Fair Warning

Make sure you are using a capable system — ideally with a powerful CPU, GPU, and adequate cooling — before running large language models locally. LLMs can consume significant resources, generate substantial heat, and may cause system instability or damage if your hardware isn’t up to the task. Please proceed with caution!

This guide walks you through setting up Ollama (with deepseek-r1-goose) and Goose CLI.

Step 1: Download & Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Or, if you prefer to download manually then checkout:https://ollama.com/download Ollama-SetUpGuide

Step 2:Pull and Run the model

The following model is optimized for the agent we are going to install next so lets pull and run the model:

ollama run michaelneale/deepseek-r1-goose

more info about the model is available here https://www.ollama.com/michaelneale/deepseek-r1-goose

Step 3: Download And configure Goose-cli

Download the goose via HomeBrew if you don’t have it installed please check this article HomeBrew-SetUpGuide

brew install block-goose-cli

now you can run the goose

goose

Running after the first installation, the configure menu will be shown, make sure you select Ollama as the model provider, you can navigate by up and down arrow and hit return/enter to select the option.

After the model provider, next comes the model selection option, just type michaelneale/deepseek-r1-goose and hit return/enter.

Later if you want to change the model you can always run bash goose configure, i would recommend you use this model others are not working as expected this is already slow.

You can stop goose by given /exit command.

Where Offline Agents Work Best

  • The task is narrow, well-defined, and focused.
  • You want fast, private processing without sending data to the cloud.
  • You are working with small to moderate inputs and outputs, as local models may struggle with large contexts or long conversations on limited hardware.
  • Context limit required is less than 32K tokens

Again, always monitor your system’s health, and don’t hesitate to stop the model if things heat up!