asppj/cog-comfyui-img:c493b0bb | Run with an API on Replicate

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asppj /cog-comfyui-img:c493b0bb

Input

workflow_json

string

Shift + Return to add a new line

{"3": {"inputs": {"seed": 237514639057514, "steps": 20, "cfg": 2.5, "sampler_name": "euler", "scheduler": "karras", "denoise": 1, "model": ["14", 0], "positive": ["12", 0], "negative": ["12", 1], "latent_image": ["12", 2]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "8": {"inputs": {"samples": ["3", 0], "vae": ["15", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "10": {"inputs": {"filename_prefix": "ComfyUI", "fps": 10, "lossless": false, "quality": 85, "method": "default", "images": ["8", 0]}, "class_type": "SaveAnimatedWEBP", "_meta": {"title": "SaveAnimatedWEBP"}}, "12": {"inputs": {"width": 1024, "height": 576, "video_frames": 25, "motion_bucket_id": 127, "fps": 6, "augmentation_level": 0, "clip_vision": ["15", 1], "init_image": ["20", 0], "vae": ["15", 2]}, "class_type": "SVD_img2vid_Conditioning", "_meta": {"title": "SVD_img2vid_Conditioning"}}, "14": {"inputs": {"min_cfg": 1, "model": ["15", 0]}, "class_type": "VideoLinearCFGGuidance", "_meta": {"title": "VideoLinearCFGGuidance"}}, "15": {"inputs": {"ckpt_name": "svd_xt.safetensors"}, "class_type": "ImageOnlyCheckpointLoader", "_meta": {"title": "Image Only Checkpoint Loader (img2vid model)"}}, "16": {"inputs": {"ckpt_name": "sd_xl_base_1.0.safetensors"}, "class_type": "CheckpointLoaderSimple", "_meta": {"title": "Load Checkpoint"}}, "17": {"inputs": {"seed": 144698910769133, "steps": 15, "cfg": 8, "sampler_name": "uni_pc_bh2", "scheduler": "normal", "denoise": 1, "model": ["16", 0], "positive": ["18", 0], "negative": ["19", 0], "latent_image": ["22", 0]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "18": {"inputs": {"text": "A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.", "clip": ["16", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "19": {"inputs": {"text": "watermark", "clip": ["16", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "20": {"inputs": {"samples": ["17", 0], "vae": ["16", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "21": {"inputs": {"images": ["20", 0]}, "class_type": "PreviewImage", "_meta": {"title": "Preview Image"}}, "22": {"inputs": {"width": 1024, "height": 576, "batch_size": 1}, "class_type": "EmptyLatentImage", "_meta": {"title": "Empty Latent Image"}}}{"3": {"inputs": {"seed": 237514639057514, "steps": 20, "cfg": 2.5, "sampler_name": "euler", "scheduler": "karras", "denoise": 1, "model": ["14", 0], "positive": ["12", 0], "negative": ["12", 1], "latent_image": ["12", 2]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "8": {"inputs": {"samples": ["3", 0], "vae": ["15", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "10": {"inputs": {"filename_prefix": "ComfyUI", "fps": 10, "lossless": false, "quality": 85, "method": "default", "images": ["8", 0]}, "class_type": "SaveAnimatedWEBP", "_meta": {"title": "SaveAnimatedWEBP"}}, "12": {"inputs": {"width": 1024, "height": 576, "video_frames": 25, "motion_bucket_id": 127, "fps": 6, "augmentation_level": 0, "clip_vision": ["15", 1], "init_image": ["20", 0], "vae": ["15", 2]}, "class_type": "SVD_img2vid_Conditioning", "_meta": {"title": "SVD_img2vid_Conditioning"}}, "14": {"inputs": {"min_cfg": 1, "model": ["15", 0]}, "class_type": "VideoLinearCFGGuidance", "_meta": {"title": "VideoLinearCFGGuidance"}}, "15": {"inputs": {"ckpt_name": "svd_xt.safetensors"}, "class_type": "ImageOnlyCheckpointLoader", "_meta": {"title": "Image Only Checkpoint Loader (img2vid model)"}}, "16": {"inputs": {"ckpt_name": "sd_xl_base_1.0.safetensors"}, "class_type": "CheckpointLoaderSimple", "_meta": {"title": "Load Checkpoint"}}, "17": {"inputs": {"seed": 144698910769133, "steps": 15, "cfg": 8, "sampler_name": "uni_pc_bh2", "scheduler": "normal", "denoise": 1, "model": ["16", 0], "positive": ["18", 0], "negative": ["19", 0], "latent_image": ["22", 0]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "18": {"inputs": {"text": "A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.", "clip": ["16", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "19": {"inputs": {"text": "watermark", "clip": ["16", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "20": {"inputs": {"samples": ["17", 0], "vae": ["16", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "21": {"inputs": {"images": ["20", 0]}, "class_type": "PreviewImage", "_meta": {"title": "Preview Image"}}, "22": {"inputs": {"width": 1024, "height": 576, "batch_size": 1}, "class_type": "EmptyLatentImage", "_meta": {"title": "Empty Latent Image"}}}

