Novita AI Text to Image API: Generate Stunning Visuals from Text with Stable Diffusion

Text to Image

curl --request POST \
  --url https://api.novita.ai/v3/async/txt2img \
  --header 'Authorization: <authorization>' \
  --header 'Content-Type: <content-type>' \
  --data '
{
  "extra": {
    "response_image_type": "<string>",
    "webhook": {
      "url": "<string>",
      "test_mode": {
        "enabled": true,
        "return_task_status": "<string>"
      }
    },
    "custom_storage": {
      "aws_s3": {
        "region": "<string>",
        "bucket": "<string>",
        "path": "<string>",
        "save_to_path_directly": true
      }
    },
    "enterprise_plan": {
      "enabled": true
    },
    "enable_nsfw_detection": true,
    "nsfw_detection_level": 123
  },
  "request": {
    "model_name": "<string>",
    "prompt": "<string>",
    "width": 123,
    "height": 123,
    "image_num": 123,
    "steps": 123,
    "guidance_scale": 123,
    "sampler_name": "<string>",
    "negative_prompt": "<string>",
    "sd_vae": "<string>",
    "seed": 123,
    "loras": [
      {
        "model_name": "<string>",
        "strength": 123
      }
    ],
    "embeddings": [
      {
        "model_name": "<string>"
      }
    ],
    "hires_fix": {
      "target_width": 123,
      "target_height": 123,
      "strength": 123,
      "upscaler": "<string>"
    },
    "refiner": {
      "switch_at": 123
    },
    "enable_transparent_background": true,
    "restore_faces": true
  }
}
'

import requests

url = "https://api.novita.ai/v3/async/txt2img"

payload = {
    "extra": {
        "response_image_type": "<string>",
        "webhook": {
            "url": "<string>",
            "test_mode": {
                "enabled": True,
                "return_task_status": "<string>"
            }
        },
        "custom_storage": { "aws_s3": {
                "region": "<string>",
                "bucket": "<string>",
                "path": "<string>",
                "save_to_path_directly": True
            } },
        "enterprise_plan": { "enabled": True },
        "enable_nsfw_detection": True,
        "nsfw_detection_level": 123
    },
    "request": {
        "model_name": "<string>",
        "prompt": "<string>",
        "width": 123,
        "height": 123,
        "image_num": 123,
        "steps": 123,
        "guidance_scale": 123,
        "sampler_name": "<string>",
        "negative_prompt": "<string>",
        "sd_vae": "<string>",
        "seed": 123,
        "loras": [
            {
                "model_name": "<string>",
                "strength": 123
            }
        ],
        "embeddings": [{ "model_name": "<string>" }],
        "hires_fix": {
            "target_width": 123,
            "target_height": 123,
            "strength": 123,
            "upscaler": "<string>"
        },
        "refiner": { "switch_at": 123 },
        "enable_transparent_background": True,
        "restore_faces": True
    }
}
headers = {
    "Content-Type": "<content-type>",
    "Authorization": "<authorization>"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': '<content-type>', Authorization: '<authorization>'},
  body: JSON.stringify({
    extra: {
      response_image_type: '<string>',
      webhook: {url: '<string>', test_mode: {enabled: true, return_task_status: '<string>'}},
      custom_storage: {
        aws_s3: {
          region: '<string>',
          bucket: '<string>',
          path: '<string>',
          save_to_path_directly: true
        }
      },
      enterprise_plan: {enabled: true},
      enable_nsfw_detection: true,
      nsfw_detection_level: 123
    },
    request: {
      model_name: '<string>',
      prompt: '<string>',
      width: 123,
      height: 123,
      image_num: 123,
      steps: 123,
      guidance_scale: 123,
      sampler_name: '<string>',
      negative_prompt: '<string>',
      sd_vae: '<string>',
      seed: 123,
      loras: [{model_name: '<string>', strength: 123}],
      embeddings: [{model_name: '<string>'}],
      hires_fix: {target_width: 123, target_height: 123, strength: 123, upscaler: '<string>'},
      refiner: {switch_at: 123},
      enable_transparent_background: true,
      restore_faces: true
    }
  })
};

fetch('https://api.novita.ai/v3/async/txt2img', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.novita.ai/v3/async/txt2img",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'extra' => [
        'response_image_type' => '<string>',
        'webhook' => [
                'url' => '<string>',
                'test_mode' => [
                                'enabled' => true,
                                'return_task_status' => '<string>'
                ]
        ],
        'custom_storage' => [
                'aws_s3' => [
                                'region' => '<string>',
                                'bucket' => '<string>',
                                'path' => '<string>',
                                'save_to_path_directly' => true
                ]
        ],
        'enterprise_plan' => [
                'enabled' => true
        ],
        'enable_nsfw_detection' => true,
        'nsfw_detection_level' => 123
    ],
    'request' => [
        'model_name' => '<string>',
        'prompt' => '<string>',
        'width' => 123,
        'height' => 123,
        'image_num' => 123,
        'steps' => 123,
        'guidance_scale' => 123,
        'sampler_name' => '<string>',
        'negative_prompt' => '<string>',
        'sd_vae' => '<string>',
        'seed' => 123,
        'loras' => [
                [
                                'model_name' => '<string>',
                                'strength' => 123
                ]
        ],
        'embeddings' => [
                [
                                'model_name' => '<string>'
                ]
        ],
        'hires_fix' => [
                'target_width' => 123,
                'target_height' => 123,
                'strength' => 123,
                'upscaler' => '<string>'
        ],
        'refiner' => [
                'switch_at' => 123
        ],
        'enable_transparent_background' => true,
        'restore_faces' => true
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <authorization>",
    "Content-Type: <content-type>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.novita.ai/v3/async/txt2img"

