ComfyUI prompt control

Control LoRA and prompt scheduling, advanced text encoding, regional prompting, and much more, through your text prompt. Generates dynamic graphs that are literally identical to handcrafted noodle soup.

Prompt Control comes with PCTextEncode, which provides advanced text encoding with many additional features compared to ComfyUI’s base CLIPTextEncode.

A Basic Text to Image template is included with the extension, and can be loaded from ComfyUI’s template library.

[!NOTE]

v3.0.0 is backwards compatible with existing workflows, but requires at least ComfyUI v0.8.0

The parser was rewritten using parsy. It is intended to have the same behaviour as the old parser, but is significantly faster.

Please report any bugs or incompatibilities you find.

What can it do?

You can use text prompts to control the following:

A1111-style prompt scheduling and filtering without noodle soup.

LoRA loading and scheduling via the prompt, using ComfyUI’s hook system

Masking, composition and area control (regional prompting) with an implementation of Attention Couple, also fully schedulable.

Advanced prompt encoding

Per-encoder prompts for models with multiple text encoders, such as SDXL and Flux

Prompt combinators like BREAK, as well as CAT, AVG() and AND corresponding to ComfyUI’s ConditioningConcat, ConditioningAverage and ConditioningCombine nodes.

Different weight interpretation types (ComfyUI, A1111, compel, etc.)

Prompt masking with an implementation of cutoff

Simple prompt macros with DEF

All features are fully schedulable unless otherwise stated. See the scheduling syntax documentation to get started.

If you find prompt scheduling inconvenient for some reason, PCTextEncode can be used as a drop-in replacement for CLIPTextEncode to get everything else.

This workflow shows LoRA scheduling and prompt editing and compares it with the same prompt implemented with built-in ComfyUI nodes. You can also find it in the template library.

Compatibility

Prompt Control uses graph generation, and tries to delegate functionality to core ComfyUI wherever possible, implementing any hooks and patches in a way that is maximally compatible. This means that it should just work in most cases, even with models and nodes not explicitly supported.

If you encounter issues as a user or if you’re a node developer and Prompt Control somehow breaks something, feel free to file a bug report.

Requirements

The v3 node schema uses features that require at least ComfyUI v0.8.0

If you run into problems, update ComfyUI first.

Core nodes

Note: The documentation refers to the nodes with their internal names for consistency. The display name may change, but ComfyUI’s search will always find the nodes with the internal name. PCLazyTextEncode and PCLazyLoraLoader are the main ones you’ll want to use, also known as PC: Schedule Prompt and PC: Schedule LoRas.

PCLazyTextEncode and PCLazyTextEncodeAdvanced

PCLazyTextEncode uses ComfyUI’s lazy graph execution mechanism to generate a graph of PCTextEncode and SetConditioningTimestepRange nodes from a prompt with schedules. This has the advantage that if a part of the schedule doesn’t change, ComfyUI’s caching mechanism allows you to avoid re-encoding the non-changed part.

for example, if you first encode [cat:dog:0.1] and later change that to [cat:dog:0.5], no re-encoding takes place.

for added fun, put NODE(NodeClassName, textinputname) in a prompt to generate a graph using any other node that’s compatible. The node can’t have required parameters besides a single CLIP parameter (which must be named clip) and the text prompt, and it must return a CONDITIONING as its first return value. The “default” values are PCTextEncode and text.

For example, if you for some reason do not want the advanced features of PCTextEncode, use NODE(CLIPTextEncode) in the prompt and you’ll still get scheduling with ComfyUI’s regular TE node.

The advanced node enables filtering the prompt for multi-pass workflows.

PCLazyLoraLoader and PCLazyLoraLoaderAdvanced

This node reads LoRA expressions from the scheduled prompt and constructs a graph of LoraLoaders and CreateHookLoras as necessary to provide the necessary LoRA scheduling. Just use it in place of a LoRALoader and use the output normally.

The Advanced node gives you access to the generated hooks. If you have apply_hooks set to true, you do not need to apply the HOOKS output to a CLIP model separately; it’s provided in case you want to use it elsewhere. The advanced node also enables filtering the prompt for multi-pass workflows.

PCTextEncode

Encodes a single prompt with advanced (non-scheduling) syntax enabled. This is what actually does most of the work under the hood.

Note: PCTextEncode does not ignore and will treat it as part of the prompt. To use a combined prompt for LoRAs and your input, use PCLazyTextEncode and PCLazyLoraLoader

PCAddMaskToCLIP

This node attaches masks to a CLIP model so that they can be referred to when using the IMASK custom mask function of PCTextEncode.

PCSetTextEncodeSettings

This node configures PCTextEncode default values for some functions by attaching the information to a CLIP model.

Known issues

ComfyUI’s caching mechanism has an issue that makes it unnecessarily invalidate caches for certain inputs; you’ll still get some benefit from the lazy nodes, but changing inputs that shouldn’t affect downstream nodes (especially if using filtering) will still cause them to be recomputed because ComfyUI doesn’t realize the inputs haven’t changed.

Cutoff does not work with models that use non-CLIP text encoders, like Flux. This might be fixable, but it’s uncertain if cutoff even makes sense for those models.