Your ComfyUI workflow as JSON. You must use the API version of your workflow. Get it from ComfyUI using ‘Save (API format)’. Instructions here: https://github.com/fofr/cog-comfyui

Default: "{\"3\": {\"inputs\": {\"seed\": 237514639057514, \"steps\": 20, \"cfg\": 2.5, \"sampler_name\": \"euler\", \"scheduler\": \"karras\", \"denoise\": 1, \"model\": [\"14\", 0], \"positive\": [\"12\", 0], \"negative\": [\"12\", 1], \"latent_image\": [\"12\", 2]}, \"class_type\": \"KSampler\", \"_meta\": {\"title\": \"KSampler\"}}, \"8\": {\"inputs\": {\"samples\": [\"3\", 0], \"vae\": [\"15\", 2]}, \"class_type\": \"VAEDecode\", \"_meta\": {\"title\": \"VAE Decode\"}}, \"10\": {\"inputs\": {\"filename_prefix\": \"ComfyUI\", \"fps\": 10, \"lossless\": false, \"quality\": 85, \"method\": \"default\", \"images\": [\"8\", 0]}, \"class_type\": \"SaveAnimatedWEBP\", \"_meta\": {\"title\": \"SaveAnimatedWEBP\"}}, \"12\": {\"inputs\": {\"width\": 1024, \"height\": 576, \"video_frames\": 25, \"motion_bucket_id\": 127, \"fps\": 6, \"augmentation_level\": 0, \"clip_vision\": [\"15\", 1], \"init_image\": [\"20\", 0], \"vae\": [\"15\", 2]}, \"class_type\": \"SVD_img2vid_Conditioning\", \"_meta\": {\"title\": \"SVD_img2vid_Conditioning\"}}, \"14\": {\"inputs\": {\"min_cfg\": 1, \"model\": [\"15\", 0]}, \"class_type\": \"VideoLinearCFGGuidance\", \"_meta\": {\"title\": \"VideoLinearCFGGuidance\"}}, \"15\": {\"inputs\": {\"ckpt_name\": \"svd_xt.safetensors\"}, \"class_type\": \"ImageOnlyCheckpointLoader\", \"_meta\": {\"title\": \"Image Only Checkpoint Loader (img2vid model)\"}}, \"16\": {\"inputs\": {\"ckpt_name\": \"sd_xl_base_1.0.safetensors\"}, \"class_type\": \"CheckpointLoaderSimple\", \"_meta\": {\"title\": \"Load Checkpoint\"}}, \"17\": {\"inputs\": {\"seed\": 144698910769133, \"steps\": 15, \"cfg\": 8, \"sampler_name\": \"uni_pc_bh2\", \"scheduler\": \"normal\", \"denoise\": 1, \"model\": [\"16\", 0], \"positive\": [\"18\", 0], \"negative\": [\"19\", 0], \"latent_image\": [\"22\", 0]}, \"class_type\": \"KSampler\", \"_meta\": {\"title\": \"KSampler\"}}, \"18\": {\"inputs\": {\"text\": \"A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.\", \"clip\": [\"16\", 1]}, \"class_type\": \"CLIPTextEncode\", \"_meta\": {\"title\": \"CLIP Text Encode (Prompt)\"}}, \"19\": {\"inputs\": {\"text\": \"watermark\", \"clip\": [\"16\", 1]}, \"class_type\": \"CLIPTextEncode\", \"_meta\": {\"title\": \"CLIP Text Encode (Prompt)\"}}, \"20\": {\"inputs\": {\"samples\": [\"17\", 0], \"vae\": [\"16\", 2]}, \"class_type\": \"VAEDecode\", \"_meta\": {\"title\": \"VAE Decode\"}}, \"21\": {\"inputs\": {\"images\": [\"20\", 0]}, \"class_type\": \"PreviewImage\", \"_meta\": {\"title\": \"Preview Image\"}}, \"22\": {\"inputs\": {\"width\": 1024, \"height\": 576, \"batch_size\": 1}, \"class_type\": \"EmptyLatentImage\", \"_meta\": {\"title\": \"Empty Latent Image\"}}}"

