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a node toolkit to allow serving your workflow (for example using discord

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ComfyUI Serving Toolkit

Welcome to the ComfyUI Serving Toolkit, a powerful tool for serving image generation workflows in Discord and other platforms (soon). This toolkit is designed to simplify the process of serving your ComfyUI workflow, making image generation bots easier than ever before. You can serve on discord, or on websockets.

  • allowed_user - (Optional) The Telegram username of the user allowed to use the bot. If not set, all users can use the bot.

If you need any help, Checkout the Discord!

Features

  • Allows both Images or videos (when in batch mode, such as animatediff - if you return more than one image it will create a video)
  • Add arguments with default values, then allow your users to use them
  • Serve from your own computer, workflow is not inserted into the images so your secrets are 100% safe
  • Support for multiple serving options: Discord, Telegram, HTTP and WebSockets

Installation

Use ComfyUI Manager or put all the files inside custom_nodes and run:

..\..\..\python_embeded\python.exe -s -m pip install -r requirements.txt

The simplest configuration

Here a simple workflow that will get a !generate <prompt> and resond with an image image

You can copy the workflow json: discordserv.json

Running

After setting up your workflow, In order for the serving to always be up, you need to allow auto queue, here is an image to help you do that:

image

This will require you to keep your ComfyUI and computer running.

Nodes

DiscordServing

This node is an essencial part of the serving, queueing the prompt it will wait for a single message, process it and optionally return the image. Note that in order for it to work for all messages you would have to mark Auto Queue (details above in the running section)

Inputs:

  • discord_token - here is how you get one , make sure to enable message viewing intent
  • command_name - the command used to generate, without the '!'. defaults to generate (so you would have to do !generate <your prompt> --your_argument1 <argument value>

Outputs:

  • Serving Config - A basic reference for this serving, used by the other nodes of this toolkit to get arguments and return images.

WebsocketServing

This will connect to a websocket and wait for JSON of {_requestId, prompt, arguments} and will return a json of {_requestId, base64_img} You can see an example ws server over at examples/websocket.js to run it you would need to navigate to the examples folder and run these commands:

npm install
node websocket.js

Inputs:

  • websocket_url - the url of the websocket you connect to, if you use the example it will be ws://localhost:8080

Outputs:

  • Serving Config - A basic reference for this serving, used by the other nodes of this toolkit to get arguments and return images.

ServingInputText

Allows you to grab a text arguments from the request

Discord example:

When a user types: !generate 4k epic realism portrait --negative drawing you could set the argument=negative and then recieve the value of "drawing" inside the output text.

Inputs:

  • serving_config - a config made by a serving node
  • argument - the argument name, the prompt itself will be inside the "prompt" argument. When using discord serving, you can access attachments url using 'attachment_url_0' (and attachment_url_1 etc). then you can use nodes like WAS Image Load to download these images
  • default - the default value of this argument

Outputs: text - the value of the argument

ServingInputNumber

similar to ServingInputText, this one is for numbers. it is important to set the minimum, maximum and step to the right values in order to avoid errors (for example when trying a width that does isn't divisable by 16) Inputs that are not in ServingInputText:

  • max_value - the maximum value of this argument
  • min_value - the minimum value of this argument
  • step - the steps of this value (setting this to 1 will ensure only whole numbers, 0.5 will allow jumps of half etc)

Serving Image/Video Output

Allows you to return an image/video back to the request Inputs:

  • image - the generated image. note that if this is more than one image (for example in the case of batches or animatediff frames) it will return a video
  • duration - in the case of a video, what is the time in miliseconds each frame should appear? if you have an FPS number you can use 1000/FPS to calculate the duration value

TelegramServing

This node allows you to serve your workflow via Telegram. It listens for commands and processes them, enabling interaction with your ComfyUI workflow through a Telegram bot.

Inputs:

  • telegram_token - Your Telegram bot token obtained from the BotFather
  • command_name - The command used to generate, without the '/'. Defaults to 'generate' (so you would have to do /generate --your_argument1 )

Outputs:

  • Serving Config - A basic reference for this serving, used by the other nodes of this toolkit to get arguments and return images.

HTTPServing

This node enables serving your workflow via HTTP, allowing you to interact with your ComfyUI workflow through HTTP POST requests.

Inputs:

  • port - The port number on which the HTTP server will run. Defaults to 8000.

Outputs:

  • Serving Config - A basic reference for this serving, used by the other nodes of this toolkit to get arguments and return images.

ServingMultiImageOutput

Allows you to return multiple images back to the request. This is useful for batch processing or when generating animations.

Inputs:

  • serving_config - A config made by a serving node
  • images - The generated images

ServingInputImage

Allows you to input images from the serving platform (e.g., attachments in Discord, Telegram, or files sent via HTTP).

Inputs:

  • serving_config - A config made by a serving node
  • default_image - (Optional) A default image to use if no attachment is found

Outputs:

  • image - The input image as a tensor

ServingInputImageAsLatent

Similar to ServingInputImage, but converts the input image directly into a latent representation for use in your workflow.

Inputs:

  • serving_config - A config made by a serving node
  • vae - The VAE model to use for encoding
  • default_latent - (Optional) A default latent to use if no attachment is found

Outputs:

  • latent - The input image encoded as a latent

Support

image

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