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, 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.

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, ipadapter, lineart, canny, depth, mlsd, hed, pose, pose_with_hand, pose_with_face, pose_face_and_hand, 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.

Returns

Returns a prompt object if successful which will start processing if tune is processed.

POST /tunes/:id/prompts

cURL

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" 

Node.js

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())

Python

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"tune[prompts_attributes][{i}][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"
}