From fc74163065e7b160b15c29fd1ee4d53a3454abed Mon Sep 17 00:00:00 2001 From: GitLab CI Date: Wed, 5 Nov 2025 18:35:04 +0000 Subject: [PATCH] chore: Regenerate all playbooks --- nvidia/comfy-ui/README.md | 238 +++++++++++++++++++------------------- 1 file changed, 119 insertions(+), 119 deletions(-) diff --git a/nvidia/comfy-ui/README.md b/nvidia/comfy-ui/README.md index 0faa504..0e475a4 100644 --- a/nvidia/comfy-ui/README.md +++ b/nvidia/comfy-ui/README.md @@ -14,185 +14,185 @@ ## Basic idea -ComfyUI is an open-source web server application for AI image generation using diffusion-based models like SDXL, Flux and others. -It has a browser-based UI that lets you create, edit and run image generation and editing workflows with multiple steps. -Generation and editing steps (e.g. loading a model, adding text or sampling) are configurable in the UI as a node, and you connect nodes with wires to form a workflow. + ComfyUI is an open-source web server application for AI image generation using diffusion-based models like SDXL, Flux and others. + It has a browser-based UI that lets you create, edit and run image generation and editing workflows with multiple steps. + Generation and editing steps (e.g. loading a model, adding text or sampling) are configurable in the UI as a node, and you connect nodes with wires to form a workflow. -ComfyUI uses the host's GPU for inference, so you can install it on your Spark and do all of your image generation and editing directly on device. + ComfyUI uses the host's GPU for inference, so you can install it on your Spark and do all of your image generation and editing directly on device. -Workflows are saved as JSON files, so you can version them for future work, collaboration and reproducibility. + Workflows are saved as JSON files, so you can version them for future work, collaboration and reproducibility. -## What you'll accomplish +# # What you'll accomplish -You'll install and configure ComfyUI on your NVIDIA DGX Spark device so you can use the unified memory to work with large models. + You'll install and configure ComfyUI on your NVIDIA DGX Spark device so you can use the unified memory to work with large models. -## What to know before starting +# # What to know before starting -- Experience working with Python virtual environments and package management -- Familiarity with command line operations and terminal usage -- Basic understanding of deep learning model deployment and checkpoints -- Knowledge of container workflows and GPU acceleration concepts -- Understanding of network configuration for accessing web services + - Experience working with Python virtual environments and package management + - Familiarity with command line operations and terminal usage + - Basic understanding of deep learning model deployment and checkpoints + - Knowledge of container workflows and GPU acceleration concepts + - Understanding of network configuration for accessing web services -## Prerequisites +# # Prerequisites -**Hardware Requirements:** -- NVIDIA Spark device with Blackwell architecture -- Minimum 8GB GPU memory for Stable Diffusion models -- At least 20GB available storage space + **Hardware Requirements:** + - NVIDIA Spark device with Blackwell architecture + - Minimum 8GB GPU memory for Stable Diffusion models + - At least 20GB available storage space -**Software Requirements:** -- Python 3.8 or higher installed: `python3 --version` -- pip package manager available: `pip3 --version` -- CUDA toolkit compatible with Blackwell: `nvcc --version` -- Git version control: `git --version` -- Network access to download models from Hugging Face -- Web browser access to `:8188` port + **Software Requirements:** + - Python 3.8 or higher installed: `python3 --version` + - pip package manager available: `pip3 --version` + - CUDA toolkit compatible with Blackwell: `nvcc --version` + - Git version control: `git --version` + - Network access to download models from Hugging Face + - Web browser access to `:8188` port -## Ancillary files +# # Ancillary files -All required assets can be found [in the ComfyUI repository on GitHub](https://github.com/comfyanonymous/ComfyUI) + All required assets can be found [in the ComfyUI repository on GitHub](https://github.com/comfyanonymous/ComfyUI) -- `requirements.txt` - Python dependencies for ComfyUI installation -- `main.py` - Primary ComfyUI server application entry point -- `v1-5-pruned-emaonly-fp16.safetensors` - Stable Diffusion 1.5 checkpoint model + - `requirements.txt` - Python dependencies for ComfyUI installation + - `main.py` - Primary ComfyUI server application entry point + - `v1-5-pruned-emaonly-fp16.safetensors` - Stable Diffusion 1.5 checkpoint model -## Time & risk +# # Time & risk -* **Estimated time:** 30-45 minutes (including model download) -* **Risk level:** Medium - * Model downloads are large (~2GB) and may fail due to network issues - * Port 8188 must be accessible for web interface functionality -* **Rollback:** Virtual environment can be deleted to remove all installed packages. Downloaded models can be removed manually from the checkpoints directory. + * **Estimated time:** 30-45 minutes (including model download) + * **Risk level:** Medium + * Model downloads are large (~2GB) and may fail due to network issues + * Port 8188 must be accessible for web interface functionality + * **Rollback:** Virtual environment can be deleted to remove all installed packages. Downloaded models can be removed manually from the checkpoints directory. ## Instructions ## Step 1. Verify system prerequisites -Check that your NVIDIA Spark device meets the requirements before proceeding with installation. + Check that your NVIDIA Spark device meets the requirements before proceeding with installation. -```bash -python3 --version -pip3 --version -nvcc --version -nvidia-smi -``` + ```bash + python3 --version + pip3 --version + nvcc --version + nvidia-smi + ``` -Expected output should show Python 3.8+, pip available, CUDA toolkit and GPU detection. + Expected output should show Python 3.8+, pip available, CUDA toolkit and GPU detection. -## Step 2. Create Python virtual environment +# # Step 2. Create Python virtual environment -You will install ComfyUI on your host system, so you should create an isolated environment to avoid conflicts with system packages. + You will install ComfyUI on your host system, so you should create an isolated environment to avoid conflicts with system packages. -```bash -python3 -m venv comfyui-env -source comfyui-env/bin/activate -``` + ```bash + python3 -m venv comfyui-env + source comfyui-env/bin/activate + ``` -Verify the virtual environment is active by checking the command prompt shows `(comfyui-env)`. + Verify the virtual environment is active by checking the command prompt shows `(comfyui-env)`. -## Step 3. Install PyTorch with CUDA support +# # Step 3. Install PyTorch with CUDA support -Install PyTorch with CUDA 12.9 support. + Install PyTorch with CUDA 12.9 support. -```bash -pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu129 -``` + ```bash + pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu129 + ``` -This installation targets CUDA 12.9 compatibility with Blackwell architecture GPUs. + This installation targets CUDA 12.9 compatibility with Blackwell architecture GPUs. -## Step 4. Clone ComfyUI repository +# # Step 4. Clone ComfyUI repository -Download the ComfyUI source code from the official repository. + Download the ComfyUI source code from the official repository. -```bash -git clone https://github.com/comfyanonymous/ComfyUI.git -cd ComfyUI/ -``` + ```bash + git clone https://github.com/comfyanonymous/ComfyUI.git + cd ComfyUI/ + ``` -## Step 5. Install ComfyUI dependencies +# # Step 5. Install ComfyUI dependencies -Install the required Python packages for ComfyUI operation. + Install the required Python packages for ComfyUI operation. -```bash -pip install -r requirements.txt -``` + ```bash + pip install -r requirements.txt + ``` -This installs all necessary dependencies including web interface components and model handling libraries. + This installs all necessary dependencies including web interface components and model handling libraries. -## Step 6. Download Stable Diffusion checkpoint +# # Step 6. Download Stable Diffusion checkpoint -Navigate to the checkpoints directory and download the Stable Diffusion 1.5 model. + Navigate to the checkpoints directory and download the Stable Diffusion 1.5 model. -```bash -cd models/checkpoints/ -wget https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/resolve/main/v1-5-pruned-emaonly-fp16.safetensors -cd ../../ -``` + ```bash + cd models/checkpoints/ + wget https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/resolve/main/v1-5-pruned-emaonly-fp16.safetensors + cd ../../ + ``` -The download will be approximately 2GB and may take several minutes depending on network speed. + The download will be approximately 2GB and may take several minutes depending on network speed. -## Step 7. Launch ComfyUI server +# # Step 7. Launch ComfyUI server -Start the ComfyUI web server with network access enabled. + Start