LangChain + Local LLMs: Build Private AI Apps Using LangChain and Open Source Models

By Hosea Leviton

Do you want to build AI apps that stay private, secure, and fully in your control?

Most books on large language models focus on cloud APIs, but this one is different. LangChain + Local LLMs is for developers, engineers, and technical teams who want to create AI applications without giving up data ownership. If you care about privacy, offline deployment, and running open source models like LLaMA, Mistral, or GPT4All, this book shows you how to do it step by step.

You will learn how to move beyond basic prototypes and build real, production-ready systems powered by LangChain and local models. The content is clear, practical, and designed to help you avoid guesswork when setting up your own pipelines, tools, and security measures.

What makes this book stand out is its focus on real-world local AI development. You will see exactly how to:

Use Ollama, Hugging Face, and GPT4All to run models on your own machinesBuild private retrieval pipelines that keep sensitive data secureApply efficient fine-tuning with LoRA, QLoRA, and Hugging Face PEFT for custom use casesDeploy with LangServe while monitoring with LangSmith and open evaluation toolsProtect against unsafe inputs and prompt injection so your apps can be trusted

Instead of abstract theory, you get practical workflows and code that are up to date and ready to adapt to your environment. Whether you are building a lightweight assistant for your team, a secure enterprise deployment, or experimenting with cutting-edge open source models, this book gives you the structure and confidence to make it work.

Your data should stay yours. Your AI apps should run the way you decide. This guide shows you how.

Scroll up and get your copy today to start building private, reliable, and secure AI applications with LangChain and local LLMs.

• Format: Paperback
• Language: English
• ISBN: B0FNDNNQ4P
• ISBN13: 9798299219609
• Release Date: August 2025
• Publisher: Independently Published
• Length: 136 Pages
• Weight: 0.42 lbs.
• Dimensions: 0.3" x 6.0" x 9.0"