[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-wrtnlabs--autobe":3,"tool-wrtnlabs--autobe":62},[4,18,26,36,46,54],{"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",160784,2,"2026-04-19T11:32:54",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":42,"last_commit_at":43,"category_tags":44,"status":17},8272,"opencode","anomalyco\u002Fopencode","OpenCode 是一款开源的 AI 编程助手（Coding Agent），旨在像一位智能搭档一样融入您的开发流程。它不仅仅是一个代码补全插件，而是一个能够理解项目上下文、自主规划任务并执行复杂编码操作的智能体。无论是生成全新功能、重构现有代码，还是排查难以定位的 Bug，OpenCode 都能通过自然语言交互高效完成，显著减少开发者在重复性劳动和上下文切换上的时间消耗。\n\n这款工具专为软件开发者、工程师及技术研究人员设计，特别适合希望利用大模型能力来提升编码效率、加速原型开发或处理遗留代码维护的专业人群。其核心亮点在于完全开源的架构，这意味着用户可以审查代码逻辑、自定义行为策略，甚至私有化部署以保障数据安全，彻底打破了传统闭源 AI 助手的“黑盒”限制。\n\n在技术体验上，OpenCode 提供了灵活的终端界面（Terminal UI）和正在测试中的桌面应用程序，支持 macOS、Windows 及 Linux 全平台。它兼容多种包管理工具，安装便捷，并能无缝集成到现有的开发环境中。无论您是追求极致控制权的资深极客，还是渴望提升产出的独立开发者，OpenCode 都提供了一个透明、可信",144296,1,"2026-04-16T14:50:03",[13,45],"插件",{"id":47,"name":48,"github_repo":49,"description_zh":50,"stars":51,"difficulty_score":32,"last_commit_at":52,"category_tags":53,"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。",109154,"2026-04-18T11:18:24",[14,15,13],{"id":55,"name":56,"github_repo":57,"description_zh":58,"stars":59,"difficulty_score":32,"last_commit_at":60,"category_tags":61,"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",[45,13,15,14],{"id":63,"github_repo":64,"name":65,"description_en":66,"description_zh":67,"ai_summary_zh":67,"readme_en":68,"readme_zh":69,"quickstart_zh":70,"use_case_zh":71,"hero_image_url":72,"owner_login":73,"owner_name":74,"owner_avatar_url":75,"owner_bio":76,"owner_company":77,"owner_location":77,"owner_email":78,"owner_twitter":77,"owner_website":79,"owner_url":80,"languages":81,"stars":105,"forks":106,"last_commit_at":107,"license":108,"difficulty_score":32,"env_os":109,"env_gpu":110,"env_ram":111,"env_deps":112,"category_tags":120,"github_topics":121,"view_count":32,"oss_zip_url":77,"oss_zip_packed_at":77,"status":17,"created_at":136,"updated_at":137,"faqs":138,"releases":168},9640,"wrtnlabs\u002Fautobe","autobe","AI Vibe Coding Agent of TS backend server, enhanced by compiler skills, generating 100% working code","AutoBE 是一款专为 TypeScript 后端开发打造的 AI 编程助手，旨在帮助用户通过自然语言对话，快速从原型构建出可投入生产环境的后端应用。它主要解决了传统后端开发中需求分析耗时、代码易出错以及测试覆盖不足等痛点，能够根据用户的描述自动生成包含完整规格说明书、数据库设计、API 文档及端到端测试用例在内的全套代码，并确保生成的代码 100% 可通过编译且运行稳定。\n\n这款工具非常适合希望快速验证想法的创业者、需要提升交付效率的资深开发者，以及渴望学习规范后端架构的初级程序员。其独特的技术亮点在于深度融合了“编译器技能”，利用 AI 友好的编译机制在生成阶段即规避语法与逻辑错误，同时内置强大的 E2E 测试功能以保障系统稳定性。用户只需在聊天界面描述需求（如“创建一个电商系统”），AutoBE 便能自动完成从需求分析报告到实体关系图、API 控制器及具体业务逻辑实现的全过程。配合本地部署的 Playground 环境，开发者还能灵活接入各类大模型，轻松实现从概念到落地的高效转化。","# AutoBE - AI backend builder for prototype to production\n\n[![GitHub License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-AGPL--3.0-blue.svg)](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmaster\u002FLICENSE)\n[![NPM Version](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fv\u002F@autobe\u002Fagent.svg)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@autobe\u002Fagent)\n[![NPM Downloads](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fdm\u002F@autobe\u002Fagent.svg)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@autobe\u002Fagent)\n[![Build Status](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fworkflows\u002Fbuild\u002Fbadge.svg?branch=main)](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Factions?query=workflow%3Abuild)\n[![Guide Documents](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGuide-Documents-forestgreen)](https:\u002F\u002Fautobe.dev\u002Fdocs\u002F)\n[![Discord Badge](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002Fhttps:\u002F\u002Fdiscord.gg\u002FaMhRmzkqCx?style=flat)](https:\u002F\u002Fdiscord.gg\u002FaMhRmzkqCx)\n\nDescribe your backend requirements in natural language through AutoBE's chat interface. \n\nAutoBE will analyze your requirements and build the backend application for you. The generated backend application is designed to be 100% buildable by AI-friendly compilers and ensures stability through powerful e2e test functions.\n\nWith such AutoBE, build your first backend application quickly, then maintain and extend it with AI code assistants like Claude Code for enhanced productivity and stability.\n\nAutoBE will generate complete specifications, detailed database and API documentation, comprehensive test coverage for stability, and clean implementation logic that serves as a learning foundation for juniors while significantly improving senior developer productivity.\n\nCheck out these complete backend application examples generated by AutoBE:\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fb995dd2a-23bd-43c9-96cb-96d5c805f19f\n\n1. **To Do List**: [`todo`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ftodo)\n2. **Reddit Community**: [`reddit`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit)\n3. **E-Commerce**: [`shopping`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Fshopping)\n4. **ERP System**: [`erp`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp)\n   - Requirements Analysis: [Report](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fdocs\u002Fanalysis)\n   - Database Design: [Entity Relationship Diagram](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fdocs\u002FERD.md) \u002F [Prisma Schema](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fprisma\u002Fschema)\n   - API Design: [API Controllers](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fsrc\u002Fcontrollers) \u002F [DTO Structures](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fsrc\u002Fapi\u002Fstructures)\n   - E2E Test Functions: [`test\u002Ffeatures\u002Fapi`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Ftest\u002Ffeatures\u002Fapi)\n   - API Implementations: [`src\u002Fproviders`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fsrc\u002Fproviders)\n\n## Getting Started\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe --depth=1\ncd autobe\npnpm install\npnpm run playground\n```\n\nTo use AutoBE, clone the repository and run the playground application locally. This allows you to chat with AutoBE's AI agents, manage multiple sessions, and use various LLM providers including local models like `qwen3.5-397b-a17b`.\n\nAfter installation, the playground will be available at http:\u002F\u002Flocalhost:5173. You can interact with AutoBE through a chat interface - simply describe what you want to build, and AutoBE will generate the backend application for you.\n\nHere's an example conversation script that guides AutoBE to create an \"Economic\u002FPolitical Discussion Board\":\n\n1. **Requirements Analysis**: \"I want to create an economic\u002Fpolitical discussion board. Since I'm not familiar with programming, please write a requirements analysis report as you see fit.\"\n2. **Database Design**: \"Design the database schema.\"\n3. **API Specification**: \"Create the API interface specification.\"\n4. **Testing**: \"Make the e2e test functions.\"\n5. **Implementation**: \"Implement API functions.\"\n\n![Compilation Success Dashboard](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fwrtnlabs_autobe_readme_598f0a719915.png)\n\n> The playground includes a replay feature at http:\u002F\u002Flocalhost:5173\u002Freplay\u002Findex.html where you can view chat sessions from the AutoBE development team's testing and benchmarks.\n\n## Documentation Resources\n\nFind comprehensive resources at our [official website](https:\u002F\u002Fautobe.dev).\n\n### 🏠 Home\n\n- 🙋🏻‍♂️ [Introduction](https:\u002F\u002Fautobe.dev\u002Fdocs)\n- 📦 [Setup](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fsetup)\n- 🔍 Concepts\n  - [Waterfall Model](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fconcepts\u002Fwaterfall)\n  - [Compiler Strategy](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fconcepts\u002Fcompiler)\n  - [AI Function Calling](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fconcepts\u002Ffunction-calling)\n\n### 📖 Features\n\n- 🤖 Agent Library\n  - [Facade Controller](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Ffacade)\n  - [Configuration](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Fconfig)\n  - [Event Handling](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Fevent)\n  - [Prompt Histories](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Fhistory)\n- 📡 WebSocket Protocol\n  - [Remote Procedure Call](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Frpc)\n  - [NestJS Server](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Fnestjs)\n  - [NodeJS Server](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Fnodejs)\n  - [Client Application](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Fclient)\n- 🛠️ Backend Stack\n  - [TypeScript](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fstack\u002Ftypescript)\n  - [Prisma ORM](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fstack\u002Fprisma)\n  - [NestJS Framework](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fstack\u002Fnestjs)\n\n### 🔗 Appendix\n\n- 🌐 [No-Code Ecosystem](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fecosystem)\n- 📅 Roadmap\n  - [Alpha Release (done)](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Falpha)\n  - [Beta Release (done)](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Fbeta)\n  - [Gamma Release (done)](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Fgamma)\n  - [Delta Release (active)](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Fdelta)\n- 🔧 [API Documentation](https:\u002F\u002Fautobe.dev\u002Fapi)\n\n## How AutoBE Works\n\n```mermaid\nflowchart\nsubgraph \"Backend Coding Agent\"\n  coder(\"Facade Controller\")\nend\nsubgraph \"Functional Agents\"\n  coder --\"Requirements Analysis\"--> analyze(\"Analyze\")\n  coder --\"ERD\"--> database(\"Database\")\n  coder --\"API Design\"--> interface(\"Interface\")\n  coder --\"Test Codes\" --> test(\"Test\")\n  coder --\"Main Program\" --> realize(\"Realize\")\nend\nsubgraph \"Compiler Feedback\"\n  database --\"validates\" --> prismaCompiler(\"\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmain\u002Fpackages\u002Finterface\u002Fsrc\u002Fdatabase\u002FAutoBeDatabase.ts\" target=\"_blank\">Database Compiler\u003C\u002Fa>\")\n  interface --\"generates\" --> openapiCompiler(\"\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmain\u002Fpackages\u002Finterface\u002Fsrc\u002Fopenapi\u002FAutoBeOpenApi.ts\" target=\"_blank\">OpenAPI Compiler\u003C\u002Fa>\")\n  test --\"analyzes\" --> testCompiler(\"\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmain\u002Fpackages\u002Finterface\u002Fsrc\u002Ftest\u002FAutoBeTest.ts\" target=\"_blank\">Test Compiler\u003C\u002Fa>\")\n  realize --\"compiles\" --> realizeCompiler(\"Hybrid Compiler\")\nend\n```\n\nAutoBE follows a waterfall methodology to generate backend applications, with 40+ specialized agents handling each phase. The agents work in coordinated teams throughout the development process.