The Self-Hosted AI Builder's Guide: Deploy, Secure, and Operate Private LLMs, AI Agents, Voice Pipelines, and Document Intelligence with Docker (Paperback or Softback)
Language: English
Published by Vectorharbor Books 8/17/2026, 2026
- Softcover
- New

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The Self-Hosted AI Builder's Guide: Deploy, Secure, and Operate Private LLMs, AI Agents, Voice Pipelines, and Document Intelligence with Docker.
Seller Inventory # BBS-9781970482072
- Title
- The Self-Hosted AI Builder's Guide: Deploy, Secure, and Operate Private LLMs, AI Agents, Voice Pipelines, and Document Intelligence with Docker (Paperback or Softback)
- Author
- Song, Lin
- Publisher
- Vectorharbor Books 8/17/2026
- Publication year
- 2026
- Condition
- New
- Book Type
- Book
- Binding
- Paperback or Softback
- Language
- English
- ISBN 10
- 1970482079
- ISBN 13
- 9781970482072
- Item weight
- 0.6 pounds
- Series
- Book 1 of 4: Self-Hosted AI, VPNs, and Privacy
Build an AI Platform You Understand, Secure, and Control
The Self-Hosted AI Builder’s Guide is a practical, hands-on guide to deploying and operating private AI services with Docker, local models, and open source components. It shows how model serving, private chat, document intelligence, voice pipelines, MCP tools, and an optional AI agent fit together as one maintainable system.
You will learn how to:
- Run and route local LLMs with Ollama and LiteLLM, then chat privately with AnythingLLM
- Build batch and live transcription plus text-to-speech with Whisper, WhisperLive, and Kokoro
- Build RAG pipelines with Docling, embeddings, reranking, and pgvector
- Connect authenticated MCP tools and run an optional containerized goose agent
- Choose the right deployment, then secure, troubleshoot, back up, and upgrade it
Designed for developers, system administrators, homelab users, and small teams, the book emphasizes practical deployment and operation rather than AI theory. The Linux examples include CPU-only starting points and NVIDIA CUDA acceleration where supported. Local models are the default, with optional hosted providers and their data boundaries clearly explained.
Companion open source repositories provide maintained deployment files and commands. The book adds the architecture, integration guidance, security practices, and operating knowledge needed to use them as a coherent platform.
Get your copy of this book today and start building a private AI platform you can understand, secure, and operate with confidence.
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BargainBookStores
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