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chore: Regenerate all playbooks
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## Basic idea
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ComfyUI is an open-source web server application for AI image generation using diffusion based models like SDXL, Flux and others.
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ComfyUI is an open-source web server application for AI image generation using diffusion-based models like SDXL, Flux and others.
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It has a browser-based UI that lets you create, edit and run image generation and editing workflows with multiple steps.
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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.
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Workflows are saved as JSON files, so you can version them for future work, collaboration and reproducibility.
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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.
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Workflows are saved as JSON files, so you can version them for future work, collaboration and reproducibility.
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## What you'll accomplish
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You'll install and configure ComfyUI on your NVIDIA DGX Spark device so you can use the unified memory to work with large models.
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@ -35,17 +36,17 @@ You'll install and configure ComfyUI on your NVIDIA DGX Spark device so you can
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## Prerequisites
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**Hardware Requirements:**
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- [ ] NVIDIA Spark device with Blackwell architecture
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- [ ] Minimum 8GB GPU memory for Stable Diffusion models
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- [ ] At least 20GB available storage space
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- NVIDIA Spark device with Blackwell architecture
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- Minimum 8GB GPU memory for Stable Diffusion models
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- At least 20GB available storage space
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**Software Requirements:**
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- [ ] Python 3.8 or higher installed: `python3 --version`
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- [ ] pip package manager available: `pip3 --version`
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- [ ] CUDA toolkit compatible with Blackwell: `nvcc --version`
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- [ ] Git version control: `git --version`
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- [ ] Network access to download models from Hugging Face
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- [ ] Web browser access to `<SPARK_IP>:8188` port
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- Python 3.8 or higher installed: `python3 --version`
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- pip package manager available: `pip3 --version`
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- CUDA toolkit compatible with Blackwell: `nvcc --version`
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- Git version control: `git --version`
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- Network access to download models from Hugging Face
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- Web browser access to `<SPARK_IP>:8188` port
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## Ancillary files
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@ -80,7 +81,7 @@ nvcc --version
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nvidia-smi
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```
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Expected output should show Python 3.8+, pip available, CUDA toolkit, and GPU detection.
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Expected output should show Python 3.8+, pip available, CUDA toolkit and GPU detection.
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## Step 2. Create Python virtual environment
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@ -165,6 +166,7 @@ Open a web browser and navigate to `http://<SPARK_IP>:8188` where `<SPARK_IP>` i
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| Web interface inaccessible | Firewall blocking port 8188 | Configure firewall to allow port 8188, check IP address |
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| Out of GPU memory errors | Insufficient VRAM for model | Use smaller models or enable CPU fallback mode |
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## Step 10. Optional - Cleanup and rollback
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If you need to remove the installation completely, follow these steps:
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