Kling v3 视频生成

• 异步处理模式，返回任务ID用于后续查询
• 支持文本转视频、图生视频（首帧/首尾帧控制）
• 支持标准模式（720P）、专业模式（1080P）和 4K 模式
• 支持 3-15 秒视频时长
• 支持生成有声视频

POST /v1/videos/generations

cURL

curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-v3",
    "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'

import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "kling-v3",
    "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "kling-v3",
  prompt: "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/videos/generations"

    payload := map[string]interface{}{
        "model":        "kling-v3",
        "prompt":       "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
        "mode":         "std",
        "duration":     5,
        "aspect_ratio": "16:9",
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}

import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/videos/generations";

        String payload = """
        {
          "model": "kling-v3",
          "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
          "mode": "std",
          "duration": 5,
          "aspect_ratio": "16:9"
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}

<?php

$url = "https://api.apimart.ai/v1/videos/generations";

$payload = [
    "model" => "kling-v3",
    "prompt" => "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode" => "std",
    "duration" => 5,
    "aspect_ratio" => "16:9"
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>

require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/videos/generations")

payload = {
  model: "kling-v3",
  prompt: "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
}

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 = payload.to_json

response = http.request(request)
puts response.body

import Foundation

let url = URL(string: "https://api.apimart.ai/v1/videos/generations")!

let payload: [String: Any] = [
    "model": "kling-v3",
    "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()

using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/videos/generations";

        var payload = @"{
            ""model"": ""kling-v3"",
            ""prompt"": ""一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感"",
            ""mode"": ""std"",
            ""duration"": 5,
            ""aspect_ratio"": ""16:9""
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}

200

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_xxxxxxxxxx"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "请求参数无效",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "身份验证失败，请检查您的API密钥",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "账户余额不足，请充值后再试",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 429,
    "message": "请求过于频繁，请稍后再试",
    "type": "rate_limit_error"
  }
}

{
  "error": {
    "code": 500,
    "message": "服务器内部错误，请稍后重试",
    "type": "server_error"
  }
}

cURL

curl --request POST \
  --url https://api.apimart.ai/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-v3",
    "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'

import requests

url = "https://api.apimart.ai/v1/videos/generations"

payload = {
    "model": "kling-v3",
    "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/videos/generations";

const payload = {
  model: "kling-v3",
  prompt: "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/videos/generations"

    payload := map[string]interface{}{
        "model":        "kling-v3",
        "prompt":       "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
        "mode":         "std",
        "duration":     5,
        "aspect_ratio": "16:9",
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}

import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/videos/generations";

        String payload = """
        {
          "model": "kling-v3",
          "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
          "mode": "std",
          "duration": 5,
          "aspect_ratio": "16:9"
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}

<?php

$url = "https://api.apimart.ai/v1/videos/generations";

$payload = [
    "model" => "kling-v3",
    "prompt" => "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode" => "std",
    "duration" => 5,
    "aspect_ratio" => "16:9"
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>

require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/videos/generations")

payload = {
  model: "kling-v3",
  prompt: "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
  mode: "std",
  duration: 5,
  aspect_ratio: "16:9"
}

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 = payload.to_json

response = http.request(request)
puts response.body

import Foundation

let url = URL(string: "https://api.apimart.ai/v1/videos/generations")!

let payload: [String: Any] = [
    "model": "kling-v3",
    "prompt": "一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感",
    "mode": "std",
    "duration": 5,
    "aspect_ratio": "16:9"
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()

using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/videos/generations";

        var payload = @"{
            ""model"": ""kling-v3"",
            ""prompt"": ""一只金色的猫咪在阳光下的草地上奔跑，慢动作，电影质感"",
            ""mode"": ""std"",
            ""duration"": 5,
            ""aspect_ratio"": ""16:9""
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}

200

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_xxxxxxxxxx"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "请求参数无效",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "身份验证失败，请检查您的API密钥",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "账户余额不足，请充值后再试",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 429,
    "message": "请求过于频繁，请稍后再试",
    "type": "rate_limit_error"
  }
}

{
  "error": {
    "code": 500,
    "message": "服务器内部错误，请稍后重试",
    "type": "server_error"
  }
}

