Local AI & LLM Workflows for macOS IT Automation

1. Overview: Local AI on Apple Silicon Unified Memory

Apple Silicon's Unified Memory Architecture (UMA) provides memory bandwidth up to 800 GB/s across CPU, GPU, and Neural Engine cores. This enables Mac SysAdmins and software engineers to run large language models (LLMs) like Llama 3, Mistral, and DeepSeek 100% locally without leaking corporate IP or sensitive log telemetry to public cloud APIs.

2. Installing & Serving Models via Ollama

# Install Ollama CLI engine via Homebrew
brew install ollama

# Start local model server daemon in background
ollama serve &

# Download and execute lightweight Llama 3.2 model
ollama run llama3.2

3. Automated Log Analysis Script using Local REST API

You can query local models via REST calls in shell automation scripts to parse error logs automatically:

# Capture last 5 minutes of system log errors
LOG_SAMPLE=$(log show --last 5m --predicate 'messageType == error' | tail -n 20)

# Send log prompt to local Ollama API
curl -s http://localhost:11434/api/generate -d "{
  "model": "llama3.2",
  "prompt": "Analyze these macOS log errors and list root cause in 2 bullet points:
$LOG_SAMPLE",
  "stream": false
}" | jq -r '.response'

4. Frequently Asked Questions (FAQ)