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#

RatioUse Case16:9Landscape (default) — YouTube, TV9:16Portrait — TikTok, Instagram Stories1:1Square — Social media4:3Classic — Presentations21:9Ultra-wide — Cinematic

Parameters#

ParameterTypeDefaultDescriptionpromptstring—Text description of the video (required)actionstring"generate"``"generate" or "extend"``aspect_ratiostring"16:9"Video aspect ratioloopboolfalseCreate seamless loopenhancementbooltrueEnhance prompt for better resultsstart_image_urlstring—Reference image for first frameend_image_urlstring—Reference image for last framevideo_idstring—ID of video to extend (alternative to video_url)video_urlstring—URL of video to extend (alternative to video_id)timeoutnumber—Timeout in seconds for the API to return datacallback_urlstring—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