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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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Toc

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

Index

Symbols

.env file

secrets, storing 114, 115

A

agent 109, 110

initializing 245

agentic approach 154

versus hard-coded approach 256

versus out-of-the-box approach 256

agent types

conversational 111

OpenAI Functions 111

plan-and-execute agents 111

ReAct document store 111

self ask with search 111

structured input ReAct 111

AI2 Reasoning Challenge (ARC) 19, 51

AI orchestrators

components 31-34

framework, selecting 38, 39

Haystack 35, 36

LangChain 34, 35

Semantic Kernel 36-38

Amazon Web Services (AWS) RDS 173

area under the ROC curve (AUC) 273

artificial general intelligence (AGI) 226

artificial intelligence (AI) 226

artificial neural networks (ANNs) 4

artificial neuron 4

ASCII characters 203

assistant models 52

versus base models 52

attention mechanisms 11

autoencoders 145

AutoGen 296, 297

Automated Multi Agent Chat

reference link 297

...
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