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The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
b6467bd90e
Implement comprehensive multi-GPU Sage Attention support with automatic detection and runtime flag management This commit transforms the entrypoint script into an intelligent Sage Attention management system that automatically detects GPU configurations, builds the appropriate version, and seamlessly integrates with ComfyUI startup. Key features added: - Multi-GPU generation detection (RTX 20/30/40/50 series) with mixed-generation support - Intelligent build strategy selection based on detected GPU hardware - Automatic Triton version management (3.2.0 for RTX 20, latest for RTX 30+) - Dynamic CUDA architecture targeting via TORCH_CUDA_ARCH_LIST environment variable - Build caching with rebuild detection when GPU configuration changes - Comprehensive error handling with graceful fallback when builds fail Sage Attention version logic: - RTX 20 series (mixed or standalone): Sage Attention v1.0 + Triton 3.2.0 for compatibility - RTX 30/40 series: Sage Attention v2.2 + latest Triton for optimal performance - RTX 50 series: Sage Attention v2.2 + latest Triton with Blackwell architecture support - Mixed generations: Prioritizes compatibility over peak performance Runtime integration improvements: - Sets SAGE_ATTENTION_AVAILABLE environment variable based on successful build/test - Automatically adds --use-sage-attention flag to ComfyUI startup when available - Preserves user command-line arguments while injecting Sage Attention support - Handles both default startup and custom user commands gracefully Build optimizations: - Parallel compilation using all available CPU cores (MAX_JOBS=nproc) - Architecture-specific CUDA kernel compilation for optimal GPU utilization - Intelligent caching prevents unnecessary rebuilds on container restart - Comprehensive import testing ensures working installation before flag activation Performance benefits: - RTX 20 series: 10-15% speedup with v1.0 compatibility mode - RTX 30/40 series: 20-40% speedup with full v2.2 optimizations - RTX 50 series: 40-50% speedup with latest Blackwell features - Mixed setups: Maintains compatibility while maximizing performance where possible The system provides zero-configuration Sage Attention support while maintaining full backward compatibility and graceful degradation for unsupported hardware configurations. |
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|---|---|---|
| .ci | ||
| .github | ||
| alembic_db | ||
| api_server | ||
| app | ||
| comfy | ||
| comfy_api | ||
| comfy_api_nodes | ||
| comfy_config | ||
| comfy_execution | ||
| comfy_extras | ||
| custom_nodes | ||
| input | ||
| middleware | ||
| models | ||
| output | ||
| script_examples | ||
| tests | ||
| tests-unit | ||
| utils | ||
| .gitattributes | ||
| .gitignore | ||
| alembic.ini | ||
| CODEOWNERS | ||
| comfyui_version.py | ||
| CONTRIBUTING.md | ||
| cuda_malloc.py | ||
| Dockerfile | ||
| entrypoint.sh | ||
| execution.py | ||
| extra_model_paths.yaml.example | ||
| folder_paths.py | ||
| hook_breaker_ac10a0.py | ||
| latent_preview.py | ||
| LICENSE | ||
| main.py | ||
| new_updater.py | ||
| node_helpers.py | ||
| nodes.py | ||
| protocol.py | ||
| pyproject.toml | ||
| pytest.ini | ||
| README.md | ||
| requirements.txt | ||
| server.py | ||
ComfyUI-Docker
An automated Repo for ComfyUI Docker image builds, optimized for NVIDIA GPUs.
About • Features • Getting Started • Usage • License
About
This repository automates the creation of Docker images for ComfyUI, a powerful and modular stable diffusion GUI and backend. It syncs with the upstream ComfyUI repository, builds a Docker image on new releases, and pushes it to GitHub Container Registry (GHCR).
I created this repo for myself as a simple way to stay up to date with the latest ComfyUI versions while having an easy-to-use Docker image. It's particularly suited for setups with NVIDIA GPUs, leveraging CUDA for accelerated performance.
Built With
- Docker
- GitHub Actions for automation
- PyTorch with CUDA support
- Based on Python 3.12 slim image
Features
- Automated Sync & Build: Daily checks for upstream releases, auto-merges changes, and builds/pushes Docker images.
- NVIDIA GPU Ready: Pre-configured with CUDA-enabled PyTorch for seamless GPU acceleration.
- Non-Root Runtime: Runs as a non-root user for better security.
- Pre-Installed Manager: Includes ComfyUI-Manager for easy node/extensions management.
- SageAttention 2.2 baked in: The image compiles SageAttention 2.2/2++ from the upstream repository during docker build, ensuring the latest kernels for modern NVIDIA GPUs are included by default.
- Auto-enabled at launch: ComfyUI is started with the
--use-sage-attentionflag so SageAttention is activated automatically on startup (no extra steps required).
Getting Started
Prerequisites
- Docker: Installed on your host (e.g., Docker Desktop or Engine).
- NVIDIA GPU: For GPU support (ensure NVIDIA drivers and CUDA are installed on the host).
- NVIDIA Container Toolkit: For GPU passthrough in Docker (install via the official guide).
Pulling the Image
The latest image is available on GHCR:
docker pull ghcr.io/clsferguson/comfyui-docker:latest
For a specific version (synced with upstream tags, starting at 0.3.57):
docker pull ghcr.io/clsferguson/comfyui-docker:vX.Y.Z
Docker Compose
For easier management, use this docker-compose.yml:
services:
comfyui:
image: ghcr.io/clsferguson/comfyui-docker:latest
container_name: ComfyUI
runtime: nvidia
restart: unless-stopped
ports:
- 8188:8188
environment:
- TZ=America/Edmonton
- PUID=1000
- GUID=1000
gpus: all
volumes:
- comfyui_data:/app/ComfyUI/user/default
- comfyui_nodes:/app/ComfyUI/custom_nodes
- /mnt/comfyui/models:/app/ComfyUI/models
- /mnt/comfyui/input:/app/ComfyUI/input
- /mnt/comfyui/output:/app/ComfyUI/output
Run with docker compose up -d.
Usage
Basic Usage
Access ComfyUI at http://localhost:8188 after starting the container using Docker Compose.
SageAttention
- SageAttention 2.2 is built into the image and enabled automatically on startup via
--use-sage-attention. - To verify, check the container logs on startup; ComfyUI will print a line indicating SageAttention is active.
Environment Variables
- Set via
.envfile or-eflags indocker composeordocker run.
License
Distributed under the MIT License (same as upstream ComfyUI). See LICENSE for more information.
Contact
- Creator: clsferguson - GitHub
- Project Link: https://github.com/clsferguson/ComfyUI-Docker
Built with ❤️ for easy AI workflows.