gpt-image-2-pro 生成图像 API
curl --request POST \
--url https://www.geeknow.top/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "<string>",
"prompt": "<string>",
"n": 123,
"size": "<string>",
"image": [
"<string>"
],
"response_format": "<string>",
"quality": "<string>",
"style": {},
"background": {},
"watermark": true
}
'import requests
url = "https://www.geeknow.top/v1/images/generations"
payload = {
"model": "<string>",
"prompt": "<string>",
"n": 123,
"size": "<string>",
"image": ["<string>"],
"response_format": "<string>",
"quality": "<string>",
"style": {},
"background": {},
"watermark": True
}
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({
model: '<string>',
prompt: '<string>',
n: 123,
size: '<string>',
image: ['<string>'],
response_format: '<string>',
quality: '<string>',
style: {},
background: {},
watermark: true
})
};
fetch('https://www.geeknow.top/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://www.geeknow.top/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([
'model' => '<string>',
'prompt' => '<string>',
'n' => 123,
'size' => '<string>',
'image' => [
'<string>'
],
'response_format' => '<string>',
'quality' => '<string>',
'style' => [
],
'background' => [
],
'watermark' => true
]),
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://www.geeknow.top/v1/images/generations"
payload := strings.NewReader("{\n \"model\": \"<string>\",\n \"prompt\": \"<string>\",\n \"n\": 123,\n \"size\": \"<string>\",\n \"image\": [\n \"<string>\"\n ],\n \"response_format\": \"<string>\",\n \"quality\": \"<string>\",\n \"style\": {},\n \"background\": {},\n \"watermark\": true\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://www.geeknow.top/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"<string>\",\n \"prompt\": \"<string>\",\n \"n\": 123,\n \"size\": \"<string>\",\n \"image\": [\n \"<string>\"\n ],\n \"response_format\": \"<string>\",\n \"quality\": \"<string>\",\n \"style\": {},\n \"background\": {},\n \"watermark\": true\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://www.geeknow.top/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 \"model\": \"<string>\",\n \"prompt\": \"<string>\",\n \"n\": 123,\n \"size\": \"<string>\",\n \"image\": [\n \"<string>\"\n ],\n \"response_format\": \"<string>\",\n \"quality\": \"<string>\",\n \"style\": {},\n \"background\": {},\n \"watermark\": true\n}"
response = http.request(request)
puts response.read_body{
"created": 1735689600,
"data": [
{
"url": "https://.../images/img-pro-abc123.png",
"revised_prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富"
}
]
}
{
"created": 1735689600,
"data": [
{
"b64_json": "iVBORw0KGgoAAAANSUhEUgAA...",
"revised_prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富"
}
]
}
gpt-image-2-pro
gpt-image-2-pro 生成图像 API
使用 POST /v1/images/generations 调用 gpt-image-2-pro 生成高分辨率图像。
POST
https://www.geeknow.top
/
v1
/
images
/
generations
gpt-image-2-pro 生成图像 API
curl --request POST \
--url https://www.geeknow.top/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "<string>",
"prompt": "<string>",
"n": 123,
"size": "<string>",
"image": [
"<string>"
],
"response_format": "<string>",
"quality": "<string>",
"style": {},
"background": {},
"watermark": true
}
'import requests
url = "https://www.geeknow.top/v1/images/generations"
payload = {
"model": "<string>",
"prompt": "<string>",
"n": 123,
"size": "<string>",
"image": ["<string>"],
"response_format": "<string>",
"quality": "<string>",
"style": {},
"background": {},
"watermark": True
}
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({
model: '<string>',
prompt: '<string>',
n: 123,
size: '<string>',
image: ['<string>'],
response_format: '<string>',
quality: '<string>',
style: {},
background: {},
watermark: true
})
};
fetch('https://www.geeknow.top/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://www.geeknow.top/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([
'model' => '<string>',
'prompt' => '<string>',
'n' => 123,
'size' => '<string>',
'image' => [
'<string>'
],
'response_format' => '<string>',
'quality' => '<string>',
'style' => [
],
'background' => [
