Pan Extend
curl --request POST \
--url https://api.legnext.ai/api/v1/pan \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"scale": 2.05,
"callback": "<string>",
"remixPrompt": "<string>"
}
'import requests
url = "https://api.legnext.ai/api/v1/pan"
payload = {
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"scale": 2.05,
"callback": "<string>",
"remixPrompt": "<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',
scale: 2.05,
callback: '<string>',
remixPrompt: '<string>'
})
};
fetch('https://api.legnext.ai/api/v1/pan', 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/pan",
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',
'scale' => 2.05,
'callback' => '<string>',
'remixPrompt' => '<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/pan"
payload := strings.NewReader("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"scale\": 2.05,\n \"callback\": \"<string>\",\n \"remixPrompt\": \"<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/pan")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"scale\": 2.05,\n \"callback\": \"<string>\",\n \"remixPrompt\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.legnext.ai/api/v1/pan")
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 \"scale\": 2.05,\n \"callback\": \"<string>\",\n \"remixPrompt\": \"<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
Pan
Extend a completed image in one direction.
POST
/
v1
/
pan
Pan Extend
curl --request POST \
--url https://api.legnext.ai/api/v1/pan \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"scale": 2.05,
"callback": "<string>",
"remixPrompt": "<string>"
}
'import requests
url = "https://api.legnext.ai/api/v1/pan"
payload = {
"imageNo": 1,
"jobId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"scale": 2.05,
"callback": "<string>",
"remixPrompt": "<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',
scale: 2.05,
callback: '<string>',
remixPrompt: '<string>'
})
};
fetch('https://api.legnext.ai/api/v1/pan', 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/pan",
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',
'scale' => 2.05,
'callback' => '<string>',
'remixPrompt' => '<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/pan"
payload := strings.NewReader("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"scale\": 2.05,\n \"callback\": \"<string>\",\n \"remixPrompt\": \"<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/pan")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"imageNo\": 1,\n \"jobId\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n \"scale\": 2.05,\n \"callback\": \"<string>\",\n \"remixPrompt\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.legnext.ai/api/v1/pan")
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 \"scale\": 2.05,\n \"callback\": \"<string>\",\n \"remixPrompt\": \"<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"
}Pan is a follow-up operation. Pass the parent
jobId, zero-based imageNo, and
direction defined by the generated request schema.
Not every model or source image supports Pan. Check the parent task’s
available_actions, then handle a 400 rejection as a capability mismatch
rather than a transient failure.Authorizations
API key from the Legnext dashboard. Authorization: Bearer <key> is accepted as an alternative.
Body
application/json
Extension direction: 0 = down, 1 = right, 2 = up, 3 = left.
Available options:
0, 1, 2, 3 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).
Extension factor.
Required range:
1.1 <= x <= 3Optional webhook URL. When set, the completed TaskResponse is POSTed to this URL; when empty, poll GET /v1/job/{job_id}.
Optional prompt guiding the extension.
Maximum string length:
8192Response
Pan task accepted.
Show child attributes
Show child attributes
Reserved for future use; currently null in public API responses.
Show child attributes
Show child attributes
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).
Show child attributes
Show child attributes
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
Show child attributes
Show child attributes
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