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Building LLM Powered  Applications

You're reading from   Building LLM Powered Applications Create intelligent apps and agents with large language models

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Length 342 pages
Edition 1st Edition
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Author (1):
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Valentina Alto Valentina Alto
Author Profile Icon Valentina Alto
Valentina Alto
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Table of Contents (16) Chapters Close

Preface 1. Introduction to Large Language Models FREE CHAPTER 2. LLMs for AI-Powered Applications 3. Choosing an LLM for Your Application 4. Prompt Engineering 5. Embedding LLMs within Your Applications 6. Building Conversational Applications 7. Search and Recommendation Engines with LLMs 8. Using LLMs with Structured Data 9. Working with Code 10. Building Multimodal Applications with LLMs 11. Fine-Tuning Large Language Models 12. Responsible AI 13. Emerging Trends and Innovations 14. Other Books You May Enjoy
15. Index

Summary

In this chapter, we dove deeper into the fundamentals of LangChain, since it will be the AI orchestrator used in the upcoming chapters: we got familiar with LangChain components such as memory, agents, chains and prompt templates.We also covered how to start integrating LangChain with Hugging Face Hub and its model catalog, how to use the available LLMs and start embedding them into your code.From now on, we will see a series of concrete end-to-end use cases, starting from a Semantic Q&A Search app that we are going to develop in the next chapter.

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