🎨Stable Diffusion

Stable Diffusion Models

List Models

GET /sd/list

List all currently available Stable Diffusion models

Headers

Name	Value
Content-Type	application/json

Response

200

["Counterfeit_v3", "Anything_v5", ...]

400

List Samplers

GET /sd/sampler

List available Samplers

Headers

Name	Value
Content-Type	application/json

Response

200

["Euler", "Euler a", "LMS", ...]

400

List Loras

GET /sd/loras

List available Loras You can use loras in your prompt with <lora:Name:weight>

Headers

Name	Value
Content-Type	application/json

Response

200

[
  "0mib3_v10",
  "3DMM_V12",
  "age_slider_v20",
  "arcane_offset",
  "AstralMecha",
  ...
]

400

List Embedding

GET /sd/embeddings

List available Embeddings

Headers

Name	Value
Content-Type	application/json

Response

200

[
  "FastNegativeV2",
  "easynegative"
]

Create Image

POST /sd/:model

Send image prompt to Stable Diffusion

Headers

Name	Value
Content-Type	application/json
Authorization	Bearer <token>

Body

Name	Type	Description	Default
prompt	string	Image Prompt	none
negative_prompt	string	Negative prompt	custom
steps	number	Diffusion steps	20
cfg_scale	number	Prompt following	7
sampler	string	Diffusion sampler	DPM++ 2M Karras

Response

200

{
  "data": "d2VsbF9oZWxsb190aGVyZV90Lm1lL3N5bmFwc2VfbGFicw....."
}

400

500

Example

example.js

const res = await fetch('https://synapselabs.onrender.com/sd/Counterfeit_v3', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer <your_api_key>'
  },
  body: JSON.stringify({
    prompt: 'A cat',
    steps: 20,
    cfg_scale: 7,
    sampler: 'DPM++ 2M Karras',
  }),
});

const data = await res.json();
const buf = Buffer.from(data.data, 'base64');
fs.writeFileSync('test.png', buf);