Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph - Image 1

£44.99

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

Name: Generative AI with LangChain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph
Brand: Packt Publishing
Price: 44.99 GBP
Availability: InStock

AI & Machine Learning

It has never been this cheap. We have no record of a lower price.

£45 today · cheaper than every other day in the last 3 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 54 days · 54 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 54 days • 1 price levels

Days at Price

Price Analysis

Most common price: £45 (54 days, 100.0%)

Price range: £45 - £45

Price levels: 1 different prices over 54 days

Description

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 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. 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. Table of Contents The Rise of Generative AI: From Language Models to Agents First Steps with LangChain Building Workflows with LangGraph Building Intelligent RAG Systems with LangChain Building Intelligent Agents Advanced Applications and Multi-Agent Systems Software Development and Data Analysis Agents Evaluation and Testing Observability and Production Deployment The Future of LLM Applications

Product Specifications

Brand: Packt Publishing
Format: paperback
ASIN: 1837022011
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 23 May 2025
Listed Since: 27 February 2025

Barcode

No barcode data available

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

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents

Building AI Intensive Python Applications: Create intelligent apps with LLMs and vector databases

Building Generative AI Agents: Using LangGraph, AutoGen, and CrewAI

Generative AI with Python and PyTorch: Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications

30 Agents Every AI Engineer Must Build: Build production-ready agent systems using proven architectures and patterns

Learning LangChain: Building AI and LLM Applications with LangChain and LangGraph

GenAI on Google Cloud: Enterprise Generative AI Systems and Agents

AI Agents and Applications: With Langchain, Langgraph and Mcp

Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based agentic AI framework with tool use, memory, and multi-agent workflows

Generative AI for Software Developers: Future-proof your career with AI-powered development and hands-on skills

Building Agentic AI Systems: Create intelligent, autonomous AI agents that can reason, plan, and adapt

LangChain for RAG Beginners: Build Your First Powerful AI GPT Agent (Agents, GPTs, and Generative AI for Beginners)

Generative AI with Python: The Developer's Guide to Pretrained Llms, Vector Databases, Retrieval-Augmented Generation, and Agentic Systems

LLMs in Enterprise: Design strategies, patterns, and best practices for large language model development

Data Science Solutions on Azure: The Rise of Generative AI and Applied AI

LLM Design Patterns: A Practical Guide to Building Robust and Efficient AI Systems

Applied Generative AI for Beginners: Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs

Building Applications with Large Language Models: Techniques, Implementation, and Applications

Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning

Generative AI and LLMs: Natural Language Processing and Generative Adversarial Networks

Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems

Generative AI From Beginner to Paid Professional, Part 2: Master Prompt Design, Gemini Multimodal in Vertex AI Studio, LangChain, Launching & Deploying Generative AI Projects

Generative AI Apps with LangChain and Python: A Project-Based Approach to Building Real-World LLM Apps

Generative AI in Action