curl --request POST \
--url https://maas.apigo.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"prompt": "一只可爱的小猫在花园里玩耍,阳光明媚,油画风格",
"model": "gpt-image-1",
"size": "1024x1024",
"quality": "high"
}
'import requests
url = "https://maas.apigo.ai/v1/images/generations"
payload = {
"prompt": "一只可爱的小猫在花园里玩耍,阳光明媚,油画风格",
"model": "gpt-image-1",
"size": "1024x1024",
"quality": "high"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
prompt: '一只可爱的小猫在花园里玩耍,阳光明媚,油画风格',
model: 'gpt-image-1',
size: '1024x1024',
quality: 'high'
})
};
fetch('https://maas.apigo.ai/v1/images/generations', 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://maas.apigo.ai/v1/images/generations",
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' => '一只可爱的小猫在花园里玩耍,阳光明媚,油画风格',
'model' => 'gpt-image-1',
'size' => '1024x1024',
'quality' => 'high'
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($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://maas.apigo.ai/v1/images/generations"
payload := strings.NewReader("{\n \"prompt\": \"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格\",\n \"model\": \"gpt-image-1\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
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://maas.apigo.ai/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格\",\n \"model\": \"gpt-image-1\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://maas.apigo.ai/v1/images/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"prompt\": \"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格\",\n \"model\": \"gpt-image-1\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\"\n}"
response = http.request(request)
puts response.read_body{
"created": 1589478378,
"background": "auto",
"output_format": "png",
"quality": "high",
"size": "1024x1024",
"data": [
{
"url": "https://example.com/generated-image.png"
}
],
"usage": {
"input_tokens": 15,
"input_tokens_details": {
"image_tokens": 0,
"text_tokens": 15
},
"output_tokens": 1,
"total_tokens": 16
}
}{
"error": 123,
"message": "<string>"
}/v1/images/generations
OpenAI 호환 이미지 생성 모델을 사용하여 텍스트 프롬프트에서 이미지를 생성합니다.
curl --request POST \
--url https://maas.apigo.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"prompt": "一只可爱的小猫在花园里玩耍,阳光明媚,油画风格",
"model": "gpt-image-1",
"size": "1024x1024",
"quality": "high"
}
'import requests
url = "https://maas.apigo.ai/v1/images/generations"
payload = {
"prompt": "一只可爱的小猫在花园里玩耍,阳光明媚,油画风格",
"model": "gpt-image-1",
"size": "1024x1024",
"quality": "high"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
prompt: '一只可爱的小猫在花园里玩耍,阳光明媚,油画风格',
model: 'gpt-image-1',
size: '1024x1024',
quality: 'high'
})
};
fetch('https://maas.apigo.ai/v1/images/generations', 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://maas.apigo.ai/v1/images/generations",
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' => '一只可爱的小猫在花园里玩耍,阳光明媚,油画风格',
'model' => 'gpt-image-1',
'size' => '1024x1024',
'quality' => 'high'
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($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://maas.apigo.ai/v1/images/generations"
payload := strings.NewReader("{\n \"prompt\": \"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格\",\n \"model\": \"gpt-image-1\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
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://maas.apigo.ai/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格\",\n \"model\": \"gpt-image-1\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://maas.apigo.ai/v1/images/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"prompt\": \"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格\",\n \"model\": \"gpt-image-1\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\"\n}"
response = http.request(request)
puts response.read_body{
"created": 1589478378,
"background": "auto",
"output_format": "png",
"quality": "high",
"size": "1024x1024",
"data": [
{
"url": "https://example.com/generated-image.png"
}
],
"usage": {
"input_tokens": 15,
"input_tokens_details": {
"image_tokens": 0,
"text_tokens": 15
},
"output_tokens": 1,
"total_tokens": 16
}
}{
"error": 123,
"message": "<string>"
}- Authenticate with
Authorization: Bearer {API_KEY} - Use this as the text-to-image route; for edits, inpainting, or image expansion, use
/v1/images/edits gpt-image-1,dall-e-3, anddall-e-2expose different parameter sets, and those differences are now rendered in the native parameter panel above- If the response contains temporary
urlvalues, mirror them server-side quickly; if it containsb64_json, avoid decoding too many large images on the main thread
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
Text prompt for the desired image.
"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格"
Image generation model.
gpt-image-1, dall-e-3, dall-e-2 Only supported by gpt-image-1.
transparent, opaque, auto Only supported by gpt-image-1.
auto, low Number of images to generate. dall-e-3 only supports 1.
1 <= x <= 10Compression level for gpt-image-1 jpeg/webp output.
0 <= x <= 100Only supported by gpt-image-1.
png, jpeg, webp Number of partial images for streaming previews.
0 <= x <= 3Supported values vary by model.
auto, high, medium, low, hd, standard Only applies to dall-e-2 and dall-e-3.
url, b64_json Allowed values depend on the selected model.
1024x1024, 1536x1024, 1024x1536, auto, 256x256, 512x512, 1792x1024, 1024x1792 Only supported by gpt-image-1.
Only supported by dall-e-3.
vivid, natural Unique identifier for the end user.
Response
Successful image generation response
Unix timestamp in seconds.
Show child attributes
Show child attributes
transparent, opaque, auto png, jpeg, webp auto, high, medium, low, hd, standard Show child attributes
Show child attributes
