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  • Book Overview & Buying Generative AI on Google Cloud with LangChain
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Generative AI on Google Cloud with LangChain

Generative AI on Google Cloud with LangChain

By : Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei
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Generative AI on Google Cloud with LangChain

Generative AI on Google Cloud with LangChain

2 (1)
By: Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei

Overview of this book

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
Table of Contents (22 chapters)
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1
Part 1: Intro to LangChain and Generative AI on Google Cloud
4
Part 2: Hallucinations and Grounding Responses
9
Part 3: Common Generative AI Architectures
15
Part 4: Designing Generative AI Applications

Summary

In this chapter, we explored essential steps to set up your Google Cloud environment for AI/ML experiments. We covered the importance of establishing your organization, creating user accounts and groups, managing permissions, and configuring billing. We also discussed the different options available for AI/ML development environments: Colab Enterprise, Vertex AI Workbench instances, and Cloud Workstations, which are the best way to get started on developing LangChain applications.

By following the guidance in this chapter, you’ll be well equipped to embark on building exciting LangChain applications in Google Cloud. Remember – the choice of environment depends on your specific needs and preferences, so carefully evaluate the options to find the best fit for your workflow.

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