ComfyUI Flux Continuum: Modular Interface
Set of custom nodes to use with the ComfyUI Flux Continuum: Modular Interface. NODES: Text Versions, Image64 Display, Tabs, Step Slider, Denoise Slider, Guidance Slider, Batch Slider, Max Shift Slider, ControlNet Slider and more
Nodes (30)
How many images per run, without hunting for the right widget
The tiny bridge for ComfyUI_NetDist's odd string format
Two thresholds for edge detection, packed as one output
Burn a caption onto an image with a reusable text style
Pick a model by condition, driven by a JSON map
Strength, start, and end for one edge-controlled generation
The dial that decides how much of your image survives
The style sheet for the pack's text-on-image rendering
The node that swaps your Flux dev model by task
Pick a GPU count for a feature that's still coming
How hard Flux clings to your prompt (and the auto-30 gotcha)
Conditionally batch two images, or quietly pass one through
Stop, mute, or bypass the next node — without deleting anything
The most honest node in the pack
Three Redux reference strengths, one control
The node that does nothing, on purpose
One knob for 'make it feel different' on Flux
The node that tells the rest of the graph which mode you're in
The pass-through for Impact Pack pipes that keeps graphs tidy
The 'how big should this get' control
26 pre-calculated sizes so you never do Flux math again
Carry your sampler and scheduler as one object
Turn one fat wire back into a sampler, a scheduler, and their names
The invisible wire keeping the detailer pipeline alive
The slider that picks one image out of a queue
Cut a string down to N words without thinking about it
Unpack a 2-value vector into the two floats you actually need
Turn ControlNet's strength/start/end bundle into three honest numbers
The lazy way to dial sampling steps without typing 20
A/B test your prompts without deleting a single character
ComfyUI Flux Continuum - Modular Interface
A modular workflow that brings order to the chaos of image generation pipelines.
Updates
- 1.7.0: Enhanced workflow and usability update 📺 Watch Video Update
- Image Transfer Shortcut: Use
Ctrl+Shift+Cto copy images from Img Preview to Img Load (customizable in Settings > Keybinding > Image Transfer) - Configurable Model Router: Dynamic model selection with customizable JSON mapping for flexible workflows
- Hint System: Interactive hint nodes provide contextual help throughout the workflow
- Crop & Stitch: Enhanced inpainting/outpainting with automatic crop and stitch functionality
- Smart Guidance: Automatic guidance value of 30 for inpainting, outpainting, canny, and depth operations
- TeaCache Integration: Optional speed boost for all outputs (trades some quality for performance)
- Improved Preprocessor Preview Logic: CN Input is used for previewing when ControlNet strength > 0, otherwise uses Img Load
- Workflow Reorganization: Modules reordered for more logical flow
- Redux Naming: IP Adapter renamed to Redux for consistency with BFL terminology
- Image Transfer Shortcut: Use
-
1.6.4: ControlNet Union Pro v2 Update 📺 Watch Video Update
- ControlNet Union Pro v2: Integrated the new Depth, Canny, OpenPose ControlNets
- New canny preprocessor control
- Removed the input preview tab
- Better upscaling controls
- New Redux (IPAdapter) implementation
-
Flux Continuum Light 1.0.0:
- Light version of the workflow with all the basic functions that requires only the FLUX.1-dev model. Download
-
1.4.2: Black Forest Labs tools update
- Black Forest Labs tools: Integrated the new Redux, Depth, Canny, Fill models
- Preview Panel: Preview all your image inputs and masks at a glance
- Mask Feather Control: Feather the mask using one control
- Text Versions: Add more tabs via properties
- New Nodes: FluxContinuumModelRouter, OutputGet, OutputGetString, OutputTextDisplay, DrawTextConfig and ConfigurableDrawText
Overview
ComfyUI Flux Continuum revolutionises workflow management through a thoughtful dual-interface design:
- Front-end: A consistent control interface shared across all modules
- Back-end: Powerful, modular architecture for customisation and experimentation
✨ Core Features
Perfect for creators who want a consistent, streamlined experience across all image generation tasks, while maintaining the power to customize when needed.
-
Unified Control Interface
- Single set of controls affects all relevant modules
- Smart guidance adjustment based on operation type
- Consistent experience across all generation tasks
-
Smart Workflow Management
- Only activates nodes and models required for current task
- Toggle between different output types seamlessly
- Efficiently handles resource allocation
- Optional TeaCache for speed optimization
-
Universal Model Integration
- LoRAs, ControlNets and Redux work across all output modules
- Seamless Black Forest Labs model support
- Configurable model routing for custom workflows
-
Enhanced Usability
- Interactive hint system for contextual help
- Quick image transfer with keyboard shortcut
- Intelligent preprocessing based on control values
- Crop & stitch for seamless inpainting/outpainting
🚀 Quick Start
📺 New to Flux Continuum? Watch the tutorial first
- Clone repo to the custom nodes folder
git clone https://github.com/robertvoy/ComfyUI-Flux-Continuum
- Download and import the workflow into ComfyUI
- Install missing custom nodes using the ComfyUI Manager
- Configure your models in the config panel (press
2to access) - Download any missing models (see Model Downloads section below)
- Return to the main interface (press
1) - Select
txt2imgfrom the output selector (top left corner) - Run the workflow to generate your first image
🎯 Usage Guide
Output Selection
The workflow is controlled by the Output selector in the top-left corner. Select your desired output and all relevant controls will automatically apply.
