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β€’

2022-12-16

Prompt-Engineering-Guide logo

Prompt-Engineering-Guide

Not rated yet

77.1K GitHub stars

Type:

Tool

Platforms:

Github

Task:

Study and learnEngineer prompts

Best for:

IT & Development
Visit websiteView on GitHub

Pricing


Pricing information has not been added yet.

Overview

Prompt Engineering Guide is an open educational resource focused on techniques for communicating effectively with large language models. It covers prompt fundamentals, prompting patterns, model behavior, evaluation, retrieval, agents, reasoning approaches, safety considerations, and practical examples across a range of LLM applications.

The repository functions as both a learning path and a reference library, collecting explanations, papers, tools, and examples in one place. It is useful for developers, researchers, product teams, and learners who want to understand how prompt design affects model output and how prompting fits into broader systems such as RAG pipelines, agents, and production AI applications.

README

Prompt Engineering Guide

Sponsored byΒ Β Β Β 

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)

πŸŽ‰ We are excited to launch our new prompt engineering, RAG, and AI Agents courses under the DAIR.AI Academy. Join Now!

The courses are meant to compliment this guide and provide a more hands-on approach to learning about prompt engineering, context engineering, and AI Agents.

Use code PROMPTING20 to get an extra 20% off.

Happy Prompting!


Announcements / Updates

  • πŸŽ“ We now offer self-paced prompt engineering courses under our DAIR.AI Academy. Join Now!
  • πŸŽ“ New course on Prompt Engineering for LLMs announced! Enroll here!
  • πŸ’Ό We now offer several services like corporate training, consulting, and talks.
  • 🌐 We now support 13 languages! Welcoming more translations.
  • πŸ‘©β€πŸŽ“ We crossed 3 million learners in January 2024!
  • πŸŽ‰ We have launched a new web version of the guide here
  • πŸ”₯ We reached #1 on Hacker News on 21 Feb 2023
  • πŸŽ‰ The First Prompt Engineering Lecture went live here

Join our Discord

Follow us on Twitter

Subscribe to our YouTube

Subscribe to our Newsletter


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:

  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:

  • 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!

Releases

Release information has not been added yet.

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