Shorten Prompt
curl --request POST \
--url https://api.legnext.ai/api/v1/shorten \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"prompt": "<string>",
"callback": "<string>"
}
'import requests
url = "https://api.legnext.ai/api/v1/shorten"
payload = {
"prompt": "<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({prompt: '<string>', callback: '<string>'})
};
fetch('https://api.legnext.ai/api/v1/shorten', 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/shorten",
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([
'prompt' => '<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/shorten"
payload := strings.NewReader("{\n \"prompt\": \"<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/shorten")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"<string>\",\n \"callback\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.legnext.ai/api/v1/shorten")
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 \"prompt\": \"<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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}Image Generation
Shorten
Turn a long prompt into shorter Midjourney prompt suggestions.
POST
/
v1
/
shorten
Shorten Prompt
curl --request POST \
--url https://api.legnext.ai/api/v1/shorten \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"prompt": "<string>",
"callback": "<string>"
}
'import requests
url = "https://api.legnext.ai/api/v1/shorten"
payload = {
"prompt": "<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({prompt: '<string>', callback: '<string>'})
};
fetch('https://api.legnext.ai/api/v1/shorten', 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/shorten",
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([
'prompt' => '<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/shorten"
payload := strings.NewReader("{\n \"prompt\": \"<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/shorten")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"<string>\",\n \"callback\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.legnext.ai/api/v1/shorten")
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 \"prompt\": \"<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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}{
"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
}
},
"model": "midjourney",
"output": {
"image_url": "<string>",
"image_urls": [
"<string>"
],
"seed": "<string>",
"available_actions": {}
}
}Shorten returns text suggestions rather than generated media. It is
asynchronous, so persist
job_id and wait for completed before reading the
output.
Treat the returned prompts as suggestions. If you later submit one to Text to
Image, apply model parameters using the
image parameter matrix.Authorizations
API key from the Legnext dashboard. Authorization: Bearer <key> is accepted as an alternative.
Body
application/json
Response
Shorten 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 ⌘I