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AI Math Agent

An AI-powered mathematical assistant built with LangChain and Google Gemini.

Description

AI Math Agent is an intelligent chatbot that uses Google Gemini and LangChain to solve mathematical expressions accurately.

Instead of relying on the LLM's own calculations, the agent uses a custom calculator tool powered by SymPy for accurate mathematical operations.

The project also implements a custom conversation memory system that allows the AI to remember previous messages during the conversation.

Features

  • 🤖 AI Agent powered by Google Gemini
  • 🔧 Custom tool calling using LangChain
  • 🧮 Accurate mathematical calculations using SymPy
  • 🧠 Custom conversation memory system
  • 💬 Maintains chat history during runtime
  • 🏗️ Clean modular architecture
  • 🔐 Secure API key management using environment variables

How It Works

User Input
     |
     v
Human Message
     |
     v
AI Agent (Gemini)
     |
     v
Tool Required?
     |
  +--+--+
  |     |
 No    Yes
  |     |
  v     v
Answer  Calculator Tool
             |
             v
        Tool Response
             |
             v
        Final AI Response

Project Structure

AI-Math-Agent/
│
├── agent.py              # Agent workflow and tool handling
├── tools.py              # Calculator tool implementation
├── memory.py             # Custom conversation memory
├── config.py             # Configuration management
├── main.py               # Application entry point
├── requirements.txt      # Project dependencies
├── .env.example          # Environment variable template
├── .gitignore            # Git ignored files
└── README.md             # Documentation

Installation

Clone Repository

git clone https://github.com/ridazahra-ai/AI-Math-Agent.git

Navigate to Project Folder

cd AI-Math-Agent

Create Virtual Environment

python -m venv venv

Activate Virtual Environment

Windows:

venv\Scripts\activate

Install Dependencies

pip install -r requirements.txt

Environment Setup

Create a .env file in the project directory.

Add your Google Gemini API key:

GOOGLE_API_KEY=your_api_key_here
MODEL_NAME=gemini-2.5-flash

Usage

Run the application:

python main.py

Example:

You: What is 25 * 17?

AI: The answer is 425.

Example with memory:

You: My name is Rida.

AI: Nice to meet you, Rida.

You: What is my name?

AI: Your name is Rida.

Technologies Used

  • Python
  • LangChain
  • Google Gemini API
  • LangChain Google GenAI
  • SymPy
  • python-dotenv

Concepts Implemented

  • Large Language Model (LLM) Integration
  • AI Agent Workflow
  • Tool Calling
  • Custom Conversation Memory
  • Message-Based Conversation Handling
  • Environment Configuration
  • Modular Software Architecture

Future Improvements

  • Implement LangGraph agent workflow
  • Add persistent database memory
  • Support multiple tools
  • Improve error handling
  • Build FastAPI backend
  • Add frontend interface
  • Deploy as a cloud-based AI service

License

MIT License