Key Controls
🎨 Main Generation
- Prompt: Your text description for generation
- Denoise: Controls strength for img2img operations (0 = no change, 1 = completely new)
- Steps: Number of sampling steps (higher = more detail, slower)
- Guidance: How closely to follow the prompt (automatically set to 30 for inpainting/outpainting/canny/depth)
- TeaCache: Toggle for speed boost (some quality trade-off)
🖼️ Input Images
- Img Load: Primary image for all img2img operations (inpainting, outpainting, detailer, upscaling)
- CN Input: Source for ControlNet preprocessing
- Redux 1-3: Up to 3 reference images for style transfer (use very low strength values)
- Tip: Use
Ctrl+Shift+Cto quickly copy from Img Preview to Img Load
🎛️ ControlNet & Redux
- ControlNets activate when strength > 0
- When CN strength > 0, preprocessor uses CN Input; otherwise uses Img Load
- Preview preprocessor results by selecting corresponding output (e.g., "preprocessor canny")
- Redux sliders control each Redux input individually (1 = Redux 1, etc.)
Recommended ControlNet Values:
- Canny: Strength=0.7, End=0.8
- Depth: Strength=0.8, End=0.8
- Pose: Strength=0.9, End=0.65
🔧 Image Processing
- Resize, crop, sharpen, color correct, or pad images
- Preview results with "imgload prep" output
- Bypass nodes after processing to avoid reprocessing (
Ctrl+B)
⬆️ Upscaling
- Resolution Multiply: Multiplies image resolution after any preprocessing
- Upscale Model: Choose your upscaling model (recommended: 4xNomos8kDAT)
- 📺 Watch Upscaling Tutorial
🎯 Workflow Modules
Main Modules
All modules use the same unified control interface
| Module | Description | |--------|-------------| | txt2img | Standard text-to-image generation from prompts | | txt2img noise injection | Enhanced detail generation (Learn more) | | img2img | Transform existing images with text prompts | | inpainting | Edit specific areas with automatic crop & stitch using BFL Fill model | | outpainting | Expand images beyond boundaries with smart padding and BFL Fill model | | canny | Edge-guided generation using BFL Canny model | | depth | Depth-guided generation using BFL Depth model | | detailer | Focused refinement using mask selection | | ultimate upscaler | Advanced tiled upscaling with full control | | upscaler | Simple model-based upscaling |
Utility Modules
| Module | Description | |--------|-------------| | imgload prep | Preview processed images after crop/sharpen/resize/padding | | preprocessor canny | Preview canny edge detection results | | preprocessor depth | Preview depth map generation | | preprocessor openpose | Preview pose detection results |
🔧 Custom Nodes
These custom nodes were made specifically for this workflow and are required for it to work
Interface Enhancement Nodes
-
Hint Node:
- Interactive help system throughout the workflow
- Hover for contextual information
- Right-click to edit hint content
- Supports markdown formatting
-
Tabs:
- Space-saving node organization
- Add tabs via properties panel
- Compatible with most nodes
- Special handling for unsupported nodes
-
Sliders:
- Suite of pre-configured sliders
- Optimized ranges and defaults for common operations
- Includes: Denoise, Step, Guidance, Batch, GPU, ControlNet, Redux, and more
-
OutputGet System:
- Filters set nodes with prefix
Output - - OutputTextDisplay: Visual display of selected output
- OutputGetString: String output for conditional routing
- Filters set nodes with prefix
-
Text Versions:
- Multi-tab text management (default 5 tabs)
- Add more tabs via properties panel
- Save different prompt versions
- Perfect for A/B testing
-
ImageDisplay:
- Base64 image display on canvas
- Configurable via properties
- Useful for reference images
Workflow Control Nodes
-
Image Transfer Shortcut:
Ctrl+Shift+Ccopies from Img Preview to Img Load- Customizable in ComfyUI keybindings
-
Configurable Model Router:
- Dynamic model selection with JSON mapping
- Flexible routing based on conditions
- Supports lazy loading for efficiency
-
Sampler Parameter Packer/Unpacker:
- Consolidate sampler settings
- Tabbed interface for version control
-
Image Batch Boolean:
- Conditional batch processing
- Smart second image loading
-
Configurable Draw Text:
- Advanced text rendering on images
- Configurable fonts, colors, shadows, alignment
-
Pass Nodes:
- Extended pass-through for Latent, Pipe, SEGS, and Int data types
- Maintains data flow integrity
📥 Model Downloads
Required Models
unet folder:
- flux1-dev.safetensors
- flux1-depth-dev.safetensors
- flux1-canny-dev.safetensors
- flux1-fill-dev.safetensors
Note: If you don't use Canny or Depth models, you can bypass their load nodes and skip downloading them.
vae folder:
clip folder:
style_models folder:
clip_vision folder:
controlnet/FLUX folder:
- FLUX.1-dev-ControlNet-Union-Pro-2.0.safetensors (rename file)
🔜 Coming Soon
- Multi-GPU Support: Distributed processing across multiple GPUs
🙏 Acknowledgments
Special thanks to the creators of these essential custom node packs: