec = \"json\"`.\n- **`jq`** -- for ad-hoc inspection:\n\n```bash\n# Stream logs, filter for errors\ntail -f ~\u002F.oxen\u002Flogs\u002Foxen-server.2026-04-06 | jq 'select(.level == \"ERROR\")'\n```\n\n## Prometheus Metrics\n\n`oxen-server` exposes a Prometheus-compatible metrics endpoint.\nSee [Prometheus Metrics](crates\u002Fserver\u002FREADME.md#prometheus-metrics) for details.\n\n## OpenTelemetry Tracing\n\n`oxen-server` can export tracing spans to any OTLP-compatible collector (Jaeger, Tempo, etc.).\nRequires building with the `otel` feature flag.\nSee [OpenTelemetry Tracing](crates\u002Fserver\u002FREADME.md#opentelemetry-tracing) for details.\n\n## FmtSpan Events\n\nSpan lifecycle events can be emitted as log lines on stderr for lightweight tracing.\nSee [FmtSpan Events](crates\u002Fserver\u002FREADME.md#fmtspan-events) for details.\n\n## Why build Oxen?\n\nOxen was build by a team of machine learning engineers, who have spent countless hours in their careers managing datasets. We have used many different tools, but none of them were as easy to use and as ergonomic as we would like.\n\nIf you have ever tried [git lfs](https:\u002F\u002Fgit-lfs.com\u002F) to version large datasets and became frustrated, we feel your pain. Solutions like git-lfs are too slow when it comes to the scale of data we need for machine learning.\n\nIf you have ever uploaded a large dataset of images, audio, video, or text to a cloud storage bucket with the name:\n\n`s3:\u002F\u002Fdata\u002Fimages_july_2022_final_2_no_really_final.tar.gz`\n\nWe built Oxen to be the tool we wish we had.\n\n## Why the name Oxen?\n\n\"Oxen\" 🐂 comes from the fact that the tooling will plow, maintain, and version your data like a good farmer tends to their fields 🌾. Let Oxen take care of the grunt work of your infrastructure so you can focus on the higher-level problems that matter to your product.\n\n\u003C!---------------------------------------------------------------------------->\n\n[Learn The Basics]: https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLearn_The_Basics-37a779?style=for-the-badge\n","\u003Cdiv align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fdocs.oxen.ai\u002F\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%93%9A-Documentation-245AF0\" alt=\"Oxen.ai 文档\">\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Foxen.ai\u002F\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%90%82-Oxen%20Hub-245AF0\" alt=\"Oxen.ai\">\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fcrates.io\u002Fcrates\u002Fliboxen\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fcrates\u002Fv\u002Fliboxen.svg?color=245AF0\" alt=\"Oxen.ai Crate\"\u002F>\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Foxenai\u002F\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Foxenai.svg?color=245AF0\" alt=\"PyPi 最新版本\"\u002F>\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fdiscord.com\u002Finvite\u002Fs3tBEn7Ptg\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fjoin-discord-245AF0?logo=discord\" alt =\"Oxen.ai Discord\">\n  \u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Ftwitter.com\u002Foxen_ai\" style=\"padding: 2px;\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Furl\u002Fhttps\u002Ftwitter.com\u002Foxenai.svg?style=social&label=Follow%20%40Oxen.ai\" alt =\"Oxen.ai Twitter\">\n  \u003C\u002Fa>\n  \u003Cbr\u002F>\n\u003C\u002Fdiv>\n\n#\n\n![Oxen.ai Logo](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_readme_5408eb7a5c90.png)\n![Oxen.ai Logo](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_readme_b4064ba1bed5.png)\n\n## 🐂 Oxen 是什么？