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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

Introduction to conversational design

Conversational design predates the new concepts introduced by Gen AI and has been around for many years to make the chatbots that have replaced customer service representatives across industries perform better. It involves crafting and refining the conversation flow, prompts, and responses to create natural, engaging, and goal-oriented interactions between the chatbot and its users. The key challenge of conversational design has been to predict the behavior (intent) of human users and model possible responses in advance to give the perception of an intelligent conversation partner. With Gen AI, this step has gotten a lot easier, as LLMs are able to effectively identify intents and craft suitable responses. LangChain as a framework has expanded on these capabilities by giving engineers the ability to craft sophisticated systems with developer-friendly instruction and state handling.

There are two different types of chatbots:

  • Intent-based...
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