注册

图像生成

⚠️ 测试中

POST https://api.quickrouter.ai/kling/v1/images/generations 在线调试 →
Authorization

在 Header 添加参数 Authorization,其值为 Bearer 之后拼接 Token

示例: Authorization: Bearer ********************

请求参数

Header 参数
Content-Type string
可选
示例: application/json
Authorization string
可选
示例: Bearer {{YOUR_API_KEY}}
Body 参数 application/json
model_name string
必需
模型名称 枚举值:kling-v1, kling-v1-5, kling-v2, kling-v2-new, kling-v2-1,kling-v3
prompt string
必需
正向文本提示词 不能超过2500个字符
negative_prompt string
可选
负向文本提示词 不能超过2500个字符
image string
可选
参考图像支持传入图片Base64编码或图片URL(确保可访问)
image_reference string
可选
图片参考类型 枚举值:subject(角色特征参考), face(人物长相参考) 使用face(人物长相参考)时,上传图片需仅含1张人脸。 使用 kling-v1-5 且 image 参数不为空时,当前参数必填
image_fidelity number
可选
生成过程中对用户上传图片的参考强度 取值范围:[0,1],数值越大参考强度越大
human_fidelity number
可选
面部参考强度,即参考图中人物五官相似度 仅 image_reference 参数为 subject 时生效 取值范围:[0,1],数值越大参考强度越大
resolution string
可选
生成图片的清晰度 枚举值:1k, 2k 1k:1K标清 2k:2K高清
n integer
必需
生成图片数量 取值范围:[1,9]
aspect_ratio string
可选
生成图片的画面纵横比(宽:高) 枚举值:16:9, 9:16, 1:1, 4:3, 3:4, 3:2, 2:3, 21:9
callback_url string
可选
示例
{
    "model_name": "kling-v1",
    "prompt": "生成一张海边的图",
    "negative_prompt": "",
    "image": "",
    "image_reference": "",
    "image_fidelity": 0.5,
    "human_fidelity": 0.45,
    "resolution": "1k",
    "n": 2,
    "aspect_ratio": "16:9",
    "callback_url": ""
}

请求示例代码

curl --location --request POST 'https://api.quickrouter.ai/kling/v1/images/generations' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data-raw '{
    "model_name": "kling-v1",
    "prompt": "生成一张海边的图",
    "negative_prompt": "",
    "image": "",
    "image_reference": "",
    "image_fidelity": 0.5,
    "human_fidelity": 0.45,
    "resolution": "1k",
    "n": 2,
    "aspect_ratio": "16:9",
    "callback_url": ""
}'
var myHeaders = new Headers();
myHeaders.append("Authorization", "Bearer YOUR_API_KEY");
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "model_name": "kling-v1",
  "prompt": "生成一张海边的图",
  "negative_prompt": "",
  "image": "",
  "image_reference": "",
  "image_fidelity": 0.5,
  "human_fidelity": 0.45,
  "resolution": "1k",
  "n": 2,
  "aspect_ratio": "16:9",
  "callback_url": ""
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

fetch("https://api.quickrouter.ai/kling/v1/images/generations", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));
import http.client
import json

conn = http.client.HTTPSConnection("api.quickrouter.ai")
payload = json.dumps({
  "model_name": "kling-v1",
  "prompt": "生成一张海边的图",
  "negative_prompt": "",
  "image": "",
  "image_reference": "",
  "image_fidelity": 0.5,
  "human_fidelity": 0.45,
  "resolution": "1k",
  "n": 2,
  "aspect_ratio": "16:9",
  "callback_url": ""
})
headers = {
  'Authorization': 'Bearer YOUR_API_KEY',
  'Content-Type': 'application/json'
}
conn.request("POST", "/kling/v1/images/generations", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))

返回响应

响应参数 application/json
object string
可选
示例
{}