DanielPFlorian-ComfyUI-WorkflowGenerator/wiki/Installation.md

Installation Guide

This guide covers installation of ComfyUI-WorkflowGenerator and the required llama-cpp-python library for GGUF models.

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Prerequisites

• ComfyUI installed and running
• Python 3.10, 3.11, or 3.12
• Git installed
• For GPU acceleration: NVIDIA GPU with CUDA support (recommended) or Apple Silicon Mac

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Step 1: Install ComfyUI-WorkflowGenerator

Follow the main README for basic installation steps (cloning, dependencies, etc.).

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Step 2: Install llama-cpp-python

Why separate? llama-cpp-python is required for GGUF models but needs different installation methods for CPU/CUDA/Metal, so it's not included in requirements.txt.

Choose Your Installation Path

Standard Python Installation	Portable ComfyUI (Windows)
Use regular pip install commands	Use python_embeded\python.exe -s -m pip
→ See Standard Installation	→ See Portable Installation

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Standard Installation

Option 1: CPU Only (No GPU)

All Platforms:

pip install llama-cpp-python

Who should use this: Systems without NVIDIA GPU or Apple Silicon, or for testing purposes.

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Option 2: CUDA Support (NVIDIA GPUs) - Recommended

Compatibility:

• Python 3.10, 3.11, 3.12
• CUDA 11.8, 12.1, 12.4+
• PyTorch 2.0+

Try Quick Install First

All Platforms:

pip install llama-cpp-python[cuda]

This works if:

• Installation completes in 1-2 minutes
• You see "Downloading .whl" messages
• ✅ You're done! Skip to testing

If it fails or takes 20+ minutes, you need to compile from source →

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Compile from Source (Windows)

When needed: Pre-built wheel not available for your Python/CUDA combination (common on Windows)

Prerequisites (install these first):

1. Visual Studio 2022 Community - Select "Desktop development with C++"
2. CUDA Toolkit 12.x - Match your driver version
3. CMake - Add to PATH during installation
   • Important: After installing CMake, close and reopen your terminal (no restart needed)

PowerShell:

# Install build dependencies
pip install cmake scikit-build-core

# Set build flags and compile (takes 20-30 minutes)
$env:CMAKE_ARGS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=native"
$env:FORCE_CMAKE=1
pip install llama-cpp-python --no-cache-dir --verbose --force-reinstall

Command Prompt (cmd):

REM Install build dependencies
pip install cmake scikit-build-core

REM Set build flags and compile (takes 20-30 minutes)
set CMAKE_ARGS=-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=native
set FORCE_CMAKE=1
pip install llama-cpp-python --no-cache-dir --verbose --force-reinstall

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Compile from Source (Linux/macOS)

Prerequisites:

• GCC/Clang compiler
• CUDA Toolkit installed
• CMake installed

Linux/macOS:

# Install build dependencies
pip install cmake scikit-build-core

# Set build flags and compile
CMAKE_ARGS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=native" FORCE_CMAKE=1 pip install llama-cpp-python --no-cache-dir --verbose --force-reinstall

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Option 3: Metal Support (macOS Apple Silicon)

macOS Only:

pip install llama-cpp-python[metal]

Who should use this: Mac users with M1/M2/M3/M4 chips for GPU acceleration.

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Portable ComfyUI (Windows)

For Windows portable ComfyUI installations, all commands use the embedded Python interpreter.

Quick Install (Try First)

PowerShell:

cd <your_portable_comfyui_folder>
python_embeded\python.exe -s -m pip install llama-cpp-python[cuda]

Command Prompt:

cd <your_portable_comfyui_folder>
python_embeded\python.exe -s -m pip install llama-cpp-python[cuda]

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Compile from Source (Portable)

Prerequisites: Same as standard Windows installation (Visual Studio, CUDA Toolkit, CMake)

PowerShell:

# Step 1: Install build dependencies
python_embeded\python.exe -s -m pip install cmake scikit-build-core

# Step 2: Set environment and compile
$env:CMAKE_ARGS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=native"
$env:FORCE_CMAKE=1
python_embeded\python.exe -s -m pip install llama-cpp-python --no-cache-dir --verbose --force-reinstall

Command Prompt:

REM Step 1: Install build dependencies
python_embeded\python.exe -s -m pip install cmake scikit-build-core

REM Step 2: Set environment and compile
set CMAKE_ARGS=-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=native
set FORCE_CMAKE=1
python_embeded\python.exe -s -m pip install llama-cpp-python --no-cache-dir --verbose --force-reinstall

Note: The -s flag prevents Python from adding user site-packages to sys.path.

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Testing Your Installation

Check if CUDA is working:

python -c "from llama_cpp import Llama; print('✓ llama-cpp-python installed successfully')"

Check your versions:

python -c "import sys, torch; print(f'Python: {sys.version_info.major}.{sys.version_info.minor}'); print(f'PyTorch: {torch.__version__}'); print(f'CUDA: {torch.version.cuda if torch.cuda.is_available() else \"N/A\"}')"

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Troubleshooting

"No module named 'llama_cpp'" after installation

Cause: CPU version installed instead of CUDA version

Solution - Reinstall with CUDA support:

PowerShell:

pip uninstall llama-cpp-python; pip install llama-cpp-python[cuda]

Command Prompt / Linux / macOS:

pip uninstall llama-cpp-python && pip install llama-cpp-python[cuda]

Portable ComfyUI:

python_embeded\python.exe -s -m pip uninstall llama-cpp-python && python_embeded\python.exe -s -m pip install llama-cpp-python[cuda]

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"Cannot import 'scikit_build_core.build'"

Cause: Missing build dependencies

Solution:

pip install cmake scikit-build-core

Portable ComfyUI:

python_embeded\python.exe -s -m pip install cmake scikit-build-core

Then retry the installation with CMAKE_ARGS set.

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"CMake not found"

Solution:

1. Install CMake: pip install cmake or download from https://cmake.org/
2. Windows users: Close and reopen your terminal for PATH changes (no restart needed)
3. If still not working, you may need Visual Studio Build Tools

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"CUDA not found" or "CUDA version mismatch"

Check your CUDA version:

python -c "import torch; print(torch.version.cuda)"

Solutions:

• Ensure CUDA Toolkit is installed and matches your PyTorch CUDA version
• Check that your GPU drivers are up to date
• Verify CUDA is in your system PATH

For detailed troubleshooting, see INSTALL_LLAMACPP.md

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Installation takes 20-30 minutes

This is normal! It means you're compiling from source because no pre-built wheel is available for your system.

Requirements:

• Windows: Visual Studio Build Tools with C++ support
• Linux: build-essential package (sudo apt install build-essential)
• Be patient - the compilation will complete

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