awesome-chatgpt-prompts
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
Top Related Projects
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Examples and guides for using the OpenAI API
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
A library for helping developers craft prompts for Large Language Models
Curated list of awesome tools, demos, docs for ChatGPT and GPT-3
ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。
Quick Overview
The "awesome-chatgpt-prompts" repository is a curated collection of prompts for ChatGPT, designed to help users get the most out of the AI language model. It provides a wide range of creative and practical prompts that can be used to generate various types of content, solve problems, or engage in specific conversations with ChatGPT.
Pros
- Extensive collection of diverse prompts covering numerous topics and use cases
- Regularly updated with new prompts contributed by the community
- Well-organized and easy to navigate, with prompts categorized by purpose or theme
- Helps users unlock the full potential of ChatGPT by providing targeted conversation starters
Cons
- Some prompts may not work as effectively as others, depending on the specific version or fine-tuning of the ChatGPT model being used
- The quality of responses can vary based on the prompt and the user's ability to refine or adapt it
- May lead to over-reliance on pre-written prompts rather than encouraging users to develop their own creative prompts
- The large number of prompts can be overwhelming for new users
Getting Started
To use the prompts from this repository:
- Visit the GitHub repository: f/awesome-chatgpt-prompts
- Browse through the README.md file to find prompts that interest you
- Copy the desired prompt
- Paste the prompt into your ChatGPT conversation
- Modify the prompt as needed to suit your specific requirements
- Press enter to submit the prompt and wait for ChatGPT's response
Remember to experiment with different prompts and adjust them to get the best results for your particular use case.
Competitor Comparisons
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Pros of Prompt-Engineering-Guide
- Comprehensive guide covering various aspects of prompt engineering
- Includes practical examples and techniques for different AI models
- Regularly updated with new content and research findings
Cons of Prompt-Engineering-Guide
- More complex and time-consuming to navigate for beginners
- Focuses on theoretical concepts rather than ready-to-use prompts
- Requires more effort to implement in practical scenarios
Code Comparison
Prompt-Engineering-Guide:
def generate_prompt(topic, style):
return f"Write a {style} article about {topic}."
prompt = generate_prompt("AI ethics", "informative")
Awesome-ChatGPT-Prompts:
Act as an AI writing tutor. I will provide you with a student's essay and your task is to provide feedback and suggestions for improvement.
The Prompt-Engineering-Guide example demonstrates a programmatic approach to generating prompts, while Awesome-ChatGPT-Prompts offers ready-to-use, specific prompts for various scenarios. The former is more flexible but requires coding knowledge, while the latter is more accessible for immediate use.
Examples and guides for using the OpenAI API
Pros of openai-cookbook
- Provides comprehensive examples and best practices for using OpenAI's APIs
- Includes code snippets and tutorials for various programming languages
- Offers guidance on advanced techniques like fine-tuning and embeddings
Cons of openai-cookbook
- Focuses primarily on OpenAI's products, limiting its scope compared to awesome-chatgpt-prompts
- May be more technical and less accessible for non-developers
- Lacks the diverse range of creative prompts found in awesome-chatgpt-prompts
Code Comparison
openai-cookbook:
import openai
response = openai.Completion.create(
engine="text-davinci-002",
prompt="Translate the following English text to French: '{}'",
max_tokens=60
)
awesome-chatgpt-prompts:
Act as an English to French translator. I will speak to you in English and you will translate it to French. Please don't explain the translation, just translate. My first sentence is "Hello, how are you?"
The openai-cookbook example demonstrates API usage, while awesome-chatgpt-prompts focuses on natural language prompts for ChatGPT interactions.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Pros of Awesome-Prompt-Engineering
- Broader focus on prompt engineering across multiple AI models and platforms
- More comprehensive coverage of prompt engineering techniques and strategies
- Includes educational resources and research papers on prompt engineering
Cons of Awesome-Prompt-Engineering
- Less focused on specific, ready-to-use prompts for ChatGPT
- May be overwhelming for beginners looking for simple, practical prompts
- Requires more time to navigate and find relevant information
Code Comparison
While both repositories primarily consist of markdown files and don't contain significant code, Awesome-Prompt-Engineering includes some example prompts in code blocks:
Awesome-Prompt-Engineering:
[INST] <<SYS>> You are a helpful AI assistant. <</SYS>>
Human: What is the capital of France?
