[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-argilla-io--argilla":3,"tool-argilla-io--argilla":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",150037,2,"2026-04-10T23:33:47",[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":121,"forks":122,"last_commit_at":123,"license":124,"difficulty_score":10,"env_os":125,"env_gpu":125,"env_ram":125,"env_deps":126,"category_tags":130,"github_topics":131,"view_count":149,"oss_zip_url":76,"oss_zip_packed_at":76,"status":17,"created_at":150,"updated_at":151,"faqs":152,"releases":182},1079,"argilla-io\u002Fargilla","argilla","Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets","Argilla 是一个面向 AI 工程师与领域专家的协作平台，专注于通过高效的数据迭代提升模型质量。它解决了 AI 开发中数据质量参差不齐导致模型效果不佳的核心问题，帮助团队系统化构建、标注和优化训练数据集。核心用户包括需要处理文本分类、命名实体识别、大语言模型调优（如 RAG、偏好排序）或多模态任务（如文生图）的开发者与研究人员。\n\n区别于传统数据标注工具，Argilla 强调「数据驱动」的模型迭代理念，提供语义搜索、智能标注建议和动态过滤功能，使用户能快速定位关键数据样本。其程序化工作流设计支持持续评估与模型优化，同时确保用户对数据资产与模型版本的完全控制权。技术层面，它采用轻量级架构实现快速部署，并通过 Hugging Face Spaces 提供一键式云端体验，适合需要快速验证原型或构建最小可行数据集的团队。\n\n目前项目代码库已稳定运行多年，社区持续维护核心功能，适合注重长期数据治理且无需频繁功能更新的团队使用。用户可通过 Discord 或 GitHub 参与项目维护，共同推动工具演进。","> [!IMPORTANT]\nThe original authors have moved on to exciting new projects! The codebase is mature and stable, having served users reliably for years. While we won't be adding new features going forward, we're committed to solve bug fixes and publish patches as needed.\nIf you're interested in helping maintain or extend this project, we'd love to hear from you! Please open an issue to discuss becoming a maintainer - we're looking for dedicated contributors who can take ownership of the project's future development.\n>\n\u003Ch1 align=\"center\">\n  \u003Ca href=\"\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Fdvsrepo\u002Fimgs\u002Fraw\u002Fmain\u002Frg.svg\" alt=\"Argilla\" width=\"150\">\u003C\u002Fa>\n  \u003Cbr>\n  Argilla\n  \u003Cbr>\n\u003C\u002Fh1>\n\u003Ch3 align=\"center\">Build high quality datasets for your AI models\u003C\u002Fh3>\n\n\u003Cp align=\"center\">\n\u003Ca  href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Fargilla\u002F\">\n\u003Cimg alt=\"CI\" src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fargilla.svg?style=flat-round&logo=pypi&logoColor=white\">\n\u003C\u002Fa>\n\u003Cimg alt=\"Codecov\" src=\"https:\u002F\u002Fcodecov.io\u002Fgh\u002Fargilla-io\u002Fargilla\u002Fbranch\u002Fmain\u002Fgraph\u002Fbadge.svg?token=VDVR29VOMG\"\u002F>\n\u003Ca href=\"https:\u002F\u002Fpepy.tech\u002Fproject\u002Fargilla\">\n\u003Cimg alt=\"CI\" src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_readme_16c7b5a5f99e.png\">\n\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fnew-space?template=argilla\u002Fargilla-template-space\">\n\u003Cimg src=\"https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fhuggingface\u002Fbadges\u002Fraw\u002Fmain\u002Fdeploy-to-spaces-sm.svg\"\u002F>\n\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n\u003Ca href=\"https:\u002F\u002Ftwitter.com\u002Fargilla_io\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Ftwitter-black?logo=x\"\u002F>\n\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fargilla-io\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flinkedin-blue?logo=linkedin\"\u002F>\n\u003C\u002Fa>\n\u003Ca href=\"http:\u002F\u002Fhf.co\u002Fjoin\u002Fdiscord\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-7289DA?&logo=discord&logoColor=white\"\u002F>\n\u003C\u002Fa>\n\u003C\u002Fp>\n\nArgilla is a collaboration tool for AI engineers and domain experts who need to build high-quality datasets for their projects.\n\nIf you just want to get started, [deploy Argilla on Hugging Face Spaces](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fgetting_started\u002Fquickstart\u002F). Curious, and want to know more? Read our [documentation](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002F).\n\nOr, play with the Argilla UI by signing in with your Hugging Face account:\n\n\u003Cp>\n  \u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fspaces\u002Fargilla\u002Fargilla-template-space\" title=\"Redirect to homepage\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_readme_5ffce7ed8207.png\" alt=\"homepage\" \u002F>\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n## Why use Argilla?\n\nArgilla can be used for collecting human feedback for a wide variety of AI projects like traditional NLP (text classification, NER, etc.), LLMs (RAG, preference tuning, etc.), or multimodal models (text to image, etc.). Argilla's programmatic approach lets you build workflows for continuous evaluation and model improvement. The goal of Argilla is to ensure your data work pays off by quickly iterating on the right data and models.\n\n### Improve your AI output quality through data quality\n\nCompute is expensive and output quality is important. We help you focus on data, which tackles the root cause of both of these problems at once. Argilla helps you to **achieve and keep high-quality standards** for your data. This means you can improve the quality of your AI output.\n\n### Take control of your data and models\n\nMost AI tools are black boxes. Argilla is different. We believe that you should be the owner of both your data and your models. That's why we provide you with all the tools your team needs to **manage your data and models in a way that suits you best**.\n\n### Improve efficiency by quickly iterating on the right data and models\n\nGathering data is a time-consuming process. Argilla helps by providing a tool that allows you to **interact with your data in a more engaging way**. This means you can quickly and easily label your data with filters, AI feedback suggestions and semantic search. So you can focus on training your models and monitoring their performance.\n\n## 🏘️ Community\n\nWe are an open-source community-driven project and we love to hear from you. Here are some ways to get involved:\n\n- [Community Meetup](https:\u002F\u002Flu.ma\u002Fembed-checkout\u002Fevt-IQtRiSuXZCIW6FB): listen in or present during one of our bi-weekly events.\n\n- [Discord](http:\u002F\u002Fhf.co\u002Fjoin\u002Fdiscord): get direct support from the community in #argilla-distilabel-general and #argilla-distilabel-help.\n\n- [Roadmap](https:\u002F\u002Fgithub.com\u002Forgs\u002Fargilla-io\u002Fprojects\u002F10\u002Fviews\u002F1): plans change but we love to discuss those with our community so feel encouraged to participate.\n\n## What do people build with Argilla?\n\n### Open-source datasets and models\n\nThe community uses Argilla to create amazing open-source [datasets](https:\u002F\u002Fhuggingface.co\u002Fdatasets?library=library:argilla&sort=trending) and [models](https:\u002F\u002Fhuggingface.co\u002Fmodels?other=distilabel).\n\n- [Cleaned UltraFeedback dataset](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fargilla\u002Fultrafeedback-binarized-preferences-cleaned) used to fine-tune the [Notus](https:\u002F\u002Fhuggingface.co\u002Fargilla\u002Fnotus-7b-v1) and [Notux](https:\u002F\u002Fhuggingface.co\u002Fargilla\u002Fnotux-8x7b-v1) models. The original UltraFeedback dataset was curated using Argilla UI filters to find and report a bug in the original data generation code. Based on this data curation process, Argilla built this new version of the UltraFeedback dataset and fine-tuned Notus, outperforming Zephyr on several benchmarks.\n- [distilabel Intel Orca DPO dataset](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fargilla\u002Fdistilabel-intel-orca-dpo-pairs) used to fine-tune the [improved OpenHermes model](https:\u002F\u002Fhuggingface.co\u002Fargilla\u002Fdistilabeled-OpenHermes-2.5-Mistral-7B). This dataset was built by combining human curation in Argilla with AI feedback from distilabel, leading to an improved version of the Intel Orca dataset and outperforming models fine-tuned on the original dataset.\n\n### Examples Use cases\n\nAI teams from organizations such as the [Red Cross](https:\u002F\u002F510.global\u002F), [Loris.ai](https:\u002F\u002Floris.ai\u002F) and [Prolific](https:\u002F\u002Fwww.prolific.com\u002F) use Argilla to improve the quality and efficiency of AI projects. They shared their experiences in our [AI community meetup](https:\u002F\u002Flu.ma\u002Fembed-checkout\u002Fevt-IQtRiSuXZCIW6FB).\n\n- AI for good: [the Red Cross presentation](https:\u002F\u002Fyoutu.be\u002FZsCqrAhzkFU?feature=shared) showcases how the Red Cross domain experts and AI team collaborated by classifying and redirecting requests from refugees of the Ukrainian crisis to streamline the support processes of the Red Cross.\n- Customer support: during [the Loris meetup](https:\u002F\u002Fyoutu.be\u002FjWrtgf2w4VU?feature=shared) they showed how their AI team uses unsupervised and few-shot contrastive learning to help them quickly validate and gain labeled samples for a huge amount of multi-label classifiers.\n- Research studies: [the showcase from Prolific](https:\u002F\u002Fyoutu.be\u002FePDlhIxnuAs?feature=shared) announced their integration with our platform. They use it to actively distribute data collection projects among their annotating workforce. This allows Prolific to quickly and efficiently collect high-quality data for research studies.\n\n## 👨‍💻 Getting started\n\n### Installation\n\nFirst things first! You can install the SDK with pip as follows:\n\n```console\npip install argilla\n```\n\nAfter that, you will need to deploy Argilla Server. The easiest way to do this is through our [free Hugging Face Spaces deployment integration](https:\u002F\u002Fhuggingface.co\u002Fnew-space?template=argilla\u002Fargilla-template-space).\n\nTo use the client, you need to import the `Argilla` class and instantiate it with the API URL and API key.\n\n```python\nimport argilla as rg\n\nclient = rg.Argilla(api_url=\"https:\u002F\u002F[your-owner-name]-[your_space_name].hf.space\", api_key=\"owner.apikey\")\n```\n\n### Create your first dataset\n\nWe can now create a dataset with a simple text classification task. First, you need to define the dataset settings.\n\n```python\nsettings = rg.Settings(\n    guidelines=\"Classify the reviews as positive or negative.\",\n    fields=[\n        rg.TextField(\n            name=\"review\",\n            title=\"Text from the review\",\n            use_markdown=False,\n        ),\n    ],\n    questions=[\n        rg.LabelQuestion(\n            name=\"my_label\",\n            title=\"In which category does this article fit?\",\n            labels=[\"positive\", \"negative\"],\n        )\n    ],\n)\ndataset = rg.Dataset(\n    name=f\"my_first_dataset\",\n    settings=settings,\n    client=client,\n)\ndataset.create()\n```\n\nNext, we can add records to the dataset.\n\n```bash\npip install datasets\n```\n\n```python\nfrom datasets import load_dataset\n\ndata = load_dataset(\"imdb\", split=\"train[:100]\").to_list()\ndataset.records.log(records=data, mapping={\"text\": \"review\"})\n```\n\n🎉 You have successfully created your first dataset with Argilla. You can now access it in the Argilla UI and start annotating the records.