[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-72837":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":25,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":41,"readmeContent":42,"aiSummary":43,"trendingCount":16,"starSnapshotCount":16,"syncStatus":44,"lastSyncTime":45,"discoverSource":46},72837,"LangGPT","langgptai\u002FLangGPT","langgptai","LangGPT: Empowering everyone to become a prompt expert! 🚀  📌 结构化提示词（Structured Prompt）提出者 📌 元提示词（Meta-Prompt）发起者   📌 最流行的提示词落地范式 | Language of GPT  The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide  Created by 云中江树","https:\u002F\u002Fgithub.com\u002Flanggptai",null,"Jupyter Notebook",12190,936,101,1,0,19,52,134,57,118.92,"Apache License 2.0",false,"main",true,[27,28,29,30,31,32,33,34,35,36,37,38,39,40],"chatgpt","claude","deeplearning","doubao","framework","gemini","gpt-4","gpt3-prompts","langgpt","meta-prompting","prompt","prompt-engineering","qwen","structured-prompts","2026-06-12 04:01:07","# 🚀 LangGPT — Empowering Everyone to Create High-Quality Prompts!\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"imgs\u002Flogo.png\" width=\"60%\" height=\"auto\">\n\n[![License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-MIT-blue.svg)](\u002FLICENSE)\n[![Status](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fstatus-active-success.svg)]()\n[![Paper](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FarXiv-2402.16929-b31b1b.svg)](https:\u002F\u002Farxiv.org\u002Fabs\u002F2402.16929)\n[![Stars](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FLangGPT)](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FLangGPT)\n\n[English](README.md) | [简体中文](README_zh.md) | [日本語](README_ja.md)\n\n[Quick Start](#-quick-start) | [Theoretical Foundations](#-theoretical-foundations) | [Ecosystem](#-langgpt-ecosystem) | [Community](http:\u002F\u002Ffeishu.langgpt.ai)\n\n\u003C\u002Fdiv>\n\n---\n\n## 📖 What is LangGPT?\n\n**LangGPT is a structured, reusable prompt design framework** that enables anyone to create high-quality prompts for Large Language Models. Think of it as a **\"programming language for prompts\"** — systematic, template-based, and infinitely scalable.\n\n### Why LangGPT?\n\nTraditional prompt engineering relies on scattered tips and trial-and-error. LangGPT transforms this chaos into a structured methodology:\n\n- 🎯 **Structured Templates** — Hierarchical organization inspired by programming paradigms\n- 🔄 **Reusability** — Create once, adapt infinitely like code modules  \n- 📦 **Modularity** — Variables, commands, and conditional logic at your fingertips\n- ⚡ **Efficiency** — Go from idea to working prompt in minutes\n- 🌍 **Community-Driven** — 11,000+ stars, battle-tested by thousands of users\n\n> **Academic Foundation**: Published research at [arXiv:2402.16929](https:\u002F\u002Farxiv.org\u002Fabs\u002F2402.16929) | [中文版](Papers\u002FLangGPT_paper_cn.md)\n\n---\n\n## 🚀 Quick Start\n\n### Method 1: Use Automated Tools (Fastest)\n\nLet AI create prompts for you:\n\n- **[LangGPT GPTs](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-Apzuylaqk-langgpt)** — Full-featured generator (GPT-4)\n- **[Kimi+ LangGPT](https:\u002F\u002Fkimi.moonshot.cn\u002Fkimiplus\u002Fconpg00t7lagbbsfqkq0)** — For Moonshot Kimi users\n- **[PromptGPT](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-YKe3gmydD-promptgpt)** — Lite version (GPT-3.5)\n\n### Method 2: Master the Template (5 Minutes)\n\nBasic LangGPT structure:\n\n```markdown\n# Role: Your_Role_Name\n\n## Profile\n- Author: YourName\n- Version: 1.0\n- Language: English\n- Description: Clear role description and core capabilities\n\n## Goal\n- Outcome: