Running LLMs Locally with Docker Model Runner and Python (theaiops.substack.com)

The latest tutorial in the Docker Model Runner series unveils how to run large language models (LLMs) locally using the OpenAI Python SDK. Following an introduction to Docker Model Runner (DMR) in previous sessions, this guide emphasizes seamless integration between DMR and the OpenAI API, enabling developers to create and interact with LLMs through straightforward Python code. This is particularly significant for the AI/ML community, as it democratizes access to LLMs, allowing developers to run models locally without relying solely on cloud resources. The tutorial covers essential technical details, such as using Docker Engine or Docker Desktop to set up DMR and the configuration steps for connecting to local models. Users learn to substitute the standard OpenAI API endpoint with a DMR server URL, streamlining the workflow while maintaining familiarity with existing OpenAI SDK functions. With support for both containerized and traditional environments, DMR provides flexibility that can enhance development workflows. The next installment will focus on integrating models from Hugging Face, further expanding local LLM capabilities.