\n\nOxen 是一个针对大型数据集的超快速数据版本控制系统。我们的目标是让数据版本控制像代码版本控制一样简单。\n\n其接口与 Git 非常相似，但在许多 Git 或 Git LFS 存在短板的领域表现出色。Oxen 从头开始构建，适用于任何数据类型，并经过优化以处理包含数百万个文件、规模可达 TB 级别的仓库。\n\n```bash\noxen init\noxen add images\u002F\noxen add annotations\u002F*.parquet\noxen commit \"添加 20 万张图片及其对应标注\"\noxen push origin main\n```\n\nOxen 包含一个 [命令行界面](https:\u002F\u002Fdocs.oxen.ai\u002Fgetting-started\u002Fcli)，以及用于 [Rust](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Ftree\u002Fmain\u002Fcrates) 🦀、[Python](https:\u002F\u002Fdocs.oxen.ai\u002Fgetting-started\u002Fpython) 🐍 和 [HTTP 接口](https:\u002F\u002Fdocs.oxen.ai\u002Fhttp-api) 🌎 的绑定，方便您将其集成到工作流中。\n\n## 🌾 适用哪些数据？\n\nOxen 旨在高效管理各种格式的大数据——包括图像、音频、视频、文本，以及包含数百万行记录的 Parquet 文件等表格数据。在底层，Oxen 可以存储任何二进制大对象（Blob），但它为特定文件类型配备了专门的元数据提取器，并将这些信息缓存在 Merkle 树中，以便后续快速访问。\n\n## 🚀 专为速度而生\n\n数据集难以维护的主要原因之一，在于对数据进行索引和通过网络传输时的性能瓶颈。我们希望能够在几秒钟内完成对数十万张图像、视频、音频和文本文件的索引。\n\n请观看下方演示，我们在几秒钟内就完成了 **数十万张图像** 的版本控制 🔥\n\n\u003Cp align=\"center\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_readme_ba7360e5e990.gif\" alt=\"oxen cli demo\" \u002F>\n\u003C\u002Fp>\n\n但速度只是起点。\n\n## ✅ 主要特性\n\nOxen 的设计注重人体工学、易用性和学习曲线的平缓性。只要会使用 Git，就能轻松上手 Oxen。\n\n* 🔥 高速（高效的数据索引与同步）\n* 🧠 易于学习（与 Git 使用相同的命令）\n* 💪 能够处理大文件（图像、视频、音频、文本、Parquet、Arrow、JSON、模型等）\n* 🗄️ 可索引海量文件（数百万张图片？毫无压力）\n* 📊 原生 DataFrame 处理能力（索引、比较并提供 DataFrame）\n* 📈 跟踪数据随时间的变化（再也不用担心数据状态丢失）\n* 🤝 与团队协作（同步至 Oxen 服务器）\n* 🌎 [工作区](https:\u002F\u002Fdocs.oxen.ai\u002Fconcepts\u002Fworkspace) 功能，无需下载即可直接操作数据\n* 👀 在 [OxenHub](https:\u002F\u002Foxen.ai) 上获得更好的数据可视化效果\n\n## 🐮 学习基础知识\n\n如需了解 Oxen 的全部功能，完整的文档请访问 [https:\u002F\u002Fdocs.oxen.ai](https:\u002F\u002Fdocs.oxen.ai)。\n\n## 🧑‍💻 开始使用\n\n您可以通过 Homebrew、pip 或我们的 [发布页面](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Freleases) 进行安装。\n\n### 🐂 安装命令行工具\n\n通过 [Homebrew](https:\u002F\u002Fbrew.sh\u002F) 安装：\n\n```bash\nbrew install oxen\n```\n\n### 🐍 安装 Python 库\n\n```bash\npip install oxenai\n```\n\n### ⬇️ 克隆数据集\n\n从 [OxenHub](https:\u002F\u002Foxen.ai\u002Fexplore) 克隆您的第一个 Oxen 仓库。\n\n\u003CCodeGroup>\n\n```bash\noxen clone https:\u002F\u002Fhub.oxen.ai\u002Fox\u002FCatDogBBox\n```\n\n## 🤝 支持\n\n如果您有任何问题、意见、建议，或只是想与团队取得联系，请随时发送邮件至 `hello@oxen.ai`。\n\n## 👥 贡献\n\n本仓库包含封装核心 Rust 代码库的 Python 库。我们非常欢迎对 Python 接口、文档或核心 Rust 库进行扩展的贡献。\n\n可参与贡献的代码库：\n\n* 🦀 [核心 Rust 库](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Ftree\u002Fmain\u002Fcrates\u002Flib)\n* 🐍 [Python 接口](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Ftree\u002Fmain\u002Foxen-python)\n* 📚 [文档](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002Fdocs)\n\n如果您正在使用 Oxen.ai 构建项目，或有任何疑问，欢迎加入我们的 [Discord](https:\u002F\u002Fdiscord.gg\u002Fs3tBEn7Ptg) 交流。\n\n## 构建 🔨\n\n每个代码库都有各自的构建说明，请参阅 [Rust 构建说明](.\u002Fcrates\u002Flib\u002FREADME.md#-build--run) 和 [`oxen-python` 的构建说明](.\u002Foxen-python\u002FREADME.md#build) 获取详细信息。\n\n不过，所有代码库都共享相同的前置条件和提交前钩子。\n\n### 先决条件\n\n#### 自动安装\n\n您应该使用 [`bin\u002Finstall-prereqs`](.\u002Fbin\u002Finstall-prereqs) 来自动安装 Rust 和 Python 所需的开发工具和工具链。执行方式如下：\n\n```bash\nbin\u002Finstall-prereqs\n```\n\n它支持 macOS 和基于 Debian 的 Linux 发行版。如果您使用的是其他操作系统或发行版，或者在运行安装脚本时遇到问题，您可以按照下面的手动安装步骤进行操作。