],
'watermark' => true
]),
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://www.geeknow.top/v1/images/generations"
payload := strings.NewReader("{\n \"model\": \"<string>\",\n \"prompt\": \"<string>\",\n \"n\": 123,\n \"size\": \"<string>\",\n \"image\": [\n \"<string>\"\n ],\n \"response_format\": \"<string>\",\n \"quality\": \"<string>\",\n \"style\": {},\n \"background\": {},\n \"watermark\": true\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://www.geeknow.top/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"<string>\",\n \"prompt\": \"<string>\",\n \"n\": 123,\n \"size\": \"<string>\",\n \"image\": [\n \"<string>\"\n ],\n \"response_format\": \"<string>\",\n \"quality\": \"<string>\",\n \"style\": {},\n \"background\": {},\n \"watermark\": true\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://www.geeknow.top/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 \"model\": \"<string>\",\n \"prompt\": \"<string>\",\n \"n\": 123,\n \"size\": \"<string>\",\n \"image\": [\n \"<string>\"\n ],\n \"response_format\": \"<string>\",\n \"quality\": \"<string>\",\n \"style\": {},\n \"background\": {},\n \"watermark\": true\n}"
response = http.request(request)
puts response.read_body{
"created": 1735689600,
"data": [
{
"url": "https://.../images/img-pro-abc123.png",
"revised_prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富"
}
]
}
{
"created": 1735689600,
"data": [
{
"b64_json": "iVBORw0KGgoAAAANSUhEUgAA...",
"revised_prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富"
}
]
}
gpt-image-2-pro 生成图像 API
gpt-image-2-pro 用于提交高分辨率图像生成请求。请求体使用 JSON 格式,按模型名、提示词、输出尺寸和返回格式描述本次生成任务。
- 请求路径为
POST /v1/images/generations。 - 通过
model = "gpt-image-2-pro"选择目标模型。 prompt描述要生成的图像内容。size传实际输出尺寸,例如2048x2048、2560x1712、3840x2160。- 支持
url和b64_json两种返回格式。 - 可在 JSON 中附带
image作为参考图。
方法与路径
POST /v1/images/generations
请求示例
curl -X POST https://www.geeknow.top/v1/images/generations \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2-pro",
"prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富",
"n": 1,
"size": "3840x2160",
"response_format": "url"
}'
import requests
resp = requests.post(
"https://www.geeknow.top/v1/images/generations",
headers={
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
json={
"model": "gpt-image-2-pro",
"prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富",
"n": 1,
"size": "3840x2160",
"response_format": "url",
},
timeout=60,
)
print(resp.json())
const response = await fetch("https://www.geeknow.top/v1/images/generations", {
method: "POST",
headers: {
Authorization: "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "gpt-image-2-pro",
prompt: "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富",
n: 1,
size: "3840x2160",
response_format: "url",
}),
});
console.log(await response.json());
响应示例
{
"created": 1735689600,
"data": [
{
"url": "https://.../images/img-pro-abc123.png",
"revised_prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富"
}
]
}
{
"created": 1735689600,
"data": [
{
"b64_json": "iVBORw0KGgoAAAANSUhEUgAA...",
"revised_prompt": "一张电影级科技城市全景海报,清晨雾气,纵深透视,细节丰富"
}
]
}
认证
Authorization: Bearer YOUR_API_KEY
Body
固定传
gpt-image-2-pro。生成提示词,用于描述想要生成的图片。
生成数量。若不传或显式传
0,按 1 处理。输出尺寸。常见值为
2048x2048、2048x1536、2560x1712、1712x2560、3840x2160、2160x3840。可选参考图输入。常见写法是 Base64 字符串或 Base64 数组。
返回格式,常见值为
url、b64_json。质量字段。是否真正生效取决于最终命中的渠道。
风格字段,原样透传给支持的上游。
背景控制字段,原样透传给支持的上游。
显式水印开关。
false 与不传语义不同。尺寸表
2K 档位
| 预设 | 实际目标尺寸 |
|---|---|
1:1(2K) | 2048x2048 |
4:3(2K) | 2048x1536 |
3:2(2K) | 2560x1712 |
2:3(2K) | 1712x2560 |
16:9(2K) | 2048x1152 |
9:16(2K) | 1152x2048 |
4K 档位
| 预设 | 实际目标尺寸 |
|---|---|
1:1(4K) | 2880x2880 |
4:3(4K) | 3840x2880 |
3:2(4K) | 3840x2560 |
2:3(4K) | 2560x3840 |
16:9(4K) | 3840x2160 |
9:16(4K) | 2160x3840 |
请求体中的
size 传“实际目标尺寸”这一列。Response
生成时间戳。
response_format = url 时返回的图片 URL。response_format = b64_json 时返回的图片 Base64 数据。部分上游会改写提示词并返回在这个字段里。
异步调用
如需提交后异步查询结果,可以使用图像异步生成入口:POST /v1/images/generations/async
model = "gpt-image-2-pro"。提交成功后读取返回的 id / task_id,再通过 GET /v1/images/generations/async/{taskId} 查询状态和结果。
相关页面
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