فهرست مطالب

• Copyright
• Table of Contents
• Preface
• Part I. Foundations
• Chapter 1. Introduction to Prompt Engineering
• LLMs Are Magic
• Language Models: How Did We Get Here?
• Prompt Engineering
• Conclusion
• Chapter 2. Understanding LLMs
• What Are LLMs?
• How LLMs See the World
• One Token at a Time
• Temperature and Probabilities
• The Transformer Architecture
• Conclusion
• Chapter 3. Moving to Chat
• Reinforcement Learning from Human Feedback
• Moving from Instruct to Chat
• The Changing API
• Prompt Engineering as Playwriting
• Conclusion
• Chapter 4. Designing LLM Applications
• The Anatomy of the Loop
• Zooming In to the Feedforward Pass
• Evaluating LLM Application Quality
• Conclusion
• Part II. Core Techniques
• Chapter 5. Prompt Content
• Sources of Content
• Static Content
• Dynamic Content
• Conclusion
• Chapter 6. Assembling the Prompt
• Anatomy of the Ideal Prompt
• What Kind of Document?
• Formatting Snippets
• Elastic Snippets
• Relationships Among Prompt Elements
• Putting It All Together
• Conclusion
• Chapter 7. Taming the Model
• Anatomy of the Ideal Completion
• Beyond the Text: Logprobs
• Choosing the Model
• Conclusion
• Part III. An Expert of the Craft
• Chapter 8. Conversational Agency
• Tool Usage
• Reasoning
• Context for Task-Based Interactions
• Building a Conversational Agent
• Conclusion
• Chapter 9. LLM Workflows
• Would a Conversational Agent Suffice?
• Basic LLM Workflows
• Advanced LLM Workflows
• Conclusion
• Chapter 10. Evaluating LLM Applications
• What Are We Even Testing?
• Offline Evaluation
• Online Evaluation
• Conclusion
• Chapter 11. Looking Ahead
• Multimodality
• Conclusion
• Index
• About the Authors
• Colophon