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Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph
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Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph
Bridge the gap between prototype and production with robust LangGraph agent architectures.
Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph
Artigo n.º: 140384724

Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph

88% of respondents would recommend this to a friend

Artigo n.º: 140384724

STD 1405787

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O que se Destaca

Production-Ready Solutions
Creates applications ready for real-world deployment, ensuring users can efficiently build robust LLM solutions that meet industry standards.
Advanced Agent Development
Empowers users to design sophisticated agents, enhancing automation and intelligence in applications, setting them apart from basic generative AI models.
Comprehensive Python Integration
Utilizes Python alongside LangChain and LangGraph, providing a seamless experience for developers, boosting productivity through familiar programming tools and frameworks.

Detalhes do produto

Shop Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph online at a best price in São Tomé and Príncipe. 1837022011
Publisher Packt Publishing
Publication date May 23, 2025
Edition 2nd ed.
Language English
Print length 476 pages
ISBN-10 1837022011
ISBN-13 978-1837022014
Item Weight 1.82 pounds (830 grams)
Dimensions 7.5 x 1.09 x 9.25 inches (19.1 x 2.8 x 23.5 cm)

Quem Deverá Comprar?

Suitable For
  • Developers

    Ideal for software developers looking to create robust LLM applications using Python and LangChain efficiently.

  • AI Researchers

    Beneficial for researchers exploring advanced AI concepts and wishing to implement them in practical applications.

  • Data Scientists

    Useful for data scientists seeking to integrate generative AI models into data analysis and decision-making processes.

Not Suitable For
  • Beginners

    Not suitable for beginners without prior programming knowledge, as it assumes familiarity with Python and AI concepts.

DESCRIÇÃO DO PRODUTO

Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph

Tem alguma Dúvida? Converse connosco

Perguntas e respostas do cliente

  • Pergunta: What is Generative AI with LangChain?

    Resposta: Generative AI with LangChain focuses on using advanced AI techniques to create language models that can generate human-like text. LangChain provides a framework for building, deploying, and running these NLP applications seamlessly. By leveraging Python and integrating with tools like LangGraph, developers can create production-ready applications that can understand context and generate responses efficiently. This is especially beneficial in chatbots, content generation, and advanced language understanding applications.
  • Pergunta: Who is this book suitable for?

    Resposta: This book is ideal for software developers, data scientists, and AI enthusiasts looking to enhance their understanding of generative models and their applications. It offers practical insights that cater to both beginners and those with prior knowledge in AI and Python programming. Whether you're looking to create AI-driven applications or just curious about the technology, this resource will equip you with the necessary skills and understanding to get started.
  • Pergunta: What topics are covered in the 2nd edition?

    Resposta: The 2nd edition of this book delves deeper into generative AI principles, best practices for building language models, and advanced techniques within LangChain and LangGraph. Key topics include the architecture of LLM applications, real-world case studies, and hands-on coding examples. Each chapter is designed to build on the last, providing a comprehensive educational pathway for effectively integrating AI into projects.
  • Pergunta: How can I apply what I learn from this book?

    Resposta: Readers will find numerous practical applications for the concepts described in the book. For instance, you can create advanced chatbots that provide customer support, automate content creation for blogs, or develop tools for data extraction. The hands-on examples guide you through building applications from scratch, providing a solid foundation to innovate and experiment further in various domains such as ecommerce, education, and personal assistants.
  • Pergunta: What programming skills do I need to understand the content?

    Resposta: A basic understanding of Python programming is essential to fully grasp the content of this book. Familiarity with concepts such as functions, modules, and data structures will be beneficial. While the book provides explanations and examples, having prior coding experience will enable you to replicate and modify the projects outlined, leading to a more enriching learning experience and allowing for greater creativity in your applications.
  • Pergunta: Is this book appropriate for self-study?

    Resposta: Absolutely, this book is designed for self-paced learning. It includes clear explanations, practical examples, and structured projects that guide readers through the complexities of generative AI. Whether you are a self-taught programmer or a student honing your skills, the content is formatted to facilitate independent study while challenging you to apply your knowledge practically.
  • Pergunta: Are there any prerequisites before starting the book?

    Resposta: While there are no strict prerequisites, having some background knowledge in machine learning concepts can enhance comprehension. Familiarity with general programming and basic library usage in Python will also set you up for success. By understanding the fundamentals, you'll be able to follow along with the more complex applications and examples provided throughout the book.
  • Pergunta: Can this book help in developing AI-driven applications?

    Resposta: Yes, this book is a valuable resource for developing AI-driven applications. It covers the framework and techniques needed to build sophisticated language model applications, whether for customer interaction or data analysis. By the end, you’ll be equipped with the knowledge to create AI solutions that can effectively interact and adapt based on user input, leading to enhanced user experiences.
  • Pergunta: How does LangChain integrate with AI technologies?

    Resposta: LangChain acts as a robust framework that integrates various AI technologies to allow for the seamless development of language models. It streamlines processes such as data handling, model management, and deployment. By utilizing its features, developers can efficiently build applications that leverage AI capabilities, enabling smoother interactions and better language understanding in different applications across industries.
  • Pergunta: Where can I buy Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph 2nd ed. Edition in São Tomé and Príncipe?

    Resposta: You can purchase Generative AI with LangChain on Ubuy. Ubuy offers various options for buying books, ensuring a smooth experience to acquire this valuable resource in São Tomé and Príncipe. Simply visit their website, search for the title, and explore the available purchasing choices tailored for your needs.

Intelligence & Semantics Editorial Review

**** "Generative AI with LangChain" stands out as a comprehensive and accessible guide for both novice and intermediate developers looking to harness the capabilities of LangChain and LangGraph for building production-ready LLM applications. The book is lauded for its clear, practical explanations that allow even those without a deep background in Python or AI to grasp complex concepts easily. Readers appreciate the hands-on labs, which encourage immediate application of the information presented, making the learning process both engaging and effective. The structure of the book is notably well-organized, guiding users from basic principles to advanced topics like multi-agent systems and robust, scalable application development. Feedback indicates that the book goes beyond mere documentation, providing rich insights into real-world application, testing strategies, and characterizing various LLM models, all while addressing potential limitations and challenges. Particularly commendable is the book's focus on real-world scenarios, helping readers not just to build prototypes, but to ensure these prototypes can function effectively in practical situations. The integration of relevant examples helps demystify complex workflows and encourages collaboration among different agents, fostering deeper understanding and skills applicable in real-world projects. Overall, "Generative AI with LangChain" is recommended as an essential resource for anyone interested in diving into the world of AI application development, especially for those looking to transition from theoretical knowledge to practical implementation using cutting-edge tools. **

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Prós

  • Accessible for beginners and non-experts in Python.
  • Clear, practical explanations with hands-on labs.
  • Well-structured and comprehensive coverage of topics.
  • Useful real-world applications and case studies.
  • Strong focus on building reliable, production-ready systems.
  • Enhance understanding of multi-agent systems and advanced frameworks.

Contras

  • Potential concerns regarding the longevity of the provided code support due to the fast-evolving nature of AI technologies.

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STD 1405787

Encomende já e receba por volta de Sexta-Feira, Outubro 09

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Recursos e benefícios

  • Ideal for Python developers focused on building GenAI applications.
  • Covers transition from prototypes to production for AI systems.
  • Details enterprise-grade practices for testing, observability, and monitoring.
  • Explores design patterns for multi-agent systems and complex tasks.
  • Includes practical implementations and updated information on modern AI practices.
  • Guides development of secure and compliant AI systems tailored for enterprise environments.

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