Building AI Agents with LLMs, RAG, and Knowledge Graphs

Building AI Agents with LLMs, RAG, and Knowledge Graphs: A Practical Guide to Autonomous and Modern AI Agents by Salvatore Raieli and Gabriele Iuculano is a comprehensive guide for developers and AI practitioners looking to create intelligent, self-sufficient agents using cutting-edge AI technologies. The book covers integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Knowledge Graphs to design agents capable of reasoning, learning, and making context-aware decisions. Through real-world examples, hands-on code, and best practices, it equips readers to develop AI solutions that can interact naturally, process complex information, and adapt to changing environments.

Building AI Agents with LLMs, RAG, and Knowledge Graphs

Author(s): Salvatore Raieli, Gabriele Iuculano
Binding: Paperback
Paper Quality: Black White Paper
Category: Artificial Intelligence, Machine Learning, Natural Language Processing
Recommended For:
AI engineers, machine learning developers, data scientists, software architects, NLP researchers, and technology enthusiasts aiming to build advanced AI agents.

Key Points

• Integrating LLMs:
  Learn how to leverage large language models for natural language understanding and generation.

• Retrieval-Augmented Generation (RAG):
  Implement RAG techniques to enhance factual accuracy and context-awareness in AI responses.

• Knowledge Graphs:
  Utilize knowledge graphs to structure and link data, enabling deeper reasoning capabilities.

• Autonomous Agent Design:
  Explore architectures for self-governing AI agents that can make decisions without human intervention.

• Hands-on Projects:
  Step-by-step tutorials and code examples to apply concepts in real-world applications.

• Advanced Use Cases:
  Applications in chatbots, customer support, research assistants, and domain-specific AI tools.