mirror of
https://github.com/The-Art-of-Hacking/h4cker.git
synced 2024-12-21 20:36:08 +00:00
79 lines
6.5 KiB
Markdown
79 lines
6.5 KiB
Markdown
# Prompt Engineering Resources
|
|
|
|
## Prompting Guide
|
|
This is a great resource for prompting LLMs:
|
|
- https://www.promptingguide.ai
|
|
|
|
## Tools and Sample Prompt Repositories
|
|
|
|
| Resource| Description | Link |
|
|
| :-------------------- | :----------: | :----------: |
|
|
| **LlamaIndex** | LlamaIndex is a project consisting of a set of data structures designed to make it easier to use large external knowledge bases with LLMs. | [[Github]](https://github.com/jerryjliu/gpt_index) |
|
|
| **Promptify** | Solve NLP Problems with LLM's & Easily generate different NLP Task prompts for popular generative models like GPT, PaLM, and more with Promptify | [[Github]](https://github.com/promptslab/Promptify) |
|
|
| **Arize-Phoenix** | Open-source tool for ML observability that runs in your notebook environment. Monitor and fine tune LLM, CV and Tabular Models. | [[Github]](https://github.com/Arize-ai/phoenix) |
|
|
| **Better Prompt** | Test suite for LLM prompts before pushing them to PROD | [[Github]](https://github.com/krrishdholakia/betterprompt) |
|
|
| **CometLLM** | Log, visualize, and evaluate your LLM prompts, prompt templates, prompt variables, metadata, and more. | [[Github]](https://github.com/comet-ml/comet-llm) |
|
|
| **Embedchain** | Framework to create ChatGPT like bots over your dataset | [[Github]](https://github.com/embedchain/embedchain) |
|
|
| **Interactive Composition Explorerx** | ICE is a Python library and trace visualizer for language model programs. | [[Github]](https://github.com/oughtinc/ice) |
|
|
| **Haystack** | Open source NLP framework to interact with your data using LLMs and Transformers. | [[Github]](https://github.com/deepset-ai/haystack) |
|
|
| **LangChainx** | Building applications with LLMs through composability | [[Github]](https://github.com/hwchase17/langchain) |
|
|
| **OpenPrompt** | An Open-Source Framework for Prompt-learning | [[Github]](https://github.com/thunlp/OpenPrompt) |
|
|
| **Prompt Engine** | This repo contains an NPM utility library for creating and maintaining prompts for Large Language Models (LLMs). | [[Github]](https://github.com/microsoft/prompt-engine) |
|
|
| **PromptInject** | PromptInject is a framework that assembles prompts in a modular fashion to provide a quantitative analysis of the robustness of LLMs to adversarial prompt attacks. | [[Github]](https://github.com/agencyenterprise/PromptInject) |
|
|
| **Prompts AI** | Advanced playground for GPT-3 | [[Github]](https://github.com/sevazhidkov/prompts-ai) |
|
|
| **Prompt Source** | PromptSource is a toolkit for creating, sharing and using natural language prompts. | [[Github]](https://github.com/bigscience-workshop/promptsource) |
|
|
| **ThoughtSource** | A framework for the science of machine thinking | [[Github]](https://github.com/OpenBioLink/ThoughtSource) |
|
|
| **PROMPTMETHEUS** | One-shot Prompt Engineering Toolkit | [[Tool]](https://promptmetheus.com) |
|
|
| **AI Config** | An Open-Source configuration based framework for building applications with LLMs | [[Github]](https://github.com/lastmile-ai/aiconfig) |
|
|
| **LastMile AI** | Notebook-like playground for interacting with LLMs across different modalities (text, speech, audio, image) | [[Tool]](https://lastmileai.dev/) |
|
|
| **XpulsAI** | Effortlessly build scalable AI Apps. AutoOps platform for AI & ML | [[Tool]](https://xpuls.ai/) |
|
|
| **Agenta** | Agenta is an open-source LLM developer platform with the tools for prompt management, evaluation, human feedback, and deployment all in one place. | [[Github]](https://github.com/agenta-ai/agenta) |
|
|
| **Promptotype** | Develop, test, and monitor your LLM { structured } tasks | [[Tool]](https://www.promptotype.io) |
|
|
|
|
## Tutorials and Videos
|
|
|
|
### Introduction to Prompt Engineering
|
|
|
|
- [Prompt Engineering 101 - Introduction and resources](https://www.linkedin.com/pulse/prompt-engineering-101-introduction-resources-amatriain)
|
|
- [Prompt Engineering 101](https://humanloop.com/blog/prompt-engineering-101)
|
|
- [Prompt Engineering Guide by SudalaiRajkumar](https://github.com/SudalaiRajkumar/Talks_Webinars/blob/master/Slides/PromptEngineering_20230208.pdf)
|
|
|
|
### Beginner's Guide to Generative Language Models
|
|
|
|
- [A beginner-friendly guide to generative language models - LaMBDA guide](https://aitestkitchen.withgoogle.com/how-lamda-works)
|
|
- [Generative AI with Cohere: Part 1 - Model Prompting](https://txt.cohere.ai/generative-ai-part-1)
|
|
|
|
### Best Practices for Prompt Engineering
|
|
|
|
- [Best practices for prompt engineering with OpenAI API](https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api)
|
|
- [How to write good prompts](https://andymatuschak.org/prompts)
|
|
|
|
### Complete Guide to 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)
|
|
|
|
### Technical Aspects of Prompt Engineering
|
|
|
|
- [3 Principles for prompt engineering with GPT-3](https://www.linkedin.com/pulse/3-principles-prompt-engineering-gpt-3-ben-whately)
|
|
- [A Generic Framework for ChatGPT Prompt Engineering](https://medium.com/@thorbjoern.heise/a-generic-framework-for-chatgpt-prompt-engineering-7097f6513a0b)
|
|
- [Methods of prompt programming](https://generative.ink/posts/methods-of-prompt-programming)
|
|
|
|
### Resources for Prompt Engineering
|
|
|
|
- [Awesome ChatGPT Prompts](https://github.com/f/awesome-chatgpt-prompts)
|
|
- [Best 100+ Stable Diffusion Prompts](https://mpost.io/best-100-stable-diffusion-prompts-the-most-beautiful-ai-text-to-image-prompts)
|
|
- [DALLE Prompt Book](https://dallery.gallery/the-dalle-2-prompt-book)
|
|
- [OpenAI Cookbook](https://github.com/openai/openai-cookbook)
|
|
- [Prompt Engineering by Microsoft](https://microsoft.github.io/prompt-engineering)
|
|
|
|
## YouTube Videos
|
|
|
|
- [Advanced ChatGPT Prompt Engineering](https://www.youtube.com/watch?v=bBiTR_1sEmI)
|
|
- [ChatGPT: 5 Prompt Engineering Secrets For Beginners](https://www.youtube.com/watch?v=2zg3V66-Fzs)
|
|
- [CMU Advanced NLP 2022: Prompting](https://youtube.com/watch?v=5ef83Wljm-M&feature=shares)
|
|
- [Prompt Engineering - A new profession ?](https://www.youtube.com/watch?v=w102J3_9Bcs&ab_channel=PatrickDebois)
|
|
- [ChatGPT Guide: 10x Your Results with Better Prompts](https://www.youtube.com/watch?v=os-JX1ZQwIA)
|
|
- [Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLP](https://youtube.com/watch?v=OsbUfL8w-mo&feature=shares)
|
|
- [Prompt Engineering 101: Autocomplete, Zero-shot, One-shot, and Few-shot prompting](https://youtube.com/watch?v=v2gD8BHOaX4&feature=shares)
|