\n\n#### 手动安装\n\nOxen 完全由 Rust 🦀 编写。您需要使用 [`rustup`](https:\u002F\u002Fwww.rust-lang.org\u002Ftools\u002Finstall) 安装 Rust 工具链。\n\n```bash\ncurl --proto '=https' --tlsv1.2 -sSf https:\u002F\u002Fsh.rustup.rs | sh\n```\n\n安装完 Rust 后，请安装以下开发者工具：\n- [`bacon`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fbacon)：带有更改后自动重新加载功能的服务器运行工具\n- [`cargo-machete`](https:\u002F\u002Fgithub.com\u002Fbnjbvr\u002Fcargo-machete)：用于识别并移除未使用的依赖项\n- [`cargo-llvm-cov`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fcargo-llvm-cov)：用于计算测试代码覆盖率\n- [`cargo-sort`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fcargo-sort)：确保 `Cargo.toml` 文件的有序性\n- [`cargo-nextest`](https:\u002F\u002Fcrates.io\u002Fcrates\u002Fcargo-nextest)：用于运行单元测试\n\n您可以通过以下命令一次性安装所有这些工具：\n\n```bash\ncargo install bacon cargo-machete cargo-llvm-cov cargo-sort\ncargo install --locked cargo-nextest\n```\n\n请确保已安装 [`cmake`](https:\u002F\u002Fcmake.org\u002Fdownload\u002F)。在 macOS 上，可以使用以下命令安装 CMake：\n\n```bash\nbrew install cmake\n```\n\n[Python 接口](.\u002Foxen-python\u002FREADME.md) 使用 PyO3 提供的 [`liboxen`](.\u002Fcrates\u002Flib\u002F) 绑定。\n\n`oxen-python` 代码库需要安装 [`uv`](https:\u002F\u002Fdocs.astral.sh\u002Fuv\u002Fgetting-started\u002Finstallation\u002F)：\n\n```bash\ncurl --LsSf https:\u002F\u002Fastral.sh\u002Fuv\u002Finstall.sh | sh\n```\n\n如果您使用 [`mise`](https:\u002F\u002Fmise.jdx.dev\u002F) 来管理您的 Python 安装，可能会遇到 oxen-py crate 无法找到要链接的 Python 动态库的问题，例如 `dyld[31558]: Library not loaded: @rpath\u002Flibpython3.13.dylib`。\n\n您可以通过将以下内容添加到您的 mise 配置文件（`~\u002F.config\u002Fmise\u002Fconfig.toml`）来解决此问题：\n\n```toml\n[env]\nDYLD_LIBRARY_PATH = \"{{ exec(command='mise where python') }}\u002Flib\"\n```\n\n### Pre-Commit 钩子\n\n我们使用 [pre-commit-hooks](https:\u002F\u002Fpre-commit.com\u002F) 来检查提交的一致性。\n\n使用 `uv` 作为工具进行安装：\n\n```bash\nuv tool install pre-commit\n```\n\n使用以下命令在本地安装 Oxen 的 pre-commit 钩子：\n\n```bash\npre-commit install\n```\n\n### 生产环境发布构建\n\n在部署时，请使用 `production` 特性标志和 `--release` 标志进行构建：\n\n```bash\ncargo build --workspace --release --features production\n```\n\n这将启用：\n- **OpenTelemetry 跟踪** (`otel`) -- 将跟踪跨度导出到任何兼容 OTLP 的收集器（Jaeger、Tempo、Datadog 等）。有关运行时配置，请参阅 [OpenTelemetry 跟踪](crates\u002Fserver\u002FREADME.md#opentelemetry-tracing)。\n- **FFmpeg 缩略图** (`ffmpeg`) -- 通过 FFmpeg 生成视频\u002F图像缩略图（需要在主机上安装 FFmpeg 库）。\n- **性能日志记录** (`perf-logging`) -- 用于内部操作的额外计时监控。\n\n如果不使用 `--features production`，默认构建将排除 OTel 依赖项和 FFmpeg 支持，从而使二进制文件更小，适合本地开发。\n\n## 日志记录\n\nOxen 使用 [`tracing`](https:\u002F\u002Fdocs.rs\u002Ftracing) crate 进行结构化日志记录。默认情况下，所有日志输出都会以人类可读的格式发送到 **stderr**。这适用于 CLI（`oxen`）、服务器（`oxen-server`）以及任何使用 `liboxen` 的代码（包括 Python 绑定）。\n\n### 控制日志级别\n\n设置 `RUST_LOG` 环境变量来控制日志的详细程度。\n\n```bash\n# 显示 oxen 库的调试日志\nRUST_LOG=debug oxen push origin main\n\n# 仅显示警告和错误\nRUST_LOG=warn oxen-server start\n\n# 细粒度：liboxen 的日志为调试级别，其他部分为警告级别\nRUST_LOG=warn,liboxen=debug oxen-server start\n```\n\n### 使用 `OXEN_LOG_DIR` 进行文件日志记录\n\n设置 `OXEN_LOG_DIR` 可以在 stderr 之外启用基于文件的日志记录。该环境变量指定一个目录，用于存放轮转的日志文件。日志文件以 **换行分隔的 JSON 格式**（每行一个 JSON 对象）写入，并按天轮转。每行包含时间戳、日志级别、目标、线程 ID、源文件和行号。\n\n```bash\nOXEN_LOG_DIR=.\u002Flogs\u002F RUST_LOG=warn oxen clone https:\u002F\u002Fhub.oxen.ai\u002Fox\u002FCatDogBBox\nOXEN_LOG_DIR=\u002Fvar\u002Flog\u002Foxen oxen-server start\n```\n\n日志文件在配置的目录中命名为 `{app_name}.{date}`（例如 `oxen-server.2026-04-06`）。