Prompt Engineering Guide
GitHub - dair-ai/Prompt-Engineering-Guide: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
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 for LLMs.
🌐 Prompt Engineering Guide (Web Version)
🎉 We are excited to launch our brand new prompt engineering courses under the DAIR.AI Academy. Join Now!
Happy Prompting!

Announcements / Updates

🎓 We now offer self-paced prompt engineering courses under our DAIR.AI Academy. Join Now!
🎓 New course on Prompt Engineering for LLMs announced! Enroll here!
💼 We now offer several services like corporate training, consulting, and talks.
🌐 We now support 13 languages! Welcoming more translations.
👩‍🎓 We crossed 3 million learners in January 2024!
🎉 We have launched a new web version of the guide here
🔥 We reached #1 on Hacker News on 21 Feb 2023
🎉 The First Prompt Engineering Lecture went live here

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Guides
You can also find the most up-to-date guides on our new website https://www.promptingguide.ai/.

Prompt Engineering - Introduction

Prompt Engineering - LLM Settings
Prompt Engineering - Basics of Prompting
Prompt Engineering - Prompt Elements
Prompt Engineering - General Tips for Designing Prompts
Prompt Engineering - Examples of Prompts


Prompt Engineering - Techniques

Prompt Engineering - Zero-Shot Prompting
Prompt Engineering - Few-Shot Prompting
Prompt Engineering - Chain-of-Thought Prompting
Prompt Engineering - Self-Consistency
Prompt Engineering - Generate Knowledge Prompting
Prompt Engineering - Prompt Chaining
Prompt Engineering - Tree of Thoughts (ToT)
Prompt Engineering - Retrieval Augmented Generation
Prompt Engineering - Automatic Reasoning and Tool-use (ART)
Prompt Engineering - Automatic Prompt Engineer
Prompt Engineering - Active-Prompt
Prompt Engineering - Directional Stimulus Prompting
Prompt Engineering - Program-Aided Language Models
Prompt Engineering - ReAct Prompting
Prompt Engineering - Multimodal CoT Prompting
Prompt Engineering - Graph Prompting


Prompt Engineering - Applications

Prompt Engineering - Function Calling
Prompt Engineering - Generating Data
Prompt Engineering - Generating Synthetic Dataset for RAG
Prompt Engineering - Takling Generated Datasets Diversity
Prompt Engineering - Generating Code
Prompt Engineering - Graduate Job Classification Case Study


Prompt Engineering - Prompt Hub

Prompt Engineering - Classification
Prompt Engineering - Coding
Prompt Engineering - Creativity
Prompt Engineering - Evaluation
Prompt Engineering - Information Extraction
Prompt Engineering - Image Generation
Prompt Engineering - Mathematics
Prompt Engineering - Question Answering
Prompt Engineering - Reasoning
Prompt Engineering - Text Summarization
Prompt Engineering - Truthfulness
Prompt Engineering - Adversarial Prompting


Prompt Engineering - Models

Prompt Engineering - ChatGPT
Prompt Engineering - Code Llama
Prompt Engineering - Flan
Prompt Engineering - Gemini
Prompt Engineering - GPT-4
Prompt Engineering - LLaMA
Prompt Engineering - Mistral 7B
Prompt Engineering - Mixtral
Prompt Engineering - OLMo
Prompt Engineering - Phi-2
Prompt Engineering - Model Collection


Prompt Engineering - Risks and Misuses

Prompt Engineering - Adversarial Prompting
Prompt Engineering - Factuality
Prompt Engineering - Biases


Prompt Engineering - Papers

Prompt Engineering - Overviews
Prompt Engineering - Approaches
Prompt Engineering - Applications
Prompt Engineering - Collections


Prompt Engineering - Tools
Prompt Engineering - Notebooks
Prompt Engineering - Datasets
Prompt Engineering - Additional Readings


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

Video Lecture
Notebook with code
Slides


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

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


Appearances
Some places where we have been featured:

Wall Street Journal - ChatGPT Can Give Great Answers. But Only If You Know How to Ask the Right Question
Forbes - Mom, Dad, I Want To Be A Prompt Engineer
Markettechpost - Best Free Prompt Engineering Resources (2023)


If you are using the guide for your work or research, 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!