​

认证

Authorization · string · 必填

所有接口均需要使用 Bearer Token 进行认证

获取 API Key：

访问 API Key 管理页面 获取您的 API Key

使用时在请求头中添加：

Authorization: Bearer YOUR_API_KEY

​

请求参数

model · string · 必填

视频生成模型名称

支持的模型：

• kling-v3 - 可灵 v3（推荐）

prompt · string · 必填

正向文本提示词

建议详细描述场景、动作、风格等，以获得更好的生成效果。建议使用英文提示词。

示例："一只金毛犬在沙滩上奔跑，日落，电影质感"

negative_prompt · string

负面提示词，用于排除不想要的内容

示例："模糊, 低画质, 变形"

mode · string · 默认值: "std"

生成模式

可选值：

• std - 标准模式（720P）
• pro - 专业模式（1080P）
• 4k - 4K 模式

默认值：std

duration · integer · 默认值: "5"

默认值：5 视频时长（秒）

取值范围：3-15（最短 3 秒，最长 15 秒）

⚠️ 注意： 必须输入纯数字（如 6），不要加引号，否则会报错

aspect_ratio · string · 默认值: "16:9"

视频宽高比

可选值：

• 16:9 - 横屏
• 9:16 - 竖屏
• 1:1 - 方形

默认值：16:9

image_urls · array<url>

图片 URL 数组，用于图生视频

• 传 1 张：作为首帧图片
• 传 2 张：自动分配为首帧 + 尾帧

最多支持 2 张图片

示例：["https://example.com/first.jpg"]

• 最多支持 2 张图片
• 图片 URL 必须公开可访问，不能有防盗链
• 图生视频时，aspect_ratio 可能被图片实际比例覆盖

watermark · boolean

是否添加水印

audio · boolean · 默认值: "false"

是否生成有声视频

multi_shot · boolean · 默认值: "false"

是否启用多镜头分镜模式。

• true
• false

shot_type · string

分镜方式：customize（自定义）/ intelligence（智能）。

当 multi_shot=true 时必填。

multi_prompt · array<object>

各分镜信息，如提示词、时长等。

通过 index、prompt、duration 定义分镜序号及提示词、时长。

• 最多支持 6 个分镜，最少支持 1 个分镜
• 每个分镜相关内容的最大长度不超过 512
• 每个分镜的时长不大于当前任务总时长，且不小于 1
• 所有分镜时长之和等于当前任务总时长

用 key:value 承载，格式如下：

"multi_prompt": [
  { "index": 1, "prompt": "string", "duration": 5 },
  { "index": 2, "prompt": "string", "duration": 5 }
]

当 multi_shot=true 且 shot_type=customize 时当前参数必填。

element_list · array<object>

引用元素列表，最多支持 3 个主体。支持两种方式：

• 现场创建主体：传 name、description、element_input_urls

常见写法：

[
  {
    "name": "element_dog",
    "description": "a golden retriever, fluffy fur, friendly expression",
    "element_input_urls": [
      "https://example.com/image1.png",
      "https://example.com/image2.png"
    ]
  },
  {
    "name": "element_cat",
    "description": "an orange tabby cat, round face, bright eyes",
    "element_input_urls": [
      "https://example.com/image1.png",
      "https://example.com/image2.png"
    ]
  }
]

说明：

• 现场创建时：name、description、element_input_urls 必填
• element_input_urls：每个主体至少 2 张、最多 4 张（第 1 张正面图 + 其余参考图）
• prompt 中通过 @name 引用，如："@element_dog 和 @element_cat 在草地上追逐玩耍"

​

参数互斥与边界

• mode=4k 在本页模型 kling-v3 可用
• image_urls 最多 2 张（1 张首帧，2 张首尾帧）
• 仅尾帧输入（只有 last_frame）会报错，必须配首帧
• multi_shot=true 时，顶层 prompt 可省略
• multi_prompt 最多 6 个分镜，index 从 1 连续递增