\n\n要使用标准工具摄取这些日志：\n\n- **Promtail \u002F Grafana Loki** -- 将 `file_sd` 或静态目标指向日志目录；Loki 原生支持换行分隔的 JSON。\n- **Filebeat \u002F Elasticsearch** -- 配置一个 `filebeat.inputs` 条目，设置 `type: filestream` 和 `parsers: [{ ndjson: {} }]`。\n- **Vector** -- 使用 `file` 源，并设置 `decoding.codec = \"json\"`。\n- **`jq`** -- 用于临时检查：\n\n```bash\n# 流式查看日志，筛选错误\ntail -f ~\u002F.oxen\u002Flogs\u002Foxen-server.2026-04-06 | jq 'select(.level == \"ERROR\")'\n```\n\n## Prometheus 指标\n\n`oxen-server` 暴露了一个兼容 Prometheus 的指标端点。\n有关详细信息，请参阅 [Prometheus 指标](crates\u002Fserver\u002FREADME.md#prometheus-metrics)。\n\n## OpenTelemetry 跟踪\n\n`oxen-server` 可以将跟踪跨度导出到任何兼容 OTLP 的收集器（Jaeger、Tempo 等）。\n需要使用 `otel` 特性标志进行构建。\n有关详细信息，请参阅 [OpenTelemetry 跟踪](crates\u002Fserver\u002FREADME.md#opentelemetry-tracing)。\n\n## FmtSpan 事件\n\n跨度生命周期事件可以作为日志行输出到 stderr，用于轻量级跟踪。\n有关详细信息，请参阅 [FmtSpan 事件](crates\u002Fserver\u002FREADME.md#fmtspan-events)。\n\n## 为什么构建 Oxen？\n\nOxen 是由一支机器学习工程师团队构建的，他们在职业生涯中花费了无数时间来管理数据集。我们尝试过许多不同的工具，但没有一个像我们期望的那样易于使用且符合人体工学。\n\n如果您曾经尝试过使用 [git lfs](https:\u002F\u002Fgit-lfs.com\u002F) 来版本化大型数据集并因此感到沮丧，那么我们深有同感。对于机器学习所需的海量数据来说，像 git-lfs 这样的解决方案速度太慢了。\n\n如果您曾经将大量的图像、音频、视频或文本数据集上传到云存储桶，并为其命名：\n\n`s3:\u002F\u002Fdata\u002Fimages_july_2022_final_2_no_really_final.tar.gz`\n\n我们构建 Oxen 的目的，就是让它成为我们一直渴望拥有的工具。\n\n## 为什么叫 Oxen？\n\n“Oxen” 🐂 这个名字来源于这样一个事实：该工具将像优秀的农民照料田地一样，耕耘、维护和版本化您的数据 🌾。让 Oxen 来承担您基础设施中的繁重工作，这样您就可以专注于对您的产品至关重要的更高层次的问题。\n\n\u003C!---------------------------------------------------------------------------->\n\n[了解基础知识]: https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLearn_The_Basics-37a779?style=for-the-badge","# Oxen 快速上手指南\n\nOxen 是一个专为大型数据集设计的极速数据版本控制系统。它的操作逻辑与 Git 高度相似，但针对图像、音频、视频及大规模表格数据（如 Parquet）进行了深度优化，能够轻松处理百万级文件和 TB 级数据。\n\n## 环境准备\n\n在开始之前，请确保您的系统满足以下基本要求：\n\n*   **操作系统**：macOS 或 Linux（Debian\u002FUbuntu 系列）。Windows 用户建议使用 WSL2。\n*   **网络环境**：需要能够访问 GitHub 和 PyPI。\n    *   *提示*：国内用户若遇到下载缓慢，可配置 pip 国内镜像源（如清华源或阿里源）。\n*   **前置依赖**：\n    *   若使用命令行工具：无特殊依赖，二进制包已包含所需组件。\n    *   若使用 Python 库：需安装 Python 3.8+ 及 `pip`。\n    *   （可选）开发贡献者需安装 Rust 工具链 (`rustup`) 和 `cmake`。\n\n## 安装步骤\n\n您可以根据需求选择安装命令行工具或 Python 库。\n\n### 1. 安装命令行工具 (CLI)\n\n推荐使用 Homebrew (macOS\u002FLinux) 进行安装：\n\n```bash\nbrew install oxen\n```\n\n或者从 [GitHub Releases](https:\u002F\u002Fgithub.com\u002FOxen-AI\u002FOxen\u002Freleases) 页面下载对应系统的二进制文件。\n\n### 2. 安装 Python 库\n\n如果您希望在 Python 项目中集成 Oxen，请使用 pip 安装：\n\n```bash\n# 推荐使用国内镜像源加速安装\npip install oxenai -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n```\n\n## 基本使用\n\nOxen 的命令设计与 Git 几乎一致，学习成本极低。以下是核心工作流示例：\n\n### 1. 初始化仓库\n\n在项目目录下初始化 Oxen 仓库：\n\n```bash\noxen init\n```\n\n### 2. 添加数据\n\n将数据文件（支持图片、视频、Parquet 等）添加到暂存区。Oxen 会自动处理大文件的索引和元数据提取：\n\n```bash\noxen add images\u002F\noxen add annotations\u002F*.parquet\n```\n\n### 3. 提交版本\n\n保存当前数据状态并添加备注：\n\n```bash\noxen commit \"Adding 200k images and their corresponding annotations\"\n```\n\n### 4. 同步远程仓库\n\n将数据推送到远程服务器（如 OxenHub 或自建的 oxen-server）：\n\n```bash\noxen push origin main\n```\n\n### 5. 克隆现有数据集\n\n从 OxenHub 快速获取公开数据集：\n\n```bash\noxen clone https:\u002F\u002Fhub.oxen.ai\u002Fox\u002FCatDogBBox\n```\n\n---\n\n**下一步**：更多高级功能（如 DataFrame 原生处理、工作空间管理）请参阅官方文档 [https:\u002F\u002Fdocs.oxen.ai](https:\u002F\u002Fdocs.oxen.ai)。","某自动驾驶初创公司的算法团队正在迭代一个包含 50 万张路况图像及对应标注文件的感知模型，急需在多人协作中频繁回溯数据状态。