Luma Video

Generate AI videos with Luma Dream Machine via AceDataCloud API. Use when creating videos from text prompts, generating videos from reference images, extending existing videos, or any video generation task with Luma. Supports text-to-video, image-to-video, and video extension.

Luma Video Generation

Generate AI videos through AceDataCloud's Luma Dream Machine API.

First-time setup

1. Install the official Skill with clawhub install @acedatacloud/luma. Check that the ClawHub publisher is @acedatacloud.
2. Sign in at AceDataCloud → Applications, open General application, and check Luma access, balance, and current pricing. Copy its API key, or select Manage Keys → Create for a separate key. Copy the key value without Bearer ; a platform-... management token is not a service API key.
3. If you enable Allowed APIs restrictions, include /luma/videos and /luma/tasks. Advanced workflows below may call additional routes.
4. On the OpenClaw Gateway host, put ACEDATACLOUD_API_TOKEN=your_api_key_here in ~/.openclaw/.env, then restart the Gateway and start a new session. For a direct terminal test, run export ACEDATACLOUD_API_TOKEN="your_api_key_here" in that shell. Never put the key in a prompt or commit an .env file.
5. Run the Quick Start below. If this workflow returns a task ID, query that same task until it finishes; do not submit the same billable request again just to check progress.

Illustrated key setup, first run, and troubleshooting · Token details

Quick Start

bash

curl -X POST https://api.acedata.cloud/luma/videos \
  -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "a drone flying over a mountain lake at sunrise", "action": "generate", "async": true}'

Async: See async task polling. Poll via POST /luma/tasks with {"id": "..."}.

Workflows

1. Text-to-Video

Generate video purely from a text description.

json

POST /luma/videos
{
  "prompt": "a timelapse of flowers blooming in a garden",
  "action": "generate",
  "aspect_ratio": "16:9",
  "loop": false,
  "enhancement": true
}

2. Image-to-Video

Use start and/or end reference images to guide generation.

json

POST /luma/videos
{
  "prompt": "the scene comes alive with gentle wind",
  "action": "generate",
  "start_image_url": "https://example.com/scene.jpg",
  "end_image_url": "https://example.com/scene-end.jpg",
  "aspect_ratio": "16:9"
}

3. Extend a Video

Continue an existing video with a new prompt.

json

POST /luma/videos
{
  "action": "extend",
  "video_id": "existing-video-id",
  "prompt": "the camera continues forward through the forest"
}

Aspect Ratios

Ratio	Use Case
16:9	Landscape (default) — YouTube, TV
9:16	Portrait — TikTok, Instagram Stories
1:1	Square — Social media
4:3	Classic — Presentations
21:9	Ultra-wide — Cinematic

Parameters

Parameter	Type	Default	Description
prompt	string	—	Text description of the video (required)
action	string	"generate"	"generate" or "extend"
aspect_ratio	string	"16:9"	Video aspect ratio
loop	bool	false	Create seamless loop
enhancement	bool	true	Enhance prompt for better results
start_image_url	string	—	Reference image for first frame
end_image_url	string	—	Reference image for last frame
video_id	string	—	ID of video to extend (alternative to video_url)
video_url	string	—	URL of video to extend (alternative to video_id)
timeout	number	—	Timeout in seconds for the API to return data
callback_url	string	—	Webhook URL for async notifications

Gotchas

• enhancement: true (default) improves prompt quality but may alter your intent — set to false for literal prompts
• Start/end image URLs must be publicly accessible
• loop: true creates seamless looping video — good for backgrounds and social media
• Extend requires either video_id or video_url from a previously completed generation
• Video generation takes 1–5 minutes depending on complexity
• Both start and end images are optional — you can use just one for partial guidance

MCP: pip install mcp-luma | Hosted: https://luma.mcp.acedata.cloud/mcp | See all MCP servers