Manimatic AI: Visualize Your Math & Problems with AI! ✨

---

submissionVideo.mp4

🚀 Overview

Manimatic AI is an innovative web application that bridges the gap between natural language problem statements and beautiful mathematical visualizations. Simply describe a math problem or a concept in plain English, and our AI-powered backend will interpret, solve, and generate a stunning animation using the Manim animation engine, presented right in your browser!

This project aims to make complex mathematical and scientific concepts more accessible and understandable through dynamic visual explanations.

---

✨ Features

• Natural Language Processing: Understands diverse mathematical problem statements.
• AI-Powered Problem Solving: Solves various algebraic, geometric, and arithmetic problems based on natural language input.
• Dynamic Visualization: Generates high-quality animated solutions using the Manim Community Edition.
• Real-time Interaction: Input prompts directly via a user-friendly web interface.
• Node.js Backend: Robust and scalable server-side processing for orchestrating AI and Manim.
• TypeScript Frontend & Backend: Modern, type-safe development for both client and server.
• Persistent Storage: Stores generated video and audio files on the server (for demonstration purposes, if deployed on a suitable platform).

---

💡 How It Works

Manimatic AI operates through a sophisticated integration of technologies:

1. Frontend (HTML, CSS, JavaScript/TypeScript): Users enter their problem statement into the intuitive web interface.
2. Backend (Node.js with Express & TypeScript):
   • Receives the natural language prompt from the frontend.
   • Utilizes the power of a large language model (LLM, e.g., OpenAI API) to interpret the problem, devise a step-by-step solution, and generate a precise Manim-compatible Python script.
   • Executes the generated Python script by invoking the Manim command-line tool.
   • Handles audio narration generation (if implemented) and seamlessly integrates it with the Manim output.
   • Serves the final generated video file back to the frontend for playback.
3. Manim (Python): Executes the dynamically generated Python script, rendering the mathematical visualization into a high-quality video file (.mp4).
4. System Utilities: Leverages FFmpeg for powerful video/audio encoding/decoding, LaTeX for beautiful mathematical typesetting within Manim, and Tesseract OCR for any image-to-text functionality (if integrated).

---

🛠️ Getting Started

Follow these steps to set up and run Manimatic AI on your local machine for development, or on a Linux-based VPS for deployment.

Prerequisites

Before you begin, ensure you have the following installed on your system:

• Git: For cloning the repository.
  • Download Git
• Node.js (v18+ recommended): This includes npm, which is used for managing Node.js packages.
  • Download Node.js
• Python (v3.9+ recommended): The environment for Manim and other Python libraries.
  • Download Python
• pip: Python's package installer (usually comes with Python).
• FFmpeg: Essential for Manim's video rendering and processing.
  • Linux: sudo apt install ffmpeg
  • macOS: brew install ffmpeg (using Homebrew)
  • Windows: Download from official site and add to PATH.
• LaTeX (TeX Live): For high-quality mathematical typesetting in Manim.
  • Linux: sudo apt install texlive-full (comprehensive install) or sudo apt install texlive-latex-recommended texlive-fonts-extra texlive-pictures (smaller, often sufficient)
  • macOS: MacTeX
  • Windows: MiKTeX or TeX Live
• Tesseract OCR: Required for any image-to-text processing functionalities (e.g., if AI parses images for text).
  • Linux: sudo apt install tesseract-ocr
  • macOS: brew install tesseract
  • Windows: Download from UB Mannheim and add to PATH.

Installation Steps

1. Clone the Repository:

   git clone https://github.com/adithyanotfound/Manimatic.git
   cd Manimatic

2. Set Up Node.js Dependencies: This installs all the packages required for your backend server.

   npm install

3. Set Up Python Environment (Manim & Libraries):

   • Create a Python virtual environment to isolate project dependencies:

     python3 -m venv manim_env

   • Activate the environment:

     source manim_env/bin/activate   # macOS/Linux
     # .\manim_env\Scripts\activate # Windows (in PowerShell/Cmd)

   • Install Python dependencies listed in requirements.txt:

     pip install -r requirements.txt

   • Deactivate the environment when done with Python-specific tasks:

     deactivate

4. Compile TypeScript: This step transpiles your src/ TypeScript code into executable JavaScript in the dist/ folder.

   npx tsc

   Verify that a dist/ folder now exists in your project root.

Environment Variables

You need to set up your API keys and other sensitive configurations. Create a .env file in the root of your project (the Manimatic/ folder):