Kling Video

Generate AI videos with Kuaishou Kling via AceDataCloud API. Use when creating videos from text or images, extending existing videos, or applying motion control. Supports text-to-video, image-to-video, extend, and motion generation with multiple models and quality modes.

Kling Video Generation

Generate AI videos through AceDataCloud's Kuaishou Kling API.

Authentication

bash

export ACEDATACLOUD_API_TOKEN="your-token-here"

Quick Start

bash

curl -X POST https://api.acedata.cloud/kling/videos \
  -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action": "text2video", "prompt": "a cat playing piano on a rooftop at sunset", "model": "kling-v2-5-turbo", "mode": "std", "duration": 5}'

Models

Model	Quality	Best For
kling-v1	Standard	Basic generation, lowest cost
kling-v1-6	Improved	Better quality than v1
kling-v2-master	High	High-quality output
kling-v2-1-master	High	Improved v2
kling-v2-5-turbo	High + Fast	Best speed/quality trade-off (recommended)
kling-video-o1	Premium	Highest quality

Quality Modes

Mode	Speed	Cost	Use For
std (Standard)	Slower	Lower	Draft/preview
pro (Professional)	Faster	Higher	Final output

Workflows

1. Text-to-Video

json

POST /kling/videos
{
  "action": "text2video",
  "prompt": "a futuristic city with flying cars",
  "model": "kling-v2-5-turbo",
  "mode": "std",
  "duration": 5,
  "aspect_ratio": "16:9"
}

2. Image-to-Video

Animate a still image. Optionally specify an ending frame.

json

POST /kling/videos
{
  "action": "image2video",
  "prompt": "the scene slowly comes alive with movement",
  "start_image_url": "https://example.com/scene.jpg",
  "end_image_url": "https://example.com/end-scene.jpg",
  "model": "kling-v2-5-turbo",
  "mode": "pro"
}

3. Extend Video

Continue an existing video with additional seconds.

json

POST /kling/videos
{
  "action": "extend",
  "video_id": "existing-video-id",
  "prompt": "the camera pulls back to reveal the full landscape",
  "model": "kling-v2-5-turbo"
}

4. Motion Control

Apply precise camera/motion control from an image + reference video.

json

POST /kling/motion
{
  "image_url": "https://example.com/subject.jpg",
  "video_url": "https://example.com/motion-reference.mp4"
}

Parameters

Parameter	Values	Description
action	"text2video", "image2video", "extend"	Generation mode
model	See models table	Model to use
mode	"std", "pro"	Quality mode
duration	5, 10	Duration in seconds
aspect_ratio	"16:9", "9:16", "1:1"	Video aspect ratio
cfg_scale	0–1	Prompt relevance strength
negative_prompt	string	What to avoid in the video
camera_control	object	Camera movement parameters
callback_url	string	Async callback URL

Task Polling

json

POST /kling/tasks
{"task_id": "your-task-id"}

States: processing → succeed or failed.

Gotchas

• duration only supports 5 or 10 seconds
• end_image_url is only for image2video action — it defines the last frame
• Motion control (/kling/motion) is a separate endpoint from video generation
• pro mode costs roughly 2x std mode but generates faster with better quality
• Task states use "succeed" (not "succeeded") — check for this value when polling
• negative_prompt helps avoid unwanted elements (e.g., "blurry, low quality, text")