cakirilker/cog-comfyui | Run with an API on Replicate

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=cakirilker/cog-comfyui

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run cakirilker/cog-comfyui using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cakirilker/cog-comfyui:d6d800960f9de010e4d439538e88b3f5b608e3eab9b183e1137942e1559795b8",
  {
    input: {
      workflow_json: "",
      randomise_seeds: true,
      return_temp_files: false,
      optimise_output_images: true,
      optimise_output_images_quality: 80
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run cakirilker/cog-comfyui using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cakirilker/cog-comfyui:d6d800960f9de010e4d439538e88b3f5b608e3eab9b183e1137942e1559795b8",
    input={
        "workflow_json": "",
        "randomise_seeds": True,
        "return_temp_files": False,
        "optimise_output_images": True,
        "optimise_output_images_quality": 80
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run cakirilker/cog-comfyui using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "cakirilker/cog-comfyui:d6d800960f9de010e4d439538e88b3f5b608e3eab9b183e1137942e1559795b8",
    "input": {
      "workflow_json": "",
      "randomise_seeds": true,
      "return_temp_files": false,
      "optimise_output_images": true,
      "optimise_output_images_quality": 80
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/cakirilker/cog-comfyui@sha256:d6d800960f9de010e4d439538e88b3f5b608e3eab9b183e1137942e1559795b8 \
  -i 'workflow_json=""' \
  -i 'randomise_seeds=true' \
  -i 'return_temp_files=false' \
  -i 'optimise_output_images=true' \
  -i 'optimise_output_images_quality=80'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/cakirilker/cog-comfyui@sha256:d6d800960f9de010e4d439538e88b3f5b608e3eab9b183e1137942e1559795b8
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "workflow_json": "",
      "randomise_seeds": true,
      "return_temp_files": false,
      "optimise_output_images": true,
      "optimise_output_images_quality": 80
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.