Building Ai Agents With Llms Rag And Knowledge Graphs

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Building Ai Agents With Llms Rag And Knowledge Graphs

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Author : Salvatore Raieli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-07-11

Building Ai Agents With Llms Rag And Knowledge Graphs written by Salvatore Raieli and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.

Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomously Key Features Implement RAG and knowledge graphs for advanced problem-solving Leverage innovative approaches like LangChain to create real-world intelligent systems Integrate large language models, graph databases, and tool use for next-gen AI solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis AI agents book addresses the challenge of building AI that not only generates text but also grounds its responses in real data and takes action. Authored by AI specialists with deep expertise in drug discovery and systems optimization, this guide empowers you to leverage retrieval-augmented generation (RAG), knowledge graphs, and agent-based architectures to engineer truly intelligent behavior. By combining large language models (LLMs) with up-to-date information retrieval and structured knowledge, you'll create AI agents capable of deeper reasoning and more reliable problem-solving. Inside, you'll find a practical roadmap from concept to implementation. You’ll discover how to connect language models with external data via RAG pipelines for increasing factual accuracy and incorporate knowledge graphs for context-rich reasoning. The chapters will help you build and orchestrate autonomous agents that combine planning, tool use, and knowledge retrieval to achieve complex goals. Concrete Python examples built on popular libraries, along with real-world case studies, reinforce each concept and show you how these techniques come together. By the end of this book, you’ll be well-equipped to build intelligent AI agents that reason, retrieve, and interact dynamically, empowering you to deploy powerful AI solutions across industries.What you will learn Learn how LLMs work, their structure, uses, and limits, and design RAG pipelines to link them to external data Build and query knowledge graphs for structured context and factual grounding Develop AI agents that plan, reason, and use tools to complete tasks Integrate LLMs with external APIs and databases to incorporate live data Apply techniques to minimize hallucinations and ensure accurate outputs Orchestrate multiple agents to solve complex, multi-step problems Optimize prompts, memory, and context handling for long-running tasks Deploy and monitor AI agents in production environments Who this book is for If you are a data scientist or researcher who wants to learn how to create and deploy an AI agent to solve limitless tasks, this book is for you. To get the most out of this book, you should have basic knowledge of Python and Gen AI. This book is also excellent for experienced data scientists who want to explore state-of-the-art developments in LLM and LLM-based applications.

Generative Ai With Langchain

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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-23

Generative Ai With Langchain written by Ben Auffarth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Computers categories.

Go beyond foundational LangChain documentation with detailed coverage of LangGraph interfaces, design patterns for building AI agents, and scalable architectures used in production—ideal for Python developers building GenAI applications Key Features Bridge the gap between prototype and production with robust LangGraph agent architectures Apply enterprise-grade practices for testing, observability, and monitoring Build specialized agents for software development and data analysis Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis second edition tackles the biggest challenge facing companies in AI today: moving from prototypes to production. Fully updated to reflect the latest developments in the LangChain ecosystem, it captures how modern AI systems are developed, deployed, and scaled in enterprise environments. This edition places a strong focus on multi-agent architectures, robust LangGraph workflows, and advanced retrieval-augmented generation (RAG) pipelines. You'll explore design patterns for building agentic systems, with practical implementations of multi-agent setups for complex tasks. The book guides you through reasoning techniques such as Tree-of -Thoughts, structured generation, and agent handoffs—complete with error handling examples. Expanded chapters on testing, evaluation, and deployment address the demands of modern LLM applications, showing you how to design secure, compliant AI systems with built-in safeguards and responsible development principles. This edition also expands RAG coverage with guidance on hybrid search, re-ranking, and fact-checking pipelines to enhance output accuracy. Whether you're extending existing workflows or architecting multi-agent systems from scratch, this book provides the technical depth and practical instruction needed to design LLM applications ready for success in production environments.What you will learn Design and implement multi-agent systems using LangGraph Implement testing strategies that identify issues before deployment Deploy observability and monitoring solutions for production environments Build agentic RAG systems with re-ranking capabilities Architect scalable, production-ready AI agents using LangGraph and MCP Work with the latest LLMs and providers like Google Gemini, Anthropic, Mistral, DeepSeek, and OpenAI's o3-mini Design secure, compliant AI systems aligned with modern ethical practices Who this book is for This book is for developers, researchers, and anyone looking to learn more about LangChain and LangGraph. With a strong emphasis on enterprise deployment patterns, it’s especially valuable for teams implementing LLM solutions at scale. While the first edition focused on individual developers, this updated edition expands its reach to support engineering teams and decision-makers working on enterprise-scale LLM strategies. A basic understanding of Python is required, and familiarity with machine learning will help you get the most out of this book.