\n\n### 没有 Oxen 时\n- **版本混乱难追溯**：团队成员手动复制数据集文件夹（如 `dataset_v1_final_really`），一旦模型效果回退，根本无法确定具体是哪一批标注数据出了问题。\n- **大文件同步极慢**：使用传统 Git 或网盘同步数百 GB 的图像和 Parquet 标注文件时，网络传输耗时数小时，且容易因中断导致文件损坏。\n- **协作冲突频发**：多名标注员同时修改数据时缺乏合并机制，经常发生文件覆盖，导致珍贵的长尾场景标注丢失。\n- **元数据查询困难**：想要筛选特定天气或光照条件的图片进行复训，只能写脚本遍历整个文件系统，效率极低。\n\n### 使用 Oxen 后\n- **像代码一样管理数据**：团队直接使用 `oxen commit` 记录每次数据变更，通过 `oxen log` 清晰查看历史，随时一键回滚到任意版本的“黄金数据集”。\n- **秒级索引与增量同步**：Oxen 能在几秒内索引完 50 万张图片，后续协作仅同步变动部分，将原本数小时的同步时间缩短至分钟级。\n- **无缝团队协作**：成员通过 `oxen push\u002Fpull` 与中央服务器同步，自动处理并发修改，确保每位算法工程师本地的数据状态严格一致。\n- **原生数据框支持**：利用 Oxen 内置的 DataFrame 处理能力，可直接对百万行标注数据进行快速过滤和分析，无需额外编写加载脚本。\n\nOxen 将原本杂乱无章的大数据管理变成了像代码开发一样流畅、可追溯且高效的标准化流程。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FOxen-AI_Oxen_47a923a3.png","Oxen-AI","Oxen.ai","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002FOxen-AI_7fb46a27.png","",null,"hello@oxen.ai","oxen_ai","www.oxen.ai","https:\u002F\u002Fgithub.com\u002FOxen-AI",[82,86,90,94,98,102,105],{"name":83,"color":84,"percentage":85},"Rust","#dea584",93.7,{"name":87,"color":88,"percentage":89},"Python","#3572A5",5.6,{"name":91,"color":92,"percentage":93},"Shell","#89e051",0.6,{"name":95,"color":96,"percentage":97},"Nix","#7e7eff",0.1,{"name":99,"color":100,"percentage":101},"Dockerfile","#384d54",0,{"name":103,"color":104,"percentage":101},"Makefile","#427819",{"name":106,"color":76,"percentage":101},"RenderScript",1128,25,"2026-04-11T21:58:05","Apache-2.0","Linux, macOS","未说明",{"notes":114,"python":115,"dependencies":116},"该工具核心由 Rust 编写。自动安装脚本仅支持 macOS 和基于 Debian 的 Linux 发行版。生产环境构建需启用 'production' 特性以支持 OpenTelemetry 追踪和 FFmpeg 缩略图生成（需主机安装 FFmpeg 库）。若使用 mise 管理 Python，可能需配置 DYLD_LIBRARY_PATH 以解决动态库链接问题。日志默认输出到 stderr，也可配置为 JSON 格式文件输出。","3.8+ (推断，需安装 uv 管理工具)",[117,118,119,120,121,122,123,124,125,126],"Rust toolchain (rustup)","cmake","uv","bacon","cargo-machete","cargo-llvm-cov","cargo-sort","cargo-nextest","pre-commit","FFmpeg (可选，用于生产构建生成缩略图)",[128,14,16],"其他",[130,131,132,133,134,135],"artificial-intelligence","data-science","machine-learning","python","rust","version-control","2026-03-27T02:49:30.150509","2026-04-13T09:13:31.728978",[],[140,145,150,155,160,165,170,175,180,185,190,195,200,205,210,215,220,225,230,235],{"id":141,"version":142,"summary_zh":143,"released_at":144},231225,"v0.46.11","🚀 版本 0.46.11\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- macOS arm64（Apple Silicon）\n- macOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本信息：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 作为最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 macOS 二进制文件\nmacOS arm64（Apple Silicon）二进制文件要求 macOS 最低版本为 11 Big Sur。macOS x86_64（Intel）二进制文件则要求 macOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.14、3.13、3.12、3.11）\n- Linux x86_64（Python 3.14、3.13、3.12、3.11）\n- macOS arm64 [Apple Silicon]（Python 3.14、3.13、3.12、3.11）\n- macOS x86_64 [Intel]（Python 3.14、3.13、3.12、3.11）\n- Windows x86_64（Python 3.14、3.13、3.12、3.11）","2026-04-11T18:27:36",{"id":146,"version":147,"summary_zh":148,"released_at":149},231226,"v0.46.10","🚀 版本 0.46.10\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 作为最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 最低版本为 11 Big Sur。