https://github.com/snwfdhmp/awesome-gpt-prompt-engineering

A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering.
https://github.com/snwfdhmp/awesome-gpt-prompt-engineering

List: awesome-gpt-prompt-engineering

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A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering.

• Host: GitHub
• URL: https://github.com/snwfdhmp/awesome-gpt-prompt-engineering
• Owner: snwfdhmp
• License: other
• Created: 2023-05-31T13:02:05.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-05-09T23:48:21.000Z (7 months ago)
• Last Synced: 2024-05-23T07:35:45.640Z (7 months ago)
• Topics: awesome, awesome-list, awesome-lists, awesome-readme, awesome-resources, chatgpt, gpt, gpt-3, gpt-35-turbo, gpt-4, large-language-models, llm, openai, prompt, prompt-engineering, prompt-generator, prompt-learning, prompts, resources
• Language: Python
• Homepage:
• Size: 830 KB
• Stars: 825
• Watchers: 27
• Forks: 85
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

• awesome-ChatGPT-repositories - awesome-gpt-prompt-engineering - A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering. (Awesome-lists)
• StarryDivineSky - snwfdhmp/awesome-gpt-prompt-engineering
• awesome-chatgpt - snwfdhmp/awesome-gpt-prompt-engineering - A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering. (Documentation and examples / Lists, Guides and examples)
• awesome_gpt_super_prompting - snwfdhmp/awesome-gpt-prompt-engineering - A list of awesome resources on prompt engineering. (🛠️ Prompt Engineering / Hall Of Fame:)
• ultimate-awesome - awesome-gpt-prompt-engineering - A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering. (Other Lists / PowerShell Lists)
• jimsghstars - snwfdhmp/awesome-gpt-prompt-engineering - A curated list of awesome resources, tools, and other shiny things for LLM prompt engineering. (Python)
• awesome-ai-data-github-repos - Awesome GPT Prompt Engineering: A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering
• awesome-ai-data-github-repos - Awesome GPT Prompt Engineering: A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering

README

        
# Awesome GPT Prompt Engineering 
       


A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering.

Consider giving it a ⭐️ if you like it to show your support!

🚀 **RECOMMENDED**: [Use any LLM from the command line easily](https://github.com/snwfdhmp/llm). 🚀

**Table of Contents**

- [Awesome GPT Prompt Engineering        ](#awesome-gpt-prompt-engineering--------)

	- [Roadmaps](#roadmaps)

	- [Guides](#guides)

	- [Techniques](#techniques)

	- [Prompt Collections](#prompt-collections)

	- [Papers](#papers)

	- [Books](#books)

	- [Communities](#communities)

	- [Prompt Generators](#prompt-generators)

	- [Auto-GPT Related](#auto-gpt-related)

	- [Prompt Injection](#prompt-injection)

	- [Playgrounds and Alternative UIs](#playgrounds-and-alternative-uis)

	- [ChatGPT Plug-ins](#chatgpt-plug-ins)

	- [Prompt Engineering Jobs Offers](#prompt-engineering-jobs-offers)

	- [AI Links Directories](#ai-links-directories)

- [Contributing](#contributing)

## Roadmaps

- [Prompt Engineering Roadmap](https://roadmap.sh/prompt-engineering?): Step by step guide to learning Prompt Engineering.



	



## Guides

- [Learn Prompt Engineering](https://learnprompting.org/docs/category/-basics): Introduction to Prompt Engineering and Prompt Engineering techniques.

- [Prompt Engineering Guide](https://github.com/dair-ai/Prompt-Engineering-Guide): Guides, papers, lecture, notebooks and resources for prompt engineering.

- [Prompt Engineering 101](https://www.linkedin.com/pulse/prompt-engineering-101-introduction-resources-amatriain): Prompt Engineering guide by Xavi.

- [Prompt Engineering 101](https://humanloop.com/blog/prompt-engineering-101): Prompt Engineering guide by Raza Habib & Sinan Ozdemir.

- [Prompt Engineering Guide](https://github.com/SudalaiRajkumar/Talks_Webinars/blob/master/Slides/PromptEngineering_20230208.pdf): Prompt Engineering guide by Sudalai Rajkumar.

- [How to generate text: using different decoding methods for language generation with Transformers](https://huggingface.co/blog/how-to-generate): A guide to decoding methods for language generation with Transformers.

- [The Illustrated Transformer](http://jalammar.github.io/illustrated-transformer/): A visual guide to transformers, the core model used in GPT.

