#3838th of 65 in Learning and cookbooks
prompt-engineering-guide
Written guide to prompt engineering techniques, with papers, notebooks and example prompts
- Stars
- 79.7k
- License
- MIT
- Last commit
- Mar 2026
- Language
- MDX
72,361 on 10 Apr 202679,730 on 30 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
A documentation site and source repository covering prompting techniques (zero-shot, few-shot, chain-of-thought, ReAct, RAG), applications such as function calling and data generation, and model-specific notes. It also links to papers, datasets, a one-hour lecture and a Jupyter notebook. The site is built with Nextra and runs locally with Node 18+ and pnpm.
Who it is for: Developers and researchers learning prompting techniques for LLMs
Strengths
- Covers many named techniques, each with its own page and linked papers
- Includes a lecture video, slides and a runnable notebook
- Translated into 13 languages, per the README
- Can be built locally with Node and pnpm to check changes
Weaknesses
- Mostly prose and links; little runnable code beyond one lecture notebook
- README promotes paid DAIR.AI Academy courses and services
- Model pages cover older models such as GPT-4, Mixtral and Phi-2
- No tagged releases; the web version is the maintained copy
What it needs
- no GPU
- Needs Node >=18, pnpm
- port 3000
Quick answers
Is prompt-engineering-guide open source?
Yes. Its code is on GitHub under the MIT license.
Does prompt-engineering-guide need a GPU?
No, it runs without one.
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