Jev in production › Evaluation and testing

Math-To-Manim

Reviews every checkpoint of GPT-6-authored math animation scripts via a separate Jev API call, advisory by default with an optional gated mode (Math-To-Manim).

Open on GitHub ↗

The source publishes no measured number.
Use
Evaluation and testing
Industry
Education and research
Form
Open-source tool
Stage
In production
Listed
2026-09-25
Found via
github
Repository
HarleyCoops/Math-To-Manim
Stars
2,759
Forks
306
Last push
2026-10-10
Language
Python
License
MIT
Math-To-Manim screenshot
docs/assets/quasi-riemann-film-poster.png in the HarleyCoops/Math-To-Manim README, MIT; shown from GitHub.

The README opens with

Six real renders from the Astra Morse film and the existing showcase. Explore the films →

A question becomes a mathematical world you can move through.

GPT-6 Astra builds the explanation. Jev challenges every step. Manim makes it visible.

The primary pipeline now uses the official Codex SDK, your Codex ChatGPT login, and gpt-6-astra for authors and evidence auditors. Real TypeSafe Jev (jev-1.13.0) evaluates each checkpoint through its separate API. Astra develops the learning brief, verifies the mathematics, directs the visual argument, writes the scene, and reviews the actual render. Jev reviews are advisory by default: their scores are retained, but do not trigger regeneration or extra investigations. Strict gates remain available with...

Badge

For the project's own README, linking back here:

Listed in Jev in production

Also used for evaluation and testing