\n\nEach waterfall stage includes AI-friendly compilers that guarantee type safety of the generated code. Rather than generating code directly, AutoBE's agents first construct language-neutral Abstract Syntax Trees using predefined schemas. Each AST node undergoes validation against type rules before any code generation occurs, catching structural errors at the conceptual level rather than during compilation.\n\nThis approach is designed to ensure that the final generated TypeScript and Prisma code is 100% buildable. Based on our testing with multiple example projects including e-commerce platforms, discussion boards, and task management systems, AutoBE maintains this compilation guarantee across diverse application types.\n\nTo illustrate this process, here are the phase outputs from our \"Economic\u002FPolitical Discussion Board\" example:\n\n1. **Requirements Analysis**: [Report](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fdocs\u002Fanalysis)\n2. **Database Design**: [Entity Relationship Diagram](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fdocs\u002FERD.md) \u002F [Prisma Schema](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fprisma\u002Fschema)\n3. **API Specification**: [API Controllers](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fsrc\u002Fcontrollers) \u002F [DTO Structures](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fsrc\u002Fapi\u002Fstructures)\n4. **E2E Test Functions**: [`test\u002Ffeatures\u002Fapi`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Ftest\u002Ffeatures\u002Fapi)\n5. **API Implementations**: [`src\u002Fproviders`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fsrc\u002Fproviders)\n\n## Benchmark\n\nAutoBE includes an automated evaluation pipeline that scores generated backends across 13+ LLM models and 4 project types. View the live results at **[autobe.dev\u002Fbenchmark](https:\u002F\u002Fautobe.dev\u002Fbenchmark\u002F)**.\n\nThe benchmark evaluates compilation correctness, documentation quality, requirements coverage, test coverage, logic completeness, API completeness, and AI agent analysis (security, hallucination, code quality). Each model is scored 0-100 with grades A-F.\n\n| Model | Todo | Reddit | Shopping | ERP | Avg |\n|-------|------|--------|----------|-----|-----|\n| glm-5 | 88 (B) | 87 (B) | 82 (B) | 87 (B) | **86** |\n| claude-sonnet-4.6 | 87 (B) | 85 (B) | 72 (C) | 85 (B) | 82 |\n| gpt-5.4-mini | 89 (B) | 87 (B) | 74 (C) | 78 (C) | 82 |\n| qwen3-coder-next | 86 (B) | 76 (C) | 75 (C) | 88 (B) | 81 |\n| qwen3.5-27b | 88 (B) | 81 (B) | 77 (C) | 78 (C) | 81 |\n| minimax-m2.7 | 90 (A) | 71 (C) | 77 (C) | 79 (C) | 79 |\n| gpt-5.4 | 79 (C) | 78 (C) | 79 (C) | 80 (B) | 79 |\n\n### Running the Benchmark\n\n```bash\n# All models (default)\ncorepack pnpm estimate\n\n# Single model only\ncorepack pnpm estimate -- --model kimi-k2.5\n\n# Single project only\ncorepack pnpm estimate -- --project todo\n\n# Model + project\ncorepack pnpm estimate -- --model glm-5 --project shopping\n\n# If pnpm is globally installed\npnpm estimate\n```\n\nReports are saved to:\n\n```\npackages\u002Festimate\u002Freports\u002Fbenchmark\u002F{model}\u002F{project}\u002Festimate-report.json\n```\n\nAlso, you don't need to use all phases - stop at any stage that fits your needs. Whether you want just requirements analysis, database design, API specification, or e2e testing, AutoBE adapts to your workflow.\n\nAdditionally, if you're skipping the full pipeline because of language preference rather than workflow needs, this capability is in development - AutoBE's language-neutral AST structure will soon support additional programming languages beyond TypeScript.\n\n## Type-Safe Client SDK\n\nEvery AutoBE-generated backend automatically includes a type-safe client SDK, making frontend integration seamless and error-free. This SDK provides:\n\n- **Zero Configuration**: SDK is auto-generated alongside your backend - no manual setup required\n- **100% Type Safety**: Full TypeScript support with autocomplete and compile-time validation\n- **Framework Agnostic**: Works with React, Vue, Angular, or any TypeScript\u002FJavaScript project\n- **E2E Test Integration**: Powers AI-generated test suites for comprehensive backend testing\n\n```typescript\nimport api, { IPost } from \"autobe-generated-sdk\";\n\n\u002F\u002F Type-safe API calls with full autocomplete\nconst connection: api.IConnection = {\n  host: \"http:\u002F\u002Flocalhost:1234\",\n};\nawait api.functional.users.login(connection, {\n  body: {\n    email: \"user@example.com\",\n    password: \"secure-password\",\n  },\n});\n\n\u002F\u002F TypeScript catches errors at compile time\nconst post: IPost = await api.functional.posts.create(connection, {\n  body: {\n    title: \"Hello World\",\n    content: \"My first post\",\n    \u002F\u002F authorId: \"123\" \u003C- TypeScript error if this field is missing!\n  },\n});\n```\n\nThis SDK eliminates the traditional pain points of API integration - no more manual type definitions, no more runtime surprises, and no more API documentation lookups. Your frontend developers can focus on building features, not wrestling with API contracts.\n\n**Beyond Frontend Integration**: The SDK powers both frontend development and E2E test generation. AutoBE uses the same type-safe SDK internally to generate comprehensive test suites, ensuring every API endpoint is thoroughly tested. This creates a robust feedback loop that enhances backend stability - AI writes tests using the SDK, the SDK ensures type safety, and your backend becomes more reliable with every generated test.\n\n## Roadmap Schedule\n\n```mermaid\ngantt\n  dateFormat YYYY-MM-DD\n  title AutoBE Delta Roadmap Timeline (2026 Q1)\n\n  section Local LLM Benchmark\n  Qwen3 Database Phase             : done, 2026-01-01, 31d\n  Qwen3 Interface Phase            : done, 2026-01-16, 31d\n  Qwen3 Test Phase                 : done, 2026-02-01, 21d\n  Qwen3 Realize Phase              : done, 2026-02-01, 59d\n\n  section Validation Logic Enhancement\n  Dynamic Function Calling Schema  : done, 2026-01-01, 7d\n  Validation Feedback Stringify    : done, 2026-01-08, 12d\n  JSON Schema Validator            : done, 2026-01-08, 12d\n  Schema Review Validation Logic   : done, 2026-01-20, 35d\n  Test Mapping Plan Enhancement    : done, 2026-02-05, 24d\n  Realize Mapping Plan Enhancement : done, 2026-02-15, 45d\n\n  section RAG Optimization\n  Hybrid Search (Vector + BM25)    : done, 2026-01-01, 14d\n  Dynamic K Retrieval              : done, 2026-01-15, 14d\n  RAG Preliminary Prompting        : done, 2026-01-15, 28d\n  RAG Benchmark & Tuning           : done, 2026-02-01, 28d\n  Analyze Agent Restructuring      : done, 2026-02-01, 28d\n\n  section Design Integrity\n  DB Coverage Agent                : done, 2026-01-15, 28d\n  API Endpoint Coverage Agent      : done, 2026-01-22, 28d\n  Schema Relation Agent            : done, 2026-02-01, 28d\n  Schema Structure Agent           : done, 2026-02-01, 28d\n  Schema Content Agent             : done, 2026-03-01, 28d\n\n  section Multi-lingual Support\n  Java Compiler PoC                : done,   2026-01-01, 30d\n  Java Database                    : done,   2026-01-01, 14d\n  Java Interface                   : done,   2026-01-15, 21d\n  Java Test                        : active, 2026-02-05, 28d\n  Java Realize                     : active, 2026-03-01, 31d\n\n  section Human Modification Support\n  Database Schema Parser           : active,  2026-02-15, 28d\n  Interface Schema Parser          : active,  2026-02-22, 28d\n  Requirements Sync Agent          : planned, 2026-03-08, 24d\n\n  section Miscellaneous\n  System Prompt Simplification     : done,   2026-02-01, 28d\n  Estimation Agent                 : done,   2026-02-01, 28d\n  Playground Service Enhancement   : active, 2026-02-15, 28d\n  PR Articles Writing              : active, 2026-02-15, 30d\n```\n\nAutoBE has successfully completed Alpha, Beta, and Gamma development phases, establishing a solid foundation with **100% compilation success rate**. The current **Delta Release** focuses on transitioning from horizontal expansion to vertical deepening.\n\n**Strategic Shift**: In Gamma, we rapidly implemented features like RAG, Modularization, and Complementation under a \"just ship it\" philosophy. Delta fills the stability gaps that remained by systematically discovering and fixing hidden defects through Local LLM benchmarks.