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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 (Self-Hosted AI, VPNs, and Privacy) - Softcover
Book 1 of 4: Self-Hosted AI, VPNs, and Privacy
Synopsis
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.
"synopsis" may belong to another edition of this title.
About the Author
Lin Song, PhD, is a software engineer, author, and open source developer. He creates practical tools for self-hosted AI, online privacy, and secure infrastructure, including the Self-Hosted AI Stack and Setup IPsec VPN projects. Since 2014, his VPN projects have collectively earned 40,000 GitHub stars, while their Docker images have been pulled more than 30 million times, helping millions of users build and manage their own VPN servers. He is the author of The Self-Hosted AI Builder's Guide, Privacy Tools in the Age of AI, and practical guides to building IPsec, OpenVPN, and WireGuard servers. His work combines maintained open source projects with clear, practical guidance for building and operating systems you control.
"About this title" may belong to another edition of this title.
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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 (Paperback or Softback)
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Vectorharbor Books 8/17/2026, 2026
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Paperback. Condition: new. Paperback. Build an AI Platform You Understand, Secure, and ControlThe 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 AnythingLLMBuild batch and live transcription plus text-to-speech with Whisper, WhisperLive, and KokoroBuild RAG pipelines with Docling, embeddings, reranking, and pgvectorConnect authenticated MCP tools and run an optional containerized goose agentChoose the right deployment, then secure, troubleshoot, back up, and upgrade itDesigned 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781970482072
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build an AI Platform You Understand, Secure, and ControlThe 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 AnythingLLMBuild batch and live transcription plus text-to-speech with Whisper, WhisperLive, and KokoroBuild RAG pipelines with Docling, embeddings, reranking, and pgvectorConnect authenticated MCP tools and run an optional containerized goose agentChoose the right deployment, then secure, troubleshoot, back up, and upgrade itDesigned 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. Seller Inventory # 9781970482072
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Paperback. Condition: new. Paperback. Build an AI Platform You Understand, Secure, and ControlThe 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 AnythingLLMBuild batch and live transcription plus text-to-speech with Whisper, WhisperLive, and KokoroBuild RAG pipelines with Docling, embeddings, reranking, and pgvectorConnect authenticated MCP tools and run an optional containerized goose agentChoose the right deployment, then secure, troubleshoot, back up, and upgrade itDesigned 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781970482072
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Paperback. Condition: new. Paperback. Build an AI Platform You Understand, Secure, and ControlThe 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 AnythingLLMBuild batch and live transcription plus text-to-speech with Whisper, WhisperLive, and KokoroBuild RAG pipelines with Docling, embeddings, reranking, and pgvectorConnect authenticated MCP tools and run an optional containerized goose agentChoose the right deployment, then secure, troubleshoot, back up, and upgrade itDesigned 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781970482072
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Taschenbuch. Condition: Neu. The Self-Hosted AI Builder's Guide | Deploy, Secure, and Operate Private LLMs, AI Agents, Voice Pipelines, and Document Intelligence with Docker | Lin Song | Taschenbuch | Self-Hosted AI, VPNs, and Privacy | Englisch | 2026 | VectorHarbor Books | EAN 9781970482072 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 136358210
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