	payload := strings.NewReader("{\n  \"extra\": {\n    \"response_image_type\": \"<string>\",\n    \"webhook\": {\n      \"url\": \"<string>\",\n      \"test_mode\": {\n        \"enabled\": true,\n        \"return_task_status\": \"<string>\"\n      }\n    },\n    \"custom_storage\": {\n      \"aws_s3\": {\n        \"region\": \"<string>\",\n        \"bucket\": \"<string>\",\n        \"path\": \"<string>\",\n        \"save_to_path_directly\": true\n      }\n    },\n    \"enterprise_plan\": {\n      \"enabled\": true\n    },\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123\n  },\n  \"request\": {\n    \"model_name\": \"<string>\",\n    \"prompt\": \"<string>\",\n    \"width\": 123,\n    \"height\": 123,\n    \"image_num\": 123,\n    \"steps\": 123,\n    \"guidance_scale\": 123,\n    \"sampler_name\": \"<string>\",\n    \"negative_prompt\": \"<string>\",\n    \"sd_vae\": \"<string>\",\n    \"seed\": 123,\n    \"loras\": [\n      {\n        \"model_name\": \"<string>\",\n        \"strength\": 123\n      }\n    ],\n    \"embeddings\": [\n      {\n        \"model_name\": \"<string>\"\n      }\n    ],\n    \"hires_fix\": {\n      \"target_width\": 123,\n      \"target_height\": 123,\n      \"strength\": 123,\n      \"upscaler\": \"<string>\"\n    },\n    \"refiner\": {\n      \"switch_at\": 123\n    },\n    \"enable_transparent_background\": true,\n    \"restore_faces\": true\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "<content-type>")
	req.Header.Add("Authorization", "<authorization>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.novita.ai/v3/async/txt2img")
  .header("Content-Type", "<content-type>")
  .header("Authorization", "<authorization>")
  .body("{\n  \"extra\": {\n    \"response_image_type\": \"<string>\",\n    \"webhook\": {\n      \"url\": \"<string>\",\n      \"test_mode\": {\n        \"enabled\": true,\n        \"return_task_status\": \"<string>\"\n      }\n    },\n    \"custom_storage\": {\n      \"aws_s3\": {\n        \"region\": \"<string>\",\n        \"bucket\": \"<string>\",\n        \"path\": \"<string>\",\n        \"save_to_path_directly\": true\n      }\n    },\n    \"enterprise_plan\": {\n      \"enabled\": true\n    },\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123\n  },\n  \"request\": {\n    \"model_name\": \"<string>\",\n    \"prompt\": \"<string>\",\n    \"width\": 123,\n    \"height\": 123,\n    \"image_num\": 123,\n    \"steps\": 123,\n    \"guidance_scale\": 123,\n    \"sampler_name\": \"<string>\",\n    \"negative_prompt\": \"<string>\",\n    \"sd_vae\": \"<string>\",\n    \"seed\": 123,\n    \"loras\": [\n      {\n        \"model_name\": \"<string>\",\n        \"strength\": 123\n      }\n    ],\n    \"embeddings\": [\n      {\n        \"model_name\": \"<string>\"\n      }\n    ],\n    \"hires_fix\": {\n      \"target_width\": 123,\n      \"target_height\": 123,\n      \"strength\": 123,\n      \"upscaler\": \"<string>\"\n    },\n    \"refiner\": {\n      \"switch_at\": 123\n    },\n    \"enable_transparent_background\": true,\n    \"restore_faces\": true\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.novita.ai/v3/async/txt2img")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = '<content-type>'
request["Authorization"] = '<authorization>'
request.body = "{\n  \"extra\": {\n    \"response_image_type\": \"<string>\",\n    \"webhook\": {\n      \"url\": \"<string>\",\n      \"test_mode\": {\n        \"enabled\": true,\n        \"return_task_status\": \"<string>\"\n      }\n    },\n    \"custom_storage\": {\n      \"aws_s3\": {\n        \"region\": \"<string>\",\n        \"bucket\": \"<string>\",\n        \"path\": \"<string>\",\n        \"save_to_path_directly\": true\n      }\n    },\n    \"enterprise_plan\": {\n      \"enabled\": true\n    },\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123\n  },\n  \"request\": {\n    \"model_name\": \"<string>\",\n    \"prompt\": \"<string>\",\n    \"width\": 123,\n    \"height\": 123,\n    \"image_num\": 123,\n    \"steps\": 123,\n    \"guidance_scale\": 123,\n    \"sampler_name\": \"<string>\",\n    \"negative_prompt\": \"<string>\",\n    \"sd_vae\": \"<string>\",\n    \"seed\": 123,\n    \"loras\": [\n      {\n        \"model_name\": \"<string>\",\n        \"strength\": 123\n      }\n    ],\n    \"embeddings\": [\n      {\n        \"model_name\": \"<string>\"\n      }\n    ],\n    \"hires_fix\": {\n      \"target_width\": 123,\n      \"target_height\": 123,\n      \"strength\": 123,\n      \"upscaler\": \"<string>\"\n    },\n    \"refiner\": {\n      \"switch_at\": 123\n    },\n    \"enable_transparent_background\": true,\n    \"restore_faces\": true\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "task_id": "<string>"
}