- [Reddit's r/aipromptprogramming Tutorials Collection](https://www.reddit.com/r/aipromptprogramming/collection/d3a393ad-ef15-4f2a-a23e-18a5c90ff48d): A collection of tutorials for prompt engineering.

- [Prompt Engineering Guide](https://www.promptingguide.ai/): A comprehensive guide that contains all the latest papers, learning resources, and developments in the field of prompt engineering.

- [dair-ai/Prompt-Engineering-Guide](https://github.com/dair-ai/Prompt-Engineering-Guide): A GitHub repository that provides a prompt engineering guide with the latest papers and learning guides.

- [How to Communicate with ChatGPT – A Guide to Prompt Engineering](https://www.freecodecamp.org/news/how-to-communicate-with-chatgpt-a-guide-to-prompt-engineering/): A guide that explains what prompt engineering is and how you can use it to improve your communication with AI tools.

- [A Beginner's Guide to ChatGPT Prompt Engineering](https://www.datacamp.com/tutorial/a-beginners-guide-to-chatgpt-prompt-engineering): A beginner-friendly guide that delves into the art and science of Prompt Engineering.

- [A Complete Introduction to Prompt Engineering for Large Language Models](https://www.mihaileric.com/posts/a-complete-introduction-to-prompt-engineering)

- [Prompt Engineering Guide: How to Engineer the Perfect Prompts](https://richardbatt.co.uk/prompt-engineering-guide-how-to-engineer-the-perfect-prompts)

- [Best practices for prompt engineering with OpenAI API](https://help.openai.com/articles/6654000-best-practices-for-prompt-engineering-with-openai-api): A guide by OpenAI that provides best practices for prompt engineering.

- [ChatGPT Prompt Engineering for Developers](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/): A short course on prompt engineering by deeplearning.ai.

- [Natural Language Processing](https://www.coursera.org/specializations/natural-language-processing): Coursera specialization focusing on NLP.

- [Learn Prompting](https://learnprompting.org/): A Free, Open Source Course on Communicating with AI.

- [Deep Learning Specialization](https://www.coursera.org/specializations/deep-learning): Coursera specialization by Andrew Ng, which includes a course on Sequence Models.

- [OpenAI Cookbook](https://github.com/openai/openai-cookbook): OpenAI's cookbook includes examples of prompt engineering.

- [Tokens and Tokenization: Understanding Cost, Speed, and Limits with OpenAI's APIs](https://www.prompthub.us/blog/tokens-and-tokenization-understanding-cost-speed-and-limits-with-openais-apis): Everything tokens and tokenization. How to control costs/performance, how to handle Max Token limits, and a real-world example on how you can make your prompts more efficient.

- [How OpenAI Parameters Actuallly Work](https://www.prompthub.us/blog/understanding-openai-parameters-how-to-optimize-your-prompts-for-better-outputs): How to use OpenAI's parameters to experiment with prompts and get better outputs.

- [A Beginner's Guide on Embeddings and Their Impact on Prompts](https://www.prompthub.us/blog/a-beginners-guide-on-embeddings-and-their-impact-on-prompts): A Beginner's Guide on Embeddings and Their Impact on Prompts.

- [Prompt Engineering for Vision Models](https://www.deeplearning.ai/short-courses/prompt-engineering-for-vision-models/): A beginner's guide to prompting vision models from DeepLearningAI.

## Techniques

- [Few Shot Learning](https://blog.paperspace.com/few-shot-learning/): Everything you need to know about Few-Shot Learning.

- [Zero Shot Learning](https://arxiv.org/pdf/2205.11916.pdf): Large Language Models are Zero-Shot Reasoners.

- [Chain of Thought](https://learnprompting.org/docs/intermediate/chain_of_thought): Encourages the LLM to explain its reasoning to improve its accuracy.

- [Zero Shot Chain of Thought](https://learnprompting.org/docs/intermediate/zero_shot_cot): Enable Chain of Thought with only a few words.

- [Tree of Thoughts](https://arxiv.org/pdf/2305.10601.pdf): Tree of Thoughts: Deliberate Problem Solving.

with Large Language Models.

- [Multi Persona Collaboration](https://www.prompthub.us/blog/exploring-multi-persona-prompting-for-better-outputs): Prompt the LLM to dynamically generate personas to collaborate to solve a task.

- [Mastering ChatGPT Prompts](https://www.reddit.com/r/aipromptprogramming/collection/d3a393ad-ef15-4f2a-a23e-18a5c90ff48d/): Mastering ChatGPT Prompts: Harnessing Zero, One, and Few-Shot Learning, Fine-Tuning, and Embeddings for Enhanced GPT Performance.

