lucafoscili / comfyui-lf

Custom nodes with a touch of extra UX ✨ History for primitives, JSON manipulation, logic switches with visual feedback, LLM chat, analytics nodes, CivitAI metadata fetching... and more!
MIT License
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LF Nodes for ComfyUI

LFNodes

Overview

A suite of custom nodes for ComfyUI aimed at enhancing user experience with more interactive and visually engaging widgets.

Whether you're after quality-of-life improvements or specific functionalities, this collection has something for everyone.

Most UI elements used by the widgets come from the Ketchup Lite web components library.

What kind of nodes does it offer?

That's a tough one—the nodes span quite a few categories. Here's a quick breakdown:

Table of Contents

Analytics nodes (analytics.py)

ImageHistogram

Displays a widget that plots the RGB channels of a photo in tensor format on a line chart. ImageHistogram

KeywordCounter

Counts the number of each keyword in a prompt and displays a bar chart showing their distribution, a chip-shaped widget will also allow to copy one or more keywords in the clipboard. KeywordCounter

UpdateUsageStatistics

Keep tracks of the resources used by saving datasets in the input folder of ComfyUI. The datasets will be plotted on area/scatter charts inside the twin node UsageStatistics. UpdateUsageStatistics

UsageStatistics

Displays datasets tracking the usage of resources saved with the UpdateUsageStatistics node. UsageStatistics

Configuration nodes (configuration.py)

CivitAIMetadataSetup

Allows to setup and generate CivitAI-compatible metadata information usable in the node SaveImageForCivitAI. CivitAIMetadataSetup

ControlPanel

Utilities to debug nodes and to change the theme of Ketchup Lite webcomponents. ControlPanel

LoadLoraTags

LoRA models are loaded in tag format, with a status widget displayed at the bottom indicating the loading progress. LoadLoraTags

Lora2Prompt

Converts a prompt and LoRAs to a formatted string. Lora2Prompt

LoraTag2Prompt

Processes a LoRA tag to extract keywords and count them. This node is useful for preparing prompts based on LoRA file names. LoraTag2Prompt

Notify

Triggers a browser notification when executed. Optionally, when clicked, it can queue a new prompt or focus the workflow's tab. Notify

Image manipulation nodes (image.py)

BlurImages

Applies the gaussian blur filter to a list of images and edits the filename of each image by adding the '_Blur' suffix. Blurimages

ClarityEffect

Applies a filter mimicking the clarity effect of Lightroom and Camera Raw. ClarityEffect

MultipleImageResizeForWeb

The node takes a list of images as input and generates eight additional images, each resized to common web resolutions (256px, 320px, 512px, 640px, 1024px, 1280px, 2048px, 2560px) along the longest edge. MultipleImageResizeForWeb

ResizeImageByEdge

Resizes one or more images in tensor format's longest or shortest edge to the specified size. ResizeImageByEdge

ResizeImageToDimension

Resizes an image to the longest dimension and then crops it/pads it to fit the canvas. ResizeImageToDimension

ResizeImageToSquare

Resizes one or more images in tensor format to fit a square (by cropping when the image is rectangular). ResizeImageToSquare

IO Operations nodes (io.py)

LoadFileOnce

Loads a file from a directory and then saves the name to the history. Files present in the history are skipped. LoadFileOnce

LoadImages

Node used to load multiple images from the disk given a directory. Optionally, it can fetch images from subdirectories. LoadImages

LoadMetadata

Enables uploading files to the input directory of ComfyUI, then on the workflow's execution the metadata will be extracted from the files included in the uploading process. LoadMetadata

SaveImageForCivitAI

Saves images with CivitAI-compatible metadata generated by the node CivitAIMetadataSetup. SaveImageForCivitAI

SaveJSON

Saves a JSON file at the specified path. SaveJSON

JSON nodes (json.py)

DisplayJSON

Displays JSON data with a handy button to copy the content. DisplayJSON

GetRandomKeyFromJSON

Extracts a random key from a given JSON object. This can be used to introduce variability or select random elements from JSON data. GetRandomKeyFromJSON

GetValueFromJSON

Extracts a specific value from a JSON object based on a provided key. This node supports extracting various types of values including JSON objects, strings, numbers, integers, floats, and booleans. GetValueFromJSON

ImageListFromJSON

Creates a list of images with the number set by the number of keys inside the input JSON. It also outputs the list of keys themselves. ImageListFromJSON

KeywordToggleFromJSON

Allows the selection of keywords received from a Ketchup Lite compatible JSON dataset. Values are refreshed every time the input changes. KeywordToggleFromJSON

LoadLocalJSON

Loads JSON data from a local file specified by a URL. This node is useful for importing static JSON configurations or datasets directly into ComfyUI workflows. LoadLocalJSON

SetValueInJSON

Sets a new key or updates an existing one with a new value. SetValueInJSON

ShuffleJSONKeys

Sorts the keys at root level of a JSON, returning the sorted object. Optionally it can also sort the input JSON in place without making a copy of it. ShuffleJSONKeys

SortJSONKeys

Sorts the keys at root level of a JSON, returning the sorted object. Optionally it can also sort the input JSON in place without making a copy of it. SortJSONKeys

StringToJSON

Converts a string to a JSON object. StringToJSON

WriteJSON

A simple text area that lets the user input a JSON file which will be validated when the workflow is queued. Each 2500ms the text is formatted, if there is an error it will be displayed in the title of the textarea (visible on mouseover).