POST

async

txt2img

Text to Image

curl --request POST \
  --url https://api.novita.ai/v3/async/txt2img \
  --header 'Authorization: <authorization>' \
  --header 'Content-Type: <content-type>' \
  --data '
{
  "extra": {
    "response_image_type": "<string>",
    "webhook": {
      "url": "<string>",
      "test_mode": {
        "enabled": true,
        "return_task_status": "<string>"
      }
    },
    "custom_storage": {
      "aws_s3": {
        "region": "<string>",
        "bucket": "<string>",
        "path": "<string>",
        "save_to_path_directly": true
      }
    },
    "enterprise_plan": {
      "enabled": true
    },
    "enable_nsfw_detection": true,
    "nsfw_detection_level": 123
  },
  "request": {
    "model_name": "<string>",
    "prompt": "<string>",
    "width": 123,
    "height": 123,
    "image_num": 123,
    "steps": 123,
    "guidance_scale": 123,
    "sampler_name": "<string>",
    "negative_prompt": "<string>",
    "sd_vae": "<string>",
    "seed": 123,
    "loras": [
      {
        "model_name": "<string>",
        "strength": 123
      }
    ],
    "embeddings": [
      {
        "model_name": "<string>"
      }
    ],
    "hires_fix": {
      "target_width": 123,
      "target_height": 123,
      "strength": 123,
      "upscaler": "<string>"
    },
    "refiner": {
      "switch_at": 123
    },
    "enable_transparent_background": true,
    "restore_faces": true
  }
}
'

import requests

url = "https://api.novita.ai/v3/async/txt2img"

payload = {
    "extra": {
        "response_image_type": "<string>",
        "webhook": {
            "url": "<string>",
            "test_mode": {
                "enabled": True,
                "return_task_status": "<string>"
            }
        },
        "custom_storage": { "aws_s3": {
                "region": "<string>",
                "bucket": "<string>",
                "path": "<string>",
                "save_to_path_directly": True
            } },
        "enterprise_plan": { "enabled": True },
        "enable_nsfw_detection": True,
        "nsfw_detection_level": 123
    },
    "request": {
        "model_name": "<string>",
        "prompt": "<string>",
        "width": 123,
        "height": 123,
        "image_num": 123,
        "steps": 123,
        "guidance_scale": 123,
        "sampler_name": "<string>",
        "negative_prompt": "<string>",
        "sd_vae": "<string>",
        "seed": 123,
        "loras": [
            {
                "model_name": "<string>",
                "strength": 123
            }
        ],
        "embeddings": [{ "model_name": "<string>" }],
        "hires_fix": {
            "target_width": 123,
            "target_height": 123,
            "strength": 123,
            "upscaler": "<string>"
        },
        "refiner": { "switch_at": 123 },
        "enable_transparent_background": True,
        "restore_faces": True
    }
}
headers = {
    "Content-Type": "<content-type>",
    "Authorization": "<authorization>"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': '<content-type>', Authorization: '<authorization>'},
  body: JSON.stringify({
    extra: {
      response_image_type: '<string>',
      webhook: {url: '<string>', test_mode: {enabled: true, return_task_status: '<string>'}},
      custom_storage: {
        aws_s3: {
          region: '<string>',
          bucket: '<string>',
          path: '<string>',
          save_to_path_directly: true
        }
      },
      enterprise_plan: {enabled: true},
      enable_nsfw_detection: true,
      nsfw_detection_level: 123
    },
    request: {
      model_name: '<string>',
      prompt: '<string>',
      width: 123,
      height: 123,
      image_num: 123,
      steps: 123,
      guidance_scale: 123,
      sampler_name: '<string>',
      negative_prompt: '<string>',
      sd_vae: '<string>',
      seed: 123,
      loras: [{model_name: '<string>', strength: 123}],
      embeddings: [{model_name: '<string>'}],
      hires_fix: {target_width: 123, target_height: 123, strength: 123, upscaler: '<string>'},
      refiner: {switch_at: 123},
      enable_transparent_background: true,
      restore_faces: true
    }
  })
};

fetch('https://api.novita.ai/v3/async/txt2img', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.novita.ai/v3/async/txt2img",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'extra' => [
        'response_image_type' => '<string>',
        'webhook' => [
                'url' => '<string>',
                'test_mode' => [
                                'enabled' => true,
                                'return_task_status' => '<string>'
                ]
        ],
        'custom_storage' => [
                'aws_s3' => [
                                'region' => '<string>',
                                'bucket' => '<string>',
                                'path' => '<string>',
                                'save_to_path_directly' => true
                ]
        ],
        'enterprise_plan' => [
                'enabled' => true
        ],
        'enable_nsfw_detection' => true,
        'nsfw_detection_level' => 123
    ],
    'request' => [
        'model_name' => '<string>',
        'prompt' => '<string>',
        'width' => 123,
        'height' => 123,
        'image_num' => 123,
        'steps' => 123,
        'guidance_scale' => 123,
        'sampler_name' => '<string>',
        'negative_prompt' => '<string>',
        'sd_vae' => '<string>',
        'seed' => 123,
        'loras' => [
                [
                                'model_name' => '<string>',
                                'strength' => 123
                ]
        ],
        'embeddings' => [
                [
                                'model_name' => '<string>'
                ]
        ],
        'hires_fix' => [
                'target_width' => 123,
                'target_height' => 123,
                'strength' => 123,
                'upscaler' => '<string>'
        ],
        'refiner' => [
                'switch_at' => 123
        ],
        'enable_transparent_background' => true,
        'restore_faces' => true
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <authorization>",
    "Content-Type: <content-type>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.novita.ai/v3/async/txt2img"

