Table of Contents

• Front Cover
• Preface
• Table of Contents
• Chapter 1: A New Paradigm
  • Who this book is for
  • Taking the world by storm
  • New software architectures for a new world
  • Using OpenAI
  • In this book
  • Summary
• Chapter 2: Large Language Models
  • Large language models
  • OpenAI models
  • Tokens
  • API responses
  • API parameters
  • Summary
• Chapter 3: Prompt Engineering
  • Prompt design & tuning
  • Prompt templates
  • Prompt selection
  • Prompt chaining
  • Summary
• Chapter 4: Learning and Tuning
  • Zero-shot learning
  • One-shot learning
  • Few-shot learning
  • Fine-tuning
  • Summary
• Chapter 5: Memory and Embeddings
  • A simple memory
  • Key-value memory
  • Embeddings
  • Vector databases
  • Simulating human memory
  • Summary
• Chapter 6: Interacting with External Systems
  • A function calling mechanism
  • OpenAI functions
  • Non-native functions
  • Function libraries
  • Summary
• Chapter 7: Planning
  • Multiple step plans
  • Auto-generated plans
  • Complex steps
  • Adjusting plans
  • Summary
• Chapter 8: Safety and Security
  • Hallucinations
  • Explainability
  • Adversarial attacks
  • Responsible AI
  • Summary
• Chapter 9: Frameworks
  • Common building blocks
  • LangChain
  • Semantic Kernel
  • Other libraries
  • Summary
• Chapter 10: Closing Thoughts
  • While writing this book
  • Multimodal models
  • GPT-4
  • Future direction
  • Summary
• Appendix A: LLM Utilities
• Appendix B: Pod Racing Dataset