Inpaint
curl --request POST \
--url https://api.legnext.ai/api/v1/inpaint \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"mask": {
"areas": [
{
"height": 123,
"points": [
123
],
"width": 123
}
],
"url": "<string>"
},
"remixPrompt": "<string>",
"callback": "<string>"
}
'import requests
url = "https://api.legnext.ai/api/v1/inpaint"
payload = {
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"mask": {
"areas": [
{
"height": 123,
"points": [123],
"width": 123
}
],
"url": "<string>"
},
"remixPrompt": "<string>",
"callback": "<string>"
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
imageNo: 1,
jobId: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
mask: {areas: [{height: 123, points: [123], width: 123}], url: '<string>'},
remixPrompt: '<string>',
callback: '<string>'
})
};
fetch('https://api.legnext.ai/api/v1/inpaint', 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.legnext.ai/api/v1/inpaint",
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([
'imageNo' => 1,
'jobId' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
'mask' => [
'areas' => [
[
'height' => 123,
'points' => [
123
],
'width' => 123
]
],
'url' => '<string>'
],
'remixPrompt' => '<string>',
'callback' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"x-api-key: <api-key>"
],
]);
$response = curl_exec($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.legnext.ai/api/v1/inpaint"
payload := strings.NewReader("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"mask\": {\n \"areas\": [\n {\n \"height\": 123,\n \"points\": [\n 123\n ],\n \"width\": 123\n }\n ],\n \"url\": \"<string>\"\n },\n \"remixPrompt\": \"<string>\",\n \"callback\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
req.Header.Add("Content-Type", "application/json")
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.legnext.ai/api/v1/inpaint")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"mask\": {\n \"areas\": [\n {\n \"height\": 123,\n \"points\": [\n 123\n ],\n \"width\": 123\n }\n ],\n \"url\": \"<string>\"\n },\n \"remixPrompt\": \"<string>\",\n \"callback\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.legnext.ai/api/v1/inpaint")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"mask\": {\n \"areas\": [\n {\n \"height\": 123,\n \"points\": [\n 123\n ],\n \"width\": 123\n }\n ],\n \"url\": \"<string>\"\n },\n \"remixPrompt\": \"<string>\",\n \"callback\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}Image Generation
Inpaint
Regenerate selected regions of a completed image.
POST
/
v1
/
inpaint
Inpaint
curl --request POST \
--url https://api.legnext.ai/api/v1/inpaint \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"mask": {
"areas": [
{
"height": 123,
"points": [
123
],
"width": 123
}
],
"url": "<string>"
},
"remixPrompt": "<string>",
"callback": "<string>"
}
'import requests
url = "https://api.legnext.ai/api/v1/inpaint"
payload = {
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"mask": {
"areas": [
{
"height": 123,
"points": [123],
"width": 123
}
],
"url": "<string>"
},
"remixPrompt": "<string>",
"callback": "<string>"
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
imageNo: 1,
jobId: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
mask: {areas: [{height: 123, points: [123], width: 123}], url: '<string>'},
remixPrompt: '<string>',
callback: '<string>'
})
};
fetch('https://api.legnext.ai/api/v1/inpaint', 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.legnext.ai/api/v1/inpaint",
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([
'imageNo' => 1,
'jobId' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
'mask' => [
'areas' => [
[
'height' => 123,
'points' => [
123
],
'width' => 123
]
],
'url' => '<string>'
],
'remixPrompt' => '<string>',
'callback' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"x-api-key: <api-key>"
],
]);
$response = curl_exec($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.legnext.ai/api/v1/inpaint"
payload := strings.NewReader("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"mask\": {\n \"areas\": [\n {\n \"height\": 123,\n \"points\": [\n 123\n ],\n \"width\": 123\n }\n ],\n \"url\": \"<string>\"\n },\n \"remixPrompt\": \"<string>\",\n \"callback\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
req.Header.Add("Content-Type", "application/json")
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.legnext.ai/api/v1/inpaint")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"mask\": {\n \"areas\": [\n {\n \"height\": 123,\n \"points\": [\n 123\n ],\n \"width\": 123\n }\n ],\n \"url\": \"<string>\"\n },\n \"remixPrompt\": \"<string>\",\n \"callback\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.legnext.ai/api/v1/inpaint")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"mask\": {\n \"areas\": [\n {\n \"height\": 123,\n \"points\": [\n 123\n ],\n \"width\": 123\n }\n ],\n \"url\": \"<string>\"\n },\n \"remixPrompt\": \"<string>\",\n \"callback\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}{
"config": {
"service_mode": "public",
"webhook_config": {
"endpoint": "<string>",
"secret": "<string>"
}
},
"detail": null,
"error": {
"code": 123,
"detail": "<unknown>",
"message": "<string>",
"raw_message": "<string>"
},
"input": {},
"job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"logs": [
"<string>"
],
"meta": {
"created_at": "2023-11-07T05:31:56Z",
"ended_at": "2023-11-07T05:31:56Z",
"started_at": "2023-11-07T05:31:56Z",
"usage": {
"consume": 123,
"frozen": 123,
"type": "credit"
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
},
"status": "pending",
"task_type": "diffusion"
}Inpaint is a follow-up operation. Pass the completed parent task and the region
data defined by the generated request schema.
The source image and its model must support editing. If the API rejects the
action, regenerate a compatible base image instead of looping on the same
parent.
Authorizations
API key from the Legnext dashboard. Authorization: Bearer <key> is accepted as an alternative.
Body
application/json
Index of the image in the parent task's grid (0-3, left-to-right, top-to-bottom).
Required range:
0 <= x <= 3ID of the original task (the job_id returned when it was created).
Mask selecting the regions to regenerate. Either url (mask image, max 1024 chars) or areas (rectangles, width/height 500-4096) must be provided.
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Prompt guiding the edit (1-8192 characters). Midjourney --flags are accepted.
Required string length:
1 - 8192Optional webhook URL. When set, the completed TaskResponse is POSTed to this URL; when empty, poll GET /v1/job/{job_id}.
Response
Inpaint task accepted.
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Reserved for future use; currently null in public API responses.
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Echo of the task's input parameters (shape depends on task_type; mirrors the create-request body of the operation that created the task). Null in error responses.
Task UUID. Pass it to GET /v1/job/{job_id} to poll, or reference it as jobId in follow-up operations.
Operational log lines of the task (progress events, retries).
Timestamps and billing usage of the task (null in error responses).
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Model family that executed the task.
Available options:
midjourney Task result, present once status is completed (null before that). Image/video tasks return URLs; describe/shorten tasks return text prompts.
- Option 1
- Option 2
- Option 3
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Lifecycle state. Terminal states: completed, failed. staged means the task is queued behind the account's concurrency limit; retry means it is being resubmitted after a transient provider error.
Available options:
pending, staged, processing, retry, completed, failed Type of the task — the operation that created it.
Available options:
diffusion, upscale, reroll, variation, inpaint, outpaint, pan, edit, remix, enhance, upload_paint, retexture, remove_background, shorten, describe, blend, video_diffusion, extend_video, video_upscale, enhance_upscale