OpenAI image generations
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>"
}图片
/v1/images/generations
OpenAI 호환 이미지 생성 모델을 사용하여 텍스트 프롬프트에서 이미지를 생성합니다.
POST
/
v1
/
images
/
generations
OpenAI image generations
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>"
}用于根据文本提示生成图片。
- 使用
Authorization: Bearer {API_KEY}鉴权 - 文生图默认走这个 endpoint;如果你需要局部重绘、扩图或基于原图修改内容,改走
/v1/images/edits gpt-image-1、dall-e-3和dall-e-2的可选参数不同,重点差异已经放进上方原生参数区- 如果返回的是临时
url,建议由服务端尽快转存;如果返回b64_json,避免前端一次性解码过多大图
授权
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
请求体
application/json
Text prompt for the desired image.
示例:
"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格"
Image generation model.
可用选项:
gpt-image-1, dall-e-3, dall-e-2 Only supported by gpt-image-1.
可用选项:
transparent, opaque, auto Only supported by gpt-image-1.
可用选项:
auto, low Number of images to generate. dall-e-3 only supports 1.
必填范围:
1 <= x <= 10Compression level for gpt-image-1 jpeg/webp output.
必填范围:
0 <= x <= 100Only supported by gpt-image-1.
可用选项:
png, jpeg, webp Number of partial images for streaming previews.
必填范围:
0 <= x <= 3Supported values vary by model.
可用选项:
auto, high, medium, low, hd, standard Only applies to dall-e-2 and dall-e-3.
可用选项:
url, b64_json Allowed values depend on the selected model.
可用选项:
1024x1024, 1536x1024, 1024x1536, auto, 256x256, 512x512, 1792x1024, 1024x1792 Only supported by gpt-image-1.
Only supported by dall-e-3.
可用选项:
vivid, natural Unique identifier for the end user.
响应
Successful image generation response
