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Prompt Engineering Guide

Prompt 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.

Motivated 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.

Happy Prompting!

Due to high demand, we've partnered with Sphere to deliver a new course on Prompt Engineering for LLMs. This includes a certificate of completion. Elvis Saravia, who has has years of experience in ML, NLP, and LLMs, will be the instructor of this course.


Announcements / Updates

  • 🌐 We now support 中文, 日本語, Português, Turkish and English. Welcoming more translations.
  • 🎉 We have launched new web version of the guide here
  • 🔥 We reached #1 on Hacker News on 21 Feb 2023
  • 🎉 The Prompt Engineering Lecture went live here

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Guides

Please note that the guides below are now outdated. You can find the most up-to-date guides on our new website https://www.promptingguide.ai/.


Lecture

We have published a 1 hour lecture that provides a comprehensive overview of prompting techniques, applications, and tools.


Running the guide locally

To run the guide locally, for example to check the correct implementation of a new translation, you will need to:

  1. Install Node >=18.0.0
  2. Install pnpm if not present in your system. Check here for detailed instructions.
  3. Install the dependencies: pnpm i next react react-dom nextra nextra-theme-docs
  4. Boot the guide with pnpm dev
  5. Browse the guide at http://localhost:3000/

Appearances

Some places where we have been featured:


If you are using the guide for your work, please cite us as follows:

@article{Saravia_Prompt_Engineering_Guide_2022,
author = {Saravia, Elvis},
journal = {https://github.com/dair-ai/Prompt-Engineering-Guide},
month = {12},
title = {{Prompt Engineering Guide}},
year = {2022}
}

License

MIT License

Feel free to open a PR if you think something is missing here. Always welcome feedback and suggestions. Just open an issue!