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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

Deploying LangChain applications with Google Cloud Run

After you have experimented with and developed your LangChain application, you need to deploy it to a production service.

Google Cloud Run is one of the options to use. It’s a serverless platform that allows you to run stateless containers that are invocable via HTTP requests. Google Cloud Run takes care of load balancing your traffic and scaling your application up and down (and you can control the scaling configuration yourself). As you only pay for the resources your application consumes, it is cost-effective for many use cases. Finally, Cloud Run integrates seamlessly with other Google Cloud services, such as Cloud Storage and BigQuery, making it easy to build complex data pipelines. You can read more in the documentation: https://cloud.google.com/run/docs/overview/what-is-cloud-run.

To deploy a LangChain application on Cloud Run, you have two options. The first is to wrap it with an HTTP API (using Flask, FastAPI...

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