1const axios = require('axios');
4const api_key = "YOUR API-KEY";
5const url = "";
7const data = {
8  "prompt": "jwst, nebula, spiral galaxy,mixed colors,outerspace, hyper quality, intricate detail, ultra realistic, maximum detail, foreground focus, instagram, 8k, volumetric light, cinematic, octane render, uplight, no blur, 8k",
9  "negative_prompt": "ng_deepnegative_v1_75t,badhandv4, (worst quality:2), (low quality:2), (normal quality:2), lowres,watermark, single color, monochrome",
10  "scheduler": "dpmpp_2m",
11  "num_inference_steps": 30,
12  "guidance_scale": 7,
13  "samples": 1,
14  "seed": 720692329,
15  "img_width": 512,
16  "img_height": 768,
17  "base64": false
20(async function() {
21    try {
22        const response = await, data, { headers: { 'x-api-key': api_key } });
23        console.log(;
24    } catch (error) {
25        console.error('Error:',;
26    }
HTTP Response Codes
200 - OKImage Generated
401 - UnauthorizedUser authentication failed
404 - Not FoundThe requested URL does not exist
405 - Method Not AllowedThe requested HTTP method is not allowed
406 - Not AcceptableNot enough credits
500 - Server ErrorServer had some issue with processing


promptstr *

Prompt to render

negative_promptstr ( default: None )

Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'

schedulerenum:str ( default: UniPC )

Type of scheduler.

Allowed values:

num_inference_stepsint ( default: 20 ) Affects Pricing

Number of denoising steps.

min : 20,

min : 100

guidance_scalefloat ( default: 7.5 )

Scale for classifier-free guidance

min : 0.1,

min : 25

samplesint ( default: 1 ) Affects Pricing

Number of samples to generate.

min : 1,

min : 4

seedint ( default: -1 )

Seed for image generation.

img_widthenum:int ( default: 512 ) Affects Pricing

Width of the image.

Allowed values:

img_heightenum:int ( default: 512 ) Affects Pricing

Height of the Image

Allowed values:

base64boolean ( default: 1 )

Base64 encoding of the output image.

To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.

Deep Space Diffusion

Deep Space Diffusion stands out with its specialized training on high-quality space imagery. By incorporating visuals from the James Webb Space Telescope and Judy Schmidt's astrophotography, the model offers unparalleled accuracy and beauty in space-themed image generation. This model is a gateway to creating breathtaking cosmic imagery, perfect for astronomers, artists, and space enthusiasts.


  1. Specialized Training: Harnesses images from the James Webb Space Telescope and Judy Schmidt for authentic space visuals..

  2. Easy-to-Use Token: Simply include "JWST" in your prompts (e.g., "jwst, green spiral galaxy") to activate the model's unique style..

  3. Optimized for Creativity:: Ideal for educational content, artistic projects, and space exploration visualizations.

Use Cases

  1. Educational Content:Create accurate and engaging visuals for astronomy education and space exploration.

  2. Scientific Visualization: Assist researchers and astronomers in visualizing celestial phenomena and theoretical concepts.

  3. Artistic Projects: Generate unique space-themed artwork for exhibitions, digital art, or personal collections.

  4. Personal Projects: For space enthusiasts and hobbyists looking to create their own interpretations of the cosmos.