Unlocking Data With Generative Ai And Rag

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Author : Keith Bourne
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-27

Unlocking Data With Generative Ai And Rag written by Keith Bourne and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-27 with Computers categories.

Leverage cutting-edge generative AI techniques such as RAG to realize the potential of your data and drive innovation as well as gain strategic advantage Key Features Optimize data retrieval and generation using vector databases Boost decision-making and automate workflows with AI agents Overcome common challenges in implementing real-world RAG systems Purchase of the print or Kindle book includes a free PDF eBook Book Description Generative AI is helping organizations tap into their data in new ways, with retrieval-augmented generation (RAG) combining the strengths of large language models (LLMs) with internal data for more intelligent and relevant AI applications. The author harnesses his decade of ML experience in this book to equip you with the strategic insights and technical expertise needed when using RAG to drive transformative outcomes. The book explores RAG’s role in enhancing organizational operations by blending theoretical foundations with practical techniques. You’ll work with detailed coding examples using tools such as LangChain and Chroma’s vector database to gain hands-on experience in integrating RAG into AI systems. The chapters contain real-world case studies and sample applications that highlight RAG’s diverse use cases, from search engines to chatbots. You’ll learn proven methods for managing vector databases, optimizing data retrieval, effective prompt engineering, and quantitatively evaluating performance. The book also takes you through advanced integrations of RAG with cutting-edge AI agents and emerging non-LLM technologies. By the end of this book, you’ll be able to successfully deploy RAG in business settings, address common challenges, and push the boundaries of what’s possible with this revolutionary AI technique. What you will learn Understand RAG principles and their significance in generative AI Integrate LLMs with internal data for enhanced operations Master vectorization, vector databases, and vector search techniques Develop skills in prompt engineering specific to RAG and design for precise AI responses Familiarize yourself with AI agents' roles in facilitating sophisticated RAG applications Overcome scalability, data quality, and integration issues Discover strategies for optimizing data retrieval and AI interpretability Who this book is for This book is for AI researchers, data scientists, software developers, and business analysts looking to leverage RAG and generative AI to enhance data retrieval, improve AI accuracy, and drive innovation. It is particularly suited for anyone with a foundational understanding of AI who seeks practical, hands-on learning. The book offers real-world coding examples and strategies for implementing RAG effectively, making it accessible to both technical and non-technical audiences. A basic understanding of Python and Jupyter Notebooks is required.

Langchain For Life Sciences And Healthcare

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Author : Ivan Reznikov
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-07-21

Langchain For Life Sciences And Healthcare written by Ivan Reznikov and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-21 with Computers categories.

Feeling overwhelmed by the volume of data in your research? Sifting through massive amounts of data to find useful insights is becoming increasingly difficult in drug discovery, genetics, and healthcare. Enter the era of generative AI with LangChain, whose groundbreaking tools are changing the way life scientists and researchers operate. In this groundbreaking book, Dr. Ivan Reznikov teaches you to harness the power of AI to elevate your research capabilities. Divided into two parts, the first is essential for any specialist, covering the transition from traditional statistics to generative AI, the fundamentals of large language models, and the practical uses of LangChain. The second part is designed for life science professionals who want to create AI applications for biology, chemistry, drug development, and more. By the end, you will: Learn how to easily create and integrate LangChain applications into research Discover how to substantially accelerate your experimental and data analysis operations Explore cutting-edge AI solutions designed to address complex research problems Gain the skills and knowledge to advance your career in AI-enhanced life sciences

Generative Ai For Cloud Solutions

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Author : Paul Singh
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-22

Generative Ai For Cloud Solutions written by Paul Singh and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-22 with Computers categories.

Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI Key Features Gain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloud Understand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AI Peek into the future to explore emerging trends like multimodal AI and autonomous agents Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms. This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements. By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.What you will learn Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together Understand how we started applying NLP to concepts like transformers Grasp the process of fine-tuning and developing apps based on RAG Explore effective prompt engineering strategies Acquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIs Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI Who this book is for This artificial intelligence book is for aspiring cloud architects, data analysts, cloud developers, data scientists, AI researchers, technical business leaders, and technology evangelists looking to understanding the interplay between GenAI and cloud computing. Some chapters provide a broad overview of GenAI, which are suitable for readers with basic to no prior AI experience, aspiring to harness AI's potential. Other chapters delve into technical concepts that require intermediate data and AI skills. A basic understanding of a cloud ecosystem is required to get the most out of this book.