\nNeed more info, check out [our docs](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002F).\n\n## 🥇 Contributors\n\nTo help our community with the creation of contributions, we have created our [community](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fcommunity\u002F) docs. \n\n\u003Ca  href=\"https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fgraphs\u002Fcontributors\">\n\n\u003Cimg  src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_readme_22e9ec34cc3f.png\" \u002F>\n\n\u003C\u002Fa>\n\n","> [!IMPORTANT]\n> 原始作者已转向令人兴奋的新项目！代码库已成熟且稳定，多年来一直为用户提供可靠服务。虽然我们将不再添加新功能，但我们致力于修复 bug（缺陷）并根据需要发布 patch（补丁）。\n> 如果您有兴趣帮助维护或扩展此项目，我们很乐意听取您的意见！请开启一个 issue（问题工单）来讨论成为 maintainer（维护者）事宜——我们正在寻找能够承担项目未来开发责任的专职 contributor（贡献者）。\n>\n\u003Ch1 align=\"center\">\n  \u003Ca href=\"\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Fdvsrepo\u002Fimgs\u002Fraw\u002Fmain\u002Frg.svg\" alt=\"Argilla\" width=\"150\">\u003C\u002Fa>\n  \u003Cbr>\n  Argilla\n  \u003Cbr>\n\u003C\u002Fh1>\n\u003Ch3 align=\"center\">为您的 AI（人工智能）模型构建高质量数据集\u003C\u002Fh3>\n\n\u003Cp align=\"center\">\n\u003Ca  href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Fargilla\u002F\">\n\u003Cimg alt=\"CI\" src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fargilla.svg?style=flat-round&logo=pypi&logoColor=white\">\n\u003C\u002Fa>\n\u003Cimg alt=\"Codecov\" src=\"https:\u002F\u002Fcodecov.io\u002Fgh\u002Fargilla-io\u002Fargilla\u002Fbranch\u002Fmain\u002Fgraph\u002Fbadge.svg?token=VDVR29VOMG\"\u002F>\n\u003Ca href=\"https:\u002F\u002Fpepy.tech\u002Fproject\u002Fargilla\">\n\u003Cimg alt=\"CI\" src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_readme_16c7b5a5f99e.png\">\n\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fnew-space?template=argilla\u002Fargilla-template-space\">\n\u003Cimg src=\"https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fhuggingface\u002Fbadges\u002Fraw\u002Fmain\u002Fdeploy-to-spaces-sm.svg\"\u002F>\n\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n\u003Ca href=\"https:\u002F\u002Ftwitter.com\u002Fargilla_io\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Ftwitter-black?logo=x\"\u002F>\n\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fargilla-io\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flinkedin-blue?logo=linkedin\"\u002F>\n\u003C\u002Fa>\n\u003Ca href=\"http:\u002F\u002Fhf.co\u002Fjoin\u002Fdiscord\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-7289DA?&logo=discord&logoColor=white\"\u002F>\n\u003C\u002Fa>\n\u003C\u002Fp>\n\nArgilla 是一款协作工具，专为需要为项目构建高质量数据集的 AI（人工智能）工程师和领域专家设计。\n\n如果您只想开始使用，[在 Hugging Face Spaces 上部署 Argilla](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fgetting_started\u002Fquickstart\u002F)。好奇并想了解更多？请阅读我们的 [文档](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002F)。\n\n或者，使用您的 Hugging Face 账户登录来体验 Argilla UI（用户界面）：\n\n\u003Cp>\n  \u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fspaces\u002Fargilla\u002Fargilla-template-space\" title=\"Redirect to homepage\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_readme_5ffce7ed8207.png\" alt=\"homepage\" \u002F>\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n## 为什么使用 Argilla？\n\nArgilla 可用于为各种 AI 项目收集人类反馈，例如传统 NLP（自然语言处理，包括文本分类、NER（命名实体识别）等）、LLM（大语言模型，包括 RAG（检索增强生成）、偏好调优等）或多模态模型（文生图等）。Argilla 的编程方法让您能够构建用于持续评估和模型改进的 workflow（工作流）。Argilla 的目标是通过快速迭代正确的数据和模型，确保您的数据工作取得成效。\n\n### 通过数据质量提高 AI 输出质量\n\n计算资源昂贵，输出质量至关重要。我们帮助您专注于数据，从而一次性解决这两个问题的根本原因。Argilla 帮助您**实现并保持**数据的高质量标准。这意味着您可以提高 AI 输出的质量。\n\n### 掌控您的数据和模型\n\n大多数 AI 工具都是黑盒。Argilla 与众不同。我们相信您应该拥有自己的数据和模型。这就是为什么我们为您提供团队所需的所有工具，以便**以最适合您的方式管理数据和模型**。\n\n### 通过快速迭代正确的数据和模型来提高效率\n\n收集数据是一个耗时的过程。Argilla 通过提供一种工具来提供帮助，让您能够**以更具互动性的方式与数据交互**。这意味着您可以使用过滤器、AI 反馈建议和语义搜索快速轻松地标记数据。这样您就可以专注于训练模型和监控其性能。\n\n## 🏘️ 社区\n\n我们是一个开源的社区驱动项目，我们很乐意听取您的意见。以下是一些参与方式：\n\n- [社区聚会](https:\u002F\u002Flu.ma\u002Fembed-checkout\u002Fevt-IQtRiSuXZCIW6FB)：旁听或在我们的双周活动中进行展示。\n\n- [Discord](http:\u002F\u002Fhf.co\u002Fjoin\u002Fdiscord)：在 #argilla-distilabel-general 和 #argilla-distilabel-help 频道获得社区的直接支持。\n\n- [路线图](https:\u002F\u002Fgithub.com\u002Forgs\u002Fargilla-io\u002Fprojects\u002F10\u002Fviews\u002F1)：计划可能会变，但我们喜欢与社区讨论这些，所以欢迎参与。\n\n## 人们用 Argilla 构建什么？\n\n### 开源数据集和模型\n\n社区使用 Argilla 创建令人惊叹的开源 [数据集](https:\u002F\u002Fhuggingface.co\u002Fdatasets?library=library:argilla&sort=trending) 和 [模型](https:\u002F\u002Fhuggingface.co\u002Fmodels?other=distilabel)。\n\n- [Cleaned UltraFeedback 数据集](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fargilla\u002Fultrafeedback-binarized-preferences-cleaned) 用于 fine-tune（微调）[Notus](https:\u002F\u002Fhuggingface.co\u002Fargilla\u002Fnotus-7b-v1) 和 [Notux](https:\u002F\u002Fhuggingface.co\u002Fargilla\u002Fnotux-8x7b-v1) 模型。原始 UltraFeedback 数据集是使用 Argilla UI 过滤器进行整理的，用于发现并报告原始数据生成代码中的 bug（缺陷）。基于此数据整理过程，Argilla 构建了这个新版本的 UltraFeedback 数据集并 fine-tune（微调）了 Notus，在多个 benchmark（基准测试）中优于 Zephyr。\n- [distilabel Intel Orca DPO（直接偏好优化）数据集](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fargilla\u002Fdistilabel-intel-orca-dpo-pairs) 用于 fine-tune（微调）[改进版的 OpenHermes 模型](https:\u002F\u002Fhuggingface.co\u002Fargilla\u002Fdistilabeled-OpenHermes-2.5-Mistral-7B)。该数据集是通过结合 Argilla 中的人工整理和 distilabel 的 AI 反馈构建的，从而产生了改进版的 Intel Orca 数据集，并且优于在原始数据集上 fine-tune（微调）的模型。\n\n### 示例用例\n\n来自 [红十字会](https:\u002F\u002F510.global\u002F)、[Loris.ai](https:\u002F\u002Floris.ai\u002F) 和 [Prolific](https:\u002F\u002Fwww.prolific.com\u002F) 等组织的 AI (人工智能) 团队使用 Argilla 来提高 AI 项目的质量和效率。他们在我们的 [AI 社区聚会](https:\u002F\u002Flu.ma\u002Fembed-checkout\u002Fevt-IQtRiSuXZCIW6FB) 中分享了他们的经验。\n\n- 公益 AI：[红十字会的演示文稿](https:\u002F\u002Fyoutu.be\u002FZsCqrAhzkFU?feature=shared) 展示了红十字会的领域专家和 AI 团队如何通过分类和重定向乌克兰危机难民请求来简化红十字会的支持流程。\n- 客户支持：在 [Loris 聚会](https:\u002F\u002Fyoutu.be\u002FjWrtgf2w4VU?feature=shared) 期间，他们展示了他们的 AI 团队如何使用无监督 (unsupervised) 学习和少样本对比学习 (few-shot contrastive learning) 来帮助他们快速验证并为大量多标签分类器 (multi-label classifiers) 获取标注样本。\n- 研究项目：[Prolific 的展示](https:\u002F\u002Fyoutu.be\u002FePDlhIxnuAs?feature=shared) 宣布了他们与我们平台的集成。他们使用它在标注人员团队之间主动分发数据收集项目。这使得 Prolific 能够为研究项目快速高效地收集高质量数据。\n\n## 👨‍💻 快速开始\n\n### 安装\n\n首先！你可以使用 pip 按如下方式安装 SDK (软件开发工具包)：\n\n```console\npip install argilla\n```\n\n之后，你需要部署 Argilla Server (服务器)。最简单的方法是通过我们的 [免费 Hugging Face Spaces 部署集成](https:\u002F\u002Fhuggingface.co\u002Fnew-space?template=argilla\u002Fargilla-template-space)。\n\n要使用客户端 (client)，你需要导入 `Argilla` 类并使用 API (应用程序接口) URL 和 API key 实例化它。\n\n```python\nimport argilla as rg\n\nclient = rg.Argilla(api_url=\"https:\u002F\u002F[your-owner-name]-[your_space_name].hf.space\", api_key=\"owner.apikey\")\n```\n\n### 创建你的第一个数据集\n\n我们现在可以创建一个带有简单文本分类任务的数据集。首先，你需要定义数据集设置。\n\n```python\nsettings = rg.Settings(\n    guidelines=\"Classify the reviews as positive or negative.\",\n    fields=[\n        rg.TextField(\n            name=\"review\",\n            title=\"Text from the review\",\n            use_markdown=False,\n        ),\n    ],\n    questions=[\n        rg.LabelQuestion(\n            name=\"my_label\",\n            title=\"In which category does this article fit?\",\n            labels=[\"positive\", \"negative\"],\n        )\n    ],\n)\ndataset = rg.Dataset(\n    name=f\"my_first_dataset\",\n    settings=settings,\n    client=client,\n)\ndataset.create()\n```\n\n接下来，我们可以向数据集添加记录。\n\n```bash\npip install datasets\n```\n\n```python\nfrom datasets import load_dataset\n\ndata = load_dataset(\"imdb\", split=\"train[:100]\").to_list()\ndataset.records.log(records=data, mapping={\"text\": \"review\"})\n```\n\n🎉 你已成功使用 Argilla 创建了第一个数据集。你现在可以在 Argilla UI (用户界面) 中访问它并开始标注记录。\n需要更多信息，请查看 [我们的文档](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002F)。\n\n## 🥇 贡献者\n\n为了帮助我们的社区进行贡献创作，我们创建了 [社区](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fcommunity\u002F) 文档。\n\n\u003Ca  href=\"https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fgraphs\u002Fcontributors\">\n\n\u003Cimg  src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_readme_22e9ec34cc3f.png\" \u002F>\n\n\u003C\u002Fa>","# Argilla 快速上手指南\n\nArgilla 是一个面向 AI 工程师和领域专家的协作工具，旨在帮助构建高质量的 AI 数据集（支持 NLP、LLM、多模态等场景）。\n\n> **项目状态提示**：原核心团队已转向新项目，当前代码库处于成熟稳定阶段。后续主要专注于修复 Bug 和发布补丁，不再添加新功能。欢迎社区贡献者参与维护。\n\n## 1. 环境准备\n\n- **操作系统**：支持主流操作系统（Linux \u002F macOS \u002F Windows）\n- **运行环境**：Python 3.8+ 推荐\n- **账号准备**：需要 Hugging Face 账号（用于部署服务和登录 UI）\n- **依赖管理**：确保已安装 `pip`\n\n## 2. 安装步骤\n\n### 安装 SDK\n在终端中执行以下命令安装 Argilla 客户端：\n\n```console\npip install argilla\n```\n\n为了运行后续的数据示例，建议同时安装 `datasets` 库：\n\n```console\npip install datasets\n```\n\n### 部署服务端\n最简单的部署方式是通过 Hugging Face Spaces 免费部署：\n\n1. 访问 [Argilla Template Space](https:\u002F\u002Fhuggingface.co\u002Fnew-space?template=argilla\u002Fargilla-template-space)\n2. 登录 Hugging Face 账号并创建 Space\n3. 记录生成的空间地址（API URL）和 API Key\n\n## 3. 基本使用\n\n### 连接客户端\n使用部署得到的 API URL 和 API Key 初始化客户端：\n\n```python\nimport argilla as rg\n\nclient = rg.Argilla(api_url=\"https:\u002F\u002F[your-owner-name]-[your_space_name].hf.space\", api_key=\"owner.apikey\")\n```\n\n### 创建数据集\n定义数据集设置（如字段、标注问题），并创建数据集：\n\n```python\nsettings = rg.Settings(\n    guidelines=\"Classify the reviews as positive or negative.\",\n    fields=[\n        rg.TextField(\n            name=\"review\",\n            title=\"Text from the review\",\n            use_markdown=False,\n        ),\n    ],\n    questions=[\n        rg.LabelQuestion(\n            name=\"my_label\",\n            title=\"In which category does this article fit?\",\n            labels=[\"positive\", \"negative\"],\n        )\n    ],\n)\ndataset = rg.Dataset(\n    name=f\"my_first_dataset\",\n    settings=settings,\n    client=client,\n)\ndataset.create()\n```\n\n### 添加记录\n加载数据并上传到数据集：\n\n```python\nfrom datasets import load_dataset\n\ndata = load_dataset(\"imdb\", split=\"train[:100]\").to_list()\ndataset.records.log(records=data, mapping={\"text\": \"review\"})\n```\n\n完成上述步骤后，即可在 Argilla UI 中访问数据集并开始标注。更多详细信息请参阅 [官方文档](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002F)。","某金融科技公司的 AI 团队正在优化基于大模型的客服系统，需要贷款领域专家协助标注数千条问答数据，以确保回复准确合规且无幻觉。\n\n### 没有 argilla 时\n- 数据散落在多个 Excel 文件中，版本管理混乱，工程师与专家之间反复确认耗费大量时间。\n- 缺乏智能筛选机制，领域专家必须逐条审阅海量普通数据，难以聚焦高风险错误样本。\n- 标注标准依赖口头沟通，一致性差，导致模型训练后效果波动，无法量化数据质量对模型的影响。\n\n### 使用 argilla 后\n- argilla 提供统一协作平台，双方在线实时标注与评论，数据版本清晰可控，沟通成本降低 70%。\n- 利用语义搜索和 AI 建议预筛选功能，专家只需关注置信度低的样本，标注效率提升 3 倍以上。\n- 内置质量评估看板实时监控标注一致性，确保每次模型迭代都有高质量数据支撑，合规风险显著下降。\n\nargilla 通过标准化的人机协作流程，让数据质量成为模型效果的可控变量，从根本上提升了金融客服系统的可靠性。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fargilla-io_argilla_5ffce7ed.png","argilla-io","Argilla","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fargilla-io_5953542f.png","Building the open-source feedback layer for LLMs",null,"contact@argilla.io","argilla_io","https:\u002F\u002Fargilla.io","https:\u002F\u002Fgithub.com\u002Fargilla-io",[82,86,90,94,98,102,106,110,114,118],{"name":83,"color":84,"percentage":85},"Python","#3572A5",59.2,{"name":87,"color":88,"percentage":89},"Jupyter Notebook","#DA5B0B",21.3,{"name":91,"color":92,"percentage":93},"Vue","#41b883",8.1,{"name":95,"color":96,"percentage":97},"TypeScript","#3178c6",7.8,{"name":99,"color":100,"percentage":101},"JavaScript","#f1e05a",2.5,{"name":103,"color":104,"percentage":105},"SCSS","#c6538c",0.5,{"name":107,"color":108,"percentage":109},"CSS","#663399",0.4,{"name":111,"color":112,"percentage":113},"Dockerfile","#384d54",0.1,{"name":115,"color":116,"percentage":117},"Shell","#89e051",0,{"name":119,"color":120,"percentage":117},"HTML","#e34c26",4929,479,"2026-04-09T19:36:40","Apache-2.0","未说明",{"notes":127,"python":125,"dependencies":128},"项目已进入维护模式，不再新增功能，仅修复 bug。