input_file

file

Input image, tar or zip file. Read guidance on workflows and input files here: https://github.com/fofr/cog-comfyui. Alternatively, you can replace inputs with URLs in your JSON workflow and the model will download them.

return_temp_files

boolean

Return any temporary files, such as preprocessed controlnet images. Useful for debugging.

Default: false

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 95

randomise_seeds

boolean

Automatically randomise seeds (seed, noise_seed, rand_seed)

Default: true

force_reset_cache

boolean

Force reset the ComfyUI cache before running the workflow. Useful for debugging.

Default: false

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

npx create-replicate --model=asppj/cog-comfyui-img

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

const output = await replicate.run(
  "asppj/cog-comfyui-img:c493b0bb1bb7d8ccbc95ff0a7787a093a018d28976e728742fda6c44f17ccc5e",
  {
    input: {
      output_format: "webp",
      workflow_json: "{\"3\": {\"inputs\": {\"seed\": 237514639057514, \"steps\": 20, \"cfg\": 2.5, \"sampler_name\": \"euler\", \"scheduler\": \"karras\", \"denoise\": 1, \"model\": [\"14\", 0], \"positive\": [\"12\", 0], \"negative\": [\"12\", 1], \"latent_image\": [\"12\", 2]}, \"class_type\": \"KSampler\", \"_meta\": {\"title\": \"KSampler\"}}, \"8\": {\"inputs\": {\"samples\": [\"3\", 0], \"vae\": [\"15\", 2]}, \"class_type\": \"VAEDecode\", \"_meta\": {\"title\": \"VAE Decode\"}}, \"10\": {\"inputs\": {\"filename_prefix\": \"ComfyUI\", \"fps\": 10, \"lossless\": false, \"quality\": 85, \"method\": \"default\", \"images\": [\"8\", 0]}, \"class_type\": \"SaveAnimatedWEBP\", \"_meta\": {\"title\": \"SaveAnimatedWEBP\"}}, \"12\": {\"inputs\": {\"width\": 1024, \"height\": 576, \"video_frames\": 25, \"motion_bucket_id\": 127, \"fps\": 6, \"augmentation_level\": 0, \"clip_vision\": [\"15\", 1], \"init_image\": [\"20\", 0], \"vae\": [\"15\", 2]}, \"class_type\": \"SVD_img2vid_Conditioning\", \"_meta\": {\"title\": \"SVD_img2vid_Conditioning\"}}, \"14\": {\"inputs\": {\"min_cfg\": 1, \"model\": [\"15\", 0]}, \"class_type\": \"VideoLinearCFGGuidance\", \"_meta\": {\"title\": \"VideoLinearCFGGuidance\"}}, \"15\": {\"inputs\": {\"ckpt_name\": \"svd_xt.safetensors\"}, \"class_type\": \"ImageOnlyCheckpointLoader\", \"_meta\": {\"title\": \"Image Only Checkpoint Loader (img2vid model)\"}}, \"16\": {\"inputs\": {\"ckpt_name\": \"sd_xl_base_1.0.safetensors\"}, \"class_type\": \"CheckpointLoaderSimple\", \"_meta\": {\"title\": \"Load Checkpoint\"}}, \"17\": {\"inputs\": {\"seed\": 144698910769133, \"steps\": 15, \"cfg\": 8, \"sampler_name\": \"uni_pc_bh2\", \"scheduler\": \"normal\", \"denoise\": 1, \"model\": [\"16\", 0], \"positive\": [\"18\", 0], \"negative\": [\"19\", 0], \"latent_image\": [\"22\", 0]}, \"class_type\": \"KSampler\", \"_meta\": {\"title\": \"KSampler\"}}, \"18\": {\"inputs\": {\"text\": \"A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.\", \"clip\": [\"16\", 1]}, \"class_type\": \"CLIPTextEncode\", \"_meta\": {\"title\": \"CLIP Text Encode (Prompt)\"}}, \"19\": {\"inputs\": {\"text\": \"watermark\", \"clip\": [\"16\", 1]}, \"class_type\": \"CLIPTextEncode\", \"_meta\": {\"title\": \"CLIP Text Encode (Prompt)\"}}, \"20\": {\"inputs\": {\"samples\": [\"17\", 0], \"vae\": [\"16\", 2]}, \"class_type\": \"VAEDecode\", \"_meta\": {\"title\": \"VAE Decode\"}}, \"21\": {\"inputs\": {\"images\": [\"20\", 0]}, \"class_type\": \"PreviewImage\", \"_meta\": {\"title\": \"Preview Image\"}}, \"22\": {\"inputs\": {\"width\": 1024, \"height\": 576, \"batch_size\": 1}, \"class_type\": \"EmptyLatentImage\", \"_meta\": {\"title\": \"Empty Latent Image\"}}}",
      output_quality: 95,
      randomise_seeds: true,
      force_reset_cache: false,
      return_temp_files: false
    }
  }
);

