OpenAI image generations
curl --request POST \
--url https://api-vip.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-2",
"size": "1024x1024",
"quality": "medium",
"output_format": "png"
}
'import requests
url = "https://api-vip.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-2",
"size": "1024x1024",
"quality": "medium",
"output_format": "png"
}
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-2',
size: '1024x1024',
quality: 'medium',
output_format: 'png'
})
};
fetch('https://api-vip.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://api-vip.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-2',
'size' => '1024x1024',
'quality' => 'medium',
'output_format' => 'png'
]),
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://api-vip.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-2\",\n \"size\": \"1024x1024\",\n \"quality\": \"medium\",\n \"output_format\": \"png\"\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://api-vip.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-2\",\n \"size\": \"1024x1024\",\n \"quality\": \"medium\",\n \"output_format\": \"png\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api-vip.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-2\",\n \"size\": \"1024x1024\",\n \"quality\": \"medium\",\n \"output_format\": \"png\"\n}"
response = http.request(request)
puts response.read_body{
"created": 1589478378,
"background": "opaque",
"output_format": "png",
"quality": "medium",
"size": "1024x1024",
"data": [
{
"b64_json": "iVBORw0KGgoAAA..."
}
],
"usage": {
"input_tokens": 15,
"input_tokens_details": {
"image_tokens": 0,
"text_tokens": 15
},
"output_tokens": 1372,
"output_tokens_details": {
"image_tokens": 1372,
"text_tokens": 0
},
"total_tokens": 1387
}
}{
"error": 123,
"message": "<string>"
}图片
/v1/images/generations
Creates images from text prompts with OpenAI-compatible image generation models.
POST
/
v1
/
images
/
generations
OpenAI image generations
curl --request POST \
--url https://api-vip.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-2",
"size": "1024x1024",
"quality": "medium",
"output_format": "png"
}
'import requests
url = "https://api-vip.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-2",
"size": "1024x1024",
"quality": "medium",
"output_format": "png"
}
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-2',
size: '1024x1024',
quality: 'medium',
output_format: 'png'
})
};
fetch('https://api-vip.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://api-vip.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-2',
'size' => '1024x1024',
'quality' => 'medium',
'output_format' => 'png'
]),
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://api-vip.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-2\",\n \"size\": \"1024x1024\",\n \"quality\": \"medium\",\n \"output_format\": \"png\"\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://api-vip.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-2\",\n \"size\": \"1024x1024\",\n \"quality\": \"medium\",\n \"output_format\": \"png\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api-vip.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-2\",\n \"size\": \"1024x1024\",\n \"quality\": \"medium\",\n \"output_format\": \"png\"\n}"
response = http.request(request)
puts response.read_body{
"created": 1589478378,
"background": "opaque",
"output_format": "png",
"quality": "medium",
"size": "1024x1024",
"data": [
{
"b64_json": "iVBORw0KGgoAAA..."
}
],
"usage": {
"input_tokens": 15,
"input_tokens_details": {
"image_tokens": 0,
"text_tokens": 15
},
"output_tokens": 1372,
"output_tokens_details": {
"image_tokens": 1372,
"text_tokens": 0
},
"total_tokens": 1387
}
}{
"error": 123,
"message": "<string>"
}用于根据文本提示生成图片。
GPT Image 2
- 使用 GPT Image 2 时请显式传入
model: "gpt-image-2";未传model时,ApiGo 默认使用dall-e-2 gpt-image-2支持文生图、灵活尺寸和low、medium、high、auto四档质量- 未传
size或quality时,ApiGo 分别使用1024x1024和medium;如需让模型自动选择,显式传入auto - 自定义尺寸的两条边必须是 16 的倍数,长短边比例不超过 3:1,单边不超过 3840 px,总像素数为 655,360–8,294,400
background可传opaque或auto;gpt-image-2当前不支持transparent- 图片通过
data[].b64_json返回。解码后按output_format保存,默认格式为png
jpeg 和 webp 可配合 output_compression(0–100)控制压缩率。moderation 支持 auto 和 low。
复杂提示词可能需要接近两分钟处理,请为客户端配置足够的请求超时时间。
如需基于原图修改、局部重绘或多图融合,请使用 /v1/images/edits。授权
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
请求体
application/json
描述目标图片的文本提示词。
示例:
"一只可爱的小猫在花园里玩耍,阳光明媚,油画风格"
图片生成模型;未传时 ApiGo 使用 dall-e-2。
可用选项:
gpt-image-2, gpt-image-1, dall-e-3, dall-e-2 GPT Image 模型支持。gpt-image-2 仅支持 opaque 和 auto,不支持 transparent。
可用选项:
transparent, opaque, auto GPT Image 模型支持 auto 和 low。
可用选项:
auto, low 生成图片的数量;dall-e-3 仅支持 1。
必填范围:
1 <= x <= 10GPT Image 模型生成 JPEG/WebP 时的压缩率。
必填范围:
0 <= x <= 100GPT Image 模型支持 png、jpeg 和 webp。
可用选项:
png, jpeg, webp 不同模型支持的值不同。GPT Image 未传时,ApiGo 使用 medium。
可用选项:
auto, high, medium, low, hd, standard 仅适用于 dall-e-2 和 dall-e-3。
可用选项:
url, b64_json 允许值取决于模型。gpt-image-2 支持 auto 或符合尺寸约束的自定义分辨率;未传时 ApiGo 使用 1024x1024。
示例:
"1024x1024"
仅 dall-e-3 支持。
可用选项:
vivid, natural 终端用户的唯一标识。
响应
Successful image generation response
