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Generative AI with LangChain

You're reading from   Generative AI with LangChain Build large language model (LLM) apps with Python, ChatGPT, and other LLMs

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781835083468
Length 368 pages
Edition 1st Edition
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Author (1):
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Ben Auffarth Ben Auffarth
Author Profile Icon Ben Auffarth
Ben Auffarth
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Table of Contents (13) Chapters Close

Preface 1. What Is Generative AI? 2. LangChain for LLM Apps FREE CHAPTER 3. Getting Started with LangChain 4. Building Capable Assistants 5. Building a Chatbot Like ChatGPT 6. Developing Software with Generative AI 7. LLMs for Data Science 8. Customizing LLMs and Their Output 9. Generative AI in Production 10. The Future of Generative Models 11. Other Books You May Enjoy
12. Index

Questions

Please have a look to see if you can come up with the answers to these questions from memory. I’d recommend you go back to the corresponding sections of this chapter if you are unsure about any of them:

  1. How can we summarize documents with LLMs?
  2. What is the chain of density?
  3. What are LangChain decorators and what’s the LangChain Expression Language?
  4. What is map-reduce in LangChain?
  5. How can we count the tokens we are using (and why should we)?
  6. How is instruction tuning related to function calling and tool usage?
  7. Give some examples of tools that are available in LangChain.
  8. Please define two agent paradigms.
  9. What is Streamlit and why do we want to use it?
  10. How does automated fact-checking work?
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