- [Prompting GPT-3 To Be Reliable](https://arxiv.org/abs/2210.09150): Prompting GPT-3 To Be Reliable.

- [Decomposed Prompting](https://arxiv.org/abs/2210.02406): A Modular Approach for Solving Complex Tasks.

- [AutoPrompt](https://arxiv.org/abs/2010.15980): Eliciting Knowledge from Language Models with Automatically Generated Prompts.

- [LangChain Github Repository](https://github.com/hwchase17/langchain): Building applications with LLMs through composability.

- [Embedchain Github Repository](https://github.com/embedchain/embedchain): Framework to create ChatGPT-like bots over your dataset.

  

## Prompt Collections

- [FlowGPT](https://flowgpt.com/): FlowGPT is the largest open source prompt community.

- [awesomegptprompts.com](https://www.awesomegptprompts.com/): Explore hundreds of the best ChatGPT Prompts.

- [fka/awesome-chatgpt-prompts](https://huggingface.co/datasets/fka/awesome-chatgpt-prompts): Dataset of awesome chatgpt prompts.

- [f/awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts): This repo includes ChatGPT prompt curation to use ChatGPT better. .

- [Awesome ChatGPT Prompts](https://github.com/f/awesome-chatgpt-prompts)

- [PromptHub](https://prompthub.us/)

- [ShowGPT.co](https://showgpt.co/templates)

- [Best Data Science ChatGPT Prompts](https://github.com/travistangvh/ChatGPT-Data-Science-Prompts)

- [ChatGPT prompts uploaded by the FlowGPT community](https://flowgpt.com)

- [Ignacio Velásquez Prompt Templates](https://ignacio-velasquez.notion.site/ignacio-velasquez/500-ChatGPT-Prompt-Templates-d9541e901b2b4e8f800e819bdc0256da): 500+ ChatGPT Prompt Templates.

- [PromptPal](https://www.promptpal.net/): A collection of prompts for GPT-3 and other language models.

- [Hero GPT](https://hero.page/ai-prompts): AI Prompt Library.

- [Reddit's ChatGPT Prompts](https://www.reddit.com/r/ChatGPT_Prompts/)

- [Snack Prompt](https://snackprompt.com): GPT prompts collection, has a a Chrome extension.

- [ShareGPT](https://sharegpt.com): Share your prompts and your entire conversations.

- [Prompt Search](https://www.ptsearch.info/tags/list/): a search engine for AI Prompts.

- [PromptBase](https://promptbase.com/): The largest prompts marketplace on the web.

- [The Ultimate 5 ChatGPT Prompts](https://ngmi.gumroad.com/l/nobsprompts): Simplify Your AI Experience.

- [The Prompt Index](https://www.thepromptindex.com/): A vast collection of carefully curated prompts, stimulating imagination and fueling creative endeavours.

- [PromptDen](https://promptden.com): A growing list of thousands of prompts for both text and image generation. Free to explore, add your own, save your favorites and even create a profile page for prompt engineering.

## Papers

- [Attention Is All You Need](https://arxiv.org/abs/1706.03762): Transformer introduction paper.

- [Language Models are Few-Shot Learners](https://arxiv.org/abs/2005.14165): GPT-3 introduction paper by OpenAI.

- [Fine-Tuning Language Models from Human Preferences](https://arxiv.org/abs/1909.08593): Important paper on fine-tuning language models by OpenAI.

- [The Power of Scale for Parameter-Efficient Prompt Tuning](https://arxiv.org/abs/2104.08691): Explores the benefits of "prompt tuning" for robust task performance.

- [Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations](https://aclanthology.org/2020.emnlp-main.676): Introduces an architecture for accurate stock forecasting using financial data and social media signals.

- [A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT](https://arxiv.org/abs/2302.11382)

- [Hard Prompts Made Easy](https://arxiv.org/abs/2302.03668): Gradient-Based Discrete Optimization for Prompt Tuning and Discovery.

- [Synthetic Prompting](https://arxiv.org/abs/2302.00618): Generating Chain-of-Thought Demonstrations for Large Language Models.

- [Progressive Prompts](https://arxiv.org/abs/2301.12314): Continual Learning for Language Models.

- [Batch Prompting](https://arxiv.org/abs/2301.08721): Efficient Inference with LLM APIs.

- [Successive Prompting for Decompleting Complex Questions](https://arxiv.org/abs/2212.04092)

- [Structured Prompting](https://arxiv.org/abs/2212.06713): Scaling In-Context Learning to 1,000 Examples.