需部署 Argilla Server（推荐通过 Hugging Face Spaces 免费部署），客户端使用 Python SDK 连接服务器进行数据标注和管理。",[64,129],"datasets",[15,13,14,16,35],[132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148],"human-in-the-loop","natural-language-processing","mlops","developer-tools","text-labeling","annotation-tool","nlp","machine-learning","active-learning","weak-supervision","weakly-supervised-learning","text-annotation","llm","ai","gpt-4","rlhf","langchain",5,"2026-03-27T02:49:30.150509","2026-04-11T16:55:55.679962",[153,158,163,167,172,177],{"id":154,"question_zh":155,"answer_zh":156,"source_url":157},4837,"Argilla server 是否可以通过 Conda 安装？","官方文档曾显示支持 Conda 安装，但包一度未发布。目前已有社区成员将其添加到 conda-forge。建议优先检查 conda-forge 最新状态，或使用 pip 安装以减少维护开销。","https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F1942",{"id":159,"question_zh":160,"answer_zh":161,"source_url":162},4838,"如何获取已推送到 Argilla 或 HuggingFace 的 FeedbackDataset URL？","Argilla URL 格式为 `\u003CAPI_URL>\u002F\u003CDATASET_ID>\u002Fannotation-mode`。HuggingFace Hub URL 格式为 `https:\u002F\u002Fhuggingface.co\u002F\u003CREPO_ID>`。用户可根据此结构手动构建访问链接，以便轻松访问数据集。","https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F3120",{"id":164,"question_zh":165,"answer_zh":166,"source_url":162},4839,"向 Argilla 推送数据集时遇到 403 Forbidden 错误如何解决？","如果 Argilla 端点位于 IAP 背后，检查代码中是否添加了额外的 labels。有用户反馈移除添加额外 labels 的代码部分后解决了 403 错误。同时确保使用的 workspace 权限正确（如用户是否为 admin）。",{"id":168,"question_zh":169,"answer_zh":170,"source_url":171},4840,"如何使用 Argilla 监控 FastAPI  inference 端口的预测结果？","可以使用 `RubrixLogHTTPMiddleware` 中间件。在 FastAPI app 中添加 middleware，指定 `api_endpoint` 和 `dataset` 名称。支持 Hugging Face transformers 和 spaCy pipeline。示例：`app.add_middleware(RubrixLogHTTPMiddleware, api_endpoint=\"\u002Fpredict\", dataset=\"monitoring_dataset_v1\")`。","https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F427",{"id":173,"question_zh":174,"answer_zh":175,"source_url":176},4841,"Token Classification 中表情符号导致重叠 span 错误及标注错误怎么办？","这是一个已知问题。临时解决方法是清除所有标注（clearing all annotations），然后重新进行标注并保存。避免在预测标注不匹配时直接使用特定表情符号。","https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F2353",{"id":178,"question_zh":179,"answer_zh":180,"source_url":181},4842,"遇到 UI Bug 或需要贡献代码时如何获取帮助？","可以通过 Slack 联系维护者，或预约 Calendly Office Hours (https:\u002F\u002Fcalendly.com\u002Fargilla-office-hours\u002F30min) 进行讨论。也可以直接提交 Pull Request。","https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F3290",[183,188,193,198,203,208,213,218,223,228,233,238,243,248,253,258,263,268,273,278],{"id":184,"version":185,"summary_zh":186,"released_at":187},202975,"v2.8.0","# 🔆 Release highlights\r\n\r\nThe **v2.8.0** comes with a better OAuth integration, and some other improvements and bug fixes.\r\n\r\n### Better OAuth integration\r\n\r\nNow, you can extend the supported providers by adding social backends classes in the configuration file:\r\n\r\n```yaml\r\n\r\nproviders:\r\n  - name: apple-id\r\n    client_id: \"\u003Cclient_id>\" # You can use the ARGILLA_OAUTH2_APPLE_ID_CLIENT_ID environment variable\r\n    client_secret: \"\u003Cclient_secret>\" # You can use the ARGILLA_OAUTH2_APPLE_ID_CLIENT_SECRET environment variable\r\n\r\nextra_backends:\r\n    - social_core.backends.apple.AppleIdAuth # Register the Apple OAuth2 provider backend\r\n...\r\n```\r\n\r\nAlso, the KeyCloak provider is supported by default.\r\n\r\n\r\nYou can visit [the docs](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Freference\u002Fargilla-server\u002Foauth2_configuration) for more info.\r\n\r\n\r\nSome relevant improvements and bugfixes are:\r\n\r\n* Add keycloak SSO by @paulbauriegel in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5711\r\n* [BUGFIXES] Fixing error when using PostgreSQL by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5795\r\n* [BUGFIX] Redirect slash when defining `ARGILLA_BASE_URL` by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5796\r\n* [BUGFIX] get dataset settings when using `client.datasets.list()` by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5810\r\n* [FEAT][HELM] set ES SSL verification by @omarmoo5 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5807\r\n* feat: Add Japanese translation by @Tomoya-Matsubara in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5816\r\n\r\n## New Contributors\r\n* @omarmoo5 made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5807\r\n* @patrickfleith made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5806\r\n* @Tomoya-Matsubara made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5816\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.7.1...v2.8.0","2025-03-11T08:58:41",{"id":189,"version":190,"summary_zh":191,"released_at":192},202976,"v2.7.1","## What's Changed\r\n* [BUGFIX] Prevent sending auth headers for public requests by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5804\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.7.0...v2.7.1","2025-02-06T14:33:25",{"id":194,"version":195,"summary_zh":196,"released_at":197},202977,"v2.7.0","# 🔆 Release highlights\r\n\r\nThe v2.7.0 release includes some minor improvements and bugfixes\r\n\r\n### Similarity score\r\n\r\nReturn similarity score when searching by similarity \r\n```python\r\n\r\nimport argilla as rg\r\n\r\n...\r\n\r\nfor record, score in dataset.records(similar=rg.Similar(\r\n    name=\"vector\",\r\n    value=[0.1, 0.2, 0.3],\r\n)):\r\n   ...\r\n```\r\n\r\nOther relevant improvements and bugfixes are:\r\n\r\n- Create users and workspaces with predefined IDs (#5786)\r\n- Prevent index errors with empty chat fields (#5787)\r\n- Pass SSL verify parameter when configuring the Argilla client (#5789)\r\n\r\n\r\n## New Contributors\r\n* @hamelsmu made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5784\r\n* @louisbrulenaudet made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5766\r\n* @Saikiranbonu1661 made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5778\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.6.0...v2.7.0","2025-01-21T13:39:59",{"id":199,"version":200,"summary_zh":201,"released_at":202},202978,"v2.6.0","# 🔆 Release highlights\r\n\r\n## Push to hub\r\n\r\nExport your dataset to the Hugging Face Hub directly from the Argilla UI:\r\n \r\n1️⃣ Go to your dataset \r\n2️⃣ Click on Push to Hub\r\n3️⃣ Make sure you include your username or organization and a Hub Access Token with write permissions\r\n \r\n\u003Cimg width=\"1624\" alt=\"Screenshot of the exporting feature\" src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fc8575ec0-47f9-4e96-908c-b1ad2fe4d7ac\" \u002F>\r\n\r\n## Share your progress\r\n\r\nShare your annotation progress on any Argilla dataset with the world!\r\n\r\n1️⃣ In your dataset, click on \"Share progress\"\r\n2️⃣ Open your preferred social media platform\r\n3️⃣ Start a post and paste the copied text\r\n4️⃣ Publish and share with the world!\r\n\r\n\u003Cimg width=\"1624\" alt=\"Screenshot of the sharing feature\" src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F89cfcb94-2a54-4416-a0fa-6a1c50f6f180\" \u002F>\r\n\r\n\r\n## Update user data\r\nYou can update all information of a user. Here's an example of how to update the role of a user:\r\n\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003CARGILLA_API_URL>\", api_key=\"\u003CARGILLA_API_KEY>\")\r\n\r\nuser = client.users(\"username\")\r\nuser.role = \"admin\"\r\nuser.update()\r\n```\r\n\r\n\r\n## Change record fields\r\nYou can now update the content of record fields.\r\n\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003CARGILLA_API_URL>\", api_key=\"\u003CARGILLA_API_KEY>\")\r\n\r\ndataset = client.datasets(\"my_dataset\")\r\nrecord = next(dataset.records(limit=1))\r\nrecord.fields[\"text\"] = \"this is my updated text\"\r\nrecord.update()\r\n\r\n# or several records at once\r\nrecords = list(dataset.records(...))\r\n\r\nfor record in records:\r\n    record.fields[\"text\"] = \"this is my updated text\"\r\n\r\ndataset.records.log(records)\r\n```\r\n\r\n\r\n## Changelog v2.6.0\r\n\r\n* [ENHANCEMENT] `argilla server`: Return users on dataset progress by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5701\r\n* [CI] Update base docker image by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5705\r\n* 🔥 Fix highlight on bulk by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5698\r\n* 🔥 Improve plugins loaders by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5697\r\n* fix: :bug: Send visible_options prop only when the questions has more… by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5716\r\n* [FEATURE] UI - update dataset list by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5684\r\n* [Docs] configure issue form by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5703\r\n* Assign field to a span question by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5717\r\n* [FEATURE]: Adding Functionality To Update Users by @sean-hickey-wf in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5615\r\n* [CI] Fix argilla-frontend build by adding the `package-lock.json` file by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5731\r\n* fix: UI - use `last_activity_at` in the dataset list by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5741\r\n* [CI] fix install deps using python.3.13  by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5745\r\n* [BUGFIX] prevent errors when updating user by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5742\r\n* [BUGFIX] `argilla`: prevent enum literal validation errors by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5679\r\n* 🎉 Improve styles file weight by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5724\r\n* [FEATURE] Add support to update record fields by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5685\r\n* 🚑 feat\u002Fcheck version by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5738\r\n* [BUGFIX] [TESTS] Remove custom isoformat parsing and let pydantic do the work by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5752\r\n* [BUGFIX] Fetch dataset setting when iterate `client.datasets` by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5753\r\n* [BUGFIX] `argilla`: review datasest import with new export flow by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5756\r\n* [FEATURE-BRANCH] feat: dataset export to the Hub by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5730\r\n* Feat\u002Fimprove export hover by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5764\r\n* [CHORE] Add missing fixed entries by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5765\r\n* ✨ Add share component by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5727\r\n* [RELEASES] v2.6.0 by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5762\r\n\r\n## New Contributors\r\n\r\n* @sean-hickey-wf made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5615\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.5.0...v2.6.0","2024-12-18T15:46:15",{"id":204,"version":205,"summary_zh":206,"released_at":207},202979,"v2.5.0","# 🔆 Release highlights\r\n\r\n## Webhooks\r\n\r\nYou can now create and manage webhooks to support your workflows! \r\n\r\nWebhooks allow you to submit real-time information to other applications whenever a specific event occurs within Argilla. Here's an example of how you can set up a webhook in Argilla: \r\n\r\n```python\r\n\r\nimport argilla as rg\r\n\r\n@rg.webhook_listener(\"record.completed\")\r\nasync def record_completed(record: rg.Record, **kwargs):\r\n    print (f\"Record {record.id} has been completed\")\r\n```\r\n\r\nVisit the [Argilla documentation](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fhow_to_guides\u002Fwebhooks) for more information.