	payload := strings.NewReader("{\n  \"extra\": {\n    \"response_image_type\": \"<string>\",\n    \"webhook\": {\n      \"url\": \"<string>\",\n      \"test_mode\": {\n        \"enabled\": true,\n        \"return_task_status\": \"<string>\"\n      }\n    },\n    \"custom_storage\": {\n      \"aws_s3\": {\n        \"region\": \"<string>\",\n        \"bucket\": \"<string>\",\n        \"path\": \"<string>\",\n        \"save_to_path_directly\": true\n      }\n    },\n    \"enterprise_plan\": {\n      \"enabled\": true\n    },\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123\n  },\n  \"request\": {\n    \"model_name\": \"<string>\",\n    \"prompt\": \"<string>\",\n    \"width\": 123,\n    \"height\": 123,\n    \"image_num\": 123,\n    \"steps\": 123,\n    \"guidance_scale\": 123,\n    \"sampler_name\": \"<string>\",\n    \"negative_prompt\": \"<string>\",\n    \"sd_vae\": \"<string>\",\n    \"seed\": 123,\n    \"loras\": [\n      {\n        \"model_name\": \"<string>\",\n        \"strength\": 123\n      }\n    ],\n    \"embeddings\": [\n      {\n        \"model_name\": \"<string>\"\n      }\n    ],\n    \"hires_fix\": {\n      \"target_width\": 123,\n      \"target_height\": 123,\n      \"strength\": 123,\n      \"upscaler\": \"<string>\"\n    },\n    \"refiner\": {\n      \"switch_at\": 123\n    },\n    \"enable_transparent_background\": true,\n    \"restore_faces\": true\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "<content-type>")
	req.Header.Add("Authorization", "<authorization>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.novita.ai/v3/async/txt2img")
  .header("Content-Type", "<content-type>")
  .header("Authorization", "<authorization>")
  .body("{\n  \"extra\": {\n    \"response_image_type\": \"<string>\",\n    \"webhook\": {\n      \"url\": \"<string>\",\n      \"test_mode\": {\n        \"enabled\": true,\n        \"return_task_status\": \"<string>\"\n      }\n    },\n    \"custom_storage\": {\n      \"aws_s3\": {\n        \"region\": \"<string>\",\n        \"bucket\": \"<string>\",\n        \"path\": \"<string>\",\n        \"save_to_path_directly\": true\n      }\n    },\n    \"enterprise_plan\": {\n      \"enabled\": true\n    },\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123\n  },\n  \"request\": {\n    \"model_name\": \"<string>\",\n    \"prompt\": \"<string>\",\n    \"width\": 123,\n    \"height\": 123,\n    \"image_num\": 123,\n    \"steps\": 123,\n    \"guidance_scale\": 123,\n    \"sampler_name\": \"<string>\",\n    \"negative_prompt\": \"<string>\",\n    \"sd_vae\": \"<string>\",\n    \"seed\": 123,\n    \"loras\": [\n      {\n        \"model_name\": \"<string>\",\n        \"strength\": 123\n      }\n    ],\n    \"embeddings\": [\n      {\n        \"model_name\": \"<string>\"\n      }\n    ],\n    \"hires_fix\": {\n      \"target_width\": 123,\n      \"target_height\": 123,\n      \"strength\": 123,\n      \"upscaler\": \"<string>\"\n    },\n    \"refiner\": {\n      \"switch_at\": 123\n    },\n    \"enable_transparent_background\": true,\n    \"restore_faces\": true\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.novita.ai/v3/async/txt2img")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = '<content-type>'
request["Authorization"] = '<authorization>'
request.body = "{\n  \"extra\": {\n    \"response_image_type\": \"<string>\",\n    \"webhook\": {\n      \"url\": \"<string>\",\n      \"test_mode\": {\n        \"enabled\": true,\n        \"return_task_status\": \"<string>\"\n      }\n    },\n    \"custom_storage\": {\n      \"aws_s3\": {\n        \"region\": \"<string>\",\n        \"bucket\": \"<string>\",\n        \"path\": \"<string>\",\n        \"save_to_path_directly\": true\n      }\n    },\n    \"enterprise_plan\": {\n      \"enabled\": true\n    },\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123\n  },\n  \"request\": {\n    \"model_name\": \"<string>\",\n    \"prompt\": \"<string>\",\n    \"width\": 123,\n    \"height\": 123,\n    \"image_num\": 123,\n    \"steps\": 123,\n    \"guidance_scale\": 123,\n    \"sampler_name\": \"<string>\",\n    \"negative_prompt\": \"<string>\",\n    \"sd_vae\": \"<string>\",\n    \"seed\": 123,\n    \"loras\": [\n      {\n        \"model_name\": \"<string>\",\n        \"strength\": 123\n      }\n    ],\n    \"embeddings\": [\n      {\n        \"model_name\": \"<string>\"\n      }\n    ],\n    \"hires_fix\": {\n      \"target_width\": 123,\n      \"target_height\": 123,\n      \"strength\": 123,\n      \"upscaler\": \"<string>\"\n    },\n    \"refiner\": {\n      \"switch_at\": 123\n    },\n    \"enable_transparent_background\": true,\n    \"restore_faces\": true\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "task_id": "<string>"
}

Generate images from text prompts using Stable Diffusion models.

This is an asynchronous API; only the task_id will be returned. You should use the task_id to request the Task Result API to retrieve the image generation results.

Request Headers

Content-Type

string

required

Enum: application/json

Authorization

string

required

Bearer authentication format, for example: Bearer {{API Key}}.

Request Body

extra

object

Optional extra parameters for the request.

Show properties

response_image_type

string

The returned image type. Default is png.Enum: png, webp, jpeg

webhook

object

Webhook settings. More details can be found at Webhook Documentation.

Show properties

url

string

required

The URL of the webhook endpoint. Novita AI will send the task generated outputs to your specified webhook endpoint.

test_mode

object

By specifying Test Mode, a mock event will be sent to the webhook endpoint.