- [Large Language Models Are Human-Level Prompt Engineers](https://arxiv.org/abs/2211.01910)

- [Ask Me Anything](https://paperswithcode.com/paper/ask-me-anything-a-simple-strategy-for): A simple strategy for prompting language models.

- [PromptChainer](https://arxiv.org/abs/2203.06566): Chaining Large Language Model Prompts through Visual Programming.

- [Reframing Instructional Prompts to GPTk's Language](https://arxiv.org/abs/2109.07830)

- [Prompt Programming for Large Language Models](https://arxiv.org/abs/2102.07350): Beyond the Few-Shot Paradigm.

- [Prefix-Tuning: Optimizing Continuous Prompts for Generation](https://arxiv.org/abs/2101.00190)

- [Multimodal Chain-of-Thought Reasoning in Language Models](https://arxiv.org/abs/2302.00923)

- [On Second Thought, Let's Not Think Step by Step!](https://arxiv.org/abs/2212.08061): Bias and Toxicity in Zero-Shot Reasoning.

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://arxiv.org/abs/2210.03629)

- [Language Models Are Greedy Reasoners](https://arxiv.org/abs/2210.01240v3): A Systematic Formal Analysis of Chain-of-Thought.

- [On the Advance of Making Language Models Better Reasoners](https://arxiv.org/abs/2206.02336)

- [Large Language Models are Zero-Shot Reasoners](https://arxiv.org/abs/2205.11916)

- [Reasoning Like Program Executors](https://arxiv.org/abs/2201.11473)

- [Self-Consistency Improves Chain of Thought Reasoning in Language Models](https://arxiv.org/abs/2203.11171)

- [Chain of Thought Prompting Elicits Reasoning in Large Language Models](https://arxiv.org/abs/2201.11903)

- [Generated Knowledge Prompting for Commonsense Reasoning](https://arxiv.org/abs/2110.08387)

- [Large Language Models Can Be Easily Distracted by Irrelevant Context](https://arxiv.org/abs/2302.00093)

- [Constitutional AI: Harmlessness from AI Feedback](https://arxiv.org/abs/2212.08073)

## Books

- [The ChatGPT Prompt Book](https://lifearchitect.ai/chatgpt-prompt-book/): A book dedicated to ChatGPT prompts.

- [You Look Like a Thing and I Love You](https://janelleshane.com/book-you-look-like-a-thing-and-i-love-you): A book about AI with a focus on language models.

## Communities

- [OpenAI Discord Server](https://discord.com/invite/openai): The official OpenAI Discord server.

- [Attention Architects](https://discord.gg/XhyEWG3PTr): Prompt Engineering expert & open source community.

- [ChatGPT Prompt Engineering Discord Server](https://dsc.gg/chatgpt): A Discord server dedicated to prompt engineering.

- [Attention Architects](https://discord.gg/XhyEWG3PTr): Prompt Engineering open source community.

- [r/MachineLearning](https://www.reddit.com/r/MachineLearning/): The Machine Learning subreddit often has discussions on GPT and other language models.

- [Hugging Face Forum](https://discuss.huggingface.co/): A forum for discussing Hugging Face's transformer models, including GPT.

- [ChatGPT Community Discord Server](https://discord.gg/cgpt): A Discord server dedicated to ChatGPT.

- [Reddit's ChatGPT Discord Server](https://discord.gg/NuefU36EC2): r/chatgpt Discord server.

- [PromptsLab Discord](https://discord.gg/m88xfYMbK6): Knowledge sharing community for Generative Models, Prompt Engineering, LLMs.

- [Learn Prompting](https://discord.gg/7enStJXQzD): A Discord server dedicated to learning about prompts.

- [Artificial Intelligence Discord](https://discord.gg/XhyEWG3PTr): Discord server for AI enthusiasts and prompt engineers.

## Playgrounds and Alternative UIs

- [Official OpenAI Playground](https://platform.openai.com/playground)

- [llm](https://github.com/snwfdhmp/llm): Use any LLM from the command line, easily.

- [Nat.Dev](https://nat.dev): Multiple Chat AI Playground & Comparer.

- [Poe.com](https://poe.com): All in one playground: GPT4, Sage, Claude+, Dragonfly, and more...

- [Ora.sh GPT-4 Chatbots](https://ora.sh/gpt-4)

- [Better ChatGPT](https://bettergpt.chat): A web app with a better UI for exploring OpenAI's ChatGPT API.