而 MacOS x86_64（Intel）二进制文件则要求 macOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.14、3.13、3.12、3.11）\n- Linux x86_64（Python 3.14、3.13、3.12、3.11）\n- MacOS arm64 [Apple Silicon]（Python 3.14、3.13、3.12、3.11）\n- MacOS x86_64 [Intel]（Python 3.14、3.13、3.12、3.11）\n- Windows x86_64（Python 3.14、3.13、3.12、3.11）","2026-04-01T04:25:22",{"id":151,"version":152,"summary_zh":153,"released_at":154},231227,"v0.46.9","🚀 版本 0.46.9\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 的最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 MacOS 最低版本为 11 Big Sur。MacOS x86_64（Intel）二进制文件要求 MacOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.14、3.13、3.12、3.11）\n- Linux x86_64（Python 3.14、3.13、3.12、3.11）\n- MacOS arm64 [Apple Silicon]（Python 3.14、3.13、3.12、3.11）\n- MacOS x86_64 [Intel]（Python 3.14、3.13、3.12、3.11）\n- Windows x86_64（Python 3.14、3.13、3.12、3.11）","2026-03-31T23:29:05",{"id":156,"version":157,"summary_zh":158,"released_at":159},231228,"v0.46.7","🚀 版本 0.46.7\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版及其最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 或更高版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 11 Big Sur 或更高版本。MacOS x86_64（Intel）二进制文件则要求 macOS 10.13 High Sierra 或更高版本。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.14、3.13、3.12、3.11）\n- Linux x86_64（Python 3.14、3.13、3.12、3.11）\n- MacOS arm64 [Apple Silicon]（Python 3.14、3.13、3.12、3.11）\n- MacOS x86_64 [Intel]（Python 3.14、3.13、3.12、3.11）\n- Windows x86_64（Python 3.14、3.13、3.12、3.11）","2026-03-26T15:34:46",{"id":161,"version":162,"summary_zh":163,"released_at":164},231229,"v0.46.4","🚀 版本 0.46.4\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 或更高版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 11 Big Sur 或更高版本。MacOS x86_64（Intel）二进制文件则要求 macOS 10.13 High Sierra 或更高版本。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.14、3.13、3.12、3.11）\n- Linux x86_64（Python 3.14、3.13、3.12、3.11）\n- MacOS arm64 [Apple Silicon]（Python 3.14、3.13、3.12、3.11）\n- MacOS x86_64 [Intel]（Python 3.14、3.13、3.12、3.11）\n- Windows x86_64（Python 3.14、3.13、3.12、3.11）","2026-03-21T19:59:14",{"id":166,"version":167,"summary_zh":168,"released_at":169},231230,"v0.46.3","🚀 版本 0.46.3\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 作为最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 最低版本为 11 Big Sur。MacOS x86_64（Intel）二进制文件则要求 macOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.13、3.12、3.11、3.10）\n- Linux x86_64（Python 3.13、3.12、3.11、3.10）\n- MacOS arm64 [Apple Silicon]（Python 3.13、3.12、3.11、3.10）\n- MacOS x86_64 [Intel]（Python 3.13、3.12、3.11、3.10）\n- Windows x86_64（Python 3.13、3.12、3.11、3.10）","2026-03-19T18:10:50",{"id":171,"version":172,"summary_zh":173,"released_at":174},231231,"v0.46.2","🚀 版本 0.46.2\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 作为最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 最低版本为 11 Big Sur。MacOS x86_64（Intel）二进制文件则要求 macOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.13、3.12、3.11、3.10）\n- Linux x86_64（Python 3.13、3.12、3.11、3.10）\n- MacOS arm64 [Apple Silicon]（Python 3.13、3.12、3.11、3.10）\n- MacOS x86_64 [Intel]（Python 3.13、3.12、3.11、3.10）\n- Windows x86_64（Python 3.13、3.12、3.11、3.10）","2026-03-15T02:30:30",{"id":176,"version":177,"summary_zh":178,"released_at":179},231232,"v0.46.1","🚀 版本 0.46.1\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 作为最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 最低版本为 11 Big Sur。