curl --request POST \
--url https://api.ttapi.io/openai/gpt/generations \
--header 'Content-Type: application/json' \
--header 'TT-API-KEY: <api-key>' \
--data '
{
"prompt": "<string>",
"model": "gpt-image-2",
"referImages": [
"https://cdn.ttapi.io/xxx1.png",
"https://cdn.ttapi.io/xxx2.png"
],
"aspect_ratio": "1:1",
"size": "1024x1024",
"hookUrl": "<string>"
}
'import requests
url = "https://api.ttapi.io/openai/gpt/generations"
payload = {
"prompt": "<string>",
"model": "gpt-image-2",
"referImages": ["https://cdn.ttapi.io/xxx1.png", "https://cdn.ttapi.io/xxx2.png"],
"aspect_ratio": "1:1",
"size": "1024x1024",
"hookUrl": "<string>"
}
headers = {
"TT-API-KEY": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'TT-API-KEY': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
prompt: '<string>',
model: 'gpt-image-2',
referImages: ['https://cdn.ttapi.io/xxx1.png', 'https://cdn.ttapi.io/xxx2.png'],
aspect_ratio: '1:1',
size: '1024x1024',
hookUrl: '<string>'
})
};
fetch('https://api.ttapi.io/openai/gpt/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.ttapi.io/openai/gpt/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' => '<string>',
'model' => 'gpt-image-2',
'referImages' => [
'https://cdn.ttapi.io/xxx1.png',
'https://cdn.ttapi.io/xxx2.png'
],
'aspect_ratio' => '1:1',
'size' => '1024x1024',
'hookUrl' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"TT-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.ttapi.io/openai/gpt/generations"
payload := strings.NewReader("{\n \"prompt\": \"<string>\",\n \"model\": \"gpt-image-2\",\n \"referImages\": [\n \"https://cdn.ttapi.io/xxx1.png\",\n \"https://cdn.ttapi.io/xxx2.png\"\n ],\n \"aspect_ratio\": \"1:1\",\n \"size\": \"1024x1024\",\n \"hookUrl\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("TT-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.ttapi.io/openai/gpt/generations")
.header("TT-API-KEY", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"<string>\",\n \"model\": \"gpt-image-2\",\n \"referImages\": [\n \"https://cdn.ttapi.io/xxx1.png\",\n \"https://cdn.ttapi.io/xxx2.png\"\n ],\n \"aspect_ratio\": \"1:1\",\n \"size\": \"1024x1024\",\n \"hookUrl\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.ttapi.io/openai/gpt/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["TT-API-KEY"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"prompt\": \"<string>\",\n \"model\": \"gpt-image-2\",\n \"referImages\": [\n \"https://cdn.ttapi.io/xxx1.png\",\n \"https://cdn.ttapi.io/xxx2.png\"\n ],\n \"aspect_ratio\": \"1:1\",\n \"size\": \"1024x1024\",\n \"hookUrl\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"status": "SUCCESS",
"message": "success",
"data": {
"jobId": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}{
"status": "FAILED",
"message": "\"prompt\" cannot be empty.",
"data": {}
}{
"status": "FAILED",
"message": "Wrong TT-API-KEY or email is not activated."
}GPT-Image Generation [Unofficial]
Generate images based on text prompts and image resources
curl --request POST \
--url https://api.ttapi.io/openai/gpt/generations \
--header 'Content-Type: application/json' \
--header 'TT-API-KEY: <api-key>' \
--data '
{
"prompt": "<string>",
"model": "gpt-image-2",
"referImages": [
"https://cdn.ttapi.io/xxx1.png",
"https://cdn.ttapi.io/xxx2.png"
],
"aspect_ratio": "1:1",
"size": "1024x1024",
"hookUrl": "<string>"
}
'import requests
url = "https://api.ttapi.io/openai/gpt/generations"
payload = {
"prompt": "<string>",
"model": "gpt-image-2",
"referImages": ["https://cdn.ttapi.io/xxx1.png", "https://cdn.ttapi.io/xxx2.png"],
"aspect_ratio": "1:1",
"size": "1024x1024",
"hookUrl": "<string>"
}
headers = {
"TT-API-KEY": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'TT-API-KEY': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
prompt: '<string>',
model: 'gpt-image-2',
referImages: ['https://cdn.ttapi.io/xxx1.png', 'https://cdn.ttapi.io/xxx2.png'],
aspect_ratio: '1:1',
size: '1024x1024',
hookUrl: '<string>'
})
};
fetch('https://api.ttapi.io/openai/gpt/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.ttapi.io/openai/gpt/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' => '<string>',
'model' => 'gpt-image-2',
'referImages' => [
'https://cdn.ttapi.io/xxx1.png',
'https://cdn.ttapi.io/xxx2.png'
],
'aspect_ratio' => '1:1',
'size' => '1024x1024',
'hookUrl' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"TT-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.ttapi.io/openai/gpt/generations"
payload := strings.NewReader("{\n \"prompt\": \"<string>\",\n \"model\": \"gpt-image-2\",\n \"referImages\": [\n \"https://cdn.ttapi.io/xxx1.png\",\n \"https://cdn.ttapi.io/xxx2.png\"\n ],\n \"aspect_ratio\": \"1:1\",\n \"size\": \"1024x1024\",\n \"hookUrl\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("TT-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.ttapi.io/openai/gpt/generations")
.header("TT-API-KEY", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"<string>\",\n \"model\": \"gpt-image-2\",\n \"referImages\": [\n \"https://cdn.ttapi.io/xxx1.png\",\n \"https://cdn.ttapi.io/xxx2.png\"\n ],\n \"aspect_ratio\": \"1:1\",\n \"size\": \"1024x1024\",\n \"hookUrl\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.ttapi.io/openai/gpt/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["TT-API-KEY"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"prompt\": \"<string>\",\n \"model\": \"gpt-image-2\",\n \"referImages\": [\n \"https://cdn.ttapi.io/xxx1.png\",\n \"https://cdn.ttapi.io/xxx2.png\"\n ],\n \"aspect_ratio\": \"1:1\",\n \"size\": \"1024x1024\",\n \"hookUrl\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"status": "SUCCESS",
"message": "success",
"data": {
"jobId": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}{
"status": "FAILED",
"message": "\"prompt\" cannot be empty.",
"data": {}
}{
"status": "FAILED",
"message": "Wrong TT-API-KEY or email is not activated."
}Authorizations
You can obtain your API key from the TTAPI Dashboard.
Body
Text prompt for image generation. Since this is a reverse-engineered model, it's recommended to include keywords in your prompt such as: "draw a xxx", "generate a", 'draw a xxx', Language is not restricted; OpenAI itself supports multilingual models with excellent Chinese support.
Supported models
gpt-image-1.5, gpt-image-2, gpt-image-2-plus Reference image array
[
"https://cdn.ttapi.io/xxx1.png",
"https://cdn.ttapi.io/xxx2.png"
]
Support model: gpt-image-2
1:1, 3:4, 4:3, 16:9, 9:16 "1:1"
Image Size (width × height), support model: gpt-image-2-plus
must meet the following constraints:
Both width and height must be multiples of 16 Maximum edge ≤ 3840 Aspect ratio ≤ 3:1 Total pixels: 655,360 ~ 8,294,400
If the input size is invalid, it will be automatically adjusted to a valid range
"1024x1024"
Callback notification URL. When task completes or fails, this URL will be notified. Notification data structure [blocked] is consistent with fetch structure. If not set, you need to request the fetch endpoint [blocked] for query