Nodes for convenient prompt editing. The aim is to make basic generations in ComfyUI completely prompt-controllable.
The generated schedules depend on ComfyUI's timestep range feature unless you use the PCSplitSampling node.
Due to recent ComfyUI code refactoring, if you get import errors, you must update your ComfyUI installation.
You need to have lark installed in your Python environment for parsing to work (If you reuse A1111's venv, it'll already be there)
The basic nodes should now be stable, though I won't make interface guarantees quite yet.
This example workflow implements a two-pass workflow illustrating most features.
I try to avoid behavioural changes that break old prompts, but they may happen occasionally.
- 2023-10-04:
STYLE:...syntax changed toSTYLE(...)
ComfyUI does not use the step number to determine whether to apply conds; instead, it uses the sampler's timestep value which affected by the scheduler you're using. This means that when the sampler scheduler isn't linear, the schedules generated by prompt control will not be either.
Currently there doesn't seem to be a good way to change this.
You can try using the PCSplitSampling node to enable an alternative method of sampling.
Syntax is like A1111 for now, but only fractions are supported for steps.
a [large::0.1] [cat|dog:0.05] [<lora:somelora:0.5:0.6>::0.5]
[in a park:in space:0.4]
You can also use a [b:c:0.3,0.7] as a shortcut. The prompt be a until 0.3, a b until 0.7, and then c. [a:0.1,0.4] is equivalent to [a::0.1,0.4]
Alternating syntax is [a|b:pct_steps], causing the prompt to alternate every pct_steps. pct_steps defaults to 0.1 if not specified. You can also have more than two options.
The syntax [SEQ:a:N1:b:N2:c:N3] is shorthand for [a:[b:[c::N3]:N2]:N1] ie. it switches from a to b to c to nothing at the specified points in sequence.
Might be useful with Jinja templating (see Experiments below for details). For example:
[SEQ<% for x in steps(0.1, 0.9, 0.1) %>:<lora:test:<= sin(x*pi) + 0.1 =>>:<= x =><% endfor %>]
generates a LoRA schedule based on a sinewave
Instead of step percentages, you can use a tag to select part of an input:
a large [dog:cat<lora:catlora:0.5>:SECOND_PASS]
You can then use the tags parameter in the FilterSchedule node to filter the prompt. If the tag matches any tag tags (comma-separated), the second option is returned (cat, in this case, with the LoRA). Otherwise, the first option is chosen (dog, without LoRA).
the values in tags are case-insensitive, but the tags in the input must be uppercase A-Z and underscores only, or they won't be recognized. That is, [dog:cat:hr] will not work.
For example, a prompt
a [black:blue:X] [cat:dog:Y] [walking:running:Z] in space
with tags x,z would result in the prompt a blue cat running in space
-
<emb:xyz>is alternative syntax forembedding:xyzto work around a syntax conflict with[embedding:xyz:0.5]which is parsed as a schedule that switches fromembeddingtoxyz. -
The keyword
BREAKcauses the prompt to be tokenized in separate chunks, which results in each chunk being individually padded to the text encoder's maximum token length.
AND can be used to combine prompts. You can also use a weight at the end. It does a weighted sum of each prompt,
cat :1 AND dog :2
The weight defaults to 1 and are normalized so that a:2 AND b:2 is equal to a AND b. AND is processed after schedule parsing, so you can change the weight mid-prompt: cat:[1:2:0.5] AND dog
You can use MASK(x1 x2, y1 y2, weight) to specify a region mask for a prompt. The values are specified as a percentage with a float between 0 and 1, or as absolute pixel values (these can't be mixed). 1 will be interpreted as a percentage instead of a pixel value.
Masks assume a size of (512, 512), and pixel values will be relative to that. ComfyUI will scale the mask to match the image resolution, but you can change it manually by using MASK_SIZE(width, height) anywhere in the prompt,
The default values are MASK(0 1, 0 1, 1) and you can omit unnecessary ones, that is, MASK(0 0.5, 0.3) is MASK(0 0.5, 0.3 1, 1)
Note that because the default values are percentages, MASK(0 256, 64 512) is valid, but MASK(0 200) will raise an error.
Similarly, you can use AREA(x1 x2, y1 y2, weight) to specify an area for the prompt (see ComfyUI's area composition examples). The area is calculated by ComfyUI relative to your latent size.
These are handled per AND-ed prompt, so in prompt1 AND MASK(...) prompt2, the mask will only affect prompt2.
Like AND, these functions are parsed after regular scheduling syntax has been expanded, allowing things like [AREA:MASK:0.3](...), in case that's somehow useful.
Masking does not affect LoRA scheduling unless you set unet weights to 0 for a LoRA.
The ScheduleToModel node patches a model such that when sampling, it'll switch LoRAs between steps. You can apply the LoRA's effect separately to CLIP conditioning and the unet (model)
For me this seems to be quite slow without the --highvram switch because ComfyUI will shuffle things between the CPU and GPU. YMMV. When things stay on the GPU, it's quite fast.
