Hailuo Video Generation
Generate AI videos through AceDataCloud's Hailuo (MiniMax) API.
Setup: See authentication for token setup.
Quick Start
curl -X POST https://api.acedata.cloud/hailuo/videos \
-H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"action": "generate", "prompt": "a dolphin jumping through ocean waves at golden hour", "model": "minimax-t2v"}'
Async: See async task polling. Poll via
POST /hailuo/taskswith{"id": "..."}.
Models
| Model | Type | Best For |
|---|---|---|
minimax-t2v |
Text-to-Video | Creating video from text description |
minimax-i2v |
Image-to-Video | Animating a still image |
minimax-i2v-director |
Image-to-Video (Director) | Precise control over animation from image |
Workflows
1. Text-to-Video
POST /hailuo/videos
{
"action": "generate",
"prompt": "a time-lapse of flowers blooming in a meadow",
"model": "minimax-t2v"
}
2. Image-to-Video
Animate a still image into a video clip.
POST /hailuo/videos
{
"action": "generate",
"prompt": "gentle wind blows through the scene",
"model": "minimax-i2v",
"first_image_url": "https://example.com/landscape.jpg"
}
3. Image-to-Video (Director Mode)
More precise control over the animation.
POST /hailuo/videos
{
"action": "generate",
"prompt": "camera slowly zooms in while leaves fall gently",
"model": "minimax-i2v-director",
"first_image_url": "https://example.com/scene.jpg"
}
Parameters
| Parameter | Required | Values | Description |
|---|---|---|---|
action |
Yes | "generate" |
Action type |
prompt |
Yes | string | Video description |
model |
Yes | "minimax-t2v", "minimax-i2v", "minimax-i2v-director" |
Model |
first_image_url |
For i2v | string | Source image URL (required for image-to-video) |
callback_url |
No | string | Async callback URL |
Gotchas
first_image_urlis required forminimax-i2vandminimax-i2v-directormodels- Director mode (
minimax-i2v-director) provides finer camera/motion control than standard i2v - The
actionfield currently only supports"generate"— no extend or edit - Flat pricing per generation regardless of model