\r\n\r\n## A redesigned home page\r\n\r\n\u003Cimg width=\"1512\" alt=\"Captura de pantalla 2024-11-29 a las 12 49 32\" src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fe79448b1-31f0-4b7a-866d-2726973e6ca7\">\r\n\r\nArgilla's home page has been redesigned to provide a better user experience. The new home page now shows a new \r\ndataset card view, which provides a better overview of the datasets and annotation progress.\r\n\r\n\r\n## Python 3.13 and Pydantic v2 support\r\n\r\nThe Argilla server (and SDK) now supports Python 3.13 and Pydantic 2.0.0. This means that you can now install and use both SDK and server with Python 3.13 in the same Python environment!\r\n\r\n```bash\r\npip install argilla\r\npip install argilla-server\r\n\r\npython -m argilla_server\r\n```\r\n\r\n## Other improvements\r\n\r\n- We've added a **high contrast** theme to help users with visual impairments. To change the theme go to \"My settings\" and choose your preferred theme. Thanks @paulbauriegel for this! 🎉\r\n- You can **select the language** that you'd like to display in the Argilla UI, also from the \"My settings\" page. Your language isn't there? Visit the [Argilla documentation](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fcommunity\u002Fadding_language\u002F) to learn how you can add yours.\r\n\r\n## Changelog v2.5.0\r\n* [BUGFIX] argilla server: Prevent update `dataset.updated_at` when updating `dataset.last_activity_at` column by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5656\r\n* Docs: Typo Fix by @RahulK4102 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5642\r\n* [Docs] : fix typos in docs by @FarukhS52 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5612\r\n* [CONFIG] `argilla server`: Review and update dependencies by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5649\r\n* Improve German translation and some aria attributes by @paulbauriegel in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5658\r\n* Add a high-contrast theme & improvements for the forced-colors mode by @paulbauriegel in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5661\r\n* [BUGFIX]: argilla server: install default `psycopg2` driver used by alembic by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5672\r\n* (Typo): Update README.md by @kaleaditya779 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5655\r\n* [CONFIG] `argilla`:  Add Python 3.13 support by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5652\r\n* [ENHANCEMENT][REFACTOR] SDK: allow to remove settings by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5584\r\n* fix: improve logic for detecting ChatFields by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5667\r\n* [BUGFIX] `argilla frontend`: Avoid call router.push when opening an external URL by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5675\r\n* [BUGFIX] visualisation of highlighted text by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5678\r\n* Dataset Creation UI fixes & Improvements by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5670\r\n* [BUGFIX] Show `Import data` if user is admin or owner by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5688\r\n* docs: Add missing server configuration env vars by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5676\r\n* [REFACTOR] `argilla server`: Remove passlib dependency by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5674\r\n* [FEATURE] UI - Add language selection in user settings by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5690\r\n* ⚡️ Fix highlight text by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5693\r\n* [FEATURE] Add Webhooks by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5467\r\n* 🚑 Add missing translation by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5696\r\n* Docs - Add docs for adding a language by @paulbauriegel in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5640\r\n* [BUGFIX] `argilla server`: Prevent passing non-string values to text fields by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5682\r\n* [REFACTOR] `argilla server`: using pydantic v2 by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5666\r\n* fix: Resolve failing tests after pydantic V2 merge by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5700\r\n* [DOCS] Deploy on spaces review by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5704\r\n* [REFACTOR] `argilla`: Align questions to `Resource` API by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpu","2024-11-29T12:28:59",{"id":209,"version":210,"summary_zh":211,"released_at":212},202980,"v2.4.1","This release includes some `argilla-server` fixes:\r\n\r\n- Fixed redirection problems after users sign-in using HF OAuth. ([#5635](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5635))\r\n- Fixed highlighting of the searched text in text, span and chat fields ([#5678](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5678))\r\n- Fixed validation for rating question when creating a dataset ([#5670](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5670))\r\n- Fixed question name based on question type when creating a dataset ([#5670](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5670))\r\n- Fixed error so now `_touch_dataset_last_activity_at` function is not updating dataset's `updated_at` column. ([#5656](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5656))\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.4.0...v2.4.1","2024-11-11T11:37:46",{"id":214,"version":215,"summary_zh":216,"released_at":217},202981,"v2.4.0","# 🔆 Release highlights\r\n\r\n## Import Hub datasets from the UI\r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F3ccb808e-6242-480d-878a-7cbe26539619\r\n\r\nIn this release, we’ve focused all of our efforts in bringing you a new feature to import datasets from the Hugging Face Hub directly within our UI, making it easier and faster to get started with your AI projects.\r\n\r\nTo get started, click on the “Import dataset from Hugging Face” button and paste the repo id of the dataset you want to use. Argilla will process the columns of the dataset and map them to Fields or Questions. Then, you can add more questions or remove any unnecessary fields by selecting the “No mapping” options. All the changes you make will be automatically reflected in the preview. \r\n\r\nOnce you’re happy with the result you simply need to provide a name for your dataset, select a workspace and (if applicable) a split. Then, Argilla will start importing the dataset. \r\n\r\n>[!NOTE]\r\n> If your dataset is bigger than 10k records, at this stage Argilla will only import the first 10k. You can import the rest of the dataset using the Argilla SDK: simply click on the “Import data” button in the dataset and use the code snippet provided. \r\n\r\nIf you want to make extra changes, like customizing the titles of your fields and questions, don’t worry, you can always go back to the Dataset Settings page after the dataset has been created.\r\n\r\nLearn more about this new feature [in our docs](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fgetting_started\u002Fquickstart\u002F#create-your-first-dataset).\r\n\r\n## Deploy an Argilla Space directly from the SDK\r\n\r\nIf you're working from the SDK and don't want to leave to start your Argilla server, you can start an Argilla deployment on Spaces with a simple line of code:\r\n\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla.deploy_on_spaces(api_key=\"12345678\")\r\n````\r\n\r\nLearn more [in our docs](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Freference\u002Fargilla\u002Fclient\u002F?h=deploy_on_spaces#usage-examples).\r\n\r\n## Changelog v2.4.0\r\n* Enhancement\u002Fimprove-error-messaging-for-role-forbidden by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5554\r\n* refactor: add `DatasetPublishValidator` class by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5568\r\n* feat: set CREATOR_USER_ID to avoid difficulties with creation in orga… by @davidberenstein1957 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5556\r\n* [Refactor] remove name validations for dataset workspaces and usernames by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5575\r\n* fix: SPACES_CREATOR_USER_ID -> SPACE_CREATOR_USER_ID by @davidberenstein1957 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5590\r\n* [FIX] Prevent duplicated field text by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5592\r\n* feat: Add basic support to bool features by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5576\r\n* feat: Add support to other than str values for terms metadata properties by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5594\r\n* [BUGFIX] argilla server: parse fields for record schemas by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5600\r\n* correct phrase on docs: \"a recod question\" -> \"a question\" by @HeAndres in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5599\r\n* docs: update filter_dataset.md by @eltociear in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5571\r\n* feat: 5108 feature add method to deploy on spaces through huggingface hub by @davidberenstein1957 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5547\r\n* docs: add quickstart update for deploy on spaces by @davidberenstein1957 in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5550\r\n* Typo: missing comma by @ACMCMC in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5565\r\n* Typo fix by @ACMCMC in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5566\r\n* Fix typo by @ACMCMC in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5567\r\n* [REFACTOR] argilla server: moving all record validators by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5603\r\n* [BUGFIX] argilla server: Prevent convert `ChatFieldValue` objects by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5605\r\n* Introducing Argilla Guru on Gurubase.io by @kursataktas in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5608\r\n* [PERF][IMPROVEMENT] argilla server: improve computation for dataset progress and metrics by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5618\r\n* [PERF] argilla server: Reduce general transaction time by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5609\r\n* fix: Prevent compute metrics for draft datasets by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5624\r\n* Refine German translations and update non-localized UI elements by @paulbauriegel in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5632\r\n* [BUGFIX] Catch None in image feature columns by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5626\r\n* feat: added support for `with_vectors` with query filter in sdk by @bharath97-git in https:\u002F\u002Fgithub.com\u002F","2024-10-30T17:05:51",{"id":219,"version":220,"summary_zh":221,"released_at":222},202982,"v2.3.1","## What's Changed\r\n\r\nThis is a patch release fixing an error listing current user datasets:\r\n\r\n- Fixed error listing current user datasets and not filtering by current user id. ([#5583](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5583))\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.3.0...v2.3.1","2024-10-08T09:45:50",{"id":224,"version":225,"summary_zh":226,"released_at":227},202983,"v2.3.0","# 🌟 Release highlights\r\n\r\n## Custom Fields: the most powerful way to build custom annotation tasks\r\nWe heard you. This new type of field gives you full control over how data is presented to annotators. \r\n\r\nWith custom fields, you can use your own CSS, HTML, and even Javascript (welcome interactive fields!). Moreover, you can populate your fields with custom structures like `custom_field={\"image1\": ..., \"image_2\": ..., etc.