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

output = replicate.run(
    "asppj/cog-comfyui-img:c493b0bb1bb7d8ccbc95ff0a7787a093a018d28976e728742fda6c44f17ccc5e",
    input={
        "output_format": "webp",
        "workflow_json": "{\"3\": {\"inputs\": {\"seed\": 237514639057514, \"steps\": 20, \"cfg\": 2.5, \"sampler_name\": \"euler\", \"scheduler\": \"karras\", \"denoise\": 1, \"model\": [\"14\", 0], \"positive\": [\"12\", 0], \"negative\": [\"12\", 1], \"latent_image\": [\"12\", 2]}, \"class_type\": \"KSampler\", \"_meta\": {\"title\": \"KSampler\"}}, \"8\": {\"inputs\": {\"samples\": [\"3\", 0], \"vae\": [\"15\", 2]}, \"class_type\": \"VAEDecode\", \"_meta\": {\"title\": \"VAE Decode\"}}, \"10\": {\"inputs\": {\"filename_prefix\": \"ComfyUI\", \"fps\": 10, \"lossless\": false, \"quality\": 85, \"method\": \"default\", \"images\": [\"8\", 0]}, \"class_type\": \"SaveAnimatedWEBP\", \"_meta\": {\"title\": \"SaveAnimatedWEBP\"}}, \"12\": {\"inputs\": {\"width\": 1024, \"height\": 576, \"video_frames\": 25, \"motion_bucket_id\": 127, \"fps\": 6, \"augmentation_level\": 0, \"clip_vision\": [\"15\", 1], \"init_image\": [\"20\", 0], \"vae\": [\"15\", 2]}, \"class_type\": \"SVD_img2vid_Conditioning\", \"_meta\": {\"title\": \"SVD_img2vid_Conditioning\"}}, \"14\": {\"inputs\": {\"min_cfg\": 1, \"model\": [\"15\", 0]}, \"class_type\": \"VideoLinearCFGGuidance\", \"_meta\": {\"title\": \"VideoLinearCFGGuidance\"}}, \"15\": {\"inputs\": {\"ckpt_name\": \"svd_xt.safetensors\"}, \"class_type\": \"ImageOnlyCheckpointLoader\", \"_meta\": {\"title\": \"Image Only Checkpoint Loader (img2vid model)\"}}, \"16\": {\"inputs\": {\"ckpt_name\": \"sd_xl_base_1.0.safetensors\"}, \"class_type\": \"CheckpointLoaderSimple\", \"_meta\": {\"title\": \"Load Checkpoint\"}}, \"17\": {\"inputs\": {\"seed\": 144698910769133, \"steps\": 15, \"cfg\": 8, \"sampler_name\": \"uni_pc_bh2\", \"scheduler\": \"normal\", \"denoise\": 1, \"model\": [\"16\", 0], \"positive\": [\"18\", 0], \"negative\": [\"19\", 0], \"latent_image\": [\"22\", 0]}, \"class_type\": \"KSampler\", \"_meta\": {\"title\": \"KSampler\"}}, \"18\": {\"inputs\": {\"text\": \"A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.