- [LMQL.AI](https://lmql.ai/playground/#calc): A programming language and platform for language models.

- [Vercel Ai Playground](https://play.vercel.ai): One prompt, multiple Models (including GPT-4).

- [Conju.ai](https://app.conju.ai/): A visual prompt chaining app.

- [Voiceflow](https://www.voiceflow.com): Professional collaborative visual prompt-chaining tool.

- [CometLLM](https://github.com/comet-ml/comet-llm): Track, visualize, and evaluate your LLM prompts and chains in one simple-to-use, convenient UI.

## Prompt Generators

- [Promptify](https://promptify.pro): Automatically improve your prompt.

- [Fusion](https://fusion.tiiny.site/home.html): Elevate your output with Fusion's smart prompts.

- [Bumble-Prompts](https://bumble-prompts.vercel.app/): Let AI Write your bumble prompt.

- [ChatGPT Prompt Generator](https://huggingface.co/spaces/merve/ChatGPT-prompt-generator): Generates ChatGPT prompts based on a BART model.

- [PromptPerfect](https://promptperfect.jina.ai/): Prompt optimizer.

- [Hero GPT](https://hero.page/ai-prompts): AI Prompt Generator.

- [LMQL](https://github.com/eth-sri/lmql): Query language for programming large language models.

- [OpenPromptStudio](https://moonvy.com/apps/ops/)

- [BossGPT](https://www.gptboss.com)

  

## Auto-GPT Related

- [Auto-GPT Official Repo](https://github.com/Significant-Gravitas/Auto-GPT)

- [Auto-GPT God Mode](https://godmode.space/)

- [OpenAIMaster's Guide to Auto-GPT](https://openaimaster.com/how-does-autogpt-work-an-ai-tool-to-create-full-projects/): How does Auto-GPT work, an AI tool to create full projects.

- [AgentGPT](https://agentgpt.reworkd.ai): GPT agents in browser.

- [DemoGPT](https://github.com/melih-unsal/DemoGPT): 🧩 DemoGPT enables you to create quick demos by just using prompts.

## Prompt Injection

- [Understanding Prompt Injections and What You Can Do About Them](https://www.prompthub.us/blog/understanding-prompt-injections-and-what-you-can-do-about-them): An introduction to prompt injections with examples and tactics you can use to mitigate potential risks in your application.

- [Learn Prompting's Prompt Injection guide](https://learnprompting.org/docs/prompt_hacking/injection): A guide to prompt injections with examples.

- [Prompt injection: What's the worst that can happen?](https://simonwillison.net/2023/Apr/14/worst-that-can-happen/)

- [Prompt injections are bad, mkay?](https://greshake.github.io/)

## ChatGPT Plug-ins

- [ChatGPT plugins](https://openai.com/blog/chatgpt-plugins): OpenAI Official Page.

- [Plug-in example code in Python](https://github.com/ruvnet/chatgpt_plugin_python): Example code for creating a ChatGPT plug-in in Python.

- [Surfer Plug-in source code](https://github.com/ruvnet/Surfer)

- [Security](https://www.security.dev/): (PAID) Create, deploy, monitor and secure LLM Plugins.

## Prompt Engineering Jobs Offers

- [Prompt-Talent](https://www.prompt-talent.com): Prompt engineering job offers.

## AI Links Directories

- [llm](https://github.com/snwfdhmp/llm): Use any LLM from the command line. 

- [FuturePedia](https://www.futurepedia.io/ai-tools): The Largest AI Tools Directory Updated Daily.

- [Theresanaiforthat](https://theresanaiforthat.com/s/gpt/): The biggest AI aggregator.

- [Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering)

- [AiTreasureBox](https://github.com/superiorlu/AiTreasureBox)

- [EwingYangs Awesome-open-gpt](https://github.com/EwingYangs/awesome-open-gpt)

- [KennethanCeyer Awesome-llmops](https://github.com/KennethanCeyer/awesome-llmops)

- [KennethanCeyer awesome-llm](https://github.com/KennethanCeyer/awesome-llm)

- [tensorchord Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps)

# Contributing

Contributions are always welcome! Please read the [contribution guidelines](contributing.md) first.

How to help:

- Give a ⭐️ to increase the repository's visibility.

- Add descriptions for resources that don't have them.

- Add new resources to the list.

- Fix typos or grammatical errors.

- Share this repository with others.

# Featured

🚀 **RECOMMENDED**: [Use any LLM from the command line easily with llm](https://github.com/snwfdhmp/llm). 🚀