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Building AI Agents with LLMs, RAG, and Knowledge Graphs

You're reading from   Building AI Agents with LLMs, RAG, and Knowledge Graphs A practical guide to autonomous and modern AI agents

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Product type Paperback
Published in Jul 2025
Publisher Packt
ISBN-13 9781835087060
Length 560 pages
Edition 1st Edition
Concepts
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Authors (2):
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Salvatore Raieli Salvatore Raieli
Author Profile Icon Salvatore Raieli
Salvatore Raieli
Gabriele Iuculano Gabriele Iuculano
Author Profile Icon Gabriele Iuculano
Gabriele Iuculano
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Table of Contents (17) Chapters Close

Preface 1. Part 1: The AI Agent Engine: From Text to Large Language Models
2. Chapter 1: Analyzing Text Data with Deep Learning FREE CHAPTER 3. Chapter 2: The Transformer: The Model Behind the Modern AI Revolution 4. Chapter 3: Exploring LLMs as a Powerful AI Engine 5. Part 2: AI Agents and Retrieval of Knowledge
6. Chapter 4: Building a Web Scraping Agent with an LLM 7. Chapter 5: Extending Your Agent with RAG to Prevent Hallucinations 8. Chapter 6: Advanced RAG Techniques for Information Retrieval and Augmentation 9. Chapter 7: Creating and Connecting a Knowledge Graph to an AI Agent 10. Chapter 8: Reinforcement Learning and AI Agents 11. Part 3: Creating Sophisticated AI to Solve Complex Scenarios
12. Chapter 9: Creating Single- and Multi-Agent Systems 13. Chapter 10: Building an AI Agent Application 14. Chapter 11: The Future Ahead 15. Index 16. Other Books You May Enjoy

Understanding the abilities of single-agent and multiple-agent systems

It is important to discuss what an agent’s capabilities are, and how they can be used to accomplish tasks. Conceptually, the scenario in which our agent can act must be defined. Task-oriented deployment is the simplest scenario in which an agent assists a human in some tasks. These types of agents need to be able to solve task bases or break them down into manageable subtasks. The purpose of this agent is to understand a user’s instructions, then understand the task, decompose it into steps, plan, and execute that plan until the goal is achieved. A single agent can perform these tasks in web or real-life scenarios.

In a web scenario, an agent must be capable of performing actions on the web (and thus be connected to the internet). An LLM has the potential to automate various tasks such as online shopping, sending emails, and filling out forms. An agent devoted to these tasks must have the ability...

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