host ALL your AI locally

The video begins with the creator discussing his motivation for building a personal AI server named Terry, initially for his own use to run AI models locally. He emphasizes the importance of control, privacy, and customization, which led him to integrate a GUI and chat interface into his notes application, Obsidian. The server's hardware is showcased, including a full tower EATX case, a powerful AMD Ryzen processor, 128GB of DDR5 memory, and two MSI liquid-cooled GPUs. Despite initial difficulties with Ubuntu, the system successfully runs on Pop!_OS by System76. The video promises a tutorial on setting up a similar AI server, highlighting the need for a capable computer and a GPU for optimal performance.

The video continues with a step-by-step guide on setting up the AI server using Llama.ai as the foundation. It covers the installation process for different operating systems, including a quick setup for Windows users via WSL (Windows Subsystem for Linux). The presenter also discusses updating system packages, installing Llama with a simple command, and verifying the installation by accessing the API service through a web browser. Additional steps include adding AI models to Llama, such as Llama 2 and Code Gemma, and testing the models' functionality. The video also touches on the performance of the AI server with multiple GPUs and the ability to monitor GPU usage through terminal commands.

The presenter moves on to the web UI component, selecting Open Web UI as the preferred option for interacting with Llama. He explains how to run Open Web UI inside a Docker container, which requires Docker to be installed. The video demonstrates the process of setting up Docker, deploying the Open Web UI container, and accessing the web interface. It also covers the creation of an admin account and the customization options available, such as restricting user sign-ups, whitelisting models, and creating custom model files with specific constraints. The presenter shows how to create a restricted model for his daughter to prevent cheating and ensure educational use of the AI.

The video introduces the setup process for Stable Diffusion, an AI model for image generation, which is installed using Automatic1111 with a UI. The presenter guides viewers through installing prerequisites, managing Python versions with PI ENV, and executing a script to set up the environment for Stable Diffusion. He demonstrates the image generation process and its speed, comparing it to other AI models. The video also shows how to integrate Stable Diffusion with Open Web UI, allowing users to generate images directly from the web interface based on text prompts.

The final part of the video explores additional features of the AI server. The presenter discusses the document section in Open Web UI, which allows users to upload and utilize documents within the AI's responses. He also shares his enthusiasm for Obsidian, a note-taking application, and demonstrates how to integrate a local AI chatbot into it using a community plugin. The chatbot can reference and interact with the current note, providing a dynamic and interactive note-taking experience. The video concludes with an invitation for viewers to join the creator's Discord community for further discussion and to share their own AI projects.