\n\n**Key Focus Areas**:\n\n- **Local LLM Benchmark**: Using open-source models like Qwen3 as a touchstone to discover hidden defects that commercial models mask, ensuring more robust operation across all model types\n- **Validation Logic Enhancement**: Strengthening schemas and validation logic through dynamic function calling schemas, JSON Schema validators, and progressive validation pipelines\n- **RAG Optimization**: Completing the Hybrid Search system (Vector + BM25) with dynamic K retrieval and comprehensive benchmark tuning\n- **Design Integrity**: Building mechanisms to verify and ensure design consistency between Database and Interface phases through coverage and schema review agents\n- **Multi-lingual Support**: Launching Java\u002FSpring code generation alongside TypeScript\u002FNestJS, with language-neutral AST structures enabling future language additions\n- **Human Modification Support**: Enabling maintenance continuity by parsing user-modified code back into AutoBE's internal AST representation, ensuring AutoBE remains useful beyond initial generation\n\nThis roadmap prioritizes stability and depth over feature breadth, informed by real-world production experience from Gamma.\n\n## Current Limitations\n\nWhile AutoBE achieves 100% compilation success, please note these current limitations:\n\n**Runtime Behavior**: Generated applications compile successfully, but runtime behavior may require testing and refinement. Unexpected runtime errors can occur during server execution, such as database connection issues, API endpoint failures, or business logic exceptions that weren't caught during compilation. We strongly recommend thorough testing in development environments before deploying to production. Our v1.0 release targets 100% runtime success to address these issues.\n\n**Design Interpretation**: AutoBE's database and API designs may differ from your expectations. We recommend thoroughly reviewing generated specifications before proceeding with implementation, especially before production deployment.\n\n**Token Consumption**: AutoBE requires significant AI token usage for complex projects. Based on our testing, projects typically consume 30M-250M+ tokens depending on complexity (simple todo apps use ~4M tokens, while complex e-commerce platforms may require 250M+ tokens). We are working on RAG optimization to reduce this overhead in future releases.\n\n**Maintenance**: AutoBE focuses on initial generation and does not provide ongoing maintenance capabilities. Once your backend is generated, you'll need to handle bug fixes, feature additions, performance optimizations, and security updates manually. We recommend establishing a development workflow that combines the generated codebase with AI coding assistants like Claude Code for efficient ongoing development and maintenance tasks.\n\n![Entity Relationship Diagram Sample](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fwrtnlabs_autobe_readme_54d385d15501.png)\n\n## License\n\nAutoBE is licensed under the [GNU Affero General Public License v3.0 (AGPL-3.0)](LICENSE). If you modify AutoBE itself or offer it as a network service, you must make your source code available under the same license.\n\nHowever, backend applications generated by AutoBE can be relicensed under any license you choose, such as MIT. This means you can freely use AutoBE-generated code in commercial projects without open source obligations, similar to how other code generation tools work.\n","# AutoBE - 从原型到生产的 AI 后端构建工具\n\n[![GitHub 许可证](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-AGPL--3.0-blue.svg)](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmaster\u002FLICENSE)\n[![NPM 版本](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fv\u002F@autobe\u002Fagent.svg)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@autobe\u002Fagent)\n[![NPM 下载量](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fdm\u002F@autobe\u002Fagent.svg)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@autobe\u002Fagent)\n[![构建状态](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fworkflows\u002Fbuild\u002Fbadge.svg?branch=main)](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Factions?query=workflow%3Abuild)\n[![指南文档](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGuide-Documents-forestgreen)](https:\u002F\u002Fautobe.dev\u002Fdocs\u002F)\n[![Discord 社区徽章](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002Fhttps:\u002F\u002Fdiscord.gg\u002FaMhRmzkqCx?style=flat)](https:\u002F\u002Fdiscord.gg\u002FaMhRmzkqCx)\n\n通过 AutoBE 的聊天界面，用自然语言描述你的后端需求。\n\nAutoBE 将分析你的需求并为你构建后端应用。生成的后端应用完全兼容 AI 友好的编译器，并通过强大的端到端测试功能确保稳定性。\n\n借助 AutoBE，你可以快速搭建第一个后端应用，随后使用 Claude Code 等 AI 编码助手进行维护和扩展，从而提升开发效率与系统稳定性。\n\nAutoBE 会生成完整的规范说明、详尽的数据库与 API 文档、全面的测试覆盖率以保障稳定性，以及清晰的实现逻辑，既可作为初级开发者的学习基础，又能显著提高资深开发人员的工作效率。\n\n请查看由 AutoBE 生成的这些完整后端应用示例：\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fb995dd2a-23bd-43c9-96cb-96d5c805f19f\n\n1. **待办事项列表**：[`todo`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ftodo)\n2. **Reddit 社区**：[`reddit`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit)\n3. **电子商务**：[`shopping`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Fshopping)\n4. **ERP 系统**：[`erp`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp)\n   - 需求分析：[报告](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fdocs\u002Fanalysis)\n   - 数据库设计：[实体关系图](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fdocs\u002FERD.md) \u002F [Prisma 模式](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fprisma\u002Fschema)\n   - API 设计：[API 控制器](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fsrc\u002Fcontrollers) \u002F [DTO 结构](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fsrc\u002Fapi\u002Fstructures)\n   - 端到端测试函数：[`test\u002Ffeatures\u002Fapi`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Ftest\u002Ffeatures\u002Fapi)\n   - API 实现：[`src\u002Fproviders`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Ferp\u002Fsrc\u002Fproviders)\n\n## 快速开始\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe --depth=1\ncd autobe\npnpm install\npnpm run playground\n```\n\n要使用 AutoBE，请克隆仓库并在本地运行游乐场应用。这将允许你与 AutoBE 的 AI 代理进行对话、管理多个会话，并使用包括本地模型 `qwen3.5-397b-a17b` 在内的多种 LLM 提供商。\n\n安装完成后，游乐场将在 http:\u002F\u002Flocalhost:5173 上可用。你可以通过聊天界面与 AutoBE 互动——只需简单描述你想构建的内容，AutoBE 就会为你生成后端应用。\n\n以下是一个示例对话脚本，指导 AutoBE 创建一个“经济\u002F政治讨论版”：\n\n1. **需求分析**：“我想创建一个经济\u002F政治讨论版。由于我对编程不太熟悉，所以请按照你认为合适的方式撰写一份需求分析报告。”\n2. **数据库设计**：“设计数据库模式。”\n3. **API 规范**：“创建 API 接口规范。”\n4. **测试**：“编写端到端测试函数。”\n5. **实现**：“实现 API 函数。”\n\n![编译成功仪表盘](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fwrtnlabs_autobe_readme_598f0a719915.png)\n\n> 游乐场包含一个回放功能，地址为 http:\u002F\u002Flocalhost:5173\u002Freplay\u002Findex.html，你可以在那里查看 AutoBE 开发团队在测试和基准测试中留下的聊天记录。\n\n## 文档资源\n\n更多详细资源请访问我们的[官方网站](https:\u002F\u002Fautobe.dev)。\n\n### 🏠 首页\n\n- 🙋🏻‍♂️ [简介](https:\u002F\u002Fautobe.dev\u002Fdocs)\n- 📦 [设置](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fsetup)\n- 🔍 概念\n  - [瀑布模型](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fconcepts\u002Fwaterfall)\n  - [编译器策略](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fconcepts\u002Fcompiler)\n  - [AI 函数调用](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fconcepts\u002Ffunction-calling)\n\n### 📖 功能\n\n- 🤖 代理库\n  - [门面控制器](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Ffacade)\n  - [配置](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Fconfig)\n  - [事件处理](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Fevent)\n  - [提示历史](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fagent\u002Fhistory)\n- 📡 WebSocket 协议\n  - [远程过程调用](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Frpc)\n  - [NestJS 服务器](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Fnestjs)\n  - [NodeJS 服务器](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Fnodejs)\n  - [客户端应用](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fwebsocket\u002Fclient)\n- 🛠️ 后端技术栈\n  - [TypeScript](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fstack\u002Ftypescript)\n  - [Prisma ORM](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fstack\u002Fprisma)\n  - [NestJS 框架](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fstack\u002Fnestjs)\n\n### 🔗 附录\n\n- 🌐 [无代码生态系统](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Fecosystem)\n- 📅 路线图\n  - [Alpha 版（已完成）](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Falpha)\n  - [Beta 版（已完成）](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Fbeta)\n  - [Gamma 版（已完成）](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Fgamma)\n  - [Delta 版（正在进行中）](https:\u002F\u002Fautobe.dev\u002Fdocs\u002Froadmap\u002Fdelta)\n- 🔧 [API 文档](https:\u002F\u002Fautobe.dev\u002Fapi)\n\n## AutoBE 的工作原理\n\n```mermaid\nflowchart\nsubgraph \"后端编码代理\"\n  coder(\"Facade 控制器\")\nend\nsubgraph \"功能代理\"\n  coder --\"需求分析\"--> analyze(\"分析\")\n  coder --\"ERD\"--> database(\"数据库\")\n  coder --\"API 设计\"--> interface(\"接口\")\n  coder --\"测试代码\" --> test(\"测试\")\n  coder --\"主程序\" --> realize(\"实现\")\nend\nsubgraph \"编译器反馈\"\n  database --\"验证\" --> prismaCompiler(\"\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmain\u002Fpackages\u002Finterface\u002Fsrc\u002Fdatabase\u002FAutoBeDatabase.ts\" target=\"_blank\">数据库编译器\u003C\u002Fa>\")\n  interface --\"生成\" --> openapiCompiler(\"\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmain\u002Fpackages\u002Finterface\u002Fsrc\u002Fopenapi\u002FAutoBeOpenApi.ts\" target=\"_blank\">OpenAPI 编译器\u003C\u002Fa>\")\n  test --\"分析\" --> testCompiler(\"\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fblob\u002Fmain\u002Fpackages\u002Finterface\u002Fsrc\u002Ftest\u002FAutoBeTest.ts\" target=\"_blank\">测试编译器\u003C\u002Fa>\")\n  realize --\"编译\" --> realizeCompiler(\"混合编译器\")\nend\n```\n\nAutoBE 遵循瀑布式方法论来生成后端应用，由 40 多个专业代理负责处理每个阶段。这些代理在整个开发过程中以协调一致的团队形式协同工作。\n\n每个瀑布阶段都包含对 AI 友好的编译器，以确保生成代码的类型安全性。与直接生成代码不同，AutoBE 的代理首先使用预定义的模式构建语言中立的抽象语法树（AST）。在进行任何代码生成之前，每个 AST 节点都会根据类型规则进行验证，从而在概念层面而非编译阶段捕获结构性错误。\n\n这种方法旨在确保最终生成的 TypeScript 和 Prisma 代码能够 100% 正常构建。