MacOS x86_64（Intel）二进制文件则要求 macOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.13、3.12、3.11、3.10）\n- Linux x86_64（Python 3.13、3.12、3.11、3.10）\n- MacOS arm64 [Apple Silicon]（Python 3.13、3.12、3.11、3.10）\n- MacOS x86_64 [Intel]（Python 3.13、3.12、3.11、3.10）\n- Windows x86_64（Python 3.13、3.12、3.11、3.10）","2026-03-14T15:34:07",{"id":181,"version":182,"summary_zh":183,"released_at":184},231233,"v0.45.0","🚀 版本 0.45.0\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 或更高版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 11 Big Sur 或更高版本。MacOS x86_64（Intel）二进制文件则要求 macOS 10.13 High Sierra 或更高版本。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.13、3.12、3.11、3.10）\n- Linux x86_64（Python 3.13、3.12、3.11、3.10）\n- MacOS arm64 [Apple Silicon]（Python 3.13、3.12、3.11、3.10）\n- MacOS x86_64 [Intel]（Python 3.13、3.12、3.11、3.10）\n- Windows x86_64（Python 3.13、3.12、3.11、3.10）","2026-03-06T20:43:18",{"id":186,"version":187,"summary_zh":188,"released_at":189},231234,"v0.44.2","🚀 版本 0.44.2\n\n二进制文件适用于以下平台：\n- Docker arm64\n- Docker x86_64\n- Linux arm64\n- Linux x86_64\n- MacOS arm64（Apple Silicon）\n- MacOS x86_64（Intel）\n- Windows x86_64\n\n🐧 Linux 二进制文件\nLinux 二进制文件要求 glibc 最低版本为 2.34。\n\n以下是 glibc 2.34 或更高版本的常见发行版的最低版本：\n\n| 发行版       | 首次包含 glibc 2.34+ 的版本 |\n|--------------|-----------------------------|\n| Amazon Linux | 2023                      |\n| Arch         | 2021                      |\n| CentOS       | Stream 9                  |\n| Debian       | 12                        |\n| Fedora       | 35                        |\n| RHEL         | 9.0                       |\n| Ubuntu       | 22.04                     |\n\n🖥️ Windows 二进制文件\nWindows 二进制文件要求 Visual C++ 2022 作为最低版本。您可能需要安装最新版本的 Microsoft Visual C++ 可再分发组件。\n\n🍏 MacOS 二进制文件\nMacOS arm64（Apple Silicon）二进制文件要求 macOS 最低版本为 11 Big Sur。MacOS x86_64（Intel）二进制文件则要求 macOS 最低版本为 10.13 High Sierra。\n\n🐍 Python 轮子包\nPython 轮子包适用于以下平台：\n- Linux arm64（Python 3.13、3.12、3.11、3.10）\n- Linux x86_64（Python 3.13、3.12、3.11、3.10）\n- MacOS arm64 [Apple Silicon]（Python 3.13、3.12、3.11、3.10）\n- MacOS x86_64 [Intel]（Python 3.13、3.12、3.11、3.10）\n- Windows x86_64（Python 3.13、3.12、3.11、3.10）","2026-02-20T20:39:47",{"id":191,"version":192,"summary_zh":193,"released_at":194},231235,"v0.44.1","🚀 Release 0.44.1\r\n\r\n**Features**\r\n\r\n • Added fsck command to scan repositories for corrupted\u002Fmissing version files and --missing-files flag to pull for re-downloading missing files (Oxen-AI\u002FOxen) #267\r\n • Updated Python Workspace.add to accept multiple files, directories, and pathlib.Path instances (Oxen-AI\u002FOxen) #265\r\n • Replaced CSV delimiter sniffer with a dialect sniffer that detects both delimiter and quote character, defaulting to RFC 4180 double-quote (Oxen-AI\u002FOxen) #261\r\n • Added --workspace-name argument to oxen workspace status and renamed existing argument to --workspace-id with backward-compatible deprecation (Oxen-AI\u002FOxen) #254\r\n • Added tree API for depth-controlled recursive directory listing with hierarchical metadata (Oxen-AI\u002FOxen) #250\r\n\r\n**Bug Fixes**\r\n\r\n • Fixed workspace add_version_file ignoring file hashes and replaced add_many with unified add function (Oxen-AI\u002FOxen) #266\r\n • Added validation for repository and namespace names to require alphanumeric start and allowed characters (Oxen-AI\u002FOxen) #264\r\n • Fixed workspaces::files::exists returning Err on empty workspaces and producing false-positives (Oxen-AI\u002FOxen) #260\r\n • Changed file-serving