manim-video

Automate Manim video production by orchestrating an end-to-end pipeline from narrative planning to final clip assembly. You structure a storyboard in plan.md, implement per-scene classes in script.py, render with Manim CE, and stitch clips using ffmpeg.

The workflow for creating equation derivations and data stories with Manim CE involves planning narrative structure and pacing in a plan.md file, coding visual language in script.py per-scene classes, rendering the animations, and stitching the final video together using ffmpeg.

Yes, you can optionally add narration during the video assembly process. The workflow supports integrating audio narration alongside rendered Manim CE animation clips when stitching the final educational video together using ffmpeg.

Yes, the Manim automation workflow supports architecture diagrams and algorithm visualizations across domains. It provides guidelines for visual language and narrative pacing designed to improve learning outcomes for these technical concepts.

Yes, ffmpeg is required to stitch Manim CE rendered clips into a final video. The rendering and stitching workflow explicitly relies on Manim Community Edition for animation generation and ffmpeg for assembling individual scene clips.

Using a structured plan.md and script.py for Manim educational videos separates narrative planning from animation code, ensuring proper pacing and visual language. This structured approach orchestrates end-to-end production to generate polished, high-quality learning content.