Installation

The quick installer automatically sets up git, uv, and Python (via uv). The frontend bundle is downloaded prebuilt from the latest GitHub release, and the backend is checked out at that same release tag so the two stay in sync — end users do not need Node.js or pnpm.

:::tip Which install do I want?

• Quick Install (this page) — you just want to run CodefyUI.
• Dev Install — you want to edit the code or contribute (manual uv + pnpm setup with hot reload). :::

Quick Install

# macOS / Linux
curl -fsSL https://raw.githubusercontent.com/CodefyUI/CodefyUI/main/install.sh | bash

# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://raw.githubusercontent.com/CodefyUI/CodefyUI/main/install.ps1 | iex"

By default this installs to ~/CodefyUI (macOS/Linux) or %USERPROFILE%\CodefyUI (Windows). Override with the CODEFYUI_DIR environment variable.

On Windows, install.ps1 uses winget to install git if it's missing. winget ships with Windows 11 and recent Windows 10 via the "App Installer" package. If winget is unavailable or its package sources cannot be reached (corporate TLS interception makes the msstore source fail with 0x8a15005e), the installer falls back to extracting PortableGit into %LOCALAPPDATA%\CodefyUI\PortableGit — no administrator rights required.

The installer places a cdui launcher at ~/.local/bin/cdui (Windows: %USERPROFILE%\.local\bin\cdui.cmd). Restart your terminal, then from any directory:

cdui start

Open http://localhost:8000. A single uvicorn process serves both the API and the prebuilt React app. cdui start runs in the background by default — you can close the terminal and the server keeps running; manage it with cdui status and cdui stop. Add --foreground (-f) to run it attached and stop with Ctrl+C.

note

This quick start assumes the default PyTorch build, which works on every platform (CPU / Apple Silicon MPS). For a specific NVIDIA CUDA version, AMD ROCm, or to verify GPU detection, see GPU & Device Setup.

Switching build after the fact does not need a terminal either: on a server started with cdui start, the GPU PyTorch card in the Package Center (toolbar > Settings > Optional packs) installs the matching wheel and restarts the server for you, with the same cdui install --gpu <choice> line printed underneath for when you would rather run it yourself. See Installs that restart the server.

Install flags & environment variables

install.sh and install.ps1 read only the environment variables below. They always run cdui install --yes, accept no command-line flags, and do not prompt. After installation, run cdui install directly to pass flags or use the interactive menu. The menu appears only in a terminal when no flag or environment variable has already selected an option. In a pipe or CI, the command uses the safe defaults.

Flag	Env var	Values	Purpose
--gpu <choice>	CODEFYUI_GPU	auto / cu118 / cu121 / cu124 / cu126 / cu128 / rocm6.1 / rocm6.2 / cpu / mps / skip	Select the PyTorch wheel index. auto detects via nvidia-smi / rocm-smi / Apple Silicon. skip installs no torch (advanced).
--dev / --no-dev	CODEFYUI_DEV	1 / 0	Install the [dev] extra (pytest, httpx, httpx-ws). Required for cdui test. Off for end users, on for contributors.
--yes	—	—	Accept all defaults non-interactively (CI / headless).
--lang <code>	CODEFYUI_LANG	en / zh (the environment variable also accepts zh-TW, zh-HK, zh-CN, english, and chinese)	The flag applies to cdui install and cdui update only; the environment variable sets the output language of every cdui command.
—	CODEFYUI_DIR	path	Set the installation directory. Default: ~/CodefyUI.
—	CODEFYUI_RELEASE_TAG	tag	Pin the frontend bundle and backend checkout to the same release. Default: latest.
—	CODEFYUI_FORCE_BUILD	1	Skip the prebuilt distribution download, build locally with pnpm, and track main.
—	CODEFYUI_UV_INSTALL_TIMEOUT	seconds	Set the automatic uv download timeout when uv is missing from PATH. Default: 180. Set to 0 for no limit.

Production vs developer mode

• cdui start — single uvicorn on :8000 serves the prebuilt frontend. No Node needed. This is the default end-user mode.
• cdui dev — Vite dev server on :5173 with HMR + uvicorn on :8000. Requires Node 24+ and pnpm. Use this when editing frontend code — see Dev Install.
• cdui build — rebuild frontend/dist locally (also needs Node + pnpm).

See the full list of launcher commands in CLI Commands.

Installing on a server for a team

The steps above install a personal instance on 127.0.0.1. If several people are going to share one machine, read Deployment Behind a Reverse Proxy first: CodefyUI has no user accounts, so authentication and TLS both come from a proxy in front of it, and the proxy's hostname has to be added to CODEFYUI_EXTRA_ALLOWED_HOSTS or every request — including the page itself — is rejected with 421 and the browser shows a blank screen.

Verify it works

curl http://127.0.0.1:8000/api/health

This should return something like {"status":"ok","nodes_loaded":152,"presets_loaded":3} (the nodes_loaded count grows with each release — just confirm it's non-zero).

Then open the frontend, load the Train CNN on MNIST example, and click Run. You should see training progress appear in the bottom panel.

Optional packs

The install above is deliberately small, so the large extras some lessons need — sentence-transformers, the embedding models (90 MB to 470 MB each), the 69 MB GloVe word-vector table — are not in it; install the ones you want from the Package Center (toolbar > Settings > Optional packs) or with cdui packs install <id>. Nothing else changes: a graph run never downloads pack contents on its own, so a node whose pack is missing stops with a message naming it instead of pulling half a gigabyte mid-run.

See Optional Packs for the catalog, where the files land, and which embedding model to pick.

Updating

cdui update

Updates to the latest release (prebuilt path) or pulls main (when building from source) and re-syncs the frontend.

Unlike cdui install, this never prompts. It reuses the PyTorch variant and dev tooling already in the venv — reading the variant straight off the installed wheel — so a deliberately chosen torch build is left alone, and an unchanged one isn't re-downloaded. The same --gpu / --dev flags and CODEFYUI_GPU / CODEFYUI_DEV env vars still override when you do want a switch.