}`.\r\n\r\nHere's an example: \r\n\r\n> Imagine you want to show two images and a prompt to your users. \r\n\r\n### With a custom field\r\n\r\nWith the new custom field, you can configure something like this:\r\n\r\n\u003Cimg width=\"952\" alt=\"Screenshot 2024-10-04 at 13 04 28\" src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F1e85a5e5-7e35-4912-8f32-aeed4e32adfe\">\r\n\r\nAnd you can set this up with a few lines of code:\r\n\r\n```python\r\ncss_template = \"\"\"\r\n\u003Cstyle>\r\n#container {\r\n    display: flex;\r\n    flex-direction: column;\r\n    font-family: Arial, sans-serif;\r\n}\r\n.prompt {\r\n    margin-bottom: 10px;\r\n    font-size: 16px;\r\n    line-height: 1.4;\r\n    color: #333;\r\n    background-color: #f8f8f8;\r\n    padding: 10px;\r\n    border-radius: 5px;\r\n    box-shadow: 0 1px 3px rgba(0,0,0,0.1);\r\n}\r\n.image-container {\r\n    display: flex;\r\n    gap: 10px;\r\n}\r\n.column {\r\n    flex: 1;\r\n    position: relative;\r\n}\r\nimg {\r\n    max-width: 100%;\r\n    height: auto;\r\n    display: block;\r\n}\r\n.image-label {\r\n    position: absolute;\r\n    top: 10px;\r\n    right: 10px;\r\n    background-color: rgba(255, 255, 255, 0.7);\r\n    color: black;\r\n    padding: 5px 10px;\r\n    border-radius: 5px;\r\n    font-weight: bold;\r\n}\r\n\u003C\u002Fstyle>\r\n\"\"\"\r\n\r\nhtml_template = \"\"\"\r\n\u003Cdiv id=\"container\">\r\n    \u003Cdiv class=\"prompt\">\u003Cstrong>Prompt:\u003C\u002Fstrong> {{record.fields.images.prompt}}\u003C\u002Fdiv>\r\n    \u003Cdiv class=\"image-container\">\r\n        \u003Cdiv class=\"column\">\r\n            \u003Cimg src=\"{{record.fields.images.image_1}}\" \u002F>\r\n            \u003Cdiv class=\"image-label\">Image 1\u003C\u002Fdiv>\r\n        \u003C\u002Fdiv>\r\n        \u003Cdiv class=\"column\">\r\n            \u003Cimg src=\"{{record.fields.images.image_2}}\" \u002F>\r\n            \u003Cdiv class=\"image-label\">Image 2\u003C\u002Fdiv>\r\n        \u003C\u002Fdiv>\r\n    \u003C\u002Fdiv>\r\n\u003C\u002Fdiv>\r\n\"\"\"\r\n\r\ncustom_field = rg.CustomField(\r\n    name=\"images\",\r\n    template=css_template + html_template,\r\n)\r\n\r\n# and the log records like this\r\nrg.Record(\r\n    fields={\r\n        \"prompt\": prompt,\r\n         \"image_1\": schnell_uri,\r\n         \"image_2\": dev_uri,\r\n   }\r\n)\r\n```\r\n\r\n### Before the custom field\r\n\r\nBefore this release, you were forced to use two `ImageField` and a `TextField`, which would be displayed sequentially, limiting the ability to compare the images side-by-side, with clear labels, prompt text, etc. It would look like this:\r\n\r\n\u003Cimg width=\"736\" alt=\"Screenshot 2024-10-04 at 14 13 52\" src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F03ac0a7d-04a6-4f53-96f9-40a070d1c130\">\r\n\r\n### How to get started with custom fields\r\n\r\nHere we've shown a basic presentation-oriented custom field but you can set up anything you can think of, leveraging JS, html, and css. Imagination is the limit!\r\n\r\nTo get started check the docs: https:\u002F\u002Fdocs.argilla.io\u002Fv2.3\u002Fhow_to_guides\u002Fcustom_fields\u002F\r\n\r\n\r\n\r\n##  Other features\r\n- Support for similarity search [from the SDK](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fhow_to_guides\u002Fquery\u002F#similarity-search) and other search and [filtering improvements](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fhow_to_guides\u002Fquery\u002F#available-fields).\r\n- New Helm chart [deployment configuration](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Ftree\u002Fv2.3.0\u002Fexamples\u002Fdeployments\u002Fk8s\u002Fargilla-chart).\r\n- Support credentials from colab secrets.\r\n\r\nAn other changes and fixes \r\n\r\n### Changed\r\n\r\n- Changed the __repr__ method for `SettingsProperties` to display the details of all the properties in `Setting` object. ([#5380](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F5380))\r\n- Changed error messages when creating datasets with insufficient permissions. ([#5540](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5554))\r\n\r\n### Fixed\r\n\r\n- Fixed serialization of `ChatField` when collecting records from the hub and exporting to `datasets`. ([#5554](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5553))\r\n- Fixed error when creating default user with existing default workspace. ([#5558](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5558))\r\n- Fixed the deployment yaml used to create a new Argilla server in K8s. Added `USERNAME` and `PASSWORD` to the environment variables of pod template. ([#5434](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F5434))\r\n- Fix autofill form on sign-in page [#5522](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5522)\r\n- Support copy on clipboard for no secure context [#5535](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5535)\r\n\r\n\r\n## New Contributors\r\n* @not-lain made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5541\r\n\r\n## Thanks to\r\n* @bikash119 for Helm chart in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5512\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.2.2...v2.3.0","2024-10-03T15:11:46",{"id":229,"version":230,"summary_zh":231,"released_at":232},202984,"v2.2.2","## What's Changed\r\n\r\nThis is a patch release with certain fixes to the SDK\r\n\r\n### Fixed\r\n\r\n- Fixed `from_hub` with unsupported column names. ([#5524](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5524))\r\n- Fixed `from_hub` with missing dataset `subset` configuration value. ([#5524](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5524))\r\n\r\n### Changed\r\n\r\n- Changed `from_hub` to only generate fields not questions for strings in the dataset. ([#5524](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5524))\r\n\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.2.1...v2.2.2","2024-09-25T14:55:23",{"id":234,"version":235,"summary_zh":236,"released_at":237},202985,"v2.2.1","## What's Changed\r\n\r\nThis is a patch release with certain fixes to the SDK:\r\n\r\n- Fixed `from_hub` errors when columns names contain uppercase letters. ([#5523](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5523))\r\n- Fixed `from_hub` errors when class feature values contains unlabelled values. ([#5523](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5523))\r\n- Fixed `from_hub` errors when loading cached datasets. ([#5523](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5523))\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.2.0...v2.2.1","2024-09-23T11:52:13",{"id":239,"version":240,"summary_zh":241,"released_at":242},202986,"v2.2.0","# 🌟 Release highlights\r\n\r\n> [!IMPORTANT]\r\n> Argilla server `2.2.0` adds support for **background jobs**. These background jobs allow us to run jobs that might take a long time at request time. For this reason we now rely on [Redis](https:\u002F\u002Fredis.io) and [Python RQ](https:\u002F\u002Fpython-rq.org) workers. \r\n>\r\n> So to upgrade your Argilla instance to version `2.2.0` you need to have an available Redis server. See the [Redis get-started documentation](https:\u002F\u002Fredis.io\u002Fdocs\u002Flatest\u002Fget-started\u002F) for more information or the [Argilla server configuration documentation](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Freference\u002Fargilla-server\u002Fconfiguration\u002F).\r\n>\r\n> If you have deployed Argilla server using the docker-compose.yaml, you should download the [docker-compose.yaml](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fblob\u002Fmain\u002Fexamples\u002Fdeployments\u002Fdocker\u002Fdocker-compose.yaml) file again to bring the latest changes to set Redis and Argilla workers\r\n>\r\n> Workers are needed to process Argilla's background jobs. You can run Argilla workers with the following command:\r\n> ```sh\r\n> python -m argilla_server worker\r\n> ```\r\n\r\n## ChatField: working with text conversations in Argilla\r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F563dd57e-6f99-4b04-9bfa-c930b2a1625c\r\n\r\nYou can now work with text conversations natively in Argilla using the new `ChatField`. It is especially designed to make it easier to build datasets for conversational Large Language Models (LLMs), displaying conversational data in the form of a chat.\r\n\r\nHere's how you can create a dataset with a `ChatField`:\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003Capi_url>\", api_key=\"\u003Capi_key>\")\r\n\r\nsettings = rg.Settings(\r\n\tfields=[rg.ChatField(name=\"chat\")],\r\n\tquestions=[...]\r\n)\r\n\r\ndataset = rg.Dataset(\r\n\tname=\"chat_dataset\",\r\n\tsettings=settings,\r\n\tworkspace=\"my_workspace\",\r\n\tclient=client\r\n)\r\n\r\ndataset.create()\r\n\r\nrecord = rg.Record(\r\n\tfields={\r\n\t\t\"chat\": [\r\n\t\t\t{\"role\": \"user\", \"content\": \"Hello World, how are you?\"},\r\n\t\t\t{\"role\": \"assistant\", \"content\": \"I'm doing great, thank you!\"}\r\n\t\t]\r\n\t}\r\n)\r\n\r\ndataset.records.log([record])\r\n```\r\nRead more about how to use this new field type [here](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fhow_to_guides\u002Fdataset\u002F#fields) and [here](https:\u002F\u002Fdocs.argilla.io\u002Fdev\u002Fhow_to_guides\u002Frecord\u002F#add-records).\r\n\r\n## Adjust task distribution settings\r\nYou can now modify task distribution settings at any time, and Argilla will automatically recalculate the completed and pending records. When you update this setting, records will be removed from or added to the pending queues of your team accordingly.