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Generative AI on Google Cloud with LangChain

You're reading from   Generative AI on Google Cloud with LangChain Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud

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Product type Paperback
Published in Dec 2024
Publisher Packt
ISBN-13 9781835889329
Length 306 pages
Edition 1st Edition
Concepts
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Author (1):
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Leonid Kuligin Leonid Kuligin
Author Profile Icon Leonid Kuligin
Leonid Kuligin
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Table of Contents (22) Chapters Close

Preface 1. Part 1: Intro to LangChain and Generative AI on Google Cloud
2. Chapter 1: Using LangChain with Google Cloud FREE CHAPTER 3. Chapter 2: Foundational Models on Google Cloud 4. Part 2: Hallucinations and Grounding Responses
5. Chapter 3: Grounding Responses 6. Chapter 4: Vector Search on Google Cloud 7. Chapter 5: Ingesting Documents 8. Chapter 6: Multimodality 9. Part 3: Common Generative AI Architectures
10. Chapter 7: Working with Long Context 11. Chapter 8: Building Chatbots 12. Chapter 9: Tools and Function Calling 13. Chapter 10: Agents 14. Chapter 11: Agentic Workflows 15. Part 4: Designing Generative AI Applications
16. Chapter 12: Evaluating GenAI Applications 17. Chapter 13: Generative AI System Design 18. Index 19. Other Books You May Enjoy Appendix 1: Overview of Generative AI 1. Appendix 2: Google Cloud Foundations

Architecture design framework

As with all architecture work involving multiple parties that need to align on common goals and synchronize complex work, you should adopt an architecture framework to guide you. It doesn’t matter if you go with Zachman, TOGAF, BIZBOK, or any of the other many acronyms out there. What’s important is that you and your collaborators agree on one framework and stick to it. If your organization already has a different framework in place, we strongly suggest adopting that framework. Don’t reinvent the wheel here! For this book, we propose a simplified architecture framework that starts with business process-aligned capabilities that map to technical designs:

Figure 13.1: Generative AI architecture design framework

Figure 13.1: Generative AI architecture design framework

We also recommend that you create a central repository for storing the documentation associated with your generative AI system. Don’t go overboard here: a simple doc or wiki is more than enough...

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