WriteJSON

Large Language Model nodes (llm.py)

CharacterImpersonator

Utilizes a large language model to generate text responses as if coming from a character described by a provided biography. This node can be used for creative writing, role-playing scenarios, or generating dynamic content based on character traits. CharacterImpersonator

ImageClassifier

Utilizes a large language model to generate descriptions of images portraying characters. ImageClassifier

LLMChat

Real-time chat with an LLM model served through Koboldcpp (http://localhost:5001). It's possible to select the last messages as an output, sending them to the next node. LLMChat

LLMMessenger

A user interface capable of loading characters through a Ketchup Lite-compatible JSON and then connects to your local Koboldcpp instance (http://localhost:5001). The location, outfit and timeframe options are included in the system prompt to give more context to the LLM. Together with the biography, they define the identity of the LLM. LLMMessenger

Logic nodes (logic.py)

MathOperation

Performs mathematical operations involving up to four variables. MathOperation

ResolutionSwitcher

Selects a random resolution between portrait and landscape orientations. The chances for landscape to occur can be set with a percentage. ResolutionSwitcher

SwitchFloat

Returns one of two float values depending on a boolean condition. SwitchFloat

SwitchImage

Returns one of two images in tensor format based on a boolean condition. SwitchImage

SwitchInteger

Returns one of two integer values depending on a boolean condition. SwitchInteger

SwitchJSON

Returns one of two JSON objects depending on a boolean condition. SwitchJSON

SwitchString

Returns one of two string values based on a boolean condition. SwitchString

Primitive nodes (primitives.py)

Boolean

Used to select a boolean. It keeps record of old values, displaying a clickable list below the widget. Boolean

DisplayBoolean

Displays the value of a boolean in a widget. DisplayBoolean

DisplayFloat

Displays the value of a float in a widget. DisplayFloat

DisplayInteger

Displays the value of a integer in a widget. DisplayInteger

DisplayPrimitiveAsJSON

Displays different primitive values as a JSON output or directly in-widget through a tree-like view. DisplayPrimitiveAsJSON

DisplayString

Displays the value of a string in a widget. DisplayString

Extractor

Extracts text enclosed by a starting and ending delimiter. Extractor

Float

Used to select a float. It keeps record of old values, displaying a clickable list below the widget. Float

Integer

Used to select an integer. It keeps record of old values, displaying a clickable list below the widget. Integer

RandomBoolean

Outputs False or True depending on the chances specified by the percentage widget. 0 always false, 100 always true. RandomBoolean

Something2Number

Converts multiple inputs to integers and floats, handling nested structures and mixed types. If multiple numbers are sent to the node, they are summed. Something2Number

Something2String

Converts multiple inputs to strings, handling nested structures and mixed types. Something2String

String

Used to select a string. It keeps record of old prompts, displaying a clickable list below the textarea. String

WallOfText

Concatenates up to 10 strings, with the optional toggle to shuffle the order of concatenation. WallOfText

Seed generation nodes (seeds.py)

SequentialSeedsGenerator

Generates a series of unique seeds based on a global seed value. This node is useful for creating reproducible random sequences in workflows. SequentialSeedsGenerator

UrandomSeedGenerator

Generates up to 20 different seeds through the use of the Python urandom function which leverages CPU generated entropy for increased randomness. UrandomSeedGenerator

Selector nodes (selectors.py)

CheckpointSelector

Used to select a checkpoint. It's possible to fetch additional data from CivitAI or by loading the related cover inside the checkpoints folder. CheckpointSelector

EmbeddingSelector

Used to select an embedding. It's possible to fetch additional data from CivitAI or by loading the related cover inside the embeddings folder. EmbeddingSelector

LoraSelector

Used to select a LoRA. It's possible to fetch additional data from CivitAI or by loading the related cover inside the loras folder. LoraSelector

LoraAndEmbeddingSelector

Using a LoRA name as pilot, it also selects its related embedding (it must have the same name). Useful for models trained with pivotal training. LoraAndEmbeddingSelector

SamplerSelector

Used to select a sampler, the history widget allows for a quick swap between the most used samplers. SamplerSelector

SchedulerSelector

Used to select a scheduler, the history widget allows for a quick swap between the most used schedulers. SchedulerSelector

UpscaleModelSelector

Used to select an upscale model, the history widget allows for a quick swap between the most used upscale models. UpscaleModelSelector

VAESelector

Used to select a VAE, the history widget allows for a quick swap between the most used VAEs. VAESelector

Installation

Using ComfyUI Manager

Manual

Notes

The LLM nodes are designed to work with Koboldcpp. The model used in the workflows samples is UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3 with ChaoticNeutrals/LLaVA-Llama-3-8B-mmproj-Updated.

Contributing

Contributions to this repository are welcome, feel free to submit pull requests or open issues for discussion! To setup the environment clone this repository, then from the root open a terminal and run the command

pip install -r requirements.txt

This will install all the required dependencies for the Python back-end.

npm run setup

This command will install all the frontend dependencies. Note that the repository includes the compiled files directly to allow Comfy to load them, dependencies are only needed for actual development.

npm run build

This command will compile all the frontend sources and generate/refresh the actual web directory.

License

MIT License