offline inference

The article guides Linux users to run open-source LLMs locally for privacy, speed, and cost control, offering three paths: easiest with Ollama (CLI/API), more control by building llama.cpp (CPU/GPU, GGUF), and a web UI via Open WebUI + Ollama. It covers prerequisites, model/quantization choices, tuning (threads, GPU offload, context), bash automations, resource monitoring, and updates—ending with quick demos and action steps.

Hands-on guide to using local AI to automate Bash privately and offline: explains benefits; installs Ollama or llama.cpp; pulls qwen2.5-coder:7b and llama3.1:8b; adds an ai() CLI helper; and shows four safe patterns: generate->lint->confirm scripts, explain one-liners, summarize logs, and emit jq/awk filters; plus model/hardware tips, a security checklist, troubleshooting, and concrete next steps.