Assistant: The capital of France is Paris.
[/INST]
awesome-chatgpt-prompts:
(No specific code examples provided in the main README)
Awesome-Prompt-Engineering offers a more technical and comprehensive approach to prompt engineering, while awesome-chatgpt-prompts focuses on providing a curated list of ready-to-use prompts specifically for ChatGPT. The choice between the two depends on the user's needs and level of expertise in prompt engineering.
A library for helping developers craft prompts for Large Language Models
Pros of prompt-engine
- More structured approach to prompt engineering with TypeScript support
- Focuses on building reusable components for prompt creation
- Integrates well with Azure OpenAI and other Microsoft services
Cons of prompt-engine
- Less community-driven content compared to awesome-chatgpt-prompts
- Narrower scope, primarily tailored for Microsoft ecosystem
- Steeper learning curve for developers unfamiliar with TypeScript
Code Comparison
prompt-engine:
import { PromptTemplate } from "@microsoft/prompt-engine";
const template = new PromptTemplate("Hello, {name}!");
const prompt = template.format({ name: "World" });
awesome-chatgpt-prompts:
Act as an English Translator and Improver
Human: I want you to act as an English translator, spelling corrector and improver. I will speak to you in any language and you will detect the language, translate it and answer in the corrected and improved version of my text, in English. I want you to replace my simplified A0-level words and sentences with more beautiful and elegant, upper level English words and sentences. Keep the meaning same, but make them more literary. I want you to only reply the correction, the improvements and nothing else, do not write explanations. My first sentence is "istanbulu cok seviyom burada olmak cok guzel"
Curated list of awesome tools, demos, docs for ChatGPT and GPT-3
Pros of awesome-chatgpt
- More comprehensive coverage of ChatGPT-related topics, including tutorials, tools, and applications
- Regularly updated with new resources and information
- Includes a section on ethical considerations and potential risks of ChatGPT
Cons of awesome-chatgpt
- Less focused on specific prompts and examples
- May be overwhelming for beginners due to the large amount of information
- Lacks a clear categorization system for prompts
Code comparison
awesome-chatgpt-prompts:
# Act as a Linux Terminal
I want you to act as a linux terminal. I will type commands and you will reply with what the terminal should show. I want you to only reply with the terminal output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when i need to tell you something in english, i will do so by putting text inside curly brackets {like this}. my first command is pwd
awesome-chatgpt:
## Prompts
- [Awesome ChatGPT Prompts](https://github.com/f/awesome-chatgpt-prompts) - A collection of prompt examples to be used with ChatGPT.
- [ShowGPT](https://showgpt.co/) - See and share ChatGPT conversations.
- [FlowGPT](https://flowgpt.com/) - Share and discover the best prompts for ChatGPT.
The code comparison shows that awesome-chatgpt-prompts focuses on specific prompt examples, while awesome-chatgpt provides links to external resources for prompts.
ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。
Pros of awesome-chatgpt-prompts-zh
- Offers prompts in Chinese, catering to a broader audience
- Includes a wider variety of prompt categories and use cases
- Provides more detailed explanations and examples for each prompt
Cons of awesome-chatgpt-prompts-zh
- Less organized structure compared to awesome-chatgpt-prompts
- May have more inconsistent formatting and quality control
- Potentially slower updates due to translation and localization efforts
Code Comparison
awesome-chatgpt-prompts:
# Act as a Linux Terminal
I want you to act as a linux terminal. I will type commands and you will reply with what the terminal should show. I want you to only reply with the terminal output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when i need to tell you something in english, i will do so by putting text inside curly brackets {like this}. my first command is pwd
awesome-chatgpt-prompts-zh:
# 充当 Linux 终端
我想让你充当 Linux 终端。我将输入命令,您将回复终端应显示的内容。我希望您只在一个唯一的代码块内回复终端输出,而不是其他任何内容。不要写解释。除非我指示您这样做,否则不要键入命令。当我需要用英语告诉你一些事情时,我会把文字放在大括号内{像这样}。我的第一个命令是 pwd
Convert
designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual CopilotREADME
â ï¸ Where are all the prompts gone?
