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Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph, 2nd Edition by Ben Auffarth, Leonid Kuligin ISBN 9781837022014, 1837022011 instant download

  • SKU: EBN-236546610
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Instant download (eBook) Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph, 2nd Edition after payment.
Authors:Ben Auffarth, Leonid Kuligin
Pages:477 pages
Year:2025
Edition:2nd
Publisher:Packt Publishing
Language:english
File Size:9.35 MB
Format:pdf
ISBNS:9781837022014, 1837022011
Categories: Ebooks

Product desciption

Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph, 2nd Edition by Ben Auffarth, Leonid Kuligin ISBN 9781837022014, 1837022011 instant download

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
 
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.
 
Who this book is for
This book is for developers, researchers, and anyone looking to learn more about LangChain and LangGraph.…
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

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