Getting Started with Ollama

Installation

Linux (Recommended for mindX)

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

Docker

# CPU
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

NVIDIA GPU
docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

AMD GPU
docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm

macOS / Windows

Download from ollama.com/download

First Run

# Start the server (if not running as service)
ollama serve

Pull a model
ollama pull qwen3:1.7b

Run interactively
ollama run qwen3:1.7b "Hello!"

Pull embedding model
ollama pull mxbai-embed-large

Interactive Menu

ollama
Navigate with arrows, Enter to launch, Esc to quit

Verify

# Version
ollama -v

List models
ollama list

API test
curl http://localhost:11434/api/tags

Generate test
curl http://localhost:11434/api/generate -d '{
  "model": "qwen3:1.7b",
  "prompt": "Hello!",
  "stream": false
}'

Systemd Service (Linux)

The install script sets this up automatically. To manage:

sudo systemctl status ollama
sudo systemctl restart ollama
journalctl -u ollama --follow

Custom Configuration

sudo systemctl edit ollama
Add under [Service]:
Environment="OLLAMA_HOST=0.0.0.0:11434"
sudo systemctl daemon-reload
sudo systemctl restart ollama

Uninstall (Linux)

sudo systemctl stop ollama
sudo systemctl disable ollama
sudo rm /etc/systemd/system/ollama.service
sudo rm -r $(which ollama | tr 'bin' 'lib')
sudo rm $(which ollama)
sudo userdel ollama
sudo groupdel ollama
sudo rm -r /usr/share/ollama

mindX Quick Setup

# 1. Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

2. Pull models for mindX
ollama pull qwen3:1.7b           # Default autonomous model
ollama pull mxbai-embed-large    # Embeddings for RAGE
ollama pull nomic-embed-text     # Alternative embeddings

3. Set in .env
echo 'MINDX_LLM__OLLAMA__BASE_URL=http://localhost:11434' >> .env

4. Test connection
python scripts/test_ollama_connection.py

5. Start mindX
./mindX.sh --frontend