Show properties

enabled

boolean

required

Set to true to enable Test Mode, or false to disable it. The default is false.

return_task_status

string

required

Control the data content of the mock event. When set to TASK_STATUS_SUCCEED, you’ll receive a normal response; when set to TASK_STATUS_FAILED, you’ll receive an error response.Enum: TASK_STATUS_SUCCEED, TASK_STATUS_FAILED

custom_storage

object

Customer storage settings for saving the generated outputs.
By default, the generated outputs will be saved to Novita AI Storage temporarily and privately.

Show properties

aws_s3

object

AWS S3 Bucket settings.

Show properties

region

string

required

AWS S3 regions, more details.

bucket

string

required

AWS S3 bucket name.

path

string

required

AWS S3 bucket path for saving generated outputs.

save_to_path_directly

boolean

Set this option to True to save the generated outputs directly to the specified path without creating any additional directory hierarchy.
If set to False, Novita AI will create an additional directory in the path to save the generated outputs. The default is False.

enterprise_plan

object

Dedicated Endpoints settings, which only take effect for users who have already subscribed to the Dedicated Endpoints Documentation.

Show properties

enabled

boolean

Set to true to schedule this task to use your Dedicated Endpoints’s dedicated resources. Default is false.

enable_nsfw_detection

boolean

When set to true, NSFW detection will be enabled, incurring an additional cost of $0.0015 for each generated image.

nsfw_detection_level

integer

0: Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols.
1: Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols; Non-Explicit Nudity, Obstructed Intimate Parts, Kissing on the Lips.
2: Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols; Non-Explicit Nudity, Obstructed Intimate Parts, Kissing on the Lips; Female Swimwear or Underwear, Male Swimwear or Underwear.Enum: 0, 1, 2

request

object

required

Hide properties

model_name

string

required

This parameter specifies the name of the model checkpoint. Retrieve the corresponding sd_name value by invoking the Query Model API with filter.types=checkpoint as the query parameter.

prompt

string

required

Text input required to guide the image generation, divided by , . Range [1, 1024].

width

integer

required

Width of image. Range [128, 2048].

height

integer

required

Height of image. Range [128, 2048].

image_num

integer

required

Images numbers generated in one single generation. Range [1, 8].

steps

integer

required

The number of denoising steps. More steps usually can produce higher quality images, but take more time to generate, Range [1, 100].

guidance_scale

number

required

This setting says how close the Stable Diffusion will listen to your prompt, higer guidance forces the model to better follow the prompt, but result in lower quality output. Range [1, 30].

sampler_name

string

required

This parameter determines the denoising algorithm employed during the sampling phase of Stable Diffusion. Each option represents a distinct method by which the model incrementally generates new images. These algorithms differ significantly in their processing speed, output quality, and the specific characteristics of the images they generate, allowing users to tailor the image generation process to meet precise requirements. Get reference at A brief introduction to Sampler.Enum:

Euler a,Euler,LMS,Heun,DPM2,DPM2 a,DPM++ 2S a,DPM++ 2M,DPM++ SDE,DPM fast,DPM adaptive,LMS Karras,DPM2 Karras,DPM2 a Karras,DPM++ 2S a Karras,DPM++ 2M Karras,DPM++ SDE Karras,DDIM,PLMS,UniPC

negative_prompt

string

Text input that specifies what to exclude from the generated images, divided by , . Range [1, 1024].

sd_vae

string

VAE (Variational Auto Encoder). sd_vae can be accessed in the API /v3/models with query params type=vae, like sd_name: customVAE.safetensors. Get reference at A brief introduction to VAE.

seed

integer

A seed is a number from which Stable Diffusion generates noise, which, makes generation deterministic. Using the same seed and set of parameters will produce identical image each time, minimum -1. Defaults to -1.

loras

object[]

LoRA is a fast and lightweight training method that inserts and trains a significantly smaller number of parameters instead of all the model parameters. Currently supports up to 5 LoRAs.

Show properties

model_name

string

required

Name of lora, retrieve the corresponding sd_name_in_api value by invoking the Get Model API endpoint with filter.types=lora as the query parameter.

strength

number

required

The strength value of lora. The larger the value, the more biased the effect is towards lora, Range [0, 1]

embeddings

object[]

Textual Inversion is a training method for personalizing models by learning new text embeddings from a few example images, currently supports up to 5 embeddings.

Show properties

model_name

string

required

Name of textual Inversion model, you can call the Get Model API endpoint with parameter filter.types=textualinversion to retrieve the sd_name_in_api field as the model_name.

hires_fix

object

Upscale images while they are generating.

Show properties

target_width

integer

required

Target width, Range [128, 4096].

target_height

integer

required

Target height, Range [128, 4096].

strength

number

required

Defines the intensity of the upscaler model’s effect. A value of 0 means the upscaler has no effect, while 1 results in maximum intensity, fully utilizing the upscaler’s capabilities, range [0, 1].

upscaler

string

The upscaler model’s name.Enum: RealESRGAN_x4plus_anime_6B,RealESRNet_x4plus,Latent

refiner

object

SD refiner.

Show properties

switch_at

number

required

The switch_at parameter in the context of a refiner allows you to set the extent to which the refiner alters the output of a model. When set to 0, the refiner has no effect; at 1, it’s fully active. Intermediate values like 0.5 provide a balanced effect, where the refiner is moderately engaged, enhancing or adjusting the output without dominating the original model’s characteristics. This setting is particularly useful for fine-tuning the output to achieve a desired balance between refinement and the original generative features, Range [0, 1].

enable_transparent_background

bool

Make the resulting image’s background transparent. Please note that if the transparent_background is enabled, the extra response_image_type must be PNG, and only SDXL models are allowed.

restore_faces

bool

Used to control whether the Face Restoration feature is enabled.