LoRA scheduling supports AITemplate.
Due to sampler patching, your AITemplate nodes must be cloned to a directory called AIT under custom_nodes or the hijack won't find it.
AITemplate sometimes breaks because ComfyUI creates batches larger than what AITemplate can handle. You can apply this patch to ComfyUI to make AITemplate more reliable. The patch is a hack though, and may slightly deoptimize non-AIT sampling
You can use the syntax STYLE(weight_interpretation, normalization) in a prompt to affect how prompts are interpreted.
Without any extra nodes, only perp is available, which does the same as ComfyUI_PerpWeight extension.
If you have Advanced CLIP Encoding nodes cloned into your custom_nodes, more options will be available.
The style can be specified separately for each AND:ed prompt, but the first prompt is special; later prompts will "inherit" it as default. For example:
STYLE(A1111) a (red:1.1) cat with (brown:0.9) spots and a long tail AND an (old:0.5) dog AND a (green:1.4) (balloon:1.1)
will interpret everything as A1111, but
a (red:1.1) cat with (brown:0.9) spots and a long tail AND STYLE(A1111) an (old:0.5) dog AND a (green:1.4) (balloon:1.1)
Will interpret the first one using the default ComfyUI behaviour, the second prompt with A1111 and the last prompt with the default again
For things (ie. the code imports) to work, the nodes must be cloned in a directory named exactly ComfyUI_ADV_CLIP_emb.
Parses a schedule from a text prompt. A schedule is essentially an array of (valid_until, prompt) pairs that the other nodes can use.
Filters a schedule according to its parameters, removing any changes that do not occur within [start, end) as well as doing tag filtering. Always returns at least the last prompt in the schedule if everything would otherwise be filtered.
start=0, end=0 returns the prompt at the start and start=1.0, end=1.0 returns the prompt at the end.
Produces a combined conditioning for the appropriate timesteps. From a schedule. Also applies LoRAs to the CLIP model according to the schedule.
Produces a model that'll cause the sampler to reapply LoRAs at specific steps according to the schedule.
This depends on a callback handled by a monkeypatch of the ComfyUI sampler function, so it might not work with custom samplers, but it shouldn't interfere with them either.
Causes sampling to be split into multiple sampler calls instead of relying on timesteps for scheduling. This makes the schedules more accurate, but seems to cause weird behaviour with SDE samplers. (Upstream bug?)
Renders a String with Jinja2. See below for details
EditableCLIPEncode: A combination ofPromptToScheduleandScheduleToCondLoRAScheduler: A combination ofPromptToSchedule,FilterScheduleandScheduleToModel
Concatenates the input strings into one string. All inputs default to the empty string if not specified
Removes conditionings from the input whose timestep range ends before the cutoff and extends the remaining conds to cover the missing part. For example, set the cutoff to 1.0 to only leave the last prompt. This can be useful for HR passes.
If you have ComfyUI Cutoff cloned into your custom_nodes, you can use the CUT keyword to use cutoff functionality
The syntax is
a group of animals, [CUT:white cat:white], [CUT:brown dog:brown:0.5:1.0:1.0:_]
the parameters in the CUT section are region_text:target_text:weight;strict_mask:start_from_masked:padding_token of which only the first two are required.
If strict_mask, start_from_masked or padding_token are specified in more than one section, the last one takes effect for the whole prompt
a red [INT:dog:cat:0.2,0.8:0.05] will attempt to interpolate the tensors for a red dog and a red cat between the specified range in as many steps of 0.05 as will fit.
You can use the JinjaRender node to evaluate a string as a Jinja2 template. Note, however, that because ComfyUI's frontend uses {} for syntax, There are the following modifications to Jinja syntax:
{% %}becomes<% %>{{ }}becomes<= =>{# #}becomes<# #>
Jinja stuff is experimental.
The following functions and constants are available:
pimin,max,clamp(minimum, value, maximum),abs,round,ceil,floorsqrtsin,cos,tan,asin,acos,atan. These functions are rounded to two decimals
In addition, a special steps function exists.
The steps function will generate a list of steps for iterating.
You can call it either as steps(end), steps(end, step=0.1) or steps(start, end, step). step is an optional parameter that defaults to 0.1. It'll return steps inclusive of start and end as long as step doesn't go past the end.
The second form is equivalent to steps(step, end, step). i.e. it starts at the first step.
CUTdoes not work withSTYLE:perpPCSplitSamplingoverrides ComfyUI'sBrownianTreeNoiseSamplernoise sampling behaviour so that each split segment doesn't add crazy amounts of noise to the result with some samplers.- Split sampling may have weird behaviour if your step percentages go below 1 step.
- Interpolation is probably buggy and will likely change behaviour whenever code gets refactored.
- If execution is interrupted and LoRA scheduling is used, your models might be left in an undefined state until you restart ComfyUI