根据我们对多个示例项目的测试结果，包括电子商务平台、讨论论坛和任务管理系统，AutoBE 在各种不同类型的应用中均能保持这一编译保证。\n\n为了说明这一过程，以下是我们的“经济\u002F政治讨论论坛”示例的各阶段输出：\n\n1. **需求分析**：[报告](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fdocs\u002Fanalysis)\n2. **数据库设计**：[实体关系图](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fdocs\u002FERD.md) \u002F [Prisma 模式](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fprisma\u002Fschema)\n3. **API 规范**：[API 控制器](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fsrc\u002Fcontrollers) \u002F [DTO 结构](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fsrc\u002Fapi\u002Fstructures)\n4. **端到端测试函数**：[`test\u002Ffeatures\u002Fapi`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Ftest\u002Ffeatures\u002Fapi)\n5. **API 实现**：[`src\u002Fproviders`](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe-examples\u002Ftree\u002Fmain\u002Fz-ai\u002Fglm-5\u002Freddit\u002Fsrc\u002Fproviders)\n\n## 基准测试\n\nAutoBE 包含一个自动化评估管道，可对 13 种以上的 LLM 模型和 4 种项目类型生成的后端进行评分。实时结果请访问 **[autobe.dev\u002Fbenchmark](https:\u002F\u002Fautobe.dev\u002Fbenchmark\u002F)**。\n\n该基准测试会评估编译正确性、文档质量、需求覆盖率、测试覆盖率、逻辑完整性、API 完整性以及 AI 代理分析（安全性、幻觉问题、代码质量）。每个模型的得分范围为 0–100 分，并按 A–F 等级划分。\n\n| 模型 | Todo | Reddit | 购物 | ERP | 平均 |\n|-------|------|--------|----------|-----|-----|\n| glm-5 | 88 (B) | 87 (B) | 82 (B) | 87 (B) | **86** |\n| claude-sonnet-4.6 | 87 (B) | 85 (B) | 72 (C) | 85 (B) | 82 |\n| gpt-5.4-mini | 89 (B) | 87 (B) | 74 (C) | 78 (C) | 82 |\n| qwen3-coder-next | 86 (B) | 76 (C) | 75 (C) | 88 (B) | 81 |\n| qwen3.5-27b | 88 (B) | 81 (B) | 77 (C) | 78 (C) | 81 |\n| minimax-m2.7 | 90 (A) | 71 (C) | 77 (C) | 79 (C) | 79 |\n| gpt-5.4 | 79 (C) | 78 (C) | 79 (C) | 80 (B) | 79 |\n\n### 运行基准测试\n\n```bash\n# 执行所有模型（默认）\ncorepack pnpm estimate\n\n# 仅运行单个模型\ncorepack pnpm estimate -- --model kimi-k2.5\n\n# 仅运行单个项目\ncorepack pnpm estimate -- --project todo\n\n# 同时指定模型和项目\ncorepack pnpm estimate -- --model glm-5 --project shopping\n\n# 如果已全局安装 pnpm\npnpm estimate\n```\n\n报告将保存至以下路径：\n\n```\npackages\u002Festimate\u002Freports\u002Fbenchmark\u002F{model}\u002F{project}\u002Festimate-report.json\n```\n\n此外，您无需使用所有阶段——只需根据需求停留在任意阶段即可。无论您只需要需求分析、数据库设计、API 规范，还是端到端测试，AutoBE 都能适应您的工作流程。\n\n另外，如果您因语言偏好而非工作流程需求而跳过完整流程，此功能目前正在开发中——AutoBE 的语言中立 AST 结构很快将支持除 TypeScript 之外的其他编程语言。\n\n## 类型安全的客户端 SDK\n\n每个由 AutoBE 生成的后端都会自动附带一个类型安全的客户端 SDK，使前端集成无缝且无误。该 SDK 提供：\n\n- **零配置**：SDK 与您的后端同时自动生成，无需手动设置\n- **100% 类型安全**：全面的 TypeScript 支持，具备自动补全和编译时验证功能\n- **框架无关**：适用于 React、Vue、Angular 或任何 TypeScript\u002FJavaScript 项目\n- **端到端测试集成**：驱动 AI 生成的测试套件，实现全面的后端测试\n\n```typescript\nimport api, { IPost } from \"autobe-generated-sdk\";\n\n\u002F\u002F 类型安全的 API 调用，支持完整自动补全\nconst connection: api.IConnection = {\n  host: \"http:\u002F\u002Flocalhost:1234\",\n};\nawait api.functional.users.login(connection, {\n  body: {\n    email: \"user@example.com\",\n    password: \"secure-password\",\n  },\n});\n\n\u002F\u002F TypeScript 在编译时捕获错误\nconst post: IPost = await api.functional.posts.create(connection, {\n  body: {\n    title: \"Hello World\",\n    content: \"我的第一篇帖子\",\n    \u002F\u002F authorId: \"123\" \u003C- 如果缺少此字段，TypeScript 会报错！\n  },\n});\n```\n\n该 SDK 消除了传统 API 集成中的痛点——不再需要手动定义类型，不会再出现运行时意外，也无需再查找 API 文档。您的前端开发人员可以专注于构建功能，而不是纠结于 API 协议。\n\n**超越前端集成**：该 SDK 不仅支持前端开发，还用于生成端到端测试。AutoBE 内部同样使用这个类型安全的 SDK 来生成全面的测试套件，确保每个 API 端点都得到充分测试。这形成了一个强大的反馈回路，进一步提升后端的稳定性——AI 使用 SDK 编写测试，SDK 确保类型安全，而您的后端则随着每次生成的测试不断变得更加可靠。\n\n## 路线图时间表\n\n```mermaid\ngantt\n  dateFormat YYYY-MM-DD\n  title AutoBE Delta 路线图时间线（2026年第一季度）\n\n  section 本地 LLM 基准测试\n  Qwen3 数据库阶段             : 已完成, 2026-01-01, 31天\n  Qwen3 接口阶段            : 已完成, 2026-01-16, 31天\n  Qwen3 测试阶段                 : 已完成, 2026-02-01, 21天\n  Qwen3 实现阶段              : 已完成, 2026-02-01, 59天\n\n  section 验证逻辑增强\n  动态函数调用模式  : 已完成, 2026-01-01, 7天\n  验证反馈字符串化    : 已完成, 2026-01-08, 12天\n  JSON Schema 验证器            : 已完成, 2026-01-08, 12天\n  模式审查验证逻辑   : 已完成, 2026-01-20, 35天\n  测试映射计划优化    : 已完成, 2026-02-05, 24天\n  实现映射计划优化 : 已完成, 2026-02-15, 45天\n\n  section RAG 优化\n  混合搜索（向量 + BM25）    : 已完成, 2026-01-01, 14天\n  动态 K 检索              : 已完成, 2026-01-15, 14天\n  RAG 初步提示               : 已完成, 2026-01-15, 28天\n  RAG 基准测试与调优           : 已完成, 2026-02-01, 28天\n  分析代理重构      : 已完成, 2026-02-01, 28天\n\n  section 设计完整性\n  数据库覆盖率代理                : 已完成, 2026-01-15, 28天\n  API 端点覆盖率代理      : 已完成, 2026-01-22, 28天\n  模式关系代理            : 已完成, 2026-02-01, 28天\n  模式结构代理           : 已完成, 2026-02-01, 28天\n  模式内容代理             : 已完成, 2026-03-01, 28天\n\n  section 多语言支持\n  Java 编译器 PoC                : 已完成,   2026-01-01, 30天\n  Java 数据库                    : 已完成,   2026-01-01, 14天\n  Java 接口                   : 已完成,   2026-01-15, 21天\n  Java 测试                        : 进行中, 2026-02-05, 28天\n  Java 实现                     : 进行中, 2026-03-01, 31天\n\n  section 人工修改支持\n  数据库模式解析器           : 进行中,  2026-02-15, 28天\n  接口模式解析器          : 进行中,  2026-02-22, 28天\n  需求同步代理          : 计划中, 2026-03-08, 24天\n\n  section 其他事项\n  系统提示简化     : 已完成,   2026-02-01, 28天\n  估算代理                 : 已完成,   2026-02-01, 28天\n  Playground 服务增强   : 进行中, 2026-02-15, 28天\n  PR 文章撰写              : 进行中, 2026-02-15, 30天\n```\n\nAutoBE 已成功完成 Alpha、Beta 和 Gamma 开发阶段，以 **100% 的编译成功率** 奠定了坚实的基础。当前的 **Delta 版本** 专注于从横向扩展转向纵向深化。\n\n**战略转变**：在 Gamma 阶段，我们秉持“尽快发布”的理念，快速实现了 RAG、模块化和补充等功能。而 Delta 版本则通过本地 LLM 基准测试系统性地发现并修复隐藏缺陷，填补了 Gamma 阶段遗留下来的稳定性空白。\n\n**重点方向**：\n\n- **本地 LLM 基准测试**：以 Qwen3 等开源模型为基准，挖掘商业模型掩盖的隐藏缺陷，确保在各类模型上都能更稳健地运行。\n- **验证逻辑增强**：通过动态函数调用模式、JSON Schema 验证器以及渐进式验证流水线，强化模式和验证逻辑。\n- **RAG 优化**：完成混合搜索系统（向量 + BM25），实现动态 K 检索，并进行全面的基准测试与调优。\n- **设计完整性**：构建机制，通过覆盖率和模式审查代理，验证并确保数据库与接口阶段之间的设计一致性。\n- **多语言支持**：推出 Java\u002FSpring 代码生成功能，同时支持 TypeScript\u002FNestJS；语言中立的 AST 结构也为未来添加更多语言奠定了基础。\n- **人工修改支持**：通过将用户修改后的代码解析回 AutoBE 的内部 AST 表示，确保维护工作的连续性，使 AutoBE 在初次生成后仍具实用性。\n\n该路线图以 Gamma 阶段的实际生产经验为指导，优先考虑稳定性和深度，而非功能广度。\n\n## 当前局限性\n\n尽管 AutoBE 可实现 100% 的编译成功率，但仍存在以下局限性：\n\n**运行时行为**：生成的应用程序虽然能够成功编译，但运行时行为可能需要进一步测试和调整。在服务器执行过程中，可能会出现意外的运行时错误，例如数据库连接问题、API 端点故障或编译阶段未捕获的业务逻辑异常。我们强烈建议在部署到生产环境之前，在开发环境中进行充分的测试。我们的 v1.0 版本旨在解决这些问题，实现 100% 的运行成功率。\n\n**设计解读**：AutoBE 生成的数据库和 API 设计可能与您的预期有所不同。我们建议在继续实施之前，尤其是部署到生产环境之前，仔细审查生成的规范。\n\n**Token 消耗**：对于复杂项目，AutoBE 需要消耗大量的 AI Token。根据我们的测试，项目通常会消耗 30M 至 250M+ Token，具体取决于复杂程度（简单的待办事项应用大约需要 4M Token，而复杂的电子商务平台可能需要 250M+ Token）。我们正在通过 RAG 优化来降低未来版本中的这一开销。\n\n**维护**：AutoBE 侧重于初始生成，不提供持续的维护能力。一旦后端生成完毕，您需要手动处理 bug 修复、功能添加、性能优化和安全更新等工作。我们建议建立一种开发工作流，将生成的代码库与 Claude Code 等 AI 编码助手相结合，以高效地完成后续开发和维护任务。\n\n![实体关系图示例](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fwrtnlabs_autobe_readme_54d385d15501.png)\n\n## 许可证\n\nAutoBE 根据 [GNU Affero 通用公共许可证 v3.0 (AGPL-3.0)](LICENSE) 授权。如果您对 AutoBE 本身进行修改，或将之作为网络服务提供，则必须以相同许可证公开您的源代码。\n\n然而，由 AutoBE 生成的后端应用程序可以采用您选择的任何许可证进行再授权，例如 MIT 许可证。这意味着您可以自由地在商业项目中使用 AutoBE 生成的代码，而无需承担开源义务，这与其他代码生成工具的使用方式类似。","# AutoBE 快速上手指南\n\nAutoBE 是一款基于 AI 的后端构建工具，支持从原型设计到生产环境的全流程开发。只需通过自然语言描述需求，AutoBE 即可自动生成包含数据库设计、API 规范、E2E 测试及完整实现逻辑的后端应用。生成的代码具备 100% 可编译性，并内置类型安全的客户端 SDK。\n\n## 环境准备\n\n在开始之前，请确保您的开发环境满足以下要求：\n\n*   **操作系统**：Windows, macOS 或 Linux\n*   **Node.js**：建议安装最新 LTS 版本（推荐 v18+）\n*   **包管理器**：必须安装 `pnpm` (AutoBE 官方推荐使用 pnpm)\n    *   若未安装，可通过 npm 全局安装：`npm install -g pnpm`\n*   **Git**：用于克隆项目仓库\n\n> **提示**：国内开发者若遇到网络连接问题，建议配置国内镜像源加速依赖下载：\n> ```bash\n> pnpm config set registry https:\u002F\u002Fregistry.npmmirror.com\n> ```\n\n## 安装步骤\n\n通过以下命令克隆仓库并安装依赖，启动本地 Playground 应用：\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe --depth=1\ncd autobe\npnpm install\npnpm run playground\n```\n\n安装完成后，Playground 服务将运行在 `http:\u002F\u002Flocalhost:5173`。\n\n## 基本使用\n\n启动服务后，在浏览器打开 `http:\u002F\u002Flocalhost:5173`，您将看到聊天界面。AutoBE 采用瀑布流开发模式，建议您按以下步骤通过对话引导 AI 完成后端构建：\n\n### 1. 创建会话并描述需求\n在聊天框中输入您的项目构想。例如，创建一个“经济\u002F政治讨论区”：\n\n> \"I want to create an economic\u002Fpolitical discussion board. Since I'm not familiar with programming, please write a requirements analysis report as you see fit.\"\n> *(我想创建一个经济\u002F政治讨论板。由于我不熟悉编程，请酌情撰写一份需求分析报告。)*\n\n### 2. 分阶段构建\n根据 AutoBE 的反馈，依次发送以下指令以推进开发流程：\n\n*   **数据库设计**：\n    > \"Design the database schema.\"\n*   **API 规范定义**：\n    > \"Create the API interface specification.\"\n*   **生成测试用例**：\n    > \"Make the e2e test functions.\"\n*   **实现业务逻辑**：\n    > \"Implement API functions.\"\n\n### 3. 获取成果\nAutoBE 将在后台协调多个专用 Agent 完成上述任务，并通过编译器验证每一步的类型安全。完成后，您可以在左侧文件树中查看生成的完整项目结构，包括：\n*   需求分析报告\n*   Prisma 数据库 Schema\n*   NestJS 控制器与 DTO 结构\n*   E2E 测试代码\n*   完整的 API 实现逻辑\n\n生成的后端项目默认包含类型安全的 Client SDK，可直接在前端项目中引用，实现零配置的无缝集成。","一位初创公司的技术负责人需要在两天内向投资人演示一个具备完整后端逻辑的“社区电商原型”，但团队目前缺乏专职后端开发人员。\n\n### 没有 autobe 时\n- **架构设计耗时久**：从零开始梳理数据库实体关系（ERD）和 API 接口定义需要数天时间，严重压缩开发窗口。\n- **代码质量不稳定**：匆忙手写的 TypeScript 代码常出现类型错误或运行时崩溃，调试过程占据大量精力。\n- **测试覆盖率为零**：为确保演示不翻车需手动编写端到端测试，但在工期压力下往往被直接舍弃，导致演示风险极高。\n- **文档缺失**：缺乏自动生成的 API 文档和数据库说明，前后端协作或后续交接时沟通成本巨大。\n\n### 使用 autobe 后\n- **即时生成架构**：只需在对话框输入“构建一个带用户系统和订单管理的社区电商后端”，autobe 即刻输出完整的数据库 Schema 和 API 规范。\n- **编译器级代码保障**：autobe 利用编译器技能生成 100% 可构建的 TypeScript 代码，彻底消除低级语法错误和类型不匹配问题。\n- **内置稳定性测试**：工具自动生成全覆盖的 E2E 测试用例，确保核心业务流程在演示中稳定运行，无需人工补写测试。\n- **文档代码同步产出**：autobe 同步生成详细的 API 文档和数据结构说明，让原型不仅可用，更具备生产级的可维护性。\n\nautobe 将原本需要一周的后端搭建工作压缩至小时级，让非后端背景的开发者也能快速交付高质量、可运行的生产级原型。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fwrtnlabs_autobe_598f0a71.png","wrtnlabs","Wrtn Technologies","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fwrtnlabs_96370e4b.png","",null,"wrtnlabs@wrtn.io","https:\u002F\u002Fwrtnlabs.io","https:\u002F\u002Fgithub.com\u002Fwrtnlabs",[82,86,90,94,98,102],{"name":83,"color":84,"percentage":85},"TypeScript","#3178c6",86.7,{"name":87,"color":88,"percentage":89},"MDX","#fcb32c",10,{"name":91,"color":92,"percentage":93},"JavaScript","#f1e05a",2.3,{"name":95,"color":96,"percentage":97},"Shell","#89e051",0.6,{"name":99,"color":100,"percentage":101},"CSS","#663399",0.2,{"name":103,"color":104,"percentage":101},"HTML","#e34c26",1307,154,"2026-04-19T06:49:12","AGPL-3.0","Linux, macOS, Windows","非必需（支持本地模型如 qwen3.5，具体显存需求取决于所选模型大小；若使用云端 LLM 则无需本地 GPU）","未说明（建议根据运行的本地大模型规模配置，通常大型模型需 16GB+）",{"notes":113,"python":114,"dependencies":115},"该工具基于 Node.js 生态，需安装 pnpm 包管理器。