What concrete result\u002Foutcome should be delivered for the user\u002Fsession\n- Done Criteria: Clear acceptance criteria (how we know it’s finished and good)\n- Non-Goals: What is explicitly out of scope to avoid scope creep\n\n### Skill-1\n1. Specific skill description\n2. Expected behavior and output\n\n## Rules\n1. Don't break character under any circumstance\n2. Don't make up facts or hallucinate\n\n## Workflow\n1. Analyze user input and identify intent\n2. Apply relevant skills systematically\n3. Deliver structured, actionable output\n\n## Initialization\nAs a\u002Fan \u003CRole>, you must follow the \u003CRules>, you must talk to user in default \u003CLanguage>, you must greet the user. Then introduce yourself and introduce the \u003CWorkflow>.\n```\n\n**Prerequisites**: Basic Markdown knowledge ([Quick Guide](https:\u002F\u002Fdocs.github.com\u002Fen\u002Fget-started\u002Fwriting-on-github\u002Fgetting-started-with-writing-and-formatting-on-github\u002Fbasic-writing-and-formatting-syntax)) | GPT-4 or Claude recommended\n\n### Method 3: Start from Examples\n\nExplore our [example library](https:\u002F\u002Flanggptai.feishu.cn\u002Fwiki\u002FRXdbwRyASiShtDky381ciwFEnpe) and adapt proven templates to your needs.\n\n### Method 4: Claude Code Skill (Recommended)\n\nIf you use [Claude Code](https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fdocs\u002Fclaude-code), install the LangGPT Skill to get structured prompt writing capabilities:\n\n**Installation:**\n\n1. Download [langgpt.skill](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FLangGPT\u002Freleases)\n2. Extract to `~\u002F.claude\u002Fskills\u002F` directory\n3. Type `\u002Flanggpt` in Claude Code to use\n\n**Skill Features:**\n- 📝 Structured prompt templates (Role, Profile, Skills, Rules, Workflow)\n- 📚 Rich example library (FitnessGPT, Poet, Xiaohongshu Master, Name Master, etc.)\n- 🔧 Advanced techniques: variables, commands, conditional logic\n- 🎯 Model compatibility guide (GPT-4, Claude, GPT-3.5)\n\n---\n\n## 🧠 Theoretical Foundations\n\nBefore diving into tactics, understand the principles. These essays explore the philosophy behind effective prompting:\n\n- **[对话动力学](Docs\u002F对话动力学.md)** — The dynamics of human-AI dialogue\n- **[五种理性](Docs\u002F五种理性.md)** — Five types of rationality in prompt design\n- **[镜像性倾向](Docs\u002F镜像性倾向.md)** — Mirror tendencies in LLM behavior\n- **[统计重力井和边缘表达](Docs\u002F统计重力井和边缘表达.md)** — Statistical gravity well and edge expression\n- **[关系表达](Docs\u002F关系表达.md)** — Expressing relationships in prompts\n- **[看见与言说](Docs\u002F看见与言说.md)** — Seeing and articulation in AI interaction  \n- **[Prompt 的本质](Docs\u002FPrompt的本质.md)** — The essence and nature of prompts\n- **[面向结果的提示词写作方法](Docs\u002F面向结果的提示词写作方法.md)** — Writing prompts that focus on achieving desired outcomes\n- **[AI意识](Docs\u002FAI意识.md)** — Understanding the role of AI in human-AI interaction\n- **[AI时代的新管理：机器负责优化，人类定义应该](Docs\u002FAI时代的新管理：机器负责优化，人类定义应该.md)** — The new management in the AI era: machines optimize, humans define the criteria\n\n*These foundational insights will transform how you think about prompts.*\n\n---\n\n## 💡 Core Concepts\n\n### 1. Structured Roles\n\nDefine AI personas through clear, modular sections:\n\n| Section | Purpose | Example |\n|---------|---------|---------|\n| **Role** | Role name\u002Ftitle | \"逻辑学家\" \u002F \"Expert Analyst\" \u002F \"FitnessGPT\" |\n| **Profile** | Identity and capabilities | \"Expert Python developer with 10 years experience\" |\n| **Goal**           | Desired outcome, done criteria, and non-goals for this session\u002Ftask | “Refactor a prompt into a reusable template; acceptance criteria: pass three structured checks; non-goal: rewriting the business logic.”                    |\n| **Skills** | Specific abilities | \"Debug complex code, optimize performance\" |\n| **Rules** | Boundaries and constraints | \"Never execute destructive commands\" |\n| **Workflow** | Interaction logic | \"1. Analyze → 2. Plan → 3. Execute\" |\n| **Initialization** | Opening message and setup | \"As a \u003CRole>, I will greet you and introduce the \u003CWorkflow>\" |\n\n### 2. Variables and References\n\nUse `\u003CVariable>` syntax for dynamic content:\n\n```markdown\nAs a \u003CRole>, you must follow \u003CRules> and communicate in \u003CLanguage>\n```\n\nThis creates self-referential prompts that maintain consistency across complex instructions.\n\n### 3. Commands\n\nDefine reusable actions for better UX:\n\n```markdown\n## Commands\n- Prefix: \"\u002F\"\n- Commands:\n    - help: Display all available commands\n    - continue: Resume interrupted output\n    - improve: Enhance current response with deeper analysis\n```\n\n### 4. Conditional Logic\n\nAdd intelligence to your prompts:\n\n```markdown\nIf user provides [code], then analyze and suggest improvements\nElse if user asks [question], then provide detailed explanation\nElse, prompt for clarification\n```\n\n### 5. Advanced Techniques\n\n**Reminders** — Combat context loss in long conversations:\n```markdown\n## Reminder\n1. Always check role settings before responding\n2. Current language: \u003CLanguage>, Active rules: \u003CRules>\n```\n\n**Alternative Formats** — Use JSON\u002FYAML when markdown isn't ideal:\n```yaml\nrole: DataAnalyst\nprofile:\n  version: \"2.0\"\n  language: \"Python\"\nskills:\n  - statistical_analysis\n  - data_visualization\n```\n\n---\n\n## 🌟 Featured Examples\n\n| Prompt | Description | Link |\n|--------|-------------|------|\n| 🎯 **FitnessGPT** | Personalized diet and workout planner | [View](examples\u002FFitnessGPT.md) |\n| 💻 **Code Master CAN** | Advanced coding assistant with debugging expertise | [View](examples\u002Fcode_anything_now\u002FChatGPT-Code_Anything_Now_en.md) |\n| ✍️ **Xiaohongshu Writer** | Viral social media content generator | [View](examples\u002Fchinese_xiaohongshu_writer\u002F) |\n| 🎨 **Chinese Poet** | Classical poetry composer in traditional styles | [View](examples\u002Fchinese_poet\u002F) |\n\n[Browse 100+ more examples →](https:\u002F\u002Flanggptai.feishu.cn\u002Fwiki\u002FRXdbwRyASiShtDky381ciwFEnpe)\n\n---\n\n## 📚 Learning Resources\n\n### Essential Guides\n\n| Resource | Description | Date |\n|----------|-------------|------|\n| [Academic Paper](https:\u002F\u002Farxiv.org\u002Fabs\u002F2402.16929) | LangGPT: Rethinking Structured Reusable Prompt Design ([中文](Papers\u002FLangGPT_paper_cn.md)) | Feb 2024 |\n| [Structured Prompts Guide](Docs\u002FHowToWritestructuredPrompts.md) | Comprehensive tutorial on building high-performance prompts | Jul 2023 |\n| [Prompt Chains](Docs\u002FPromptChain.md) | Multi-prompt collaboration and task decomposition strategies | Aug 2023 |\n| [Video Tutorial](https:\u002F\u002Fwww.bilibili.com\u002Fvideo\u002FBV1rj411q78a) | BiliBili walkthrough (by AIGCLINK) | Sep 2023 |\n\n### Advanced Topics\n\n- **[推理模型提示方法变革](https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FFLY0sy1jYv6eT9151Yz_jw)** — Paradigm shift from procedural to goal-oriented prompting\n- **[提示词的道和术](https:\u002F\u002Flanggptai.feishu.cn\u002Fwiki\u002FAYMWwBPaSih46WkAo9jcfKkfntg)** — Philosophy and practice of prompt engineering by 李继刚\n- **[企业级提示词工程](https:\u002F\u002Flanggptai.feishu.cn\u002Fwiki\u002FUTyswvusTiRw0TkZLI5cIG0Tnhc)** — Building