Response

task_id

string

Use the task_id to request the Task Result API to retrieve the generated outputs.

Example

1. Txt2img request with normal parameters

Please set the Content-Type header to application/json in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported. Request:

curl --location 'https://api.novita.ai/v3/async/txt2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
    "extra": {
        "response_image_type": "jpeg"
    },
    "request": {
        "prompt": "a cute dog",
        "model_name": "sd_xl_base_1.0.safetensors",
        "negative_prompt": "nsfw, bottle, bad face",
        "width": 1024,
        "height": 1024,
        "image_num": 2,
        "steps": 20,
        "seed": -1,
        "clip_skip": 1,
        "sampler_name": "Euler a",
        "guidance_scale": 7.5
    }
}'

Response:

{
    "task_id": "f10333f2-2dd7-4f56-a177-e3c02a774d9a"
}

Use task_id to get images HTTP status codes in the 2xx range indicate that the request has been successfully accepted, while status codes in the 5xx range indicate internal server errors. You can get images url in imgs of response. Request:

curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=f10333f2-2dd7-4f56-a177-e3c02a774d9a' \
--header 'Authorization: Bearer {{API Key}}'

Response:

{
	"extra": {
		"seed": "392212448",
		"enable_nsfw_detection": false,
		"debug_info": {
			"request_info": "{\"model\":\"sd_xl_base_1.0.safetensors\",\"prompts\":[\"a cute dog\"],\"negative_prompts\":[\"nsfw, bottle,bad face\"],\"seeds\":[392212448],\"height\":384,\"width\":512,\"guidance_scale\":7.5,\"num_images_per_prompt\":2,\"num_inference_steps\":20,\"sampler_name\":\"Euler a\",\"clip_skip\":1}",
			"submit_time_ms": "1715052533293",
			"execute_time_ms": "1715052533362",
			"complete_time_ms": "1715052537148"
		}
	},
	"task": {
		"task_id": "f10333f2-2dd7-4f56-a177-e3c02a774d9a",
		"task_type": "TXT_TO_IMG",
		"status": "TASK_STATUS_SUCCEED",
		"reason": "",
		"eta": 0,
		"progress_percent": 0
	},
	"images": [{
		"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/f10333f2-2dd7-4f56-a177-e3c02a774d9a/80443e6739584fcb82bc2cf4f3b557fb.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240507%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240507T032908Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b375b64e0886d0253d5463af241a30bd4a1e4718287f37f73b0e80d5dce4d214",
		"image_url_ttl": "3600",
		"image_type": "jpeg",
		"nsfw_detection_result": null
	}, {
		"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/f10333f2-2dd7-4f56-a177-e3c02a774d9a/9b16e333242244e58a4d03c4bfb1bca5.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240507%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240507T032908Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=fff0623985c741661497532eb682a7ae23094bcf2e55c4eee61e256e97c81e3c",
		"image_url_ttl": "3600",
		"image_type": "jpeg",
		"nsfw_detection_result": null
	}],
	"videos": [],
	"audios": []
}

2.Txt2img request with lora

Please set the Content-Type header to application/json in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported. Request:

curl --location 'https://api.novita.ai/v3/async/txt2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
    "extra": {
        "response_image_type": "jpeg"
    },
    "request": {
        "prompt": "a cute dog",
        "model_name": "majicmixRealistic_v6_65516.safetensors",
        "negative_prompt": "nsfw, bottle,bad face",
        "width": 512,
        "height": 512,
        "image_num": 2,
        "steps": 20,
        "seed": 123,
        "clip_skip": 1,
        "sampler_name": "Euler a",
        "guidance_scale": 7.5,
        "loras": [
          {
            "model_name": "add_detail_44319",
            "strength": 0.7
          },
          {
            "model_name": "more_details_59655",
            "strength": 0.7
          }
        ]
    }
}'

Response:

{
    "task_id": "6469ca5b-5929-4200-b263-241020763eb8"
}

curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=6469ca5b-5929-4200-b263-241020763eb8' \
--header 'Authorization: Bearer {{API Key}}'

Response:

{
    "extra": {
        "seed": "123"
    },
    "task": {
        "task_id": "6469ca5b-5929-4200-b263-241020763eb8",
        "task_type": "TXT_TO_IMG",
        "status": "TASK_STATUS_SUCCEED",
        "reason": "",
        "eta": 0,
        "progress_percent": 0
    },
    "images": [
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/6469ca5b-5929-4200-b263-241020763eb8/xxx.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240111%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240111T134101Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=bbe71142c83df530e1dfb6be1a26faa1d9907b24f0fc77b2aee399683c51b134",
            "image_url_ttl": "3600",
            "image_type": "jpeg"
        },
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/6469ca5b-5929-4200-b263-241020763eb8/xxx.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240111%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240111T134101Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=8fc609a70c35d7b12f7690443dae6e59d2550b76461e73b2fd8296ec4333e208",
            "image_url_ttl": "3600",
            "image_type": "jpeg"
        }
    ],
    "videos": []
}

3.Txt2img request with upscale

Please set the Content-Type header to application/json in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported. Request:

curl --location 'https://api.novita.ai/v3/async/txt2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
    "extra": {
        "response_image_type": "jpeg"
    },
    "request": {
        "prompt": "a cute dog",
        "model_name": "realisticVisionV51_v51VAE_94301.safetensors",
        "negative_prompt": "nsfw, bottle,bad face",
        "width": 512,
        "height": 512,
        "image_num": 2,
        "steps": 20,
        "seed": 123,
        "clip_skip": 1,
        "sampler_name": "Euler a",
        "guidance_scale": 7.5,
        "hires_fix": {
            "target_width": 1024,
            "target_height": 1024,
            "strength": 0.8,
            "upscaler": "Latent"
        }
    }
}'