the ComfyUI web server with network access enabled. -```bash -python main.py --listen 0.0.0.0 -``` + ```bash + python main.py --listen 0.0.0.0 + ``` -The server will bind to all network interfaces on port 8188, making it accessible from other devices. + The server will bind to all network interfaces on port 8188, making it accessible from other devices. -## Step 8. Validate installation +# # Step 8. Validate installation -Check that ComfyUI is running correctly and accessible via web browser. + Check that ComfyUI is running correctly and accessible via web browser. -```bash -curl -I http://localhost:8188 -``` + ```bash + curl -I http://localhost:8188 + ``` -Expected output should show HTTP 200 response indicating the web server is operational. + Expected output should show HTTP 200 response indicating the web server is operational. -Open a web browser and navigate to `http://:8188` where `` is your device's IP address. + Open a web browser and navigate to `http://:8188` where `` is your device's IP address. -## Step 9. Optional - Cleanup and rollback +# # Step 9. Optional - Cleanup and rollback -If you need to remove the installation completely, follow these steps: + If you need to remove the installation completely, follow these steps: -> [!WARNING] -> This will delete all installed packages and downloaded models. + > [!WARNING] + > This will delete all installed packages and downloaded models. -```bash -deactivate -rm -rf comfyui-env/ -rm -rf ComfyUI/ -``` + ```bash + deactivate + rm -rf comfyui-env/ + rm -rf ComfyUI/ + ``` -To rollback during installation, press `Ctrl+C` to stop the server and remove the virtual environment. + To rollback during installation, press `Ctrl+C` to stop the server and remove the virtual environment. -## Step 10. Optional - Next steps +# # Step 10. Optional - Next steps -Test the installation with a basic image generation workflow: + Test the installation with a basic image generation workflow: -1. Access the web interface at `http://:8188` -2. Load the default workflow (should appear automatically) -3. Click "Run" to generate your first image -4. Monitor GPU usage with `nvidia-smi` in a separate terminal + 1. Access the web interface at `http://:8188` + 2. Load the default workflow (should appear automatically) + 3. Click "Run" to generate your first image + 4. Monitor GPU usage with `nvidia-smi` in a separate terminal -The image generation should complete within 30-60 seconds depending on your hardware configuration. + The image generation should complete within 30-60 seconds depending on your hardware configuration. ## Troubleshooting | Symptom | Cause | Fix | -|---------|-------|-----| -| PyTorch CUDA not available | Incorrect CUDA version or missing drivers | Verify `nvcc --version` matches cu129, reinstall PyTorch | -| Model download fails | Network connectivity or storage space | Check internet connection, verify 20GB+ available space | -| Web interface inaccessible | Firewall blocking port 8188 | Configure firewall to allow port 8188, check IP address | -| Out of GPU memory errors after manually flushing buffer cache | Insufficient VRAM for model | Use smaller models or enable CPU fallback mode | + |---------|-------|-----| + | PyTorch CUDA not available | Incorrect CUDA version or missing drivers | Verify `nvcc --version` matches cu129, reinstall PyTorch | + | Model download fails | Network connectivity or storage space | Check internet connection, verify 20GB+ available space | + | Web interface inaccessible | Firewall blocking port 8188 | Configure firewall to allow port 8188, check IP address | + | Out of GPU memory errors after manually flushing buffer cache | Insufficient VRAM for model | Use smaller models or enable CPU fallback mode | -> [!NOTE] -> DGX Spark uses a Unified Memory Architecture (UMA), which enables dynamic memory sharing between the GPU and CPU. -> With many applications still updating to take advantage of UMA, you may encounter memory issues even when within -> the memory capacity of DGX Spark. If that happens, manually flush the buffer cache with: -```bash -sudo sh -c 'sync; echo 3 > /proc/sys/vm/drop_caches' -``` + > [!NOTE] + > DGX Spark uses a Unified Memory Architecture (UMA), which enables dynamic memory sharing between the GPU and CPU. + > With many applications still updating to take advantage of UMA, you may encounter memory issues even when within + > the memory capacity of DGX Spark. If that happens, manually flush the buffer cache with: + ```bash + sudo sh -c 'sync; echo 3 > /proc/sys/vm/drop_caches' + ```