Kling Video O1 Video Generation

curl --request POST \
  --url https://toapis.com/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "mode": "std",
    "duration": 5,
    "metadata": {
      "image_list": [{"image_url": "https://example.com/portrait.jpg"}]
    }
  }'

import requests

response = requests.post(
    "https://toapis.com/v1/videos/generations",
    headers={"Authorization": "Bearer <token>", "Content-Type": "application/json"},
    json={
        "model": "kling-video-o1",
        "prompt": "Make the person in <<<image_1>>> wave at the camera",
        "mode": "std",
        "duration": 5,
        "metadata": {"image_list": [{"image_url": "https://example.com/portrait.jpg"}]},
    },
)

print(response.json())

const response = await fetch("https://toapis.com/v1/videos/generations", {
  method: "POST",
  headers: {
    Authorization: "Bearer <token>",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "kling-video-o1",
    prompt: "Make the person in <<<image_1>>> wave at the camera",
    mode: "std",
    duration: 5,
    metadata: {
      image_list: [{ image_url: "https://example.com/portrait.jpg" }]
    }
  })
});

console.log(await response.json());

POST

videos

generations

curl --request POST \
  --url https://toapis.com/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "mode": "std",
    "duration": 5,
    "metadata": {
      "image_list": [{"image_url": "https://example.com/portrait.jpg"}]
    }
  }'

import requests

response = requests.post(
    "https://toapis.com/v1/videos/generations",
    headers={"Authorization": "Bearer <token>", "Content-Type": "application/json"},
    json={
        "model": "kling-video-o1",
        "prompt": "Make the person in <<<image_1>>> wave at the camera",
        "mode": "std",
        "duration": 5,
        "metadata": {"image_list": [{"image_url": "https://example.com/portrait.jpg"}]},
    },
)

print(response.json())

const response = await fetch("https://toapis.com/v1/videos/generations", {
  method: "POST",
  headers: {
    Authorization: "Bearer <token>",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "kling-video-o1",
    prompt: "Make the person in <<<image_1>>> wave at the camera",
    mode: "std",
    duration: 5,
    metadata: {
      image_list: [{ image_url: "https://example.com/portrait.jpg" }]
    }
  })
});

console.log(await response.json());

Note for users in mainland China: Please use https://toapis.cn as the API endpoint (Base URL). Replace https://toapis.com with https://toapis.cn in the examples in this document.

Async task API, returns a task ID after submission
Uses the official Omni reference structures: image_list, video_list, and element_list
mode=std maps to 720P, mode=pro maps to 1080P
audio=true generates an audio video and is billed as Sound
Requests with video_list are billed as Video
audio and video_list are mutually exclusive

Use publicly accessible image or video URLs. Do not pass base64 media data. Upload local images with the Upload Image API first.

Authorization

string

required

All endpoints require Bearer Token authentication.

Authorization: Bearer YOUR_API_KEY

Request Parameters

string

required

Video generation model name, fixed as kling-video-o1.

string

required

Text prompt. Use official Omni placeholders to reference input assets:

<<<image_N>>> references metadata.image_list
<<<video_N>>> references video_list
<<<element_N>>> references metadata.element_list

Example: "Make the person in <<<image_1>>> wave at the camera"

List order must match the placeholder order in the prompt. The system does not auto-prepend a first frame or insert placeholders for you.

string

default:"std"

Generation mode. This also determines the billing resolution.

std - standard mode, 720P
pro - professional mode, 1080P

integer

default:"5"

Video duration in seconds. Options: 3, 4, 5, 6, 7, 8, 9, 10

string

default:"16:9"

Video aspect ratio. Common values: 16:9, 9:16, 1:1

boolean

default:"false"

Whether to generate an audio video.

audio and video_list are mutually exclusive. Do not pass audio=true when video_list is provided.

Official Omni reference video list. Reference videos in the prompt with <<<video_1>>>, <<<video_2>>>, and so on.

Show Show video_list object fields

string

required

Reference video URL. It must be publicly accessible.

string

default:"base"

Reference type: base for source video editing, or feature for feature/motion reference.

string

default:"no"

Whether to keep the original video sound: yes or no.

object

Extended parameters.

Show Show metadata fields

object[]

Official Omni image list. Reference images in the prompt with <<<image_1>>>, <<<image_2>>>, and so on.

