Turn challenges into opportunities by learning advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud tools DRM-free PDF version + access to Packt's next-gen Reader* Key Features Solve real-world business problems with hands-on examples of GenAI applications on Google Cloud - Learn repeatable design patterns for Gen AI on Google Cloud with a focus on architecture and AI ethics - Build and implement GenAI agents and workflows, such as RAG and NL2SQL, using LangChain and Vertex AI - Purchase of the print or Kindle book includes a free PDF eBook Book Description The rapid transformation and enterprise adoption of GenAI has created an urgent demand for developers to quickly build and deploy AI applications that deliver real value. Written by three distinguished Google AI engineers and LangChain contributors who have shaped Google Cloud’s integration with LangChain and implemented AI solutions for Fortune 500 companies, this book bridges the gap between concept and implementation, exploring LangChain and Google Cloud’s enterprise-ready tools for scalable AI solutions. You'll start by exploring the fundamentals of LLMs and how LangChain simplifies the development of AI workflows by connecting LLMs with external data and services. This book guides you through using essential tools like the Gemini and PaLM 2 APIs, Vertex AI, and Vertex AI Search to create sophisticated, production-ready GenAI applications. You'll also overcome the context limitations of LLMs by mastering advanced techniques like RAG and external memory layers. Through practical patterns and real-world examples, you’ll gain everything you need to harness Google Cloud’s AI ecosystem, reducing the time to market while ensuring enterprise scalability. You’ll have the expertise to build robust GenAI applications that can be tailored to solve real-world business challenges. *Email sign-up and proof of purchase required What you will learn Build enterprise-ready applications with LangChain and Google Cloud - Navigate and select the right Google Cloud generative AI tools - Apply modern design patterns for generative AI applications - Plan and execute proof-of-concepts for enterprise AI solutions - Gain hands-on experience with LangChain's and Google Cloud's AI products - Implement advanced techniques for text generation and summarization - Leverage Vertex AI Search and other tools for scalable AI solutions Who this book is for If you’re an application developer or ML engineer eager to dive into GenAI, this book is for you. Whether you're new to LangChain or Google Cloud, you'll learn how to use these tools to build scalable AI solutions. This book is ideal for developers familiar with Python and machine learning basics looking to apply their skills in GenAI. Professionals who want to explore Google Cloud's powerful suite of enterprise-grade GenAI products and their implementation will also find this book useful. Table of Contents Using LangChain with Google Cloud - Foundational Models on Google Cloud - Grounding Responses - Vector Search on Google Cloud - Ingesting Documents - Multimodality - Working with Long Context - Building Chatbots - Tools and Function Calling - Agents - Agentic Workflows - Evaluating GenAI Applications - Generative AI System Design “Generative AI on Google Cloud with LangChain is an invaluable resource for application developers and ML engineers eager to build scalable Generative AI solutions. Authored by Google engineers Leonid Kuligin, Jorge Zaldívar, and Maximilian Tschochohei, this book demonstrates how to combine the power of the LangChain framework with Google Cloud’s enterprise-ready AI models and infrastructure. Through hands-on, practical examples and clear code samples, the book guides readers in implementing modern AI workflows, such as retrieval-augmented generation (RAG) and agent-based applications. Whether you’re new to LangChain or exploring advanced GenAI architectures, this book provides an experiential learning journey that is both engaging and practical.” Manvinder Singh, VP of AI Products at Redis “This book provides a comprehensive, practical overview of LangChain, a key framework for managing LLMs. By combining theoretical background with practical instruction, it's a valuable tool for both new and experienced generative AI practitioners. A key highlight is the book's focus on addressing the challenge of hallucinations in LLMs. This book goes beyond theory to offer practical advice on chatbot development, including conversation engineering and RAG integration. I really liked Part 3, "Common Generative AI Architectures." It was super helpful in explaining why LLMs struggle with long pieces of text and gave some good ideas on how to fix it. The stuff about dealing with long context, making chatbots, and using tools and function calling was very useful for making apps better and boosting what LLMs can do. This book's an excellent guide if you want to us