\r\n\r\nYou can make this change in the dataset settings page or using the SDK:\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003Capi_url>\", api_key=\"\u003Capi_key>\")\r\n\r\ndataset = client.datasets(\"my_dataset\")\r\ndataset.settings.distribution.min_submitted = 2\r\ndataset.update()\r\n````\r\n## Track team progress from the SDK\r\nThe Argilla SDK now provides a way to retrieve data on annotation progress. This feature allows you to monitor the number of completed and pending records in a dataset and also the number of responses made by each user:\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003Capi_url>\", api_key=\"\u003Capi_key>\")\r\n\r\ndataset = client.datasets(\"my_dataset\")\r\n\r\nprogress = dataset.progress(with_users_distribution=True)\r\n````\r\nThe expected output looks like this:\r\n```json\r\n{\r\n    \"total\": 100,\r\n    \"completed\": 50,\r\n    \"pending\": 50,\r\n    \"users\": {\r\n        \"user1\": {\r\n           \"completed\": { \"submitted\": 10, \"draft\": 5, \"discarded\": 5},\r\n           \"pending\": { \"submitted\": 5, \"draft\": 10, \"discarded\": 10},\r\n        },\r\n        \"user2\": {\r\n           \"completed\": { \"submitted\": 20, \"draft\": 10, \"discarded\": 5},\r\n           \"pending\": { \"submitted\": 2, \"draft\": 25, \"discarded\": 0},\r\n        },\r\n        ...\r\n}\r\n````\r\nRead more about this feature [here](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fhow_to_guides\u002Fdistribution\u002F#track-your-teams-progress).\r\n\r\n## Automatic settings inference\r\nWhen you import a dataset using the from_hub method, Argilla will automatically infer the settings, such as the fields and questions, based on the dataset Features. This will save you time and effort when working with datasets from the Hub.\r\n\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003Capi_url>\", api_key=\"\u003Capi_key>\")\r\n\r\ndataset = rg.Dataset.from_hub(\"yahma\u002Falpaca-cleaned\")\r\n````\r\n\r\n## Task templates\r\nWe've added pre-built templates for common dataset types, including text classification, ranking, and rating tasks. These templates provide a starting point for your dataset creation, with pre-configured settings. You can use these templates to get started quickly, without having to configure everything from scratch.\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(api_url=\"\u003Capi_url>\", api_key=\"\u003Capi_key>\")\r\n\r\nsettings = rg.Settings.for_classification(labels=[\"positive\", \"negative\"])\r\n\r\ndataset = rg.Dataset(\r\n\tname=\"my_dataset\",\r\n\tsettings=settings,\r\n\tclient=c","2024-09-19T14:59:38",{"id":244,"version":245,"summary_zh":246,"released_at":247},202987,"v2.1.0","# 🌟 Release highlights \r\n\r\n## Image Field\r\n![Screenshot showing Argilla's new Image Field and Dark Mode](https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fb55c029b-0902-4f1a-ab99-fd68765975cb)\r\nArgilla now supports multimodal datasets with the introduction of a native `ImageField`. This new type of field allows you to work seamlessly with image data, making it easier to annotate and curate datasets that combine text and images. \r\n\r\nHere's an example of a dataset with an image field:\r\n```python\r\n\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(...)\r\n\r\nsettings = rg.Settings(\r\n\tfields = [\r\n\t\trg.ImageField(name=\"image\"),\r\n\t\trg.TextField(name=\"caption\")\r\n\t],\r\n\tquestions = [\r\n\t\trg.LabelQuestion(\r\n\t\t\tname=\"good_or_bad\", \r\n\t\t\ttitle=\"Is the caption good or bad\",\r\n\t\t\tlabels=[\"good\", \"bad\"]\r\n\t\t),\r\n\t\trg.TextQuestion(name=\"comments\")\r\n\t]\r\n)\r\n\r\ndataset = rg.Dataset(name=\"image_captions\", settings=settings)\r\ndataset.create()\r\n\r\nrecord = rg.Record(\r\n\tfields= {\r\n\t  \"image\": \"https:\u002F\u002Fdocs.argilla.io\u002Fdev\u002Fassets\u002Flogo.svg\", \r\n\t  \"caption\": \"This is the Argilla logo\"\r\n\t}\r\n)\r\ndataset.records.log([record])\r\n\r\n```\r\n[Read more](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Fhow_to_guides\u002Fdataset\u002F#fields)\r\n\r\n## Dark Mode\r\nArgilla seems too bright for you? You can now try our new Dark Mode: a theme designed to reduce eye strain and give a new modern look to the app. You can enable Dark Mode under \"My Settings\".\r\n\r\n## Spanish Translation\r\n\r\n\u003Cimg width=\"1510\" alt=\"Captura de pantalla 2024-09-05 a las 17 28 29\" src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F0f82e3ce-3654-4e99-9055-db9173619f2f\">\r\n\r\nWe're committed to making Argilla accessible to a broader audience. With the addition of Spanish translation, we're taking another step towards breaking language barriers and enabling more teams to collaborate on data curation projects.\r\nThere's nothing you need to do to enable it: Argilla will automatically switch to Spanish when your browser's main language is set to Spanish. ¡Disfrutadla!\r\n\r\n\r\n## Import any dataset from the Hugging Face Hub\r\nThe `from_hub` method just got a major boost! You can now input your own settings, allowing you to use this method with almost any dataset from the Hugging Face Hub, not just Argilla datasets. \r\n\r\nHere's how easy it is to import a dataset from the Hub: \r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(...)\r\n\r\nsettings = rg.Settings(\r\n    fields=[\r\n        rg.TextField(name=\"input\"),\r\n    ],\r\n    questions=[\r\n        rg.TextQuestion(name=\"output\"),\r\n    ],\r\n)\r\n\r\ndataset = rg.Dataset.from_hub(\r\n    repo_id=\"yahma\u002Falpaca-cleaned\",\r\n    settings=settings,\r\n)\r\n\r\n```\r\n[Read more](https:\u002F\u002Fdocs.argilla.io\u002Flatest\u002Freference\u002Fargilla\u002Fdatasets\u002Fdatasets\u002F?h=from_hub#src.argilla.datasets._export._hub.HubImportExportMixin.from_hub)\r\n\r\n## Other Notable Fixes and Improvements\r\n\r\n* Adaptable text areas for `TextQuestion`'s, providing a better user experience in the UI.\r\n* Enhanced messaging for empty queues, keeping you informed when no records are available in the UI.\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.0.1...v2.1.0","2024-09-05T15:11:08",{"id":249,"version":250,"summary_zh":251,"released_at":252},202988,"v2.0.1","## What's Changed\r\n\r\n🧹 Patch release of bug fixes and minor documentation and messaging improvements. Enjoy your summer while we change the world in `v2.1.0`.\r\n\r\n### Fixed\r\n\r\n- Fixed error when creating optional fields. ([#5362](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5362))\r\n- Fixed error creating integer and float metadata with `visible_for_annotators`. ([#5364](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5364))\r\n- Fixed error when logging records with `suggestions` or `responses` for non-existent questions. ([#5396](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5396) by @maxserras)\r\n- Fixed error from conflicts in testing suite when running tests in parallel. ([#5349](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcommit\u002F1119b164d0623170d44561c6b75d439d2dc96bd0))\r\n- Fixed error in response model when creating a response with a `None` value. ([#5343](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcommit\u002F9e3705061a2dd88a7852288d9f6fd1aaeaa9b062))\r\n\r\n### Changed\r\n\r\n- Changed `from_hub` method to raise an error when a dataset with the same name exists. ([#5258](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5358))\r\n- Changed `log` method when ingesting records with no known keys to raise a descriptive error. ([#5356](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5356))\r\n- Changed `code snippets` to add new datasets ([#5395](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5395))\r\n\r\n### Added\r\n\r\n- Added Google Analytics to the documentation site. ([#5366](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5366))\r\n- Added frontend skeletons to progress metrics to optimise load time and improve user experience. ([#5391](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5391))\r\n- Added documentation in methods in API references for the Python SDK. ([#5400](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcommit\u002Fa6fc0117bc4923aec0be80df27eb79ddf3f007c7))\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.0.0...v2.0.1","2024-08-13T14:35:37",{"id":254,"version":255,"summary_zh":256,"released_at":257},202989,"v2.0.0","# 🔆 Release highlights\r\n## One `Dataset` to rule them all\r\nThe main difference between Argilla 1.x and Argilla 2.x is that we've converted the previous dataset types tailored for specific NLP tasks into a single highly-configurable `Dataset` class. \r\n\r\nWith the new `Dataset` you can combine multiple fields and question types, so you can adapt the UI for your specific project. This offers you more flexibility, while making Argilla easier to learn and maintain.\r\n\r\n> [!IMPORTANT]\r\n>  If you want to continue using your legacy datasets in Argilla 2.x, you will need to convert them into  v2 `Dataset`'s as explained in this [migration guide](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fhow_to_guides\u002Fmigrate_from_legacy_datasets\u002F).  This includes: `DatasetForTextClassification`, `DatasetForTokenClassification`, and `DatasetForText2Text`.\r\n>  \r\n>  `FeedbackDataset`'s do not need to be converted as they are already compatible with the Argilla v2 format.\r\n\r\n## New SDK & documentation\r\nWe've redesigned our SDK with the idea to adapt it to the new single `Dataset` and `Record` classes and, most importantly, improve the user and developer experience.\r\n\r\nThe main goal of the new design is to make the SDK easier to use and learn, making it simpler and faster to configure your dataset and get it up and running.\r\n\r\nHere's an example of what creating a `Dataset` looks like:\r\n```python\r\nimport argilla as rg\r\nfrom datasets import load_dataset\r\n\r\n# log to the Argilla client\r\nclient = rg.Argilla(\r\n    api_url=\"\u003Capi_url>\",\r\n    api_key=\"\u003Capi_key>\"\r\n    # headers={\"Authorization\": f\"Bearer {HF_TOKEN}\"}\r\n)\r\n\r\n# configure dataset settings\r\nsettings = rg.Settings(\r\n    guidelines=\"Classify the reviews as positive or negative.\",\r\n    fields=[\r\n        rg.TextField(\r\n            name=\"review\",\r\n            title=\"Text from the review\",\r\n            use_markdown=False,\r\n        ),\r\n    ],\r\n    questions=[\r\n        rg.LabelQuestion(\r\n            name=\"my_label\",\r\n            title=\"In which category does this article fit?