Response:

{
    "task_id": "6469ca5b-5929-4200-b263-241020763eb8"
}

curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=6469ca5b-5929-4200-b263-241020763eb8' \
--header 'Authorization: Bearer {{API Key}}'

Response:

{
    "extra": {
        "seed": "123",
        "enable_nsfw_detection": false
    },
    "task": {
        "task_id": "6469ca5b-5929-4200-b263-241020763eb8",
        "task_type": "TXT_TO_IMG",
        "status": "TASK_STATUS_SUCCEED",
        "reason": "",
        "eta": 0,
        "progress_percent": 0
    },
    "images": [
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/6469ca5b-5929-4200-b263-241020763eb8/23a98c94383e466289b4ae39a2d1fe73.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240307%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240307T034029Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=3f45b6214e176fc90f3c78e04bc01e5883f25a0a8122409eb00ae8ea971d1be6",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": null
        },
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/6469ca5b-5929-4200-b263-241020763eb8/19146c52474445e4ae2554ad807f7f6b.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240307%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240307T034029Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=a69c62262cdec60dd74f2efc2fd965cb98473112ce291542930d5b7d9b37755a",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": null
        }
    ],
    "videos": []
}

4.Txt2img request with SDXL 1.0

Please set the Content-Type header to application/json in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported. Request:

curl --location 'https://api.novita.ai/v3/async/txt2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
    "extra": {
        "response_image_type": "jpeg"
    },
    "request": {
        "prompt": "a cute dog",
        "model_name": "sd_xl_base_1.0.safetensors",
        "negative_prompt": "nsfw, bottle,bad face",
        "width": 1024,
        "height": 1024,
        "image_num": 1,
        "steps": 20,
        "seed": -1,
        "clip_skip": 1,
        "sampler_name": "Euler a",
        "guidance_scale": 7.5
    }
}'

Response:

{
    "task_id": "6469ca5b-5929-4200-b263-241020763eb8"
}

curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=6469ca5b-5929-4200-b263-241020763eb8' \
--header 'Authorization: Bearer {{API Key}}'

Response:

{
    "extra": {
        "seed": "3706472920",
        "enable_nsfw_detection": false
    },
    "task": {
        "task_id": "346b3562-ae4e-4849-a9fb-9318cb1a689d",
        "task_type": "TXT_TO_IMG",
        "status": "TASK_STATUS_SUCCEED",
        "reason": "",
        "eta": 0,
        "progress_percent": 0
    },
    "images": [
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/346b3562-ae4e-4849-a9fb-9318cb1a689d/5698013f545d425cbcdeae00cef8c435.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240307%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240307T033747Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=68f00e2800de145d5c2c9d05f957a684283fa8dce41049337b8ce59267c49cf2",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": null
        }
    ],
    "videos": []
}

5.Txt2img request with Textual Inversion(embedding)

Please set the Content-Type header to application/json in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported. Request for textual inversion names:

curl --location --request GET 'https://api.novita.ai/v3/model?filter.visibility=public&pagination.limit=\
100&pagination.cursor=c_0&filter.types=textualinversion&filter.source=civitai' \
--header 'Authorization: Bearer {{API Key}}' | jq '.models[].sd_name'

Response:

"epiCPhotoGasm-colorfulPhoto-neg_108119.pt"
"epiCNegative_66017.pt"
"verybadimagenegative_v1.3_21434.pt"
"FastNegativeV2_65067.pt"
"AS-YoungV2.pt"
"AS-YoungV2-neg.pt"
"AS-YoungestV2.pt"
"AS-YoungerV2.pt"
"AS-MidAged.pt"
"AS-Elderly.pt"
"AS-Adult.pt"
"AS-Adult-neg.pt"
"Adult.pt"
"MidAged.pt"
"unaestheticXLv13_98060.safetensors"
"unaestheticXL_Sky3.1_134255.safetensors"
"EasyNegativeV2_75525.safetensors"
"BadDream_53202.pt"
"UnrealisticDream_53204.pt"
"negative_hand-neg_43127.pt"
"bad_prompt_version2-neg_42594.pt"
"Asian-Less-Toon_39763.pt"
"badhandv4_16755.pt"
"easynegative_8955.safetensors"
"aestheticc-65800_8615.pt"
"corneo_side_deepthroat_6490.pt"
"corneo_tentacle_sex.pt"
"By bad artist -neg_6310.pt"
"dpthrt_5441.pt"
"ng_deepnegative_v1_75t_5845.pt"
"pureerosface_v1_5162.pt"

Request:

curl --location 'https://api.novita.ai/v3/async/txt2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
    "extra": {
        "response_image_type": "jpeg"
    },
    "request": {
        "prompt": "1girl",
        "model_name": "realisticVisionV51_v51VAE_94301.safetensors",
        "negative_prompt": "nsfw, bottle,bad face",
        "width": 512,
        "height": 512,
        "image_num": 1,
        "steps": 20,
        "seed": -1,
        "clip_skip": 1,
        "sampler_name": "Euler a",
        "guidance_scale": 7.5,
        "embeddings": [
            {
                "model_name": "badhandv4_16755.pt"
            },
            {
                "model_name": "BadDream_53202.pt"
            }
        ]
    }
}'

Response:

{
    "task_id": "6469ca5b-5929-4200-b263-241020763eb8"
}

curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=6469ca5b-5929-4200-b263-241020763eb8' \
--header 'Authorization: Bearer {{API Key}}'

Response:

