Prompt Engineering for Generative AI

Prompt Engineering for Generative AI is a comprehensive guide co-authored for O'Reilly, focusing on the art of prompt engineering for GPT-4, Stable Diffusion and other generative AI models. Dive deep into the world of prompt engineering and LLMs (large language models) with our book, which is your ultimate resource for mastering the techniques and methodologies in this rapidly evolving field.

Purchase the book:

• Amazon - Paperback

Installation

In order to ensure compatibility and stability, this project uses specific versions of libraries, tailored for Python version 3.9.12. Given the rapid advancements in Large Language Models (LLMs) and AI frameworks, this version locking helps maintain a consistent and error-free environment.

There is a requirements.txt file that contains all of the dependencies for the project. To install them, run the following command:

pip install -r requirements.txt

If you would prefer to use a virtual environment, you can create one with the following command:

python -m venv venv

Then, activate the virtual environment:

source venv/bin/activate

Finally, install the dependencies:

pip install -r requirements.txt

Content

Access all of the jupyter notebooks and python files within the content folder.

Table of Contents

• Chapter 1: Five Pillars of Prompting

  • Giving Direction
  • Specifying Format
  • Providing Examples
  • Evaluating Quality
  • Dividing Labor

• Chapter 2: Intro to Text Generation Models

  • What are LLMs?
  • OpenAI’s GPT-4
  • Google’s Bard
  • ... and more

• Chapter 3: Standard Practices for Text Generation

  • List Generation
  • Explain It Like I’m Five
  • ... and more

• Chapter 4: Advanced Techniques for Text Generation with Langchain

  • Introduction to Langchain
  • Prompt Templates
  • ... and more

• Chapter 5: Vector Databases

  • What are Vector Databases?
  • What are Embeddings?
  • ... and more

• Chapter 6: Autonomous Agents with Memory and Tools

  • Agents
  • Callbacks
  • ... and more

• Chapter 7: Intro to Diffusion Models for Image Generation

  • What are Diffusion models?
  • OpenAI’s DALL-E
  • ... and more

• Chapter 8: Standard Practices for Image Generation

  • Art Style Modifiers
  • Meme Unbundling
  • ... and more

• Chapter 9: Advanced Techniques for Image Generation

  • Prompt Expansion
  • Meme Mapping
  • ... and more

• Chapter 10: Building AI-powered Applications

  • Progressive Text Summarization with Langchain
  • Blog Article Generation
  • ... and more

Features

• Practical Examples: Illustrative real-world examples to showcase prompt engineering techniques.
• In-depth Analysis: Comprehensive coverage of each topic, offering foundational knowledge and advanced insights.
• Expert Guidance: Insights from leading experts in AI and prompt engineering.

Audience

Ideal for AI Researchers, Data Scientists, Software Developers, Tech Enthusiasts, and anyone interested in AI and prompt engineering.

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