Run LLM Locally With Docker Desktop · Step by Step · April 26

Run an LLM Locally With Docker Desktop — Step by Step From Zero

Running an LLM locally with Docker Desktop is simpler than most developers expect — if you know the right steps in the right order. This live workshop takes you through every step, from enabling Docker Model Runner to a deployed private AI assistant in 4 hours.

Sunday, April 26   9am to 1pm EDT
4 Hours   Hands-on coding
Live Online   Interactive
Register Now → See what you will build ↓

Workshop Details

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Date and Time
Sunday, April 26, 2026
9:00am to 1:00pm EDT
⏱
Duration
4 Hours · Hands-on
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Format
Live Online · Interactive
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Includes
Certificate of Completion
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Privacy
100% Local · No Cloud Required
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By Packt Publishing · Refunds up to 10 days before

✦ OpenClaw — 200K+ GitHub Stars
✦ 4 Hours Live Hands-On Coding
✦ By Packt Publishing
✦ No Cloud Dependency Required
✦ Certificate of Completion
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About This Step by Step Workshop

The Step by Step Approach to Running LLMs Locally With Docker Desktop

The most common reason developers struggle with running LLMs locally using Docker Desktop is attempting steps in the wrong order or missing critical configuration details. This workshop covers the correct sequence with live instructor support to keep you on track.

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What is OpenClaw?

OpenClaw is the open-source personal AI assistant that went viral in early 2026 with 200K+ GitHub stars. It runs on your own devices and connects to WhatsApp, Telegram, Slack and more. No subscription. No data leaving your machine.

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What is Docker Model Runner?

Docker Model Runner is Docker's native feature for running large language models locally on your machine. It gives you an OpenAI-compatible API that OpenClaw uses as its AI brain — complete data privacy, no cloud costs.

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Why Combine OpenClaw and Docker?

OpenClaw gives you the assistant interface and messaging integrations. Docker Model Runner gives you the AI brain running privately on your machine. Together they create a production grade private AI assistant you fully own.

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Why Attend as a Live Workshop?

Setting this up from scattered documentation takes days of debugging. This live workshop gives you a complete guided build in 4 hours with a live instructor answering your questions. Packt has delivered 108 workshops worldwide.

Step by Step Workshop Curriculum

The Complete Step by Step Guide to Running LLMs Locally With Docker Desktop

Six modules covering every step from Docker Model Runner setup to production deployment.

01

How OpenClaw Works

Understand the Gateway, channels, and skills architecture. Set up and configure OpenClaw locally from scratch.

02

Docker Model Runner Setup

Run and manage local LLMs using Docker Model Runner. Pull models, configure memory, and understand the OpenAI-compatible API.

03

Security and Privacy

Configure DM pairing, allowlists, sandbox mode, and proper access controls for your local AI deployment.

04

Connect to WhatsApp or Telegram

Deploy your AI assistant to real messaging platforms without sending data to any third party cloud service.

05

Scalable Architecture

Design an extensible assistant architecture. Add skills, configure personality, and set up proactive automation.

06

Production Deployment

Deploy your OpenClaw and Docker setup to a VPS for always-on availability running 24 hours a day.

What You Walk Away With

By the End of This Step by Step Workshop You Will Have

An LLM running locally in Docker Desktop powering a working private AI assistant.

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A fully functional local AI assistant running on your machine

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Docker Model Runner configured with your chosen LLM model

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OpenClaw connected to WhatsApp or Telegram

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Security and privacy configuration you can trust

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A reusable architecture for future AI assistant projects

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Certificate of completion from Packt Publishing

Your Instructor

Follow the Steps With a Docker Captain Guiding You

Rami Krispin walks through every step live — so you never get stuck without guidance.

Rami Krispin

Rami Krispin

Workshop Instructor · April 26, 2026

Rami is a Senior Manager of Data Science and Engineering, Docker Captain, and LinkedIn Learning Instructor with deep expertise in building and deploying production AI systems. He guides you step by step from a blank terminal to a fully deployed private AI assistant — answering your questions live throughout the 4-hour session.

Prerequisites

Who Is This Step by Step Workshop For?

Developers who want a clear step by step path to running LLMs locally with Docker Desktop.

Frequently Asked Questions

Common Questions About Running LLMs Locally With Docker Desktop Step by Step

Everything you need to know about this step by step approach.

What are the exact steps to run an LLM locally with Docker Desktop? +

The steps are: update Docker Desktop to a version with Model Runner support, enable Docker Model Runner in settings, use the Docker CLI to pull your chosen open weight model, verify the model is running and the local API endpoint is accessible, install and configure OpenClaw to connect to that endpoint, test the connection, then configure your messaging platform integration. This workshop covers each of these steps in order with live instructor guidance.

Which step is most commonly missed when running LLMs locally with Docker Desktop? +

The most commonly missed step is verifying the local API endpoint is actually accessible before trying to connect OpenClaw to it. Many setup issues stem from skipping this verification step. This workshop covers how to test each component before proceeding to the next, preventing the cascading errors that make debugging difficult.

How long does each step take when running an LLM locally with Docker Desktop? +

The Docker Desktop and Model Runner setup typically takes around 30 minutes. Pulling your chosen model takes 5 to 15 minutes depending on your internet speed. OpenClaw installation and configuration takes around 45 minutes. Messaging platform integration takes around 30 minutes. Security and deployment cover the final hour of the 4-hour session.

What if I get stuck on a step during this local LLM setup workshop? +

The instructor watches for participants who fall behind and provides real-time support. You can ask questions at any point during the session. All participants also receive a full recording so you can rewatch any step that was unclear and complete it at your own pace after the session.

Is this step by step approach different from just reading the Docker Model Runner documentation? +

Yes. Documentation lists what to do but does not show you the expected output at each step, does not tell you what errors look like when something goes wrong, and cannot answer your specific questions. The step by step workshop provides all of this — including live troubleshooting when the expected output does not match what you see on your screen.

Will the steps in this workshop work on both Mac and Windows? +

Yes. The instructor covers Docker Desktop setup and Docker Model Runner configuration on both Mac and Windows. Platform-specific differences are noted at each step and the instructor helps troubleshoot any platform-specific issues that arise during the live session.

Run LLM Locally With Docker Desktop Step by Step · April 26, 2026

Ready to Follow the Step by Step Guide to Local LLMs With Docker Desktop?

4 hours. Live Docker Captain. Clear steps to a working local LLM setup. Seats are limited.

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Sunday April 26 · 9am to 1pm EDT · Online · Packt Publishing