macOS Setup and Local AI Guide¶
This guide answers four things: - What is missing from your current setup - How to install everything quickly - What each tool is for and when to use it - What to install for local AI on a Mac mini M4 (16GB/256GB)
Current State (from scripts/dev-check.sh)¶
Core environment is healthy. Missing items are mostly optional productivity tools:
- gh, wget
- bat, eza, fd, fzf, zoxide, tlrc, httpie, git-delta
- nvm, pnpm, code
- starship, optional runtimes (go, rust)
Install Everything You Listed¶
CLI tools (recommended baseline)¶
brew install gh wget bat eza fd fzf zoxide tlrc httpie git-delta nvm pnpm starship
GUI app (if you want VS Code)¶
brew install --cask visual-studio-code
Optional language toolchains¶
brew install go rust
After installing nvm¶
mkdir -p ~/.nvm
source ~/.zshrc
nvm install --lts
nvm alias default 'lts/*'
Do Your Dotfiles Handle This?¶
Mostly yes:
- Installers already include essentials and optional tools in os/mac/
- scripts/dev-check.sh checks health and now shows accurate required vs optional status
- scripts/sync.sh handles symlinks and config refresh
What is not fully automatic yet: - Installing every optional GUI app by default (intentionally interactive/optional) - Local AI stack (recommended to keep optional because of disk/RAM tradeoffs)
Tool Cheat Sheet (What + When)¶
gh: GitHub from terminal. Use for PRs, issues, auth.wget: quick file downloads, recursive/mirror-style fetch.bat: syntax-highlighted file viewing.eza: betterlswith git status/icons.rg(ripgrep): fast code/text search.fd: fast file discovery.fzf: fuzzy picker for history/files/branches.zoxide: smart directory jumping (z project).tlrc: concise examples for commands (maintained replacement for oldtldrformula on Homebrew).httpie: readable API calls (http GET ...).jq: JSON parsing/transform.git-delta: better colored git diffs.nvm: manage multiple Node versions safely.pnpm: fast, space-efficient Node package manager.starship: cross-shell prompt.
Local AI on Mac mini M4 (16GB RAM, 256GB SSD)¶
For this hardware, prioritize efficient 7B/8B models and keep disk usage controlled.
Recommended stack¶
Ollamafor model management and servingOpen WebUI(or another lightweight UI) for chat UX- Optional
llama.cppfor low-level tuning/benchmarking
Install¶
brew install ollama
brew install llama.cpp
Start Ollama:
ollama serve
Pull practical models (start small):
ollama pull llama3.1:8b
ollama pull qwen2.5-coder:7b
About the tools you mentioned¶
- Ollama: best default choice for local model lifecycle.
- OpenClaw: UI option; use if you prefer this UX, but keep one UI to avoid bloat.
- GPT4All: all-in-one desktop app; good for quick start, less flexible than CLI-first stack.
- llama.cpp: best for advanced control, quantization experiments, benchmarking.
- Core ML variants: useful for Apple Silicon optimization; good once baseline setup is stable.
Storage and Performance Advice for 16GB/256GB¶
- Keep only 2-3 active models locally.
- Prefer 7B/8B quantized models for responsiveness.
- Avoid many 14B+ models on internal disk.
- Consider external SSD for model cache if you expand model library.
Suggested Next Steps¶
- Install baseline CLI tools now (
brew install ...above). - Re-run
scripts/dev-check.sh. - Add Ollama + one coding model first (
qwen2.5-coder:7b). - Add a UI only if you actually need browser/chat workflows.