Run AI Assistant Locally Free · Live · April 26

Run an AI Assistant Locally for Free — Complete Setup in 4 Hours

Running an AI assistant locally for free is no longer a weekend project for experts. Docker Model Runner and OpenClaw in 2026 make it a guided 4-hour workshop. You leave with a working private AI assistant in WhatsApp or Telegram — at zero ongoing cost.

Sunday, April 26 9am to 1pm EDT

4 Hours Hands-on coding

Live Online Interactive

Workshop Details

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Date and Time

Sunday, April 26, 2026

9:00am to 1:00pm EDT

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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

By Packt Publishing · Refunds up to 10 days before

About Running an AI Assistant Locally for Free

Why Running an AI Assistant Locally for Free Is Now Practical

The tools to run an AI assistant locally for free have matured significantly. Docker Model Runner handles local model inference. OpenClaw provides the assistant and messaging layer. This workshop brings both together in one complete guided setup.

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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.

Workshop Curriculum

What You Will Set Up to Run AI Locally for Free

Six modules. A fully free locally running AI assistant by the end.

How OpenClaw Works

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

Docker Model Runner Setup

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

Security and Privacy

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

Connect to WhatsApp or Telegram

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

Scalable Architecture

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

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 Workshop You Will Have

A completely free AI assistant running locally and ready to use.

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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

Learn to Run AI Locally for Free From a Docker Captain

Rami Krispin is a Docker Captain with expertise in free local AI deployment.

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.

Frequently Asked Questions

Common Questions About Running an AI Assistant Locally for Free

Everything you need to know about setting up a free local AI assistant.

Is running an AI assistant locally really free? +

Yes. OpenClaw is open source and free. Docker Model Runner is included in Docker Desktop at no cost. The open weight models are free. Running an AI assistant locally with this setup has zero ongoing cost — no subscription, no API fees, no usage limits whatsoever.

How capable is a free locally running AI assistant? +

Modern open weight models available through Docker Model Runner are highly capable for everyday assistant tasks. Writing help, question answering, summarisation, coding assistance, and conversational interaction all work very well. The instructor covers model selection to help you get the best results from your free local setup.

How long does it take to get a free AI assistant running locally? +

Following this live 4-hour workshop, you will have a free AI assistant running locally and connected to WhatsApp or Telegram by the end of the session. On your own without guidance the same setup typically takes several days.

Does my free locally running AI assistant need internet to work? +

The AI inference itself runs completely offline — the model processes your messages on your own hardware with no internet needed for the AI reasoning. The WhatsApp or Telegram messaging integration requires internet for message routing, but the AI model itself is fully local.

Can I run an AI assistant locally for free on any operating system? +

Docker Model Runner supports Mac, Windows, and Linux. This workshop covers setup on Mac and Windows specifically. The instructor helps troubleshoot any operating system-specific issues during the live session.

What is the difference between running AI locally for free versus using a free cloud AI service? +

Free cloud AI services still send your data to their servers, have usage limits, and operate under their terms of service. Running AI locally for free means your data never leaves your machine, there are no usage limits, and you have complete control. The tradeoff is that local models are generally slower and slightly less capable than frontier cloud models.