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AI Agents and Applications. With LangChain, LangGraph, and MCP (2026) [PDF]

Roberto Infante
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Программирование (книга #339)
Издатель
Дата публикации
17.02.2026 14:33
Добавлена в библиотеку
17.05.2026 15:59
Последнее изменение
30.11.-0001 00:00
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PDF (11769 KB)
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Roberto Infante/AI Agents and Applications. With L (12715)
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c113555a-382f-4af6-81ae-6643b64ca5d7

Аннотация

Roberto Infante | AI Agents and Applications. With LangChain, LangGraph, and MCP (2026) [PDF]

picАвтор: Roberto Infante

Издательство: Manning

ISBN: 978-1633436541

Жанр: Artificial Intelligence, Natural Language Processing, Artificial Intelligence & Semantics

Язык: Английский

 

Формат: PDF

Качество: Изначально электронное (ebook)

Иллюстрации: Цветные и черно-белые

 

Описание:

AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot.

 

This is your hands-on guide to creating real, production-ready language model solutions. With LangChain and LangGraph, you’ll orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, reason, and act. You’ll move from essential prompt engineering to advanced Retrieval Augmented Generation (RAG), and finally to deploying multi-agent systems using modern integration standards like the Model Context Protocol (MCP).

 

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Дополнительная информация:

AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot.

 

This is your hands-on guide to creating real, production-ready language model solutions. With LangChain and LangGraph, you’ll orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, reason, and act. You’ll move from essential prompt engineering to advanced Retrieval Augmented Generation (RAG), and finally to deploying multi-agent systems using modern integration standards like the Model Context Protocol (MCP).