Install Python dependencies

Overview

In this step, you’ll set up a Python virtual environment and install the required dependencies for working with Llama.cpp. This ensures you have a clean, isolated Python environment with all the necessary packages for model optimization.

Create a Python virtual environment

    

        
        
virtualenv env-llama-cpp

    

This command creates a new Python virtual environment named env-llama-cpp, which has the following benefits:

• Provides an isolated Python environment to prevent package conflicts between projects
• Creates a local directory containing its own Python interpreter and installation space
• Ensures Llama.cpp dependencies don’t interfere with your global Python setup
• Supports reproducible and portable development environments

Activate the virtual environment

Run the following command to activate the virtual environment:

    

        
        
source env-llama-cpp/bin/activate

    

This command does the following:

• Runs the activation script, which modifies your shell environment
• Updates your shell prompt to show env-llama-cpp, indicating the environment is active
• Updates PATH to use the environment’s Python interpreter
• Ensures all pip commands install packages into the isolated environment

Upgrade pip to the latest version

Before installing dependencies, it’s a good idea to upgrade pip:

    

        
        
pip install --upgrade pip

    

This command:

• Ensures you have the latest version of pip
• Helps avoid compatibility issues with modern packages
• Applies the --upgrade flag to fetch and install the newest release
• Brings in security patches and better dependency resolution logic

Install project dependencies

Use the following command to install all required Python packages:

    

        
        
pip install -r requirements.txt

    

This command does the following:

• Uses the -r flag to read the list of dependencies from requirements.txt
• Installs the exact package versions required for the project
• Ensures consistency across development environments and contributors
• Includes packages for model loading, inference, and Python bindings for llama.cpp

This step sets up everything you need to run AFM-4.5B in your Python environment.

What the environment includes

After the installation completes, your virtual environment includes:

• NumPy: for numerical computations and array operations
• Requests: for HTTP operations and API calls
• Other dependencies: additional packages required by llama.cpp’s Python bindings and utilities

Your environment is now ready to run Python scripts that integrate with the compiled Llama.cpp binaries.