[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-416":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":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":38,"readmeContent":39,"aiSummary":40,"trendingCount":16,"starSnapshotCount":16,"syncStatus":41,"lastSyncTime":42,"discoverSource":43},416,"Prompt-Engineering-Guide","dair-ai\u002FPrompt-Engineering-Guide","dair-ai","🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.","https:\u002F\u002Fwww.promptingguide.ai\u002F",null,"MDX",75534,8208,745,177,0,32,242,1084,185,45,"MIT License",false,"main",true,[27,28,29,30,31,32,33,34,35,36,37],"agent","agents","ai-agents","chatgpt","deep-learning","generative-ai","language-model","llms","openai","prompt-engineering","rag","2026-06-12 02:00:13","# Prompt Engineering Guide\n\n\u003Ch5 align=\"center\">\n  Sponsored by    \u003Ca href=\"https:\u002F\u002Fserpapi.com\u002F\">\u003Cimg src=\"https:\u002F\u002Fcdn.rawgit.com\u002Fstandard\u002Fstandard\u002Fmaster\u002Fdocs\u002Flogos\u002Fserpapi.png\" height=35 valign=\"middle\">\u003C\u002Fa>\n\u003C\u002Fh5>\n\nPrompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.\n\nMotivated by the high interest in developing with LLMs, we have created this new prompt engineering guide that contains all the latest papers, learning guides, lectures, references, and tools related to prompt engineering for LLMs.\n\n🌐 [Prompt Engineering Guide (Web Version)](https:\u002F\u002Fwww.promptingguide.ai\u002F)\n\n🎉 We are excited to launch our new prompt engineering, RAG, and AI Agents courses under the DAIR.AI Academy. [Join Now](https:\u002F\u002Facademy.dair.ai\u002Fpricing)!\n\nThe courses are meant to compliment this guide and provide a more hands-on approach to learning about prompt engineering, context engineering, and AI Agents. \n\nUse code PROMPTING20 to get an extra 20% off.\n\nHappy Prompting!\n\n---\n## Announcements \u002F Updates\n\n- 🎓 We now offer self-paced prompt engineering courses under our DAIR.AI Academy. [Join Now](https:\u002F\u002Facademy.dair.ai\u002Fpricing)! \n- 🎓 New course on Prompt Engineering for LLMs announced! [Enroll here](https:\u002F\u002Facademy.dair.ai\u002Fcourses\u002Fintroduction-prompt-engineering)!\n- 💼 We now offer several [services](https:\u002F\u002Fwww.promptingguide.ai\u002Fservices) like corporate training, consulting, and talks.\n- 🌐 We now support 13 languages! Welcoming more translations.\n- 👩‍🎓 We crossed 3 million learners in January 2024!\n- 🎉 We have launched a new web version of the guide [here](https:\u002F\u002Fwww.promptingguide.ai\u002F)\n- 🔥 We reached #1 on Hacker News on 21 Feb 2023\n- 🎉 The First Prompt Engineering Lecture went live [here](https:\u002F\u002Fyoutu.be\u002FdOxUroR57xs)\n\n[Join our Discord](https:\u002F\u002Fdiscord.gg\u002FYbMT8k6GfX)\n\n[Follow us on Twitter](https:\u002F\u002Ftwitter.com\u002Fdair_ai)\n\n[Subscribe to our YouTube](https:\u002F\u002Fwww.youtube.com\u002Fchannel\u002FUCyna_OxOWL7IEuOwb7WhmxQ)\n\n[Subscribe to our Newsletter](https:\u002F\u002Fnlpnews.substack.com\u002F)\n\n---\n\n## Guides\nYou can also find the most up-to-date guides on our new website [https:\u002F\u002Fwww.promptingguide.ai\u002F](https:\u002F\u002Fwww.promptingguide.ai\u002F).\n\n- [Prompt Engineering - Introduction](https:\u002F\u002Fwww.promptingguide.ai\u002Fintroduction)\n  - [Prompt Engineering - LLM Settings](https:\u002F\u002Fwww.promptingguide.ai\u002Fintroduction\u002Fsettings)\n  - [Prompt Engineering - Basics of Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Fintroduction\u002Fbasics)\n  - [Prompt Engineering - Prompt Elements](https:\u002F\u002Fwww.promptingguide.ai\u002Fintroduction\u002Felements)\n  - [Prompt Engineering - General Tips for Designing Prompts](https:\u002F\u002Fwww.promptingguide.ai\u002Fintroduction\u002Ftips)\n  - [Prompt Engineering - Examples of Prompts](https:\u002F\u002Fwww.promptingguide.ai\u002Fintroduction\u002Fexamples)\n- [Prompt Engineering - Techniques](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques)\n  - [Prompt Engineering - Zero-Shot Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fzeroshot)\n  - [Prompt Engineering - Few-Shot Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Ffewshot)\n  - [Prompt Engineering - Chain-of-Thought Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fcot)\n  - [Prompt Engineering - Self-Consistency](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fconsistency)\n  - [Prompt Engineering - Generate Knowledge Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fknowledge)\n  - [Prompt Engineering - Prompt Chaining](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fprompt_chaining)\n  - [Prompt Engineering - Tree of Thoughts (ToT)](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Ftot)\n  - [Prompt Engineering - Retrieval Augmented Generation](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Frag)\n  - [Prompt Engineering - Automatic Reasoning and Tool-use (ART)](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fart)\n  - [Prompt Engineering - Automatic Prompt Engineer](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fape)\n  - [Prompt Engineering - Active-Prompt](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Factiveprompt)\n  - [Prompt Engineering - Directional Stimulus Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fdsp)\n  - [Prompt Engineering - Program-Aided Language Models](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fpal)\n  - [Prompt Engineering - ReAct Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Freact)\n  - [Prompt Engineering - Multimodal CoT Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fmultimodalcot)\n  - [Prompt Engineering - Graph Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Ftechniques\u002Fgraph)\n- [Prompt Engineering - Applications](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications)\n  - [Prompt Engineering - Function Calling](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications\u002Ffunction_calling)\n  - [Prompt Engineering - Generating Data](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications\u002Fgenerating)\n  - [Prompt Engineering - Generating Synthetic Dataset for RAG](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications\u002Fsynthetic_rag)\n  - [Prompt Engineering - Takling Generated Datasets Diversity](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications\u002Fgenerating_textbooks)\n  - [Prompt Engineering - Generating Code](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications\u002Fcoding)\n  - [Prompt Engineering - Graduate Job Classification Case Study](https:\u002F\u002Fwww.promptingguide.ai\u002Fapplications\u002Fworkplace_casestudy)\n- [Prompt Engineering - Prompt Hub](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts)\n  - [Prompt Engineering - Classification](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fclassification)\n  - [Prompt Engineering - Coding](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fcoding)\n  - [Prompt Engineering - Creativity](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fcreativity)\n  - [Prompt Engineering - Evaluation](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fevaluation)\n  - [Prompt Engineering - Information Extraction](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Finformation-extraction)\n  - [Prompt Engineering - Image Generation](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fimage-generation)\n  - [Prompt Engineering - Mathematics](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fmathematics)\n  - [Prompt Engineering - Question Answering](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fquestion-answering)\n  - [Prompt Engineering - Reasoning](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Freasoning)\n  - [Prompt Engineering - Text Summarization](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Ftext-summarization)\n  - [Prompt Engineering - Truthfulness](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Ftruthfulness)\n  - [Prompt Engineering - Adversarial Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Fprompts\u002Fadversarial-prompting)\n- [Prompt Engineering - Models](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels)\n  - [Prompt Engineering - ChatGPT](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fchatgpt)\n  - [Prompt Engineering - Code Llama](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fcode-llama)\n  - [Prompt Engineering - Flan](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fflan)\n  - [Prompt Engineering - Gemini](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fgemini)\n  - [Prompt Engineering - GPT-4](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fgpt-4)\n  - [Prompt Engineering - LLaMA](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fllama)\n  - [Prompt Engineering - Mistral 7B](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fmistral-7b)\n  - [Prompt Engineering - Mixtral](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fmixtral)\n  - [Prompt Engineering - OLMo](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Folmo)\n  - [Prompt Engineering - Phi-2](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fphi-2)\n  - [Prompt Engineering - Model Collection](https:\u002F\u002Fwww.promptingguide.ai\u002Fmodels\u002Fcollection)\n- [Prompt Engineering - Risks and Misuses](https:\u002F\u002Fwww.promptingguide.ai\u002Frisks)\n  - [Prompt Engineering - Adversarial Prompting](https:\u002F\u002Fwww.promptingguide.ai\u002Frisks\u002Fadversarial)\n  - [Prompt Engineering - Factuality](https:\u002F\u002Fwww.promptingguide.ai\u002Frisks\u002Ffactuality)\n  - [Prompt Engineering - Biases](https:\u002F\u002Fwww.promptingguide.ai\u002Frisks\u002Fbiases)\n- [Prompt Engineering - Papers](https:\u002F\u002Fwww.promptingguide.ai\u002Fpapers)\n  - [Prompt Engineering - Overviews](https:\u002F\u002Fwww.promptingguide.ai\u002Fpapers#overviews)\n  - [Prompt Engineering - Approaches](https:\u002F\u002Fwww.promptingguide.ai\u002Fpapers#approaches)\n  - [Prompt Engineering - Applications](https:\u002F\u002Fwww.promptingguide.ai\u002Fpapers#applications)\n  - [Prompt Engineering - Collections](https:\u002F\u002Fwww.promptingguide.ai\u002Fpapers#collections)\n- [Prompt Engineering - Tools](https:\u002F\u002Fwww.promptingguide.ai\u002Ftools)\n- [Prompt Engineering - Notebooks](https:\u002F\u002Fwww.promptingguide.ai\u002Fnotebooks)\n- [Prompt Engineering - Datasets](https:\u002F\u002Fwww.promptingguide.ai\u002Fdatasets)\n- [Prompt Engineering - Additional Readings](https:\u002F\u002Fwww.promptingguide.ai\u002Freadings)\n\n\n---\n## Lecture\n\nWe have published a 1 hour lecture that provides a comprehensive overview of prompting techniques, applications, and tools.\n- [Video Lecture](https:\u002F\u002Fyoutu.be\u002FdOxUroR57xs)\n- [Notebook with code](https:\u002F\u002Fgithub.com\u002Fdair-ai\u002FPrompt-Engineering-Guide\u002Fblob\u002Fmain\u002Fnotebooks\u002Fpe-lecture.ipynb)\n- [Slides](https:\u002F\u002Fgithub.com\u002Fdair-ai\u002FPrompt-Engineering-Guide\u002Fblob\u002Fmain\u002Flecture\u002FPrompt-Engineering-Lecture-Elvis.pdf)\n\n---\n## Running the guide locally\n\nTo run the guide locally, for example to check the correct implementation of a new translation, you will need to:\n\n1. Install Node >=18.0.0\n1. Install `pnpm` if not present in your system. Check [here](https:\u002F\u002Fpnpm.io\u002Finstallation) for detailed instructions.\n1. Install the dependencies: `pnpm i next react react-dom nextra nextra-theme-docs`\n1. Boot the guide with `pnpm dev`\n2. Browse the guide at `http:\u002F\u002Flocalhost:3000\u002F`\n\n---\n## Appearances\nSome places where we have been featured:\n- Wall Street Journal - [ChatGPT Can Give Great Answers. But Only If You Know How to Ask the Right Question](https:\u002F\u002Fwww.wsj.com\u002Farticles\u002Fchatgpt-ask-the-right-question-12d0f035)\n- Forbes - [Mom, Dad, I Want To Be A Prompt Engineer](https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Fcraigsmith\u002F2023\u002F04\u002F05\u002Fmom-dad-i-want-to-be-a-prompt-engineer\u002F?sh=7f1213159c8e)\n- Markettechpost - [Best Free Prompt Engineering Resources (2023)](https:\u002F\u002Fwww.marktechpost.com\u002F2023\u002F04\u002F04\u002Fbest-free-prompt-engineering-resources-2023\u002F)\n\n\n---\nIf you are using the guide for your work or research, please cite us as follows:\n\n```\n@article{Saravia_Prompt_Engineering_Guide_2022,\nauthor = {Saravia, Elvis},\njournal = {https:\u002F\u002Fgithub.com\u002Fdair-ai\u002FPrompt-Engineering-Guide},\nmonth = {12},\ntitle = {{Prompt Engineering Guide}},\nyear = {2022}\n}\n```\n\n## License\n\n[MIT License](https:\u002F\u002Fgithub.com\u002Fdair-ai\u002FPrompt-Engineering-Guide\u002Fblob\u002Fmain\u002FLICENSE.md)\n\n\nFeel free to open a PR if you think something is missing here. Always welcome feedback and suggestions. Just open an issue!\n","该项目是一个关于提示工程、上下文工程、检索增强生成（RAG）和AI代理的综合指南，涵盖了相关领域的论文、教程、笔记本和资源。它通过提供最新的研究文献、学习资料和实用工具来帮助用户更好地理解和优化大型语言模型（LLM）的应用。该指南适合希望提升自己在提示工程方面技能的研究人员和开发者使用，特别是在涉及复杂任务如问答系统或算术推理时。此外，项目还提供了多种语言版本支持，并通过DAIR.AI Academy提供配套课程以进一步加深理解。",2,"2026-06-11 02:35:30","top_all"]