production-ready prompt systems (百川智能)\n- **[多模态提示词](https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FAan9NXO_vEZ9h0YrugpoGQ)** — GPT-4V and multi-modal prompting techniques\n- **[提示词攻击与防护](https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FaaABXnxRqDF716qRk79wYQ)** — Security: prompt injection, jailbreaks, and defenses\n- **[大模型绘画指南](https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FbJbZ9bwPXxlpyREqLKhDvA)** — AI image generation with structured prompts\n\n### Community Hub\n\n**[Feishu Knowledge Base](http:\u002F\u002Ffeishu.langgpt.ai)** — Curated resources, templates, and community contributions\n\n---\n\n## 🎨 LangGPT Ecosystem\n\n### Core Framework & Tools\n\n| Project | Description | Stars |\n|---------|-------------|-------|\n| **[LangGPT](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FLangGPT)** | Core framework and methodology | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FLangGPT) |\n| **[PromptVer](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FPromptVer)** | Semantic versioning for prompts — version control like Git | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FPromptVer) |\n| **[PromptShow](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FPromptShow)** | Create beautiful prompt images ([Try it](https:\u002F\u002Fshow.langgpt.ai\u002F)) | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FPromptShow) |\n| **[Minstrel](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FMinstrel)** | Multi-agent system for auto-generating prompts | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FMinstrel) |\n\n### Model-Specific Prompt Collections\n\nRather than writing prompts as procedures, write the persona. Writing prompts as procedures gives the model steps and tools. Writing prompts as a persona gives the model a worldview, motivations, a value system, and a preference profile. Below are prompts that Yunzhong Jiangshu wrote while studying some well-known figures. \n\n* [巴菲特AI分身](Prompts\u002F巴菲特AI分身.md)\n* [梵高AI分身](Prompts\u002F梵高AI分身.md)\n* [马斯克AI分身](Prompts\u002F马斯克AI分身.md)\n* [段永平AI分身](Prompts\u002F段永平AI分身.md)\n\nCurated, optimized prompts for different AI models:\n\n| Collection | Target Model | Stars |\n|------------|--------------|-------|\n| [wonderful-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fwonderful-prompts) | ChatGPT (Chinese) | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fwonderful-prompts) |\n| [awesome-claude-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-claude-prompts) | Anthropic Claude | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-claude-prompts) |\n| [awesome-deepseek-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-deepseek-prompts) | DeepSeek & R1 | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-deepseek-prompts) |\n| [awesome-gemini-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-gemini-prompts) | Google Gemini | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-gemini-prompts) |\n| [awesome-grok-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-grok-prompts) | xAI Grok | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-grok-prompts) |\n| [qwen-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fqwen-prompts) | Alibaba Qwen | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fqwen-prompts) |\n| [awesome-llama-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-llama-prompts) | Meta Llama 2\u002F3 | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-llama-prompts) |\n| [awesome-doubao-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-doubao-prompts) | ByteDance Doubao | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-doubao-prompts) |\n| [awesome-system-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-system-prompts) | System prompts from AI tools | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-system-prompts) |\n\n### Specialized Domains\n\n| Repository | Focus Area | Stars |\n|------------|------------|-------|\n| [Awesome-Multimodal-Prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FAwesome-Multimodal-Prompts) | GPT-4V, DALL-E 3, image\u002Fvideo prompts | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FAwesome-Multimodal-Prompts) |\n| [deep-research-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fdeep-research-prompts) | Deep research across models | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fdeep-research-prompts) |\n| [awesome-voice-prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002Fawesome-voice-prompts) | Voice AI and conversational agents | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002Fawesome-voice-prompts) |\n| [GraphRAG-Prompts](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FGraphRAG-Prompts) | Graph-based retrieval prompts | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FGraphRAG-Prompts) |\n| [LLM-Jailbreaks](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FLLM-Jailbreaks) | Security research and defenses | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FLLM-Jailbreaks) |\n\n### Applications\n\n| Project | Description | Stars |\n|---------|-------------|-------|\n| [BookAI](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FBookAI) | AI-powered book generation | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FBookAI) |\n| [AI-Resume](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FAI-Resume) | Beautiful resumes with Claude Artifacts | ![](https:\u002F\u002Fbadgen.net\u002Fgithub\u002Fstars\u002Flanggptai\u002FAI-Resume) |\n\n---\n\n## 🛠️ Popular GPTs Built with LangGPT\n\nTransform ChatGPT with these specialized assistants:\n\n| GPT | Purpose | Link |\n|-----|---------|------|\n| 🎯 **LangGPT Expert** | Auto-generate structured prompts | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-Apzuylaqk-langgpt) |\n| ✍️ **PromptGPT** | Professional prompt engineer | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-YKe3gmydD-promptgpt) |\n| 🧠 **SmartGPT-5** | Never lazy, always diligent assistant | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-sRQtxpN4C-smartgpt-5) |\n| 💻 **Coding Expert** | Comprehensive programming assistant | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-ky06YjwaP-coding-expert) |\n| 📊 **Data Table GPT** | Transform messy data into clean tables | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-nb6RjxHsb-data-table-gpt) |\n| 🔥 **PytorchGPT** | PyTorch code specialist | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-kyj3zKyHK-pytorchgpt) |\n| 🎨 **LogoGPT** | Professional logo designer | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-wdz2JlUBv-logogpt) |\n| 📄 **PDF Reader** | Deep document analysis and extraction | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-YaMjCVW0t-pdf-reader) |\n| 🏅 **MathGPT** | Precise mathematical problem solver | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-UIOlPhTjK-mathgpt) |\n| 📝 **WriteGPT** | Professional writing across industries | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-jwTMtRiL8-writegpt) |\n| 🎙️ **时事热评员** | Current events commentator | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-gbfs6fy7c-shi-shi-re-ping-yuan) |\n| 🎀 **翻译大小姐** | Elegant Chinese translations | [Launch](https:\u002F\u002Fchat.openai.com\u002Fg\u002Fg-2V90YGvVD-fan-yi-da-xiao-jie) |\n\n[Discover 20+ more GPTs →](https:\u002F\u002Fgithub.com\u002Flanggptai\u002FLangGPT#langgpt-gpts)\n\n---\n\n## 🤝 Contributing\n\nWe welcome all contributions to make LangGPT better!