Zopia AI Video Creation

Problem It Solves

Zopia AI Video Creation targets the management problem of multi-stage AI video projects, not just one-shot generation. A short prompt can trigger a pipeline where the script, character images, storyboard keyframes, and video clips all depend on each other. Without project-level state, it is easy to lose context, miss async progress, mix assets across episodes, or fail to export a coherent final video. This skill turns that flow into a scriptable workflow.

How It Works

The workflow is organized around Project, Episode, Session, and Workspace:

• Create and configure: use create_project.py, then save_settings.py for style, aspect ratio, video model, storyboard image model, and entity image model.
• Send creative intent: use send_message.py to forward the user's original request asynchronously to the backend agent, avoiding local rewriting or task splitting.
• Track progress: use query_session.py to poll the workspace and infer stage from entities, storyboard.images.pending, and storyboard.videos.pending.
• Retrieve and compose: use download_results.py after completion; manage multi-episode work with manage_episodes.py; trigger cloud rendering with render_episode.py when a full MP4 is needed.

Boundaries and Caveats

This skill is suited to exposing Zopia backend creation capabilities to scripts, agents, or automation, not local video generation. Keep the configured video model compatible with the selected --generation-method; each episode has independent characters and storyboards, so cross-episode continuity must be requested explicitly; MP4 rendering requires at least one completed storyboard video; and long-running or failed polling should stop cleanly and point the user to the project.