​

功能支持矩阵

类型	功能	std 5s	std 10s	std 15s	pro 5s	pro 10s
文生视频	视频生成	✅	✅	✅	✅	✅
图生视频	视频生成	✅	✅	✅	✅	✅
图生视频	首帧	✅	✅	✅	✅	✅
图生视频	尾帧	✅	✅	✅	✅	✅

​

文生视频 vs 图生视频

系统会根据 image_urls 自动判断生成模式（文生 / 图生）。

参数	文生视频	图生视频
prompt	✅ 必填	✅ 建议填写
image_urls	❌ 不传	✅ 可选（1-2 张）
negative_prompt	✅ 可选	✅ 可选
mode	✅ 可选	✅ 可选
duration	✅ 可选（3-15）	✅ 可选（3-15）
aspect_ratio	✅ 可选	✅ 可选（图生可能受输入图影响）
watermark	✅ 可选	✅ 可选
audio	✅ 可选	✅ 可选

​

响应

code · integer

响应状态码，成功时为 200

data · array

返回数据数组

显示 数组元素

status · string

任务状态，初始提交时为 submitted

task_id · string

任务唯一标识符，用于查询任务状态和结果

​

使用场景

​

场景 1：文生视频（标准模式）

{
  "model": "kling-v3",
  "prompt": "一只金毛犬在沙滩上奔跑，日落，电影质感",
  "mode": "std",
  "duration": 5,
  "aspect_ratio": "16:9"
}

​

场景 2：文生视频（专业模式 + 负面提示词）

{
  "model": "kling-v3",
  "prompt": "东京涩谷十字路口，雨夜霓虹灯倒映在湿漉漉的地面上，行人撑伞穿行",
  "negative_prompt": "模糊, 低画质, 变形",
  "mode": "pro",
  "duration": 10,
  "aspect_ratio": "16:9"
}

​

场景 3：文生视频（15 秒）

{
  "model": "kling-v3",
  "prompt": "花园中一朵花绽放的延时摄影",
  "duration": 15,
  "aspect_ratio": "16:9"
}

​

场景 4：图生视频（首帧图片）

{
  "model": "kling-v3",
  "prompt": "猫咪缓缓向前走，环顾四周",
  "image_urls": ["https://example.com/cat.jpg"],
  "mode": "std",
  "duration": 5
}

​

场景 5：图生视频（首帧 + 尾帧控制）

{
  "model": "kling-v3",
  "prompt": "流畅的电影级画面过渡",
  "image_urls": [
    "https://example.com/frame-start.jpg",
    "https://example.com/frame-end.jpg"
  ],
  "mode": "std",
  "duration": 5
}

​

场景 6：生成有声视频

{
  "model": "kling-v3",
  "prompt": "一个在这个舞台上唱歌的摇滚歌手，演唱会现场，灯光闪烁",
  "audio": true,
  "mode": "std",
  "duration": 5
}

​

场景 7：多镜头分镜（customize，15 秒，有声竖屏）

{
  "model": "kling-v3",
  "multi_prompt": [
    {
      "index": 1,
      "prompt": "Two friends talking under a streetlight at night. Warm glow, casual poses, no dialogue.",
      "duration": 2
    },
    {
      "index": 2,
      "prompt": "A runner sprinting through a forest, leaves flying. Low-angle shot, focus on movement.",
      "duration": 3
    },
    {
      "index": 3,
      "prompt": "A woman hugging a cat, smiling. Soft sunlight, cozy home setting, emphasize warmth.",
      "duration": 3
    },
    {
      "index": 4,
      "prompt": "A door creaking open, shadowy hallway. Dark tones, minimal details, eerie mood.",
      "duration": 3
    },
    {
      "index": 5,
      "prompt": "A man slipping on a banana peel, shocked expression. Exaggerated pose, bright colors.",
      "duration": 3
    },
    {
      "index": 6,
      "prompt": "A sunset over mountains, small figure walking away. Wide angle, peaceful atmosphere.",
      "duration": 1
    }
  ],
  "multi_shot": true,
  "shot_type": "customize",
  "duration": 15,
  "mode": "pro",
  "audio": true,
  "aspect_ratio": "9:16"
}

查询任务结果

视频生成为异步任务，提交后会返回 task_id。使用 获取任务状态 接口查询生成进度和结果。