This project automates the setup of a fresh Ubuntu LTS Server, streamlining the installation of AI tools like OpenClaw, Ollama, and CUDA. Its interactive menu simplifies the configuration process, ensuring a ready-to-use environment for developers. Tailored for efficiency, it's designed to handle everything from driver installation to model optimization without complicated setups.
The Ubuntu-AI-Tools-Install project provides an automated script designed to quickly set up an Ubuntu LTS Server environment optimized for AI and machine learning applications. This comprehensive script facilitates the installation of essential packages, including Nvidia GPU drivers, CUDA, various developer tools, and powerful local model management systems like Ollama and Llama.cpp. The goal is to create a streamlined and efficient setup experience for developers looking to harness the capabilities of local AI models.
To initiate the setup process, a simple command is provided for direct execution:
bash -c "$(curl -fsSL https://raw.githubusercontent.com/chsbusch-dot/ubuntu-prep/main/ubuntu-prep-setup.sh)"
Users can easily navigate through an interactive menu that presents various options:
--- Ubuntu Prep Script Menu ---
Hardware: NVIDIA GPU/vGPU Detected
Target User: chris (/home/chris)
Use numbers [1-16] to toggle an option. Press 'a' to select all.
Press 'i' to install selected, or 'q' to quit.
---------------------------------
[x] 1. Update System Packages (apt update && upgrade) (Required)
[ ] 2. Install Oh My Zsh & Dev Tools (git, tmux, micro)
[ ] 3. Install Python Environment
[ ] 4. Install Docker and Docker Compose
[ ] 5. Install NVM, Node.js & NPM
[ ] 6. Install Homebrew
[ ] 7. Install Google Gemini CLI
[ ] 8. Install NVIDIA vGPU Driver
[ ] 9. Install btop (System Monitor)
[ ] 10. Install nvtop (GPU Monitor)
[ ] 11. Install CUDA
[✓] 12. Install gcc compiler
[ ] 13. Install NVIDIA Container Toolkit
[ ] 14. Install cuDNN
[ ] 15. Install Local LLM Support (Ollama, llama.cpp, Open-WebUI, LibreChat)
[ ] 16. Install OpenClaw
This project equips developers to run advanced machine learning applications locally, offering integration with cutting-edge tools such as Google Gemini CLI and OpenClaw for efficient model management and deployment. With ongoing updates and forthcoming enhancements planned, it stands as a significant resource for anyone engaging with AI on the Ubuntu platform.
Users are advised to enhance security measures on their installations, especially when deploying on VPS or open network environments. The script provides initial configurations, but additional hardening is recommended for production use.
For more information and further details on potential future features, users are encouraged to check the repository's documentation.
No comments yet.
Sign in to be the first to comment.