\", \"clip\": [\"16\", 1]}, \"class_type\": \"CLIPTextEncode\", \"_meta\": {\"title\": \"CLIP Text Encode (Prompt)\"}}, \"19\": {\"inputs\": {\"text\": \"watermark\", \"clip\": [\"16\", 1]}, \"class_type\": \"CLIPTextEncode\", \"_meta\": {\"title\": \"CLIP Text Encode (Prompt)\"}}, \"20\": {\"inputs\": {\"samples\": [\"17\", 0], \"vae\": [\"16\", 2]}, \"class_type\": \"VAEDecode\", \"_meta\": {\"title\": \"VAE Decode\"}}, \"21\": {\"inputs\": {\"images\": [\"20\", 0]}, \"class_type\": \"PreviewImage\", \"_meta\": {\"title\": \"Preview Image\"}}, \"22\": {\"inputs\": {\"width\": 1024, \"height\": 576, \"batch_size\": 1}, \"class_type\": \"EmptyLatentImage\", \"_meta\": {\"title\": \"Empty Latent Image\"}}}",
        "output_quality": 95,
        "randomise_seeds": True,
        "force_reset_cache": False,
        "return_temp_files": False
    }
)
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 asppj/cog-comfyui-img 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": "asppj/cog-comfyui-img:c493b0bb1bb7d8ccbc95ff0a7787a093a018d28976e728742fda6c44f17ccc5e",
    "input": {
      "output_format": "webp",
      "workflow_json": "{\\"3\\": {\\"inputs\\": {\\"seed\\": 237514639057514, \\"steps\\": 20, \\"cfg\\": 2.5, \\"sampler_name\\": \\"euler\\", \\"scheduler\\": \\"karras\\", \\"denoise\\": 1, \\"model\\": [\\"14\\", 0], \\"positive\\": [\\"12\\", 0], \\"negative\\": [\\"12\\", 1], \\"latent_image\\": [\\"12\\", 2]}, \\"class_type\\": \\"KSampler\\", \\"_meta\\": {\\"title\\": \\"KSampler\\"}}, \\"8\\": {\\"inputs\\": {\\"samples\\": [\\"3\\", 0], \\"vae\\": [\\"15\\", 2]}, \\"class_type\\": \\"VAEDecode\\", \\"_meta\\": {\\"title\\": \\"VAE Decode\\"}}, \\"10\\": {\\"inputs\\": {\\"filename_prefix\\": \\"ComfyUI\\", \\"fps\\": 10, \\"lossless\\": false, \\"quality\\": 85, \\"method\\": \\"default\\", \\"images\\": [\\"8\\", 0]}, \\"class_type\\": \\"SaveAnimatedWEBP\\", \\"_meta\\": {\\"title\\": \\"SaveAnimatedWEBP\\"}}, \\"12\\": {\\"inputs\\": {\\"width\\": 1024, \\"height\\": 576, \\"video_frames\\": 25, \\"motion_bucket_id\\": 127, \\"fps\\": 6, \\"augmentation_level\\": 0, \\"clip_vision\\": [\\"15\\", 1], \\"init_image\\": [\\"20\\", 