Graph Algorithms For Data Science

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Author : Tomaž Bratanic
language : en
Publisher: Simon and Schuster
Release Date : 2024-02-27

Graph Algorithms For Data Science written by Tomaž Bratanic and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-27 with Computers categories.

Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.

Chatbots And Human Centered Ai

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Author : Asbjørn Følstad
language : en
Publisher: Springer Nature
Release Date : 2025-04-03

Chatbots And Human Centered Ai written by Asbjørn Følstad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-03 with Computers categories.

This book constitutes the refereed proceedings of the 8th International Workshop on Chatbots and Human-Centered AI, CONVERSATIONS 2024, held in Thessaloniki, Greece, during December 4–5, 2024. The 12 full papers and 3 short papers were carefully reviewed and selected from 35 submissions. They were organized in topical sections as follows: Understanding and Designing for Human-AI Interactions; Human-Centred AI in Education and Social Support; Conversational AI for Citizens and Customers.

Urban Human Mobility

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Author : Xiao Huang
language : en
Publisher: CRC Press
Release Date : 2025-07-03

Urban Human Mobility written by Xiao Huang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-03 with Science categories.

This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners. Features Provides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applications Covers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and tools Discusses cutting-edge technologies involved in mobility data analytics Addresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the field Offers future directions of human mobility research under the big data and artificial intelligence (AI) revolution Urban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.

Periodic Table The Past Present And Future

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Author : Geoff Rayner-canham
language : en
Publisher: World Scientific
Release Date : 2020-08-04

Periodic Table The Past Present And Future written by Geoff Rayner-canham and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with Science categories.

'This is an an absolutely wonderful book that is full of gems about the elements and the periodic table … All in all, the book is highly recommended to philosophers of chemistry. As philosophers we have a natural tendency to concentrate on generalities and not to get too involved in the specifics and the details. Above all else, this new book reminds us that such an approach needs to be tempered by a detailed knowledge of the exceptions and features that go against the simplified generalities which we so cherish.' [Read Full Review]Eric ScerriFoundations of Chemistry'Many questions are dealt with in a clearly written way in this stimulating and innovative book. The reader will quickly become interested in the subject and will be taken on tour through this Periodic Table in a very readable way, both for students and teachers … The number of illustrations is good, and clear. This book is indeed unique and quite thought-provoking … This book is highly recommended for students, teachers, researchers and not only chemists! Geologists, biochemist and also physicists will find it very interesting to read.' [Read Full Review]Chemistry InternationalThat fossilized chart on every classroom wall — isn't that The Periodic Table? Isn't that what Mendeléev devised about a century ago? No and No. There are many ways of organizing the chemical elements, some of which are thought-provoking, and which reveal philosophical challenges. Where does hydrogen 'belong'? Can an element occupy more than one location on the chart? Which are the Group 3 elements? Is aluminum in the wrong place? Why is silver(I) like thallium(I)? Why is vanadium like molybdenum? Why does gold form an auride ion like a halide ion? Does an atom 'know' if it is a non-metal or metal? Which elements are the 'metalloids'? Which are the triels? So many questions! In this stimulating and innovative book, the Reader will be taken on a voyage from the past to the present to the future of the Periodic Table. This book is unique. This book is readable. This book is thought-provoking. It is a multi-dimensional examination of patterns and trends among the chemical elements. Every reader will discover something about the chemical elements which will provoke thought and a new appreciation as to how the elements relate together.

Spring Data

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Author : Mark Pollack
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-10-12

Spring Data written by Mark Pollack and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-12 with Computers categories.

You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop. Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers. Learn about Spring’s template helper classes to simplify the use ofdatabase-specific functionality Explore Spring Data’s repository abstraction and advanced query functionality Use Spring Data with Redis (key/value store), HBase(column-family), MongoDB (document database), and Neo4j (graph database) Discover the GemFire distributed data grid solution Export Spring Data JPA-managed entities to the Web as RESTful web services Simplify the development of HBase applications, using a lightweight object-mapping framework Build example big-data pipelines with Spring Batch and Spring Integration