🧮 100+ Language STEM Solver (Math, Physics, Chemistry)

Developed by Rashedul Albab

A powerful, AI-driven multimodal reasoning engine designed to break language barriers in STEM education. Whether it's a handwritten calculus problem, a physics circuit diagram, or a chemical equation, this app provides instant, step-by-step solutions in over 100 languages (including Bengali, Hindi, English, etc.).

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✨ Features

• 🌍 100+ Language Support: Explain complex concepts in your native language (Bengali, Hindi, Spanish, Arabic, etc.).
• 🔬 Multi-Subject Mastery:
  • Mathematics: Algebra, Calculus, Geometry, Statistics.
  • Physics: Mechanics, Thermodynamics, Electromagnetism, Quantum Physics.
  • Chemistry: Stoichiometry, Organic Chemistry, Balancing Equations.
• 📸 AI Image Solver (OCR): Simply upload a photo or PDF of your homework/diagram, and the AI will analyze and solve it.
• 🔢 Step-by-Step Solutions: Don't just get the answer; understand the process with detailed walkthroughs.
• 💡 "Explain Like I'm 5" Mode: If the solution is too complex, one click gives you a simplified, easier-to-understand explanation focusing on core concepts.
• 🎨 Premium UI: A modern, responsive interface built with Tailwind CSS, featuring glassmorphism and smooth animations.

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🚀 Tech Stack

• Frontend: HTML5, Vanilla JavaScript, Tailwind CSS
• Backend API: FastAPI (Python)
• AI Engine: Google Gemini 2.5 Flash
• Cloud Platform: Docker Hub & GitHub Actions
• Monitoring: Google Analytics

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🛠️ Project Structure

The project is organized into a clear Backend/Frontend separation:

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├── backend/                # FastAPI Backend
│   ├── main.py             # Server logic & Gemini integration
│   ├── requirements.txt    # Python dependencies
│   └── .env                # Gemini API Key (keep secure!)
├── frontend/               # Plain HTML/CSS/JS Frontend
│   ├── index.html          # Structure
│   ├── style.css           # Styling
│   └── script.js           # Frontend logic
├── Dockerfile              # Docker image definition
├── docker-compose.yml      # Local orchestration
└── .github/workflows/      # CI/CD Pipeline

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⚙️ Installation & Setup

🚀 Getting Started (FastAPI + HTML/CSS)

Local Development:

1. Navigate to the backend directory: cd backend
2. Install dependencies: pip install -r requirements.txt
3. Add your Gemini API Key to .env
4. Run the server: python main.py

Frontend:

1. Open frontend/index.html in your browser.
2. Ensure the API_BASE_URL in script.js matches your backend URL.

🐳 Docker Deployment

1. Build the image:

   docker build -t rashedulalbab1234/global-math-solver:latest .

2. Run with Docker Compose:

   docker-compose up -d

   Note: Ensure your .env file is in backend/ as it will be loaded by the container.

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☁️ Deploy on Hugging Face Spaces (Free & Easy)

1. Create an Account: Go to huggingface.co and sign up.
2. Create a New Space:
   • Click your profile picture -> New Space.
   • Name: global-stem-solver (or similar).
   • License: MIT.
   • SDK: Select Docker.
   • Template: Select Blank.
3. Upload Files:
   • Upload Dockerfile, backend/, frontend/, requirements.txt via web interface or git.
4. Add Secret:
   • Go to Settings -> Variables and secrets.
   • New Secret -> Name: GEMINI_API_KEY, Value: (Your Key).
5. Done! Your app will build and launch automatically.

☁️ Deploy on Render

1. Push your code to a GitHub repository.
2. Log in to Render.
3. Click "New +" -> "Web Service".
4. Connect your GitHub repository.
5. Render will automatically detect the render.yaml or Dockerfile (if you choose Docker runtime).
6. Important: Add your GEMINI_API_KEY in the "Environment" tab on Render dashboard.

🏗️ CI/CD (GitHub Actions)

The project includes a GitHub Actions workflow to automatically build and push the Docker image to Docker Hub.

1. Secrets required in your GitHub repository:
   • DOCKER_HUB_USERNAME: rashedulalbab1234
   • DOCKER_HUB_ACCESS_TOKEN: Your Docker Hub Access Token.
2. The workflow triggers on every push to the main branch.

🛡️ Security & Scalability

• Environment Variables: API keys are stored in .env files and never exposed to the frontend.
• FastAPI: Provides a robust, asynchronous backend capable of handling multiple concurrent requests.
• Gemini AI: Uses the latest gemini-2.5-flash model for high-speed, accurate mathematical reasoning.

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📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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