routes to return 404 instead of 500 for missing resources and added corresponding CLI error handling (Oxen-AI\u002FOxen) #259\r\n • Added missing async_zip dependency to oxen-server (Oxen-AI\u002FOxen) #258\r\n\r\n---\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2026-02-14T00:31:29",{"id":196,"version":197,"summary_zh":198,"released_at":199},231236,"v0.43.1","🚀 Release 0.43.1\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2026-02-10T01:41:41",{"id":201,"version":202,"summary_zh":203,"released_at":204},231237,"v0.43.0","🚀 Release 0.43.0\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2026-01-29T18:48:29",{"id":206,"version":207,"summary_zh":208,"released_at":209},231238,"v0.42.5","🚀 Release 0.42.5\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2026-01-08T17:28:29",{"id":211,"version":212,"summary_zh":213,"released_at":214},231239,"v0.42.4","🚀 Release 0.42.4\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2026-01-05T05:58:56",{"id":216,"version":217,"summary_zh":218,"released_at":219},231240,"v0.42.3","🚀 Release 0.42.3\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2025-12-31T06:32:13",{"id":221,"version":222,"summary_zh":223,"released_at":224},231241,"v0.42.2","🚀 Release 0.42.2\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2025-12-20T05:24:02",{"id":226,"version":227,"summary_zh":228,"released_at":229},231242,"v0.42.0","🚀 Release 0.42.0\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2025-12-18T15:56:20",{"id":231,"version":232,"summary_zh":233,"released_at":234},231243,"v0.41.3","🚀 Release 0.41.3\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2025-12-13T14:23:09",{"id":236,"version":237,"summary_zh":238,"released_at":239},231244,"v0.40.3","🚀 Release 0.40.3\r\n\r\nBinaries are available for the following platforms:\r\n- Docker arm64\r\n- Docker x86_64\r\n- Linux arm64\r\n- Linux x86_64\r\n- MacOS arm64 (Apple Silicon)\r\n- MacOS x86_64 (Intel)\r\n- Windows x86_64\r\n\r\n🐧 Linux Binaries\r\nThe Linux binaries require a minimum glibc version of 2.34.\r\n\r\nThese are the minimum versions of common distributions with glibc 2.34 or later.\r\n\r\n| Distribution | First version with glibc 2.34+ |\r\n|--------------|--------------------------------|\r\n| Amazon Linux | 2023                           |\r\n| Arch         | 2021                           |\r\n| CentOS       | Stream 9                       |\r\n| Debian       | 12                             |\r\n| Fedora       | 35                             |\r\n| RHEL         | 9.0                            |\r\n| Ubuntu       | 22.04                          |\r\n\r\n🖥️ Windows Binaries\r\nThe Windows binaries require a minimum version of Visual C++ 2022.\r\nYou may need to install the latest Microsoft Visual C++ Redistributable.\r\n\r\n🍏 MacOS Binaries\r\nThe MacOS arm64 (Apple Silicon) binaries require a minimum version of MacOS 11 Big Sur.\r\nThe MacOS x86_64 (Intel) binaries require a minimum version of MacOS 10.13 High Sierra.\r\n\r\n🐍 Python Wheels\r\nThe Python wheels are available for the following platforms:\r\n- Linux arm64 (Python 3.13 3.12 3.11 3.10)\r\n- Linux x86_64 (Python 3.13 3.12 3.11 3.10)\r\n- MacOS arm64 [Apple Silicon] (Python 3.13 3.12 3.11 3.10)\r\n- MacOS x86_64 [Intel] (Python 3.13 3.12 3.11 3.10)\r\n- Windows x86_64 (Python 3.13 3.12 3.11 3.10)","2025-12-08T17:54:11"]