0], \\"vae\\": [\\"15\\", 2]}, \\"class_type\\": \\"SVD_img2vid_Conditioning\\", \\"_meta\\": {\\"title\\": \\"SVD_img2vid_Conditioning\\"}}, \\"14\\": {\\"inputs\\": {\\"min_cfg\\": 1, \\"model\\": [\\"15\\", 0]}, \\"class_type\\": \\"VideoLinearCFGGuidance\\", \\"_meta\\": {\\"title\\": \\"VideoLinearCFGGuidance\\"}}, \\"15\\": {\\"inputs\\": {\\"ckpt_name\\": \\"svd_xt.safetensors\\"}, \\"class_type\\": \\"ImageOnlyCheckpointLoader\\", \\"_meta\\": {\\"title\\": \\"Image Only Checkpoint Loader (img2vid model)\\"}}, \\"16\\": {\\"inputs\\": {\\"ckpt_name\\": \\"sd_xl_base_1.0.safetensors\\"}, \\"class_type\\": \\"CheckpointLoaderSimple\\", \\"_meta\\": {\\"title\\": \\"Load Checkpoint\\"}}, \\"17\\": {\\"inputs\\": {\\"seed\\": 144698910769133, \\"steps\\": 15, \\"cfg\\": 8, \\"sampler_name\\": \\"uni_pc_bh2\\", \\"scheduler\\": \\"normal\\", \\"denoise\\": 1, \\"model\\": [\\"16\\", 0], \\"positive\\": [\\"18\\", 0], \\"negative\\": [\\"19\\", 0], \\"latent_image\\": [\\"22\\", 0]}, \\"class_type\\": \\"KSampler\\", \\"_meta\\": {\\"title\\": \\"KSampler\\"}}, \\"18\\": {\\"inputs\\": {\\"text\\": \\"A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.\\", \\"clip\\": [\\"16\\", 1]}, \\"class_type\\": \\"CLIPTextEncode\\", \\"_meta\\": {\\"title\\": \\"CLIP Text Encode (Prompt)\\"}}, \\"19\\": {\\"inputs\\": {\\"text\\": \\"watermark\\", \\"clip\\": [\\"16\\", 1]}, \\"class_type\\": \\"CLIPTextEncode\\", \\"_meta\\": {\\"title\\": \\"CLIP Text Encode (Prompt)\\"}}, \\"20\\": {\\"inputs\\": {\\"samples\\": [\\"17\\", 0], \\"vae\\": [\\"16\\", 2]}, \\"class_type\\": \\"VAEDecode\\", \\"_meta\\": {\\"title\\": \\"VAE Decode\\"}}, \\"21\\": {\\"inputs\\": {\\"images\\": [\\"20\\", 0]}, \\"class_type\\": \\"PreviewImage\\", \\"_meta\\": {\\"title\\": \\"Preview Image\\"}}, \\"22\\": {\\"inputs\\": {\\"width\\": 1024, \\"height\\": 576, \\"batch_size\\": 1}, \\"class_type\\": \\"EmptyLatentImage\\", \\"_meta\\": {\\"title\\": \\"Empty Latent Image\\"}}}",
      "output_quality": 95,
      "randomise_seeds": true,
      "force_reset_cache": false,
      "return_temp_files": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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