Описание
Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph , Second Edition production-ready applications Python programming
Артикул Маркета
6036788474
Внешний вид товаров и/или упаковки может быть изменён изготовителем и отличаться от изображенных на Яндекс Маркете.
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8 809 ₽
–38%
–200 ₽
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Заказ от 1500₽
Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph , Second Edition production-ready applications Python programming
Пэй
8 809 ₽
–38%
Доставка Маркета
14 – 19 окт, по клику 0 ₽
Москва
14 – 19 окт, пункт выдачи 0 ₽
Москва
14 дней на возврат
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Описание
О книге Введение в книгу : Key benefits Bridge the gap between prototype and production with robust LangGraph agent architectures Apply enterprise-grade practices for testing, observability, and monitoring BuЧитать далее Описание Введение в книгу : Key benefits 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 Description This 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.
Характеристики
Артикул Маркета
6036788474
Внешний вид товаров и/или упаковки может быть изменён изготовителем и отличаться от изображенных на Яндекс Маркете.Возрастное ограничение 18+
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