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Unlocking the Secrets of Prompt Engineering

You're reading from   Unlocking the Secrets of Prompt Engineering Master the art of creative language generation to accelerate your journey from novice to pro

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781835083833
Length 316 pages
Edition 1st Edition
Concepts
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Author (1):
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Gilbert Mizrahi Gilbert Mizrahi
Author Profile Icon Gilbert Mizrahi
Gilbert Mizrahi
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Introduction to Prompt Engineering
2. Chapter 1: Understanding Prompting and Prompt Techniques FREE CHAPTER 3. Chapter 2: Generating Text with AI for Content Creation 4. Part 2:Basic Prompt Engineering Techniques
5. Chapter 3: Creating and Promoting a Podcast Using ChatGPT and Other Practical Examples 6. Chapter 4: LLMs for Creative Writing 7. Chapter 5: Unlocking Insights from Unstructured Text – AI Techniques for Text Analysis 8. Part 3: Advanced Use Cases for Different Industries
9. Chapter 6: Applications of LLMs in Education and Law 10. Chapter 7: The Rise of AI Pair Programmers – Teaming Up with Intelligent Assistants for Better Code 11. Chapter 8: AI for Chatbots 12. Chapter 9: Building Smarter Systems – Advanced LLM Integrations 13. Part 4:Ethics, Limitations, and Future Developments
14. Chapter 10: Generative AI – Emerging Issues at the Intersection of Ethics and Innovation 15. Chapter 11: Conclusion 16. Index 17. Other Books You May Enjoy

Moving beyond APIs – building custom LLM pipelines with LangChain

LangChain is an open source Python and JavaScript library for building workflows and systems using LLMs such as GPT-3.

Created by Harrison Chase, LangChain initially focused on streamlining integration with OpenAI APIs. It has since expanded to support other LLMs, including models such as Anthropic’s Claude.

The library implements techniques from the ReAct paper published in 2022. ReAct demonstrates prompting methods that allow LLMs to engage in reasoning by maintaining a chain-of-thought context. Models can also take action by leveraging tools such as internet search to gather information.

This combination, referred to as ReAct, enables LLMs to solve problems more effectively by thinking through logic and bringing in outside knowledge. LangChain codifies these techniques into developer-friendly frameworks.

LangChain supports a wide range of LLMs from various providers, including the following...

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