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Generative AI with LangChain

You're reading from   Generative AI with LangChain Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph

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Product type Paperback
Published in May 2025
Publisher Packt
ISBN-13 9781837022014
Length 476 pages
Edition 2nd Edition
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Rise of Generative AI: From Language Models to Agents 2. First Steps with LangChain FREE CHAPTER 3. Building Workflows with LangGraph 4. Building Intelligent RAG Systems 5. Building Intelligent Agents 6. Advanced Applications and Multi-Agent Systems 7. Software Development and Data Analysis Agents 8. Evaluation and Testing 9. Production-Ready LLM Deployment and Observability 10. The Future of Generative Models: Beyond Scaling 11. Other Books You May Enjoy 12. Index Appendix

Running local models

When building LLM applications with LangChain, you need to decide where your models will run.

  • Advantages of local models:
    • Complete data control and privacy
    • No API costs or usage limits
    • No internet dependency
    • Control over model parameters and fine-tuning
  • Advantages of cloud models:
    • No hardware requirements or setup complexity
    • Access to the most powerful, state-of-the-art models
    • Elastic scaling without infrastructure management
    • Continuous model improvements without manual updates
  • When to choose local models:
    • Applications with strict data privacy requirements
    • Development and testing environments
    • Edge or offline deployment scenarios
    • Cost-sensitive applications with predictable, high-volume usage

Let’s start with one of the most developer-friendly options for running local models.

Getting started with Ollama

Ollama provides a developer-friendly way to run powerful open-source models locally. It provides a simple interface for...

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Generative AI with LangChain - Second Edition
Published in: May 2025
Publisher: Packt
ISBN-13: 9781837022014
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