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Local AI with VS Code: Mastering Private, Offline LLM Development: Run Open-Source Models Securely with Ollama, Continue, Llama.cpp, and Zero-Cloud Extensions - Keep Your

Local AI with VS Code: Mastering Private, Offline LLM Development: Run Open-Source Models Securely with Ollama, Continue, Llama.cpp, and Zero-Cloud Extensions - Keep Your

          
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About the Book

Local AI with VS Code is the definitive guide for developers, engineers, data scientists, and privacy-conscious creators who want to build intelligent applications without sending a single byte to the cloud. Written by Liora Quillan, this hands-on book shows you how to turn VS Code into a powerful, offline AI development environment using open-source LLMs, privacy-first extensions, and fully local inference engines such as Ollama, Continue, Llama.cpp, GPT4All, and more.
With cloud AI platforms becoming increasingly expensive and restrictive, developers are turning to a new generation of local, open-source large language models for coding, automation, debugging, RAG pipelines, and intelligent agent workflows. This book teaches you exactly how to run these models efficiently, privately, and securely - right on your laptop or workstation.

You'll learn step-by-step how to:

  • Install and optimize VS Code for local AI workflows
  • Run advanced models through Ollama, Continue, and Llama.cpp
  • Build offline copilots, code assistants, and autonomous developer agents
  • Implement local RAG, embeddings, vector search, and document Q&A
  • Use zero-cloud extensions to keep your data 100% private
  • Create AI-powered automation with Python, Node.js, and shell tools
  • Develop security-hardened, air-gapped AI pipelines for enterprise or regulated environments
  • Optimize performance on CPU-only systems (no GPU required)
Whether you're a software engineer, indie hacker, DevOps engineer, ML practitioner, or cybersecurity professional, this book gives you the blueprint to develop private, offline, high-performance AI systems using the tools you already love. No subscriptions. No APIs. No cloud. Your machine, your models, your data.


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Product Details
  • ISBN-13: 9798277894347
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 156
  • Spine Width: 8 mm
  • Weight: 285 gr
  • ISBN-10: 8277894341
  • Publisher Date: 08 Dec 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Mastering Private, Offline LLM Development: Run Open-Source Models Securely with Ollama, Continue, Llama.cpp, and Zero-Cloud Extensions - Keep Your
  • Width: 178 mm


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