No worries! They're still here. The README became too large to maintain, so prompts now live in PROMPTS.md. Your contributions to prompts.chat automatically sync there. Still free, still open source.
ð View All Prompts on prompts.chat
ð View All Prompts on GitHub (PROMPTS.md)
ð View All Prompts synced on GitHub (prompts.csv)
ð View All Prompts synced on Data Studio on HF (prompts.csv)
a.k.a. Awesome ChatGPT Prompts
Sponsors
prompts.chat is built with Windsurf and Devin by Cognition
Be my sponsor and your logo will be here!
Welcome to the "Awesome ChatGPT Prompts" repository! While this collection was originally created for ChatGPT, these prompts work great with other AI models like Claude, Gemini, Hugging Face Chat, Llama, Mistral, and more.
In this repository, you will find a variety of prompts that can be used with ChatGPT and other AI chat models. We encourage you to add your own prompts to the list, and to use AI to help generate new prompts as well. Your contributions to prompts.chat will be contributions to this repository automatically.
Want to deploy your own private prompt library for your team?
Check out our Self-Hosting Guide for instructions on setting up your own instance with customizable branding, themes, and authentication.
Quick Start (Recommended)
Create a new prompts.chat instance with a single command:
npx prompts.chat new my-prompt-library
cd my-prompt-library
This will clone a clean copy, install dependencies, and launch the interactive setup wizard.
Manual Setup
git clone https://github.com/f/awesome-chatgpt-prompts.git
cd awesome-chatgpt-prompts
npm install
npm run setup
The setup wizard will guide you through:
- Branding â Set your organization name, logo, and description
- Theme â Choose colors, border radius, and UI style
- Authentication â Configure GitHub, Google, Apple, Azure AD, or email/password login
- Features â Enable/disable private prompts, categories, tags, comments, AI search, AI generation, MCP
- Languages â Select supported locales
- Sponsors â Optionally add your own sponsor logos (prompts.chat sponsors are disabled)
After setup, complete the configuration:
# Edit .env with your database and OAuth credentials
nano .env
# Run database migrations
npm run db:push
# Start development server
npm run dev
ð¡ Tip: The setup script automatically enables "clone branding mode" which hides prompts.chat branding, achievements, and sponsors from the homepage.
We hope you find these prompts useful and have fun exploring AI chat models!
View Hugging Face Dataset
â¹ï¸ NOTE: Sometimes, some of the prompts may not be working as you expected or may be rejected by the AI. Please try again, start a new thread, or log out and log back in. If these solutions do not work, please try rewriting the prompt using your own sentences while keeping the instructions same.
Want to Write Effective Prompts?
I've authored an e-book called "The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts".
ð Read the e-book
Want to Learn How to Make Money using ChatGPT Prompts?
I've authored an e-book called "How to Make Money with ChatGPT: Strategies, Tips, and Tactics".
ð Buy the e-book
Want to Learn How to write image prompts for Midjourney AI?
I've authored an e-book called "The Art of Midjourney AI: A Guide to Creating Images from Text".
ð Read the e-book
Prompts
ð View All Prompts on GitHub (prompts.csv)
ð View All Prompts as Data Studio on HF (prompts.csv)
ð View All Prompts on prompts.chat
Contributors ð
Many thanks to these AI whisperers:
License
This work is licensed under CC0 1.0 Universal (Public Domain Dedication).
You can copy, modify, distribute, and use the prompts freely â even for commercial purposes â without asking permission or giving attribution. All prompts contributed to this repository are released into the public domain.
Top Related Projects
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Examples and guides for using the OpenAI API
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
A library for helping developers craft prompts for Large Language Models
Curated list of awesome tools, demos, docs for ChatGPT and GPT-3
ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。
Convert
designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual Copilot