This repository is a curated collection of Docker projects focused on Network Attached Storage (NAS) deployments, targeting users who want to transform their NAS into a versatile productivity tool. It offers a wide range of applications across AI, development, data management, multimedia, and operations, providing deployment guides and tutorials for easy setup.

How It Works

The project functions as a comprehensive, categorized list of Docker-based applications. Each entry includes a brief description, a link to the project's repository, and a tutorial. The collection is organized into logical sections such as AI Applications, Development Tools, Data Management, Multimedia, Operations, Enterprise Collaboration, Security, IoT, and more, facilitating easy discovery and adoption of various self-hosted solutions.

Quick Start & Requirements

• Installation: No direct installation command; users select and deploy individual Docker projects using their respective Dockerfiles or Docker Compose configurations.
• Prerequisites: A NAS device or server capable of running Docker. Specific project requirements (e.g., GPU for AI, specific OS versions) will vary per application.
• Resources: Varies significantly based on the chosen applications.

Highlighted Details

• Extensive categorization covering over 10 major domains and numerous subcategories.
• Focus on AI applications, including LLM deployment, knowledge base systems, and data analysis tools.
• Emphasis on self-hosting and privacy-preserving solutions.
• Provides direct links to project repositories and deployment tutorials.

Maintenance & Community

The project is maintained by TWO-ICE and welcomes community contributions via pull requests following a specified YAML format.

Licensing & Compatibility

The repository itself is licensed under the MIT License, permitting free use and modification. Individual projects within the collection retain their original licenses, which may vary.

Limitations & Caveats

This is a curated list, not a unified deployment tool. Users are responsible for understanding and managing the individual Docker deployments and their specific dependencies and configurations. The "tutorial" links are often to external platforms like Zhihu, requiring users to navigate off-repository for setup instructions.