🧠 Math Wisdom Bot

Math Wisdom Bot is a modern, premium full-stack application designed to solve complex mathematical problems and answer factual queries. By combining the speed of the Groq Llama 3 engine, the robust reasoning of Gemini 1.5 Pro, Claude 3 Haiku, and OpenAI GPT-4o Mini with a smart intent router, this bot dynamically switches contexts to provide the best possible answer—whether that involves executing code, parsing Wikipedia, or streaming LaTeX-formatted mathematics.

✨ Key Features

• ⚡ Streaming AI Responses: Built natively with Web Streams API and FastAPI StreamingResponse for a ChatGPT-like, real-time typing effect.
• 🧠 Conversation Memory: Maintains rolling context allowing for follow-up questions and conversational problem solving.
• 🔀 Smart Auto-Routing: Intelligently classifies user intent and seamlessly routes queries between an LLM Math Solver and a Wikipedia Fact Searcher.
• 📐 KaTeX & Markdown Rendering: Mathematical equations ($inline$ and $$block$$), code blocks, and markdown are beautifully rendered client-side.
• 🔌 Multi-Model Support: Instantly switch between cutting-edge LLMs (Groq, Gemini, Claude, OpenAI) securely from the backend without exposing API keys.
• 💅 Premium UI/UX: Responsive design featuring Dark/Light mode toggles, one-click "Copy Response" tooltips, auto-resizing text areas, and bouncy "Thinking..." animations.

🛠️ Technology Stack

Backend

• Framework: FastAPI (Uvicorn)
• AI/LLM: LangChain ecosystems (langchain-core, langchain-groq, langchain-google-genai, langchain-anthropic, langchain-openai)
• Routing/Services: Python wikipedia package, Python dotenv

Frontend

• Structure/Styling: Native HTML5, CSS3 (CSS Variables for Theming)
• Logic: Vanilla JavaScript (ES6+ Fetch API, ReadableStreams)
• Rendering: KaTeX (Math), marked.js (Markdown), Highlight.js (Code Blocks)

📁 Project Structure

math-wisdom-bot/
├── .env.example                # Example environment variables file
├── README.md                   # Project documentation
├── backend/
│   ├── main.py                 # FastAPI application entry point
│   ├── requirements.txt        # Python backend dependencies
│   ├── routes/
│   │   └── chat.py             # FastAPI router handling /solve endpoint
│   └── services/
│       ├── llm_service.py      # LangChain integration, prompt engineering, streaming
│       └── wiki_service.py     # Wikipedia API scraping logic
└── frontend/
    ├── index.html              # Main UI structure and CDN imports
    ├── script.js               # Chat state, streaming parser, and UI interactions
    └── styles.css              # Custom CSS with Light/Dark themes and animations

🚀 Getting Started

Follow these instructions to set up the project locally.

1. Prerequisites

• Python 3.9 or higher
• At least one valid API Key from Groq, Google (Gemini), Anthropic (Claude), or OpenAI.

2. Clone the Repository

git clone https://github.com/yourusername/math-wisdom-bot.git
cd math-wisdom-bot

3. Backend Setup

Create a virtual environment to isolate the project's dependencies:

python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate

Install the required Python packages:

pip install -r backend/requirements.txt

4. Configure Environment Variables

Copy the example environment file and add your secret API keys:

cp .env.example .env

Open the .env file and securely paste in your required keys:

GROQ_API_KEY="your_groq_key_here"
GEMINI_API_KEY="your_gemini_key_here"
ANTHROPIC_API_KEY="your_anthropic_key_here"
OPENAI_API_KEY="your_openai_key_here"

5. Run the Application

Start the FastAPI backend server using Uvicorn:

cd backend
uvicorn main:app --reload --port 8005

The server will begin running on http://localhost:8005.

To launch the frontend, simply open frontend/index.html in your favorite web browser!

💡 Usage Guide

1. Launch the App: Open the index.html file. You will be greeted by the Math Wisdom Bot interface.
2. Select a Mode: Choose between Smart Auto (recommended), Math Solver, or Wiki Search via the left sidebar.
3. Choose an Engine: Use the dropdown to select which AI brain you want to power the bot (e.g., Llama 3, GPT-4o Mini).
4. Query: Type your prompt. Use Shift+Enter for a new line and Enter to send.
   • Example Math Prompt: "Solve for x: $2x^2 + 5x - 3 = 0$ using the quadratic formula."
   • Example Wiki Prompt: "Who was Ada Lovelace?"

🤝 Contributing

Contributions, issues, and feature requests are welcome!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📜 License

Distributed under the MIT License. See LICENSE for more information.