manim-video

Manim video production from text prompts is automated through an end-to-end pipeline that generates a planning document, Python scene classes, and renders the final output. You create a plan.md and script.py, then render scenes using Manim Community Edition.

To render Manim animations, you need Python 3.10+, Manim Community Edition, LaTeX, and ffmpeg installed. The workflow requires a structured plan.md and a script.py with a single-scene per class architecture to generate reproducible video content.

Yes, Manim CE supports creating equation derivations, algorithm visualizations, data stories, and architecture diagrams. The pipeline provides specific modes tailored for these educational and research contexts to produce polished explainer videos.

The Manim rendering pipeline supports optional audio integration and narration alongside its video generation capabilities. This allows you to stitch rendered scenes together with synchronized audio to produce complete explainer videos.

The best way to structure a Manim project for reproducible rendering is to separate the planning document (plan.md) from the code (script.py). This ensures a repeatable, publish-ready workflow with a single-scene per class structure for automated video generation.