{
    "extra": {
        "seed": "767172278",
        "enable_nsfw_detection": false
    },
    "task": {
        "task_id": "22388880-1c37-4ae1-8738-2fe7f5e8af57",
        "task_type": "TXT_TO_IMG",
        "status": "TASK_STATUS_SUCCEED",
        "reason": "",
        "eta": 0,
        "progress_percent": 0
    },
    "images": [
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/6469ca5b-5929-4200-b263-241020763eb8/72768e59c4884965824347bfb400e3fd.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240307%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240307T035327Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=e0a44ec5fe21d9e64dc59b1b53017df737218b8c7db6f4e6d2cd46ca8e42b2ab",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": null
        }
    ],
    "videos": []
}

6.Txt2img request with nsfw_detection

When set enable_nsfw_detection true, NSFW detection will be enabled, incurring an additional cost of $0.0015 for each generated image. nsfw_detection_level, nsfw check level, ranging from 0 to 2, with higher levels indicating stricter NSFW detection criteria. The default value is 0. The following table lists the NSFW detection criteria for each level.

0: Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols.
1: Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols; Non-Explicit Nudity, Obstructed Intimate Parts, Kissing on the Lips.
2: Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols; Non-Explicit Nudity, Obstructed Intimate Parts, Kissing on the Lips; Female Swimwear or Underwear, Male Swimwear or Underwear.

Please set the Content-Type header to application/json in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported. Request:

curl --location 'https://api.novita.ai/v3/async/txt2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
    "extra": {
        "response_image_type": "jpeg",
        "enable_nsfw_detection": true,
        "nsfw_detection_level": 2
    },
    "request": {
        "prompt": "1girl,sexy",
        "model_name": "dreamshaper_8_93211.safetensors",
        "negative_prompt": "nsfw, bottle,bad face",
        "width": 512,
        "height": 512,
        "image_num": 4,
        "steps": 20,
        "seed": -1,
        "clip_skip": 1,
        "sampler_name": "Euler a",
        "guidance_scale": 7.5
    }
}'

Response:

{
    "code": 0,
    "msg": "",
    "data": {
        "task_id": "0fe0f291-05c9-41a4-83bb-3365d4b54f8b"
    }
}

enable_nsfw_detection, when return with true means NSFW detection is enabled.
nsfw_detection_result, presenting an array of NSFW detection outcomes for each image. The order of elements in the nsfw_detection_result array corresponds one-to-one with the sequence of images in the images field in the response. The valid field denotes the success of the NSFW detection process, while the confidence field, ranging from 0 to 100, signifies the confidence level of the NSFW detection result. Higher confidence values, nearing 100, suggest a greater likelihood of the corresponding image containing NSFW content.

Request:

curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=0fe0f291-05c9-41a4-83bb-3365d4b54f8b' \
--header 'Authorization: Bearer {{API Key}}'

Response:

{
    "extra": {
        "seed": "1998521869",
        "enable_nsfw_detection": true
    },
    "task": {
        "task_id": "0fe0f291-05c9-41a4-83bb-3365d4b54f8b",
        "task_type": "TXT_TO_IMG",
        "status": "TASK_STATUS_SUCCEED",
        "reason": "",
        "eta": 0,
        "progress_percent": 0
    },
    "images": [
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/0fe0f291-05c9-41a4-83bb-3365d4b54f8b/50dc49337e5d4ea289050198206b6a11.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240308%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240308T091609Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b8cdebb0ffa90fa869843cbab9d2e348678f621bad35c4bf1f3f90637c512f59",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": {
                "valid": true,
                "confidence": 93.7176
            }
        },
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/0fe0f291-05c9-41a4-83bb-3365d4b54f8b/9692d408ce65497ba2c1f5da99a72f12.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240308%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240308T091609Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=f213cbabdf6d411d9e414377ae2d538cd8dff692befdbe3fa0183c737aeea0c6",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": {
                "valid": true,
                "confidence": 94.4329
            }
        },
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/0fe0f291-05c9-41a4-83bb-3365d4b54f8b/68336b4bd7194b9b87b53aabcfcd92cf.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240308%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240308T091609Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=faa315d2a0a97706486ff00d02399dc12dcd5eb08e9a538c9997bdf389137269",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": {
                "valid": true,
                "confidence": 94.4224
            }
        },
        {
            "image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/0fe0f291-05c9-41a4-83bb-3365d4b54f8b/a8bc5e8263aa4d9389215b749e56af45.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240308%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240308T091609Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4197c88e751861bbd30e8b9f1fadb67a6808f26e91b57c0ae5ed0512e05bb8ab",
            "image_url_ttl": "3600",
            "image_type": "jpeg",
            "nsfw_detection_result": {
                "valid": true,
                "confidence": 94.6823
            }
        }
    ],
    "videos": []
}

Last modified on January 14, 2026

Task Result Image to Image

⌘I

Overview

Basic

Quota

Team Budget

Model APIs

GPUs

Text to Image

Request Headers

Request Body

Response

Example

1. Txt2img request with normal parameters

2.Txt2img request with lora

3.Txt2img request with upscale

4.Txt2img request with SDXL 1.0

5.Txt2img request with Textual Inversion(embedding)

6.Txt2img request with nsfw_detection

​Request Headers

​Request Body

​Response

​Example

​1. Txt2img request with normal parameters

​2.Txt2img request with lora

​3.Txt2img request with upscale

​4.Txt2img request with SDXL 1.0

​5.Txt2img request with Textual Inversion(embedding)

​6.Txt2img request with nsfw_detection

Request Headers

Request Body

Response

Example

1. Txt2img request with normal parameters

2.Txt2img request with lora

3.Txt2img request with upscale

4.Txt2img request with SDXL 1.0

5.Txt2img request with Textual Inversion(embedding)

6.Txt2img request with nsfw_detection