Prompt-Engineering-Guide

by dair-ai · Machine Learning

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

New0 ratings78,057 starsActive
Machine LearningDeveloper ToolMDXJupyter Notebook
Open project ↗GitHub⚑ Report
Prompt-Engineering-Guide preview

About this project

Prompt Engineering Guide Sponsored by     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…

Technologies

TypeScriptJavaScriptHTMLMDXai-agentsagentsJupyter Notebookagent

Project health

Low recent activity
Last update6 months ago
Contributors193
Latest release
Open issues & PRs280
LicenseMIT
On GitHubsince 2022

GitHub

78,057
stars
8,576
forks
193
contributors
280
open issues & PRs
MDX
language
6 months ago
last commit
View on GitHub ↗

Reviews

out of 5 · 0 ratings
★★★★★
0%
★★★★
0%
★★★
0%
★★
0%
0%
Sign in to write a review
No reviews yet
Be the first to review Prompt-Engineering-Guide.

Built by

dair-ai
Imported from GitHub · not yet claimed on GitPalace
View developer pageSign in with GitHub to claim

Maintain dair-ai/Prompt-Engineering-Guide? Claiming verifies admin access through your GitHub account and gives you control of this listing.

You might also like