Create a prompt
Creates a new fine-tune model from training images which in turn will be used to create prompts and generate images.
Parameters
text (required)
Description of the image.
negative_prompt (optional)
A comma separated list of words that should not appear in the image.
callback (optional)
a URL that will be called when the prompt is done processing. The callback is a POST request where the body contains the prompt object. See more.
num_images (optional)
Number of images to generate. Range: 1-8.
seed (optional)
Random number to create consistent results. Range: 0 to 2^32.
super_resolution (optional)
Boolean. X4 super-resolution.
inpaint_faces (optional)
Boolean. Requires super-resolution on. Inpaints faces.
hires_fix (optional)
Boolean. Super resolution details. Available only when super_resolution is true. Adds details.
face_correct (optional)
Boolean. Runs another AI model on top to correct the face in the image.
face_swap (optional)
Boolean. Uses training images to swap face and enhance resemblance.
cfg_scale (optional)
Float. How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt). Range 0-15
steps (optional)
Integer. Number of diffusion steps to run . Range 0-50
use_lpw (optional)
Boolean. Use weighted prompts.
w (optional)
width - In multiples of 8.
h (optional)
height - In multiples of 8.
scheduler (optional)
enum: euler, euler_a, dpm++2m_karras, dpm++sde_karras, dpm++2m, dpm++sde, lcm, tcd. If not specified the default account scheduler will be used.
backend_version (optional)
enum: null, 1, If not specified will default to the account version will be used.
style (optional)
enum: null, Cinematic, Animated, Digital Art, Photographic, Fantasy art, Neonpunk, Enhance, Comic book, Lowpoly, Line art. See more.
color_grading (optional)
enum: Film Velvia, Film Portra, Ektar.
film_grain (optional)
boolean - Adds noise to the image to make it look more realistic.
Img2Img / ControlNet
controlnet (optional)
Requires input_image. Possible values: composition, reference, segroom, ipadapter, lineart, canny, depth, mlsd, hed, pose, tile, qr.
denoising_strength (optional)
For img2img. 1.0 - Take prompt. 0.0 - Take image. Range: 0.0-1.0. Default: 0.8
controlnet_conditioning_scale (optional)
Strength of controlnet conditioning. 0.0-1.0
controlnet_txt2img (optional)
Boolean toggle. True for text to image controlnet. False for image to image controlnet.
input_image (optional)
Binary multi-part request with the image. Used in conjunction with controlnet parameter.
input_image_url (optional)
URL to an image. Used in conjunction with controlnet parameter.
mask_image (optional)
Binary multi-part request with one channel mask image. Used in conjunction with input_image parameter for inpainting
mask_image_url (optional)
URL to a one channel mask image. Used in conjunction with input_image_url parameter for inpainting.
lora_scale (optional)
Available only when used as prompts_attributes in POST /tunes request to override the default scale of the LoRA model.
Returns
Returns a prompt object if successful which will start processing if tune is processed.
POST /tunes/:id/prompts
- cURL
- Node.js
- Python
curl -X POST -H "Authorization: Bearer $API_KEY" https://api.astria.ai/tunes/1/prompts \
-F prompt[text]="a painting of ohwx man in the style of Van Gogh" \
-F prompt[negative_prompt]="old, blemish, wrin" \
-F prompt[super_resolution]=true \
-F prompt[face_correct]=true \
-F prompt[callback]="https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1"
const fetch = require(`node-fetch');
const FormData = require('form-data');
const API_URL = 'https://api.astria.ai/tunes/1/prompts';
const API_KEY = 'YOUR_API_KEY'; // Replace with your actual API key
const headers = { Authorization: `Bearer ${API_KEY}` }
const form = new FormData();
form.append('prompt[text]', 'a painting of ohwx man in the style of Van Gogh');
form.append('prompt[negative_prompt]', 'old, blemish, wrin');
form.append('prompt[super_resolution]', true);
form.append('prompt[face_correct]', true);
form.append('prompt[callback]', 'https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1');
fetch(API_URL, {
method: 'POST',
headers: headers,
body: form
}).then(response => response.json())
import requests
API_URL = 'https://api.astria.ai/tunes/1/prompts'
API_KEY = 'YOUR_API_KEY' # Replace with your actual API key
headers = {
'Authorization': f'Bearer {API_KEY}'
}
data = {
'prompt[text]': 'a painting of ohwx man in the style of Van Gogh',
'prompt[negative_prompt]': 'old, blemish, wrin',
'prompt[super_resolution]': True,
'prompt[face_correct]': True,
'prompt[callback]': 'https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1'
}
files = []
files.append((f"prompt[input_image]", load_image(prompt['input_image'])))
response = requests.post(API_URL, headers=headers, files=files, data=data)
Response
{
"id": 1,
"callback": "https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1",
"text": "a painting of ohwx man in the style of Van Gogh",
"negative_prompt": "old, blemish, wrinkles, mole",
"cfg_scale": null,
"steps": null,
"seed": null,
"trained_at": null,
"started_training_at": null,
"created_at": "2022-10-06T16:12:54.505Z",
"updated_at": "2022-10-06T16:12:54.505Z",
"tune_id": 1,
"url": "http://api.astria.ai/tunes/1/prompts/1.json"
}