\",\r\n            labels=[\"positive\", \"negative\"],\r\n        )\r\n    ],\r\n)\r\n\r\n# create the dataset in your Argilla instance\r\ndataset = rg.Dataset(\r\n    name=f\"my_first_dataset\",\r\n    settings=settings,\r\n    client=client,\r\n)\r\ndataset.create()\r\n\r\n# get some data from the hugging face hub and load the records\r\ndata = load_dataset(\"imdb\", split=\"train[:100]\").to_list()\r\ndataset.records.log(records=data, mapping={\"text\": \"review\"})\r\n```\r\n\r\nTo learn more about this SDK and how it works, check out our revamped documentation: https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\r\n\r\nWe made this new documentation site from scratch, applying [the Diátaxis framework](https:\u002F\u002Fdiataxis.fr\u002F) and UX principles with the hope to make this version cleaner and the information easier to find.\r\n\r\n## New UI layout\r\nWe have also redesigned part of our UI for Argilla 2.0:\r\n- We've redistributed the information in the Home page.\r\n- Datasets don't have Tasks, but Questions.\r\n- A clearer way to see your team's progress over each dataset.\r\n- Annotation guidelines and your progress are now accessible at all times within the dataset page.\r\n- Dataset pages also have a new flexible layout, so you can change the size of different panels and expand or collapse the guidelines and progress.\r\n- `SpanQuestion`'s are now supported in the bulk view.\r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F2d959c8a-b4ac-446b-8326-bd66daa28816\r\n\r\n## Automatic task distribution\r\nArgilla 2.0 also comes with an automated way to split the task of annotating a dataset among a team. Here's how it works in a nutshell:\r\n- An owner or an admin can set the minimum number of submitted responses expected for each record.\r\n- When a record reaches that threshold, its status changes to `complete` and it's automatically removed from the pending queue of all team members. \r\n- A dataset is 100% complete when all records have the status `complete`.\r\n\r\nBy default, the minimum submitted answers is 1, but you can create a dataset with a different value:\r\n```python\r\nsettings = rg.Settings(\r\n    guidelines=\"These are some guidelines.\",\r\n    fields=[\r\n        rg.TextField(\r\n            name=\"text\",\r\n        ),\r\n    ],\r\n    questions=[\r\n        rg.LabelQuestion(\r\n            name=\"label\",\r\n            labels=[\"label_1\", \"label_2\", \"label_3\"]\r\n        ),\r\n    ],\r\n    distribution=rg.TaskDistribution(min_submitted=3)\r\n)\r\n```\r\n\r\nYou can also change the value of an existing dataset as long as it has no responses. You can do this from the `General` tab inside the Dataset Settings page in the UI or from the SDK:\r\n```python\r\nimport argilla as rg\r\n\r\nclient = rg.Argilla(...)\r\n\r\ndataset = client.datasets(\"my_dataset\")\r\n\r\ndataset.settings.distribution.min_submitted = 4\r\n\r\ndataset.update()\r\n```\r\n\r\nTo learn more, check our guide on how to [distribute the annotation task](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fhow_to_guides\u002Fdistribution\u002F).\r\n\r\n## Easily deploy in Hugging face Spaces\r\nWe've streamlined the deployment of an ","2024-07-31T06:49:24",{"id":259,"version":260,"summary_zh":261,"released_at":262},202990,"v1.29.1","## What's Changed\r\n* 🙏 Update community link for v1.29.1 by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5257\r\n* bug: 5123 metrics by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5245\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv1.29.0...v1.29.1","2024-07-22T08:27:55",{"id":264,"version":265,"summary_zh":266,"released_at":267},202991,"v2.0.0rc2","## What's Changed\r\n* Docs: new review UI guide by @nataliaElv in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5083\r\n* [ENHANCEMENT] ci: Review event triggers to reduce CI runs by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5075\r\n* docs: fix minor warning by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5089\r\n* 🔥 Fix reorder labels by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5084\r\n* ✨ Refactor CSS by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5085\r\n* ✨ Fix issue on iterator by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5099\r\n* [ENHANCEMENT] CI: Allow to publish hidden version for docs\u002F branches by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5088\r\n* [ENHANCEMENT \u002F BUGFIX] CI: publish version docs on tag creation by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5092\r\n* [DOCS] swap extra_headers for headers in updated sdk docs by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5100\r\n* docs: change references slack by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5101\r\n* [BUGFIX] remove name as default description in settings models by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5081\r\n* 🐛 Fix banner by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5127\r\n* ✨ Improve docs by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5094\r\n* change: delete on cascade responses when associated user is deleted by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5126\r\n* ✨ Add LaTex support by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5129\r\n* docs: small clarifications by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5131\r\n* fix: UI - scrollable records in bulk view by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5143\r\n* fix:  copy the dataset name by clicking the copy button by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5142\r\n* [ENHANCEMENT] `argilla`: simplify structure for flatten records to list by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5137\r\n* [ENHANCEMENT] `argilla`: define argilla-v1 as optional dependency by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5120\r\n* refactor: improve get pop issues by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5135\r\n* [BUGFIX] `argilla`: normalize records when exporting flatten by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5138\r\n* [BUGFIX] `argilla`: support read draft response models without values by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5124\r\n* [REFACTOR] Redefine some property methods by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5114\r\n* fix: conditional checking SQLite connection so connection configuration is correctly executed by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5149\r\n* chore: update SQLAlchemy dependencies by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5154\r\n* [ENHANCEMENT\u002FREFACTOR] `argilla`: lazy resolution for dataset workspaces by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5152\r\n* [REFACTOR]: `argilla`:  Rename `status` to `response.status` for filtering using the SDK by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5145\r\n* [ENHANCEMENT] [REFACTOR] optimise and refactor SDK ingestion methods  by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5107\r\n* [BUGFIX] `argilla-server`: `await` on similarity search when filtering response values without user by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5159\r\n* [BUGFIX] rename optional deps v1 by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5164\r\n* [REVERT] Rename `sdk-v1` to `legacy` by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5168\r\n* [RELEASES] 2.0.0rc2 by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F5160\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv2.0.0rc1...v2.0.0rc2","2024-07-05T08:34:46",{"id":269,"version":270,"summary_zh":271,"released_at":272},202992,"v2.0.0rc1","# 🔆 Release highlights\r\n## One `Dataset` to rule them all\r\nThe main difference between Argilla 1.x and Argilla 2.x is that we've converted the previous dataset types tailored for specific NLP tasks into a single highly-configurable `Dataset` class. \r\n\r\nWith the new `Dataset` you can combine multiple fields and question types, so you can adapt the UI for your specific project. This offers you more flexibility, while making Argilla easier to learn and maintain.\r\n\r\n> [!IMPORTANT]\r\n>  If you want to continue using legacy datasets in Argilla 2.x, you will need to convert them into  v2 `Dataset`'s as explained in this [migration guide](https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002Fhow_to_guides\u002Fmigrate_from_legacy_datasets\u002F).  This includes: `DatasetForTextClassification`, `DatasetForTokenClassification`, and `DatasetForText2Text`.\r\n>  \r\n>  `FeedbackDataset`'s do not need to be converted as they are already compatible with the Argilla v2 format.\r\n## New SDK\r\nWe've redesigned our SDK with the idea to adapt it to the new single `Dataset` class and, most importantly, improve the user and developer experience.\r\n\r\nThe main goal of the new design is to make the SDK easier to use and learn, making the process to configure your dataset and get it up and running much simpler and faster.\r\n\r\nTo learn more about this new SDK, you can check:\r\n- our new documentation: https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\u002F\r\n-  @burtenshaw's blog post: https:\u002F\u002Fargilla.io\u002Fblog\u002Fintroducing-argilla-new-sdk\r\n- this community meetup: https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=G3lZBtPrtgU\r\n\r\n## New UI layout\r\nWe have also revamped our UI for Argilla 2.0:\r\n- We've redistributed the information in the Home page\r\n- Datasets don't have Tasks, but Questions.\r\n- Annotation guidelines and your progress are now accessible at all times within the dataset page.\r\n- Dataset pages also have a new flexible layout, so you can change the size of different panes and expand or collapse the guidelines and progress.\r\n- `SpanQuestion`'s are now supported in the bulk view.\r\n\r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fassets\u002F126158523\u002Ff77e60de-5824-44ad-8b68-a087b223aa9d\r\n\r\n\r\n## New documentation\r\nThis new version of Argilla comes hand-in-hand with a revamped documentation: https:\u002F\u002Fargilla-io.github.io\u002Fargilla\u002Flatest\r\n\r\nWe have applied [the Diátaxis framework](https:\u002F\u002Fdiataxis.fr\u002F) and UX principles with the hope to make this version cleaner and the information easier to find. Let us know what you think!\r\n\r\n## Share your thoughts with us!\r\n\r\n>[!NOTE]\r\n>This is a release candidate ahead of the official Argilla 2.0 release. Try it out and let us know what you think.\r\n> Find us in [Discord](https:\u002F\u002Fdiscord.com\u002Fchannels\u002F879548962464493619\u002F1253640697194479676) or open a Github issue [here](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002Fnew\u002Fchoose).