核心功能依赖外部大语言模型（LLM），既支持云端 API 也支持本地部署模型（如 qwen3.5-397b）。生成的后端应用采用 TypeScript、NestJS 和 Prisma 技术栈。无需 Python 或 CUDA 环境即可运行框架本身，除非用户在本地自行部署需要 GPU 的大模型。","未说明",[116,117,118,119,83],"Node.js (通过 corepack\u002Fpnpm 管理)","@autobe\u002Fagent","NestJS","Prisma ORM",[35,45,14,13],[122,123,124,125,126,127,128,129,130,131,132,133,134,135],"all-in-one","automation","backend","generated-api","llm","prisma","server","nestia","nestjs","ai-coding-agent","vibe-coding","no-coding","no-coding-app","no-coding-tools","2026-03-27T02:49:30.150509","2026-04-20T04:05:07.108930",[139,144,149,154,159,163],{"id":140,"question_zh":141,"answer_zh":142,"source_url":143},43289,"遇到 OpenAI API 请求错误（如 429 Rate Limit 或配额超限）时该怎么办？","当遇到 'RateLimitError: 429 You exceeded your current quota' 等错误时，通常是因为触发了临时速率限制或 Token 大小限制。这在大项目初始化时偶尔会发生。解决方案是重试生成步骤（例如重试 API 接口生成）。系统计划实施随机指数退避重试功能来自动处理此类问题。如果问题持续，请检查您的 OpenAI 套餐和账单详情。","https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F136",{"id":145,"question_zh":146,"answer_zh":147,"source_url":148},43290,"生成的 Prisma Schema 中索引名称看起来有拼写错误或被截断，这是 Bug 吗？","这不是 Bug，而是参考了 TypeORM 的索引命名规范。当索引名称过长（例如超过 64 或 128 个字符）时，Postgres 等数据库管理系统会拒绝执行。因此，TypeORM 采用了通过组合子字符串和哈希来缩短索引名称的逻辑。如果您看到名称被截断或包含哈希值，这是为了确保数据库兼容性的预期行为。","https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F858",{"id":150,"question_zh":151,"answer_zh":152,"source_url":153},43291,"Test Agent 无法修复特定的 TypeScript 编译错误（如类型不匹配）怎么办？","如果遇到 Test Agent 陷入循环无法修复类似 \"Type 'string | null | undefined' is not assignable to type 'string | undefined'\" 的编译错误，建议在报告问题时上传包含复现步骤的 zip 文件（包括 snapshots.json 和编译错误日志）。维护者已针对各类模型优化了此问题，实现了 100% 的成功率，提供详细的复现文件有助于快速定位和验证修复。","https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F508",{"id":155,"question_zh":156,"answer_zh":157,"source_url":158},43292,"在 StackBlitz Playground 中生成 Prisma Schema 文件失败怎么办？","如果提示 \"Succeeded to compose AutoBePrisma.IApplication typed AST... but failed to generate Prisma schema files\"，这通常是由于约束名、索引名有字符长度限制，或者在 SQLite 中尝试为关系命名（SQLite 不允许显式命名关系）导致的。解决方法是检查生成的 prisma.json 文件，确保索引和约束名称符合长度限制，并避免在 SQLite 模式下为 relation 指定名称。提交包含 histories.json 的错误报告有助于修复此类问题。","https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F254",{"id":160,"question_zh":161,"answer_zh":162,"source_url":143},43293,"为什么在读取 SSE 流时会发生错误，且难以在 agentica 中处理？","某些特定错误（如 Issue 中提到的编号 5 的错误）发生在读取 SSE (Server-Sent Events) 流的过程中。由于这涉及底层流处理逻辑，若要在 agentica 框架层面统一处理此类错误，需要对代理核心进行大量修改。目前这类问题通常需要针对具体场景进行特殊处理或等待框架层面的架构更新。",{"id":164,"question_zh":165,"answer_zh":166,"source_url":167},43294,"Test Agent 是否支持返回 assistantMessage 或在测试过程中提问？","早期的 Test Agent 设计为不返回任何 assistantMessage，但这在处理需要向用户确认细节（如密度问题案例）的场景时会失效。目前的改进方向是允许 AI 在必要时提出问题或返回辅助消息，以打破僵化的测试流程。如果您遇到测试代理因无法交互而卡住的情况，请确认您使用的是已更新此逻辑的最新版本。","https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F348",[169,174,179,184,189,194,199,204,209,214,219,224,229,234,239,244,249,254,259,264],{"id":170,"version":171,"summary_zh":172,"released_at":173},342976,"v0.31.1","###    🐞 错误修复\n\n- **playground**: 为本地 playground 执行 Prisma db push。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1291 中提出 [\u003Csamp>(3fc85)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3fc85b4650)\n\n#####     [在 GitHub 上查看更改](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.31.0...v0.31.1)","2026-04-10T07:54:17",{"id":175,"version":176,"summary_zh":177,"released_at":178},342977,"v0.31.0","###    🚀 功能特性\n\n- **agen**:\n  - 关于实现阶段的详细指南。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1283 中提出 [\u003Csamp>(d451d)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fd451d5950c)\n- **agent**:\n  - 比较 DTO 属性类型与数据库列类型。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1258 中提出 [\u003Csamp>(145f4)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F145f459487)\n  - 实现使用收集器\u002F转换器的操作模板。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1260 中提出 [\u003Csamp>(425e6)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F425e646473)\n  - 通过基准测试增强实现阶段。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1261 中提出 [\u003Csamp>(42dda)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F42dda43203)\n  - 向 IComplete 添加提醒和确认字段，用于提前… -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1263 中提出 [\u003Csamp>(4081e)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F4081eef10a)\n  - interfaceSchemaReview 的循环式编写-验证-修正流程。 -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1225 中提出 [\u003Csamp>(06a31)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F06a318137d)\n  - 增强初步重写规则。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1269 中提出 [\u003Csamp>(219b0)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F219b06220a)\n  - 从初步编排之外分发事件。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1271 中提出 [\u003Csamp>(6fc52)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F6fc5216d98)\n  - 仅针对关键情况的初步重写。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1272 中提出 [\u003Csamp>(e7cef)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fe7cefebcd7)\n  - 不再需要评审代理。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1273 中提出 [\u003Csamp>(d08cf)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fd08cf44b8c)\n  - 增强实现模板规则。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1278 中提出 [\u003Csamp>(3ab90)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3ab90ce4b6)\n  - 自动化代理修复流程。 -  由 @samchon 和 **Copilot** 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1281 中提出 [\u003Csamp>(65d44)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F65d44032ea)\n  - 实现函数的 1 次重试变更。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1282 中提出 [\u003Csamp>(b3f70)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb3f70da160)\n- **estimate**:\n  - 为合同评估器添加路径参数支持。 -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1257 中提出 [\u003Csamp>(9b836)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F9b836b2ff5)\n  - 黄金集运行时稳定性 + Langfuse 增强。 -  由 @k08200 在 https:","2026-04-09T07:06:03",{"id":180,"version":181,"summary_zh":182,"released_at":183},342978,"v0.30.5","###    🚀 功能特性\n\n- **benchmark**:\n  - 添加包含阶段细分的评分详情模态框  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1239 中实现 [\u003Csamp>(e1101)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fe11019330b)\n  - 流水线阶段可视化、自动部署以及代理…  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1243 中实现 [\u003Csamp>(ada84)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fada843d82b)\n  - 自动将基准测试结果部署到 autobe.dev  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1247 中实现 [\u003Csamp>(1702b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F1702bc3952)\n- **interface**:\n  - 简洁的函数调用模式描述。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1231 中实现 [\u003Csamp>(afbf8)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fafbf822cb2)\n- **test**:\n  - 诊断基准测试结果。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1228 中实现 [\u003Csamp>(dc3d1)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fdc3d13f9a2)\n- **website**:\n  - 添加原生基准测试排行榜页面  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1226 中实现 [\u003Csamp>(80679)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8067973aef)\n  - 修复 qwen 韩国 meetup 演示文稿  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1230 中实现 [\u003Csamp>(7b012)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F7b012107d7)\n  - 完成 qwen meetup 演示文稿。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1233 中实现 [\u003Csamp>(4573c)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F4573ccdd74)\n  - 简洁的 qwen meetup 文章。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1244 中实现 [\u003Csamp>(63fde)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F63fdecf12e)\n  - 将 CodeShowcase 占位符替换为真实的 AutoBE 生成代码  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1246 中实现 [\u003Csamp>(81221)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F81221f53d6)\n\n###    🐞 Bug 修复\n\n- **agent**:\n  - 递归关系问题。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1253 中实现 [\u003Csamp>(60218)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F60218ae8b8)\n  - 强制 `select()` 函数使用隐式返回类型。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1255 中实现 [\u003Csamp>(8365f)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8365f11552)\n- **benchmark**:\n  - 从基准测试数据中移除 gauzy 项目和 gpt-4.1 模型  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1236 中实现 [\u003Csamp>(57d17)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F57d17403a7)\n  - 更新基准测试数据，加入 16 种模型并移除 gpt-4.1  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1237 中实现 [\u003Csamp>(57924)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F57924fa15c)\n  - 恢复正确的 JSON 格式 fo","2026-03-31T15:40:16",{"id":185,"version":186,"summary_zh":187,"released_at":188},342979,"v0.30.4","###    🚀 功能特性\n\n- **estimate**:\n  - 完善评分评估器并修复评分相关 bug  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1214 中完成 [\u003Csamp>(43352)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F433528cef3)\n- **playground**:\n  - 新增支持多会话的后端服务器。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1204 中完成 [\u003Csamp>(33562)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F335624b47b)\n  - 前端应用开发。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1213 中完成 [\u003Csamp>(5ae49)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5ae49c9fef)\n  - 集成 shadcn 组件库。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1221 中完成 [\u003Csamp>(118b3)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F118b370f5e)\n- **test**:\n  - 添加标签以避免使用伪造的 OpenRouter 模型。  -  由 @samchon 和 **Copilot** 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1215 中共同完成 [\u003Csamp>(3bbbe)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3bbbed1247)\n- **website**:\n  - 为通义千问韩国 Meetup 准备的 PPT  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1209 中完成 [\u003Csamp>(1440b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F1440bfa66f)\n  - 优化文案表述。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1211 中完成 [\u003Csamp>(6bcb2)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F6bcb27ea51)\n  - 修订通义千问 Meetup 相关文章。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1212 中完成 [\u003Csamp>(db3e3)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fdb3e31a781)\n  - 补充完善通义千问韩国 Meetup 的 PPT。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1216 中完成 [\u003Csamp>(75cde)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F75cde2881b)\n  - 搭建博客。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1217 中完成 [\u003Csamp>(b8910)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb891005aff)\n  - 使用垂直导航和交互式设计重新打造首页。  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1219 中完成 [\u003Csamp>(e4eea)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fe4eeac1b16)\n\n###    🐞 Bug 修复\n\n- **agent**: 暂时关闭 `validateEmptyProperties()` 检查。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1208 中完成 [\u003Csamp>(da805)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fda80587ff8)\n- **benchmark**: 示例归档工具中包含 ERP 数据。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1207 中完成 [\u003Csamp>(e5c82)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fe5c829f566)\n\n#####     [查看 GitHub 上的变更](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.30.3...v0.30.4)","2026-03-25T00:57:58",{"id":190,"version":191,"summary_zh":192,"released_at":193},342980,"v0.30.3","###    🚀 功能特性\n\n- **dashboard-ui**:\n  - 添加基准测试可视化仪表盘  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1192 中完成 [\u003Csamp>(73124)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F73124c3c34)\n  - 添加自动刷新轮询及模型更新时间戳  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1202 中完成 [\u003Csamp>(5c453)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5c4532f929)\n- **estimate**:\n  - 单仓库模式，因此可直接运行 `ts` 文件。  -  由 @samchon 完成 [\u003Csamp>(42718)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F427184ba8d)\n  - 单仓库模式，因此可直接运行 `ts` 文件。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1197 中完成 [\u003Csamp>(dcdb4)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fdcdb4081bf)\n- **test**:\n  - 在 exacto 模型上进行基准测试，但效果不佳。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1201 中完成 [\u003Csamp>(195ff)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F195ffd7d0d)\n- **website**:\n  - 通义千问韩国线下交流会草稿版。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1198 中完成 [\u003Csamp>(8d443)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8d4434eae3)\n\n###    🐞 Bug 修复\n\n- **estimate**: 恢复 gate 评估中的 typeWarningCount\u002FtypeIssueCount…  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1203 中完成 [\u003Csamp>(74ab9)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F74ab9e9945)\n\n#####     [在 GitHub 上查看变更](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.30.2...v0.30.3)","2026-03-18T04:46:47",{"id":195,"version":196,"summary_zh":197,"released_at":198},342981,"v0.30.2","###    🚀 功能特性\n\n- 简化 PRELIMINARY 提示文件  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1057 中完成 [\u003Csamp>(6257f)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F6257fbb676)\n- 简化 AGENTICA 提示文件  -  由 @k08200 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1054 中完成 [\u003Csamp>(74b06)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F74b06d3985)\n- 添加 TypeScript 文件的格式化脚本和 GitHub 工作流  -  由 @sunrabbit123 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1067 中完成 [\u003Csamp>(113cc)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F113ccb4095)\n- *****:\n  - 通用 LLM 模式。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F863 中完成 [\u003Csamp>(38dad)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F38dad14665)\n- **agaent**:\n  - `orchestrateInterface()` 的重构。  -  由 @samchon 和 **Copilot** 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1016 中完成 [\u003Csamp>(385cb)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F385cbeddfb)\n- **agen**:\n  - 简洁并修订接口提示  -  由 @samchon 和 **Copilot** 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F1045 中完成 [\u003Csamp>(c810e)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc810eea6cb)\n- **agent**:\n  - 幻影属性的 DTO 模式审查器。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F808 中完成 [\u003Csamp>(24332)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F243326bdfd)\n  - 向 AutoBeAgent 添加图像描述功能  -  由 @8471919 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F799 中完成 [\u003Csamp>(067e4)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F067e4f91cb)\n  - 实现代理生成代码的模块化。  -  由 @samchon 和 **Copilot** 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F837 中完成 [\u003Csamp>(9bc3c)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F9bc3cd3fcb)\n  - 测试代理集成  -  由 @8471919 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F854 中完成 [\u003Csamp>(a2aa3)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fa2aa3d7d3d)\n  - 通过 RAG 补充用户功能  -  由 @samchon 和 **Copilot** 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F850 中完成 [\u003Csamp>(b8082)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb8082814a8)\n  - 接口模式仅设计一个代理。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F866 中完成 [\u003Csamp>(38800)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F38800621d8)\n  - 为提高准确性，排除 JSON 模式类型。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F871 中完成 [\u003Csamp>(bcb34)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fbcb344d559)\n  - 使接口操作代理更加轻量化。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F872 中完成 [\u003Csamp>(aea9a)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Faea9a43f0d)\n  - 加强对 AI 的 DTO 类型限制。  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F874 中完成 [\u003Csamp>(4f13","2026-03-15T15:16:35",{"id":200,"version":201,"summary_zh":202,"released_at":203},342982,"v0.29.2","###    🚀 功能特性\n\n- **benchmark**: 报告文档  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F802 中提交 [\u003Csamp>(978e3)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F978e3dd54)\n- **compiler**: 新的生成 README  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F803 中提交 [\u003Csamp>(67321)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F67321da9e)\n\n###    🐞 错误修复\n\n- **compiler**: 未实现通用模板  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F804 中提交 [\u003Csamp>(7f95b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F7f95b11d2)\n- **website**: StackBlitz 暂停运行  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F801 中提交 [\u003Csamp>(30047)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3004788f4)\n\n#####     [在 GitHub 上查看更改](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.29.1...v0.29.2)","2025-11-18T15:14:55",{"id":205,"version":206,"summary_zh":207,"released_at":208},342983,"v0.29.1","小型模型的 RAG 优化。\n\n###    🚀 功能特性\n\n- **benchmark**: 将归档程序模块化。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F774 中提出 [\u003Csamp>(c1df9)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc1df91e28)\n\n###    🐞 错误修复\n\n- **agen**: `executeCachedBatch()` 函数中的 bug  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F800 中修复 [\u003Csamp>(a5f05)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fa5f05e237)\n\n#####     [在 GitHub 上查看更改](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.29.0...v0.29.1)","2025-11-17T14:33:51",{"id":210,"version":211,"summary_zh":212,"released_at":213},342984,"v0.29.0","> 已弃用。请使用 v0.29.1。\n\n###    🚀 功能\n\n- **agent**:\n  - 重构编排转换器。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F777 中完成 [\u003Csamp>(199ea)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F199ea4e44)\n  - 准备 `IAutoBePreliminaryApplication` 以用于 RAG 优化。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F778 中完成 [\u003Csamp>(42e45)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F42e45801b)\n  - 在接口阶段进行 RAG 优化。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F779 中完成 [\u003Csamp>(306c5)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F306c5470a)\n  - 增强初步验证逻辑。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F782 中完成 [\u003Csamp>(8f503)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8f50341bb)\n  - 不再验证已挂载的初步组件。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F784 中完成 [\u003Csamp>(b417b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb417bc3b7)\n  - 初步组件采用联合类型作为编译策略。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F786 中完成 [\u003Csamp>(e9e9f)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fe9e9f2c75)\n  - 在 Prisma 阶段的 agent 中引入 RAG。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F787 中完成 [\u003Csamp>(241b5)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F241b5472a)\n  - 提供更详细的初步消息。 -  由 @samchon 和 **Copilot** 共同在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F789 中完成 [\u003Csamp>(5e998)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5e99818b5)\n  - 在测试阶段引入初步 RAG。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F790 中完成 [\u003Csamp>(697c5)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F697c52023)\n  - 在实现阶段引入 RAG。 -  由 @samchon 完成 [\u003Csamp>(0a661)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F0a6615144)\n  - 在实现阶段再次引入 RAG。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F791 中完成 [\u003Csamp>(59e0f)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F59e0f08f2)\n  - 补充 RAG 以确保 100% 成功。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F793 中完成 [\u003Csamp>(52276)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F52276fee0)\n  - 测试 RAG 性能。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F794 中完成 [\u003Csamp>(1a49c)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F1a49c920c)\n  - 分析评审代理的 RAG。 -  由 @samchon 和 **Copilot** 共同在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F798 中完成 [\u003Csamp>(16e9b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F16e9b8376)\n- **website**:\n  - 更新路线图状态。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F780 中完成 [\u003Csamp>(3f5a1)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3f5a1d0a4)\n  - 修订 RAG 路线图。 -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwr","2025-11-17T14:32:11",{"id":215,"version":216,"summary_zh":217,"released_at":218},342985,"v0.28.1","###    🚀 功能特性\n\n- **agent**: 因 Gemini 模式问题而升级  -  由 @samchon 在 https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F776 中提出 [\u003Csamp>(f25c7)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ff25c7ba4f)\n\n#####     [在 GitHub 上查看更改](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.28.0...v0.28.1)","2025-11-09T16:07:26",{"id":220,"version":221,"summary_zh":222,"released_at":223},342986,"v0.28.0","###    🚀 Features\n\n- *****:\n  - Bump up agentica for strict validation feedback  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F773 [\u003Csamp>(bec95)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fbec9540a3)\n  - Bump up for new gemini schema model.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F775 [\u003Csamp>(34ad8)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F34ad8e232)\n- **agent**:\n  - Tuning for google gemini  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F772 [\u003Csamp>(7bbb7)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F7bbb7de89)\n- **website**:\n  - Gamma roadmap  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F770 [\u003Csamp>(5e41f)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5e41faadf)\n  - Job description for Korean  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F771 [\u003Csamp>(bbcf4)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fbbcf4c8c2)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.27.0...v0.28.0)","2025-11-07T15:19:27",{"id":225,"version":226,"summary_zh":227,"released_at":228},342987,"v0.27.0","###    🚀 Features\n\n- **agent**:\n  - Prefer code identifier in endpoint.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F741 [\u003Csamp>(8ca24)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8ca24812d)\n  - API endpoint to consider composite UKs.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F742 [\u003Csamp>(1ec10)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F1ec10e6c4)\n  - Upgrade agentica  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F764 [\u003Csamp>(eb395)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Feb3955cea)\n  - Guide file uploading system  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F765 [\u003Csamp>(24116)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F24116870a)\n- **interface**:\n  - Unify interface schema review events  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F750 and https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F761 [\u003Csamp>(92baa)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F92baa5efe)\n  - Aggregate about function calling  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F762 and https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F763 [\u003Csamp>(0f003)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F0f0037eec)\n- **test**:\n  - New chat proejct scenario  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F740 [\u003Csamp>(5f4d7)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5f4d75572)\n  - Archive new historeis (v0.26)  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F737 [\u003Csamp>(14b7b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F14b7b8e36)\n  - New chat scenario that shrinked a lot.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F743 [\u003Csamp>(5a219)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5a2196b79)\n  - Move history archiving to external repo.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F768 [\u003Csamp>(d126b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fd126b5d48)\n- **website**:\n  - New commit program of the examples.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F767 [\u003Csamp>(67d99)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F67d994da3)\n\n###    🐞 Bug Fixes\n\n- **agent**:\n  - Authorization parameters  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F760 [\u003Csamp>(ccda0)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fccda0a5d7)\n- **compiler**:\n  - `.gitignore` rule to `autobe` directory.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F744 [\u003Csamp>(09c46)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F09c461258)\n- **test**:\n  - Exact aggregation  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F766 [\u003Csamp>(939c9)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F939c961d4)\n  - Revive archive program.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F769 [\u003Csamp>(c6f04)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc6f04b71d)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.26.0...v0.27.0)","2025-11-04T15:56:55",{"id":230,"version":231,"summary_zh":232,"released_at":233},342988,"v0.26.0","###    🚀 Features\n\n- *****:\n  - Claude code guide prompts  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F718 [\u003Csamp>(87fb7)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F87fb728c3)\n- **agent**:\n  - The concept session and its authorization rule.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F699 [\u003Csamp>(8ba1b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8ba1b71e9)\n  - DTO composition rule  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F701 [\u003Csamp>(726be)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F726be11b2)\n  - DTO relationship guidance  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F703 [\u003Csamp>(3d17d)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3d17d49ca)\n  - Strict constraints  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F704 [\u003Csamp>(7722d)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F7722d8c88)\n  - Enhance interface schema prompts  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F705 [\u003Csamp>(cf048)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fcf0483106)\n  - New normalization guidance to prisma agent.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F706 [\u003Csamp>(275a2)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F275a26e48)\n  - Re-write interface schema prompts  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F707 [\u003Csamp>(9ea25)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F9ea25c298)\n  - Separate interface schema review agent  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F709 [\u003Csamp>(e7682)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fe7682c4db)\n  - Not role, but actor  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F711 [\u003Csamp>(c0ad6)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc0ad6033d)\n  - Atomic operation principle  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F712 [\u003Csamp>(d29be)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fd29beb16e)\n  - DTO type name guidance  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F714 [\u003Csamp>(7b82e)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F7b82eb7c9)\n  - Common prompt describing about the AutoBE itself.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F715 [\u003Csamp>(c762d)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc762dad60)\n  - Instruction also on interface schema reviewers  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F716 [\u003Csamp>(ce404)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fce404c722)\n  - Read reference to be summary DTO.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F717 [\u003Csamp>(94f00)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F94f009e40)\n  - Refactor interface schema relation prompts  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F719 [\u003Csamp>(8e398)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F8e39885fd)\n  - Remove FK after relation defining.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F721 [\u003Csamp>(30a03)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F30a033b86)\n  - Interface schema, password prompting  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F723 [\u003Csamp>(f00e8)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ff00e85bfb)\n  - Realize session guide  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F724 [\u003Csamp>(70f6c)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F70f6cc422)\n  - DTO type name refactoring agent.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F726 [\u003Csamp>(078ca)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F078cab36a)\n  - Enhance DTO naming rule from operation level.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F728 [\u003Csamp>(0a415)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F0a41599f9)\n  - Fix DTO type name's duplicated renaming rule.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F730 [\u003Csamp>(2f66f)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F2f66faf75)\n- **compiler**:\n  - Block infinite recursive type definition.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F736 [\u003Csamp>(7677b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F7677b69f0)\n- **test**:\n  - Chat scenario - shrinked requirements.  -  by @samchon and **Copilot** in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F700 [\u003Csamp>(622fb)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F622fb7967)\n  - Newly archive `wrtn-enterprise`  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F702 [\u003Csamp>(4fea4)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F4fea486d8)\n  - Enhance chat scenario prompt again  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F708 [\u003Csamp>(127a0)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrt","2025-10-26T16:15:55",{"id":235,"version":236,"summary_zh":237,"released_at":238},342989,"v0.25.7","###    🚀 Features\n\n- **test**: The concept session for audit tracing  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F698 [\u003Csamp>(58875)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F58875f751)\n- **website**: Screenshot on example repo  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F697 [\u003Csamp>(424cf)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F424cf0eba)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.6...v0.25.7)","2025-10-19T17:33:02",{"id":240,"version":241,"summary_zh":242,"released_at":243},342990,"v0.25.6","###    🚀 Features\n\n- **agent**:\n  - Enahnce instruction again  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F692 [\u003Csamp>(08edd)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F08edd683f)\n  - Separate instruction, but make clear  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F694 [\u003Csamp>(f7594)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ff759411b1)\n  - Make instruction guide neutral  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F696 [\u003Csamp>(de1a1)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fde1a19f3f)\n- **test**:\n  - Archive `anthropic\u002Fclaude-sonnet-4.5`  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F683 [\u003Csamp>(b1b96)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb1b966177)\n  - New scenario of Wrtn Enterprise in Korean.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F684 [\u003Csamp>(c8d91)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc8d91590e)\n  - Archive chat again  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F686 [\u003Csamp>(205d1)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F205d1a852)\n  - Wrtn enterprise again  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F687 [\u003Csamp>(c99ab)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc99abe503)\n  - Archive haiku and kimi  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F688 [\u003Csamp>(cc144)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fcc144c7d8)\n  - More qwen case  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F690 [\u003Csamp>(bab12)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fbab12e190)\n  - Enhance chat scenario prompt  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F689 [\u003Csamp>(5645e)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F5645e82ab)\n  - Archive more models with different schema model  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F685 [\u003Csamp>(f349d)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ff349d00fa)\n- **website**:\n  - Show much more demo cases  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F691 [\u003Csamp>(a7242)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fa72420c13)\n  - Benchmark and centralized examples  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F693 [\u003Csamp>(91c68)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F91c6892cc)\n  - Publish benchmark result  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F695 [\u003Csamp>(43375)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F43375cf61)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.5...v0.25.6)","2025-10-17T13:47:42",{"id":245,"version":246,"summary_zh":247,"released_at":248},342991,"v0.25.5","###    🚀 Features\n\n- **agent**:\n  - Validate empty code snippet.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F682 [\u003Csamp>(a495b)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fa495bc9f1)\n- **compiler**:\n  - Change template assets  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F680 [\u003Csamp>(2cda4)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F2cda42942)\n- **test**:\n  - Wrtn enterprise scenario  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F679 [\u003Csamp>(2aa76)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F2aa76524a)\n- **website**:\n  - Screenshot program.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F676 [\u003Csamp>(b5fc0)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb5fc0b5ea)\n  - New reddit article  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F678 [\u003Csamp>(4aeac)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F4aeac9927)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.4...v0.25.5)","2025-10-13T08:59:28",{"id":250,"version":251,"summary_zh":252,"released_at":253},342992,"v0.25.4","###    🚀 Features\n\n- **agent**: Special logic for mistra  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F675 [\u003Csamp>(550e6)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F550e68a5f)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.3...v0.25.4)","2025-10-09T15:02:58",{"id":255,"version":256,"summary_zh":257,"released_at":258},342993,"v0.25.3","###    🚀 Features\n\n- **test**: New testing prompts.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F674 [\u003Csamp>(c79ca)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc79ca6817)\n- **website**: Refactor demo content  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F672 [\u003Csamp>(aac22)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Faac22b27c)\n\n###    🐞 Bug Fixes\n\n- **website**: Landinig page layout  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F673 [\u003Csamp>(b5672)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb5672b778)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.2...v0.25.3)","2025-10-08T17:14:40",{"id":260,"version":261,"summary_zh":262,"released_at":263},342994,"v0.25.2","###    🚀 Features\n\n- **agent**: Enforce function calling even in user message  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F670 [\u003Csamp>(a56c0)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fa56c02d97)\n- **website**: Combobox on replay model selector  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F671 [\u003Csamp>(f5f73)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ff5f73cf26)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.1...v0.25.2)","2025-10-05T04:45:45",{"id":265,"version":266,"summary_zh":267,"released_at":268},342995,"v0.25.1","###    🚀 Features\n\n- **agent**:\n  - Erase un-used JSON schemas and solve `X.IPage` problem.  -  by @samchon and **Copilot** in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F649 [\u003Csamp>(acfde)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Facfde5d13)\n  - Make interface group description concisely.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F650 [\u003Csamp>(1b93a)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F1b93ad6e7)\n  - DTO constraints, especially timestamps  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F651 [\u003Csamp>(c009a)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fc009ac4ff)\n  - Realize agent to import every nested types  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F652 [\u003Csamp>(6e483)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F6e483cdfb)\n  - Concise function calling schemas.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F653 [\u003Csamp>(6d0bb)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F6d0bbcdc5)\n  - Concise revise schema  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F655 [\u003Csamp>(3e731)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F3e7319a8a)\n  - No hashed password request and none-existing timestamps.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F659 [\u003Csamp>(2925a)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F2925ad856)\n  - New schema complementation rule  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F665 [\u003Csamp>(fe356)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ffe356cba9)\n  - Concise realize agent  -  by @samchon and **Copilot** in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F666 [\u003Csamp>(d6874)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fd6874fffc)\n  - Enhance realize agent's system prompts.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F667 [\u003Csamp>(b27ea)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fb27ea3fb2)\n  - Check related prisma db schema  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F668 [\u003Csamp>(99fdb)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F99fdb6560)\n- **archive**:\n  - Change plugin key with re-archiving  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F669 [\u003Csamp>(faf03)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ffaf03aa13)\n- **interface**:\n  - `AutoBeOpenApi.IOperation.prerequisites`  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F635 [\u003Csamp>(76ffc)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F76ffcbb0f)\n- **test**:\n  - New histories archiving  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F661 [\u003Csamp>(a3994)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Fa39946a94)\n  - Reporter of failed archiving  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F664 [\u003Csamp>(f84f0)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002Ff84f091ed)\n\n###    🐞 Bug Fixes\n\n- **compiler**:\n  - Primary key name is too long  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F662 [\u003Csamp>(9032d)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F9032d67bb)\n  - Revert OpenAPI operation name  of duplicated.  -  by @samchon in https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fissues\u002F663 [\u003Csamp>(47ac6)\u003C\u002Fsamp>](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcommit\u002F47ac6e5d2)\n\n#####     [View changes on GitHub](https:\u002F\u002Fgithub.com\u002Fwrtnlabs\u002Fautobe\u002Fcompare\u002Fv0.25.0...v0.25.1)","2025-10-03T02:06:04"]