\n\n### How You Can Help\n\n1. ⭐ **Star and share** — Increase visibility and help others discover LangGPT\n2. 📝 **Submit examples** — Share your successful prompts built with LangGPT\n3. 🆕 **Propose templates** — Create new templates beyond the Role structure\n4. 📖 **Improve docs** — Fix typos, clarify instructions, add translations\n5. 💡 **Suggest features** — Open issues with ideas for new capabilities\n6. 🔧 **Code contributions** — Help build tools, utilities, and integrations\n\n### Getting Started\n\nNew to GitHub contributions? Check out this [GitHub Minimal Contribution Guide](https:\u002F\u002Fgithub.com\u002Fdatawhalechina\u002FDOPMC\u002Fblob\u002Fmain\u002FGITHUB.md)\n\n---\n\n## 📊 Star History\n\n[![Star History Chart](https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=langgptai\u002FLangGPT&type=Date)](https:\u002F\u002Fstar-history.com\u002F#langgptai\u002FLangGPT&Date)\n\n---\n\n## 📄 Citation\n\nIf you use LangGPT in research or projects, please cite:\n\n```bibtex\n@misc{wang2024langgpt,\n      title={LangGPT: Rethinking Structured Reusable Prompt Design Framework for LLMs from the Programming Language}, \n      author={Ming Wang and Yuanzhong Liu and Xiaoming Zhang and Songlian Li and Yijie Huang and Chi Zhang and Daling Wang and Shi Feng and Jigang Li},\n      year={2024},\n      eprint={2402.16929},\n      archivePrefix={arXiv},\n      primaryClass={cs.SE}\n}\n```\n\n---\n\n## 🙏 Acknowledgments\n\nLangGPT was inspired by excellent projects:\n\n- [Mr.-Ranedeer-AI-Tutor](https:\u002F\u002Fgithub.com\u002FJushBJJ\u002FMr.-Ranedeer-AI-Tutor) — Structured tutoring prompts\n- [Auto-GPT](https:\u002F\u002Fgithub.com\u002FSignificant-Gravitas\u002FAuto-GPT) — Autonomous AI agents\n- [SoM](https:\u002F\u002Fgithub.com\u002FSkalskiP\u002FSoM) — Set of Mark prompting\n- [yolov10](https:\u002F\u002Fgithub.com\u002FTHU-MIG\u002Fyolov10) — Computer vision innovations\n\n### Projects Built with LangGPT\n\nWe're proud to see LangGPT principles applied in the wild:\n- **[Prompt Optimizer](https:\u002F\u002Fgithub.com\u002Flinshenkx\u002Fprompt-optimizer)** — Intelligent prompt optimization tool leveraging LangGPT methodology\n- **[securityGPT](https:\u002F\u002Fgithub.com\u002Frryuliu\u002FsecurityGPT)** — Secure prompt protection against leaks\n- **[AIPainting-Structured-Prompts](https:\u002F\u002Fgithub.com\u002Fzhutyler21\u002FAIPainting-Structured-Prompts)** — Structured prompts for AI art generation\n\n---\n\n## 📬 Connect With Us\n\n### Author\n\n**云中江树 (Yun Zhong Jiang Shu)**\n- 📱 WeChat Official Account: **「云中江树」**\n- 💼 Creator of LangGPT Framework\n- 🎓 Prompt Engineering Researcher\n\n### Community\n\n- 📚 [Knowledge Base](http:\u002F\u002Ffeishu.langgpt.ai) — Comprehensive documentation\n- 🐦 [Twitter\u002FX](https:\u002F\u002Ftwitter.com\u002Flanggptai) — Latest updates\n- 💬 [GitHub Discussions](https:\u002F\u002Fgithub.com\u002Flanggptai) — Community forum\n- 📧 Email: contact@langgpt.ai\n\n---\n\n\u003Cdiv align=\"center\">\n\n**[⬆ Back to Top](#-langgpt--empowering-everyone-to-create-high-quality-prompts)**\n\nMade with ❤️ by the [langgptai Community](https:\u002F\u002Fgithub.com\u002Flanggptai)\n\n*Empowering everyone to become a prompt expert* 🚀\n\n\u003C\u002Fdiv>","LangGPT 是一个结构化、可复用的提示设计框架，旨在帮助任何人创建高质量的大语言模型提示。其核心功能包括基于编程范式的层次化模板组织、模块化的变量与逻辑控制以及高效的提示生成流程，使得用户能够快速从想法到实现。该项目特别适用于需要频繁使用或定制大语言模型的应用场景，如智能客服、自动写作助手等。通过提供系统性、模板化的解决方案，LangGPT 显著降低了提示工程的学习成本和开发时间，同时保证了结果的一致性和可靠性。",2,"2026-06-11 03:43:47","high_star"]