\r\n\r\n## What's Changed\r\n* change: deleted unused API v0 code by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4852\r\n* [RELEASE] 1.29.0 by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4896\r\n* 💀 feat\u002Fremove older datasets by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4903\r\n* feat: update sign-in page UI by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4915\r\n* ✨ Endpoint migration by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4883\r\n* [FEATURE-BRANCH] refactor: improve API v1 error handling by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4887\r\n* [FEAT BRANCH] Add `argilla-sdk` project by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4891\r\n* 💀 feat\u002Fimprove dataset table by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4917\r\n* [REFACTOR] Remove old API calls for `argilla-sdk` by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4937\r\n* feat: UI table styles by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4953\r\n* docs: fastfit tutorial by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4958\r\n* [DOCS] [FIX] Fix logging, typing and docstrings based on feedback by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4968\r\n* [BUGFIX] ci: Configure argilla server deps properly by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4962\r\n* Fix\u002Fadd-checked-types-to-io by @burtenshaw in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4974\r\n* [CI] Configure build on push feat\u002F branches by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4960\r\n* refactor: API folder structure improvements by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4959\r\n* feat: UI - remove sidebar components by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4978\r\n* docs: add changelog by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4983\r\n* docs: popular issues file generator by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4971\r\n* 🚄 feat\u002Fimprove performance metrics by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4981\r\n* Update ACCESS_TOKEN naming and documentation hierarchy guides by @davidberenstein1957 i","2024-06-21T10:02:49",{"id":274,"version":275,"summary_zh":276,"released_at":277},202993,"v1.29.0","# 🔆 Release highlights\r\n\r\n> [!WARNING]  \r\n> This will be the last release of Argilla v1. Starting from Argilla 2.0.0, we will only support `FeedbackDataset`s which will be renamed to `Dataset`. All other dataset types (`DatasetForTextClassification`, `DatasetForTokenClassification`, and `DatasetForText2Text`) will be deprecated. In the next release, we will provide more information and documentation on how to migrate all your datasets into Argilla 2.0 `Dataset`s.\r\n\r\n## Improved record search\r\nYour search matches are now highlighted so you can see easily the result of your search. We’ve also added a selector for datasets with more than one record fields so you can choose whether to do the search on All fields or a specific one. \r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fassets\u002F126158523\u002Fb9af3313-a5c3-46b6-83b7-6624662dba04\r\n\r\n## Record information and metadata in the UI\r\nYou can now check all the information and metadata associated for each record directly in the UI. \r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fassets\u002F126158523\u002F4a3cc4e0-8be7-4927-8d80-8cf84a0dce8b\r\n\r\n## What's Changed in `v1.29.0`\r\n* feat: small UI improvements by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4770\r\n* feat:update UI for settings page by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4767\r\n* Fix: \"cannot import name 'formatargspec' from 'inspect'\" with Python 3.11 by @walter-hernandez in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4693\r\n* 🐛 Ranking component not showing rankings by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4775\r\n* Adding LlamaIndex docs to integrations by @ignacioct in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4803\r\n* docs: use FeedbackDataset in HF example by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4805\r\n* docs: clarification\u002Ftypo in tutorial by @sdiazlor in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4810\r\n* Log if a dataset is deleted by @paulbauriegel in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4752\r\n* ✨ Search text filtering by field by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4771\r\n* ✨ Add text search for fields by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4831\r\n* ✨ Fix shift issue and Letter S on issue reported by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4836\r\n* 🚑 Fix issue for intentional submission by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4840\r\n* ci: Mono repo setup by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4742\r\n* fix: add branches and tags to argilla-server.yml GitHub workflow by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4854\r\n* fix: GitHub action names with typos by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4850\r\n* fix: remove non necessary conditional to build argilla-server docker images by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4855\r\n* chore: update datasets.py by @eltociear in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4842\r\n* docs: Fix typo Argila -> Argilla by @louisguitton in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4870\r\n* fix: add error code when searching for a record missing specific vector by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4856\r\n* 🐛 Fix highlight multiple fields by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4866\r\n* feat: add support for value zero on rating questions by @jfcalvo in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4864\r\n* fix(import): remove non-existent server module by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4874\r\n* 🐛 Fix pre selection by @damianpumar in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4872\r\n* support for Python 3.12 by @nicoloboschi in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4837\r\n* Search bar and highlight docs by @nataliaElv in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4882\r\n* feat: UI Metadata info component by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4851\r\n* [IMPROVEMENT] Update pip when building docker image by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4907\r\n* [BUGFIX] Filter record metadata value based on metadata property policies by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4906\r\n* feat: UI - metadata adjustments by @leiyre in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4905\r\n* [REVIEW] Add missing entries in  CHANGELOG files by @frascuchon in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4910\r\n\r\n## New Contributors\r\n* @walter-hernandez made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4693\r\n* @eltociear made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4842\r\n* @louisguitton made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4870\r\n* @nicoloboschi made their first contribution in https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4837\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv1.28.0...v1.29.0","2024-05-30T15:46:15",{"id":279,"version":280,"summary_zh":281,"released_at":282},202994,"v1.28.0","# 🔆 Release highlights\r\n\r\n## Improved suggestions\r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fassets\u002F126158523\u002F380004e0-28cb-409f-b11c-71d0e3b6e8bf\r\n\r\n### Multiple scores support for `MultiLabelQuestion` and `RankingQuestion`\r\n\r\n`MultiLabelQuestion` and `RankingQuestion` now take one score per suggested label \u002F value, making the scores easier to interpret. Learn more about suggestions and their scores [here](https:\u002F\u002Fdocs.argilla.io\u002Fen\u002Fdevelop\u002Fpractical_guides\u002Fcreate_update_dataset\u002Fsuggestions_and_responses.html#format-suggestions).\r\n\r\n> [!WARNING]  \r\n> If you upgrade to this version all previous scores in suggestions for MultiLabelQuestion, RankingQuestion and SpanQuestion will turn to NULL, as they will not be valid in the new schema. Please, make sure you upload scores again if you want to use them.\r\n\r\n### See scores next to its label \u002F value\r\n\r\nScores are now shown next to its label \u002F value in all questions. This makes them more visible and easier to interpret.\r\n\r\n### Suggestions first - 🌟 Community request: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fissues\u002F4647\r\n\r\nNow you can order labels in `MultiLabelQuestion` so that suggestions are always shown first. This will help you make sure that the most relevant labels are always at hand. Plus, if you’ve added scores to your labels, these will be ordered in descending order. To enable this, go to the Dataset Settings page > Questions and enable “Suggestions first” for the desired question.\r\n\r\n## `SpanQuestion` improvements\r\n\r\nhttps:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fassets\u002F126158523\u002Ffad7b9ca-3890-45ed-acc8-5b038a81db06\r\n\r\n### Pre-selection highlight\r\n\r\nWe’ve improved the way selections are shown. You can now see a highlight that represents what the final selection will look like while you’re dragging your mouse. This will help you with the selection speed and show you the difference between the token vs character selection. \r\n> [!NOTE]\r\n> Remember that character-level spans are activated by holding `Shift` while doing the selection.\r\n\r\n### New label selector\r\n\r\nWe’ve improved the way the label selector works in the `SpanQuestion` when overlapping spans are enabled so it’s easier to add or correct labels. Simply click on the desired span to activate the selector and click on the label(s) that you want to add or remove. \r\n\r\n## Persistent storage warning\r\n\r\nWe’ve added a warning for Argilla instances deployed on Hugging Face Spaces to alert of data loss when the persistent storage is not enabled. \r\n\r\nTo learn more about this warning and how to disable it, go to [our docs](https:\u002F\u002Fdocs.argilla.io\u002Fen\u002Fdevelop\u002Fgetting_started\u002Finstallation\u002Fdeployments\u002Fhuggingface-spaces.html#setting-up-persistent-storage).\r\n\r\n## [Changelog 1.28.0](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv1.27.0...v1.28.0)\r\n\r\n### Added\r\n\r\n- Added suggestion multi score attribute. ([#4730](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4730))\r\n- Added order by suggestion first. ([#4731](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4731))\r\n- Added multi selection entity dropdown for span annotation overlap. ([#4735](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4735))\r\n- Added pre selection highlight for span annotation. ([#4726](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4726))\r\n- Added banner when persistent storage is not enabled. ([#4744](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4744))\r\n- Added support on Python SDK for new multi-label questions `labels_order` attribute. ([#4757](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4757))\r\n\r\n### Changed\r\n\r\n- Changed the way how Hugging Face space and user is showed in sign in. ([#4748](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4748))\r\n\r\n### Fixed\r\n\r\n- Fixed Korean character reversed. ([#4753](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4753))\r\n\r\n### Fixed\r\n\r\n- Fixed requirements for version of wrapt library conflicting with Python 3.11 ([#4693](https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fpull\u002F4693))\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fargilla-io\u002Fargilla\u002Fcompare\u002Fv1.27.0...v1.28.0","2024-05-09T15:13:09"]