✨🌿 A node-based visual IDE for mathematical animations — with AI tooling, a structured history system, and a built-in explanation engine for students and teachers. 🎊🎯

EfficientManim turns Manim from a code-only tool into a visual, AI-augmented workspace. Wire Mobjects and animations together on an infinite canvas, generate scenes from plain English or PDF slides, and get structured explanations for every move — all without leaving the editor.

Drag-and-drop Mobjects and Animations onto an infinite canvas, connect them with smart wires, and watch your scene graph come alive. Wire validation runs automatically, and live static previews update as you build.

• 60+ Manim classes across 8 categories (Geometry, Text, Graphs, 3D, Animations…), searchable in real time via the Manim Class Browser
• Multiple Scenes per project — create, rename, delete, and switch between them in the Scenes tab; each scene carries its own node graph and auto-saves state on switch
• VGroup Utility — select Mobject nodes → click Create VGroup → get auto-generated VGroup(...) code displayed in an expandable tree
• Recents Panel — top-5 Mobjects and top-5 Animations tracked per session, persisted to ~/.efficientmanim/usage.json; double-click to add instantly

Describe an animation in plain English. Get runnable Manim code.

Upload one or more PDFs. The AI parses each slide, builds an animation plan, and produces both Manim code and a ready-to-edit node graph — turning a static lecture deck into a structured animated scene.

TTS generation with multi-voice support and automatic duration syncing to animation timing.

Clone any GitHub repo into ~/.efficientmanim/snippets/, browse .py files, and double-click to load a snippet directly into the AI panel. All repos repopulate on startup automatically.

Select a scene, a group of nodes, or a single animation — then hit 🧠 Explain in the main toolbar. The system produces a clear, student-friendly explanation of what the animation is doing and why.

Copy or regenerate instantly from the Explain Panel. Explanations can also be triggered programmatically via MCP (explain.scene, explain.selected_nodes).

Learning Mode watches what you build and fires micro-explanations as you go — turning the editor into a live tutor.

Triggers automatically when you:

• Add axes, graphs, or equations
• Apply transformations
• Attach tangent lines, slopes, or area visuals
• Hit a checkpoint or land a large batch addition

Default: OFF (to keep the workspace quiet for experienced users).
Enable: Settings → Learning Mode → Enable Learning Mode.

Generate a full structured lesson from the current scene in one click.

Output includes:

• Concept explanation
• Visual explanation tied to the animation
• Step-by-step teaching script
• Student-friendly notes
• Key takeaways

Export as: Markdown (.md), plain text (.txt), or copy to clipboard.
Enable: Settings → Teacher Mode → Enable Teacher Mode.

The rewritten HistoryManager captures grouped atomic operations — AI merges, property edits, motion, wiring — with per-node undo/redo stacks and project/scene/node checkpoints.

The explanation engine hooks directly into history:

• Explain a checkpoint state — what did the scene look like at this moment?
• Explain a diff — what changed between two checkpoints?
• Explain an undo/redo action — in plain student language, not code

See docs/history_system.md for the full data model and checkpoint API.

Every action in EfficientManim — node edits, wires, VGroups, scenes, rendering, assets, AI workflows, themes, keybindings, TTS, explanations, Learning Mode, Teacher Mode — is scriptable via structured JSON through the MCP command layer.

// Example
{ "command": "explain.scene", "mode": "detailed" }
{ "command": "teacher_mode.generate_lesson", "export": "markdown" }
{ "command": "history.restore_checkpoint", "id": "chk_42" }

Full reference in docs/mcp_commands.md.

All shortcuts are fully editable via Help → Edit Keybindings…

• Python 3.10+
• FFmpeg — required for video rendering (must be in PATH)
• Git — optional, for the GitHub Snippet Loader
• LaTeX — optional, for local LaTeX rendering

git clone https://github.com/pro-grammer-SD/EfficientManim.git
cd EfficientManim
pip install -r requirements.txt
python main.py

Manual install:

pip install manim PySide6 google-genai pydub requests numpy pdfplumber regex

Launch and initialize the workspace	A clean canvas ready for composition
Recents panel — jump back in fast	Manipulate nodes interactively
Real-time element search	GitHub snippets at your fingertips
Selecting a snippet from a cloned repo	Loading external code into the workspace
Instant preview for fast iteration	Final rendered output in the node canvas

Discuss the project on Reddit: r/manim — I built a node-based Manim IDE with AI assistance

Made with ❤️💚💙 by Soumalya · @pro-grammer-SD