Music Video

Estimated credits: ~200 per run.

Inputs

theme

scenes

music_style

visual_style

Steps

1. Layer A (parallel) — N keyframes + 1 music track all at once.
   • For each scene 1..N:

     muapi image generate

     with a beat-specific prompt +

     {{visual_style}}

     , model=nano-banana-pro (these feed video gen).
   • One

     muapi audio create

     (kind=music) using

     {{music_style}}

     , duration = N × 5 + a 2s tail.
2. Layer B (parallel, depends on Layer A) — animate each keyframe.
   • For each scene:

     muapi video from-image

     with

     image=$nX.url

     , model=veo3.1-image-to-video, duration=5, prompt=scene-specific motion direction.
3. Return:
   • The scene keyframes (asset ids in order).
   • The animation clips (asset ids in order).
   • The music track asset id.
   • A short summary describing the cut order.

Notes

• Keep character continuity by repeating the character description in every scene prompt verbatim.
• Don't auto-confirm any single video call > 50 cr — those need the user's nod (the loop will prompt automatically).
• If a scene's

  muapi video from-image

  fails after failover, fall back to

  muapi video generate

  (text-to-video) for that scene only.

Trigger Keywords

music video

mv

video story

song visualization

Notes for the Executing Agent

• This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call

  muapi

  CLI commands. Use

  muapi auth configure

  first if

  MUAPI_API_KEY

  is unset.
• For model IDs without a CLI alias yet, fall back to the raw endpoint via

  curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'

  and poll with

  muapi predict wait <request_id>

  .
• Substitute

  {{input_name}}

  placeholders with the user's actual inputs before issuing each call.