DeepExtension Installation Guide on macOS

Key Takeaways

Let's install deep extension on Mac OS platform as an installation example. Before you begin, make sure Docker engine is installed. Next, clone the deep extension repository from GitHub. Navigate into the project directory. Then start the application using the run_compose.cript. Ensure all required Docker images are pulled and container start without error. Once running, open your browser to access the web UI. By default, the web UI uses port 88. During the first launch, a root user is created automatically. The initial password is saved at admin password/admin password.txt. Congratulations. In next section, I am going to show you how to set up the training environment on Mac OS. Step one, prepare the MLX code. First, download the entire MLX repository from GitHub. This has been tested successfully with version v0.24.1. 24.1. Second, copy the MLX_LM subdirectory from the MLXLM project into training directory. Third, run the preparation script to apply the required MLX code modifications. These modifications ensure compatibility with deep extension. Step two, set up the Python environment and install required packages. Since Conda is already installed on my computer, I will now demonstrate how to use it. First create a new environment. Second, activate the environment. Third, install the required dependencies. Step three, install PM2. Install NodeJS and MPM if they are not already available on your system. Then install PM2 using MPM. Now I am going to restart all the containers. Then I will check whether PM2 is working normally. This completes the setup process for the training environment on MacOSS. [Music]