Show Show image_list object fields

string

required

Image URL. It must be publicly accessible.

string

Image type. For first/end frame semantics, use first_frame or end_frame. If end_frame is provided, first_frame is required too.

object[]

Official Omni subject/role reference list. Reference elements in the prompt with <<<element_1>>>, <<<element_2>>>, and so on.

Show Show element_list object fields

string

required

Subject image, character asset, or another official supported asset URL.

string

Element type, such as image or video.

string

Role semantics supported by the official model.

boolean

Whether to add watermark.

Omni Reference Syntax

Syntax	Description
`<<<image_1>>>`	References the first item in `metadata.image_list`
`<<<video_1>>>`	References the first item in `video_list`
`<<<element_1>>>`	References the first item in `metadata.element_list`

The order of image_list, video_list, and element_list must match the order of the corresponding placeholders in prompt.

Examples

Text-to-Video

{
  "model": "kling-video-o1",
  "prompt": "Golden hour city skyline, cinematic lens quality",
  "mode": "std",
  "duration": 5,
  "aspect_ratio": "16:9"
}

Image Reference

{
  "model": "kling-video-o1",
  "prompt": "Make the person in <<<image_1>>> wave at the camera",
  "mode": "pro",
  "duration": 5,
  "metadata": {
    "image_list": [
      {"image_url": "https://example.com/portrait.jpg"}
    ]
  }
}

First and End Frame

{
  "model": "kling-video-o1",
  "prompt": "Transition from <<<image_1>>> to <<<image_2>>>",
  "mode": "pro",
  "duration": 5,
  "metadata": {
    "image_list": [
      {"image_url": "https://example.com/start.jpg", "type": "first_frame"},
      {"image_url": "https://example.com/end.jpg", "type": "end_frame"}
    ]
  }
}

Reference Video Input

{
  "model": "kling-video-o1",
  "prompt": "Transform <<<video_1>>> into a moonlit cyberpunk street",
  "mode": "std",
  "video_list": [
    {
      "video_url": "https://example.com/source-video.mp4",
      "refer_type": "base",
      "keep_original_sound": "no"
    }
  ]
}

Subject plus Motion Reference

{
  "model": "kling-video-o1",
  "prompt": "Make <<<element_1>>> imitate the motion from <<<video_1>>>",
  "mode": "pro",
  "video_list": [
    {
      "video_url": "https://example.com/motion-reference.mp4",
      "refer_type": "feature",
      "keep_original_sound": "no"
    }
  ],
  "metadata": {
    "element_list": [
      {"url": "https://example.com/character.jpg", "type": "image", "role": "subject"}
    ]
  }
}

Video generation is asynchronous. Use the Get Video Task Status endpoint to query progress and results.

curl --request POST \
  --url https://toapis.com/v1/videos/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "kling-video-o1",
    "prompt": "Make the person in <<<image_1>>> wave at the camera",
    "mode": "std",
    "duration": 5,
    "metadata": {
      "image_list": [{"image_url": "https://example.com/portrait.jpg"}]
    }
  }'

import requests

response = requests.post(
    "https://toapis.com/v1/videos/generations",
    headers={"Authorization": "Bearer <token>", "Content-Type": "application/json"},
    json={
        "model": "kling-video-o1",
        "prompt": "Make the person in <<<image_1>>> wave at the camera",
        "mode": "std",
        "duration": 5,
        "metadata": {"image_list": [{"image_url": "https://example.com/portrait.jpg"}]},
    },
)

print(response.json())

const response = await fetch("https://toapis.com/v1/videos/generations", {
  method: "POST",
  headers: {
    Authorization: "Bearer <token>",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "kling-video-o1",
    prompt: "Make the person in <<<image_1>>> wave at the camera",
    mode: "std",
    duration: 5,
    metadata: {
      image_list: [{ image_url: "https://example.com/portrait.jpg" }]
    }
  })
});

console.log(await response.json());

Overview

Quick Start

Chat API

Image API

Video API

Task Management

File Uploads

Account

FAQs

Authorization

Request Parameters

Omni Reference Syntax

Examples

Text-to-Video

Image Reference

First and End Frame

Reference Video Input

Subject plus Motion Reference

​Authorization

​Request Parameters

​Omni Reference Syntax

​Examples

​Text-to-Video

​Image Reference

​First and End Frame

​Reference Video Input

​Subject plus Motion Reference

Authorization

Request Parameters

Omni Reference Syntax

Examples

Text-to-Video

Image Reference

First and End Frame

Reference Video Input

Subject plus Motion Reference