Google Gemini AI Calculator

Created by Vaibhav Manwatkar as a community contribution.

Overview

This simple Python application demonstrates how to integrate with Google's Gemini AI model using the google-generativeai library. The application asks Gemini to solve a basic mathematical problem (2+2) and displays the AI's response, showcasing the fundamental interaction with Google's Generative AI API.

Features

• Google Gemini Integration: Uses Google's latest Gemini 2.0 Flash Experimental model
• Environment Variable Management: Secure API key handling using python-dotenv
• Simple Mathematical Query: Demonstrates AI's ability to perform basic calculations
• Clean Output: Displays the AI's response in a readable format

Prerequisites

• Python 3.7 or higher
• Google API key with access to Gemini API
• Required Python packages (see Installation section)

Installation

1. Clone or download this file to your local machine

2. Install required dependencies:

   pip install google-generativeai python-dotenv

   Or if using uv:

   uv add google-generativeai python-dotenv

3. Set up your Google API key:

   • Get your API key from Google AI Studio
   • Create a .env file in the same directory as the script
   • Add your API key to the .env file:

     GOOGLE_API_KEY=your_actual_api_key_here

Usage

1. Run the application:

   python 1_lab1_google.py

2. Expected output:

   4

Code Structure

from dotenv import load_dotenv
load_dotenv(override=True)

import os
import google.generativeai as genai

# Configure the API key
genai.configure(api_key=os.getenv('GOOGLE_API_KEY'))

# Initialize the model
model = genai.GenerativeModel(model_name="gemini-2.0-flash-exp")

# Generate content
response = model.generate_content(["What is 2+2?"])
print(response.text)

Key Components

1. Environment Setup

• load_dotenv(override=True): Loads environment variables from .env file
• os.getenv('GOOGLE_API_KEY'): Retrieves the API key securely

2. Model Configuration

• genai.configure(): Sets up the API key for authentication
• genai.GenerativeModel(): Initializes the Gemini model with specified version

3. Content Generation

• model.generate_content(): Sends a prompt to the AI model
• response.text: Extracts the text response from the AI

Model Information

• Model Used: gemini-2.0-flash-exp (Gemini 2.0 Flash Experimental)
• Capabilities: Text generation, reasoning, mathematical calculations
• Input Format: List of strings or single string
• Output Format: Response object with .text attribute

Error Handling

The application includes a pyright: ignore[reportMissingImports] comment to suppress type checker warnings for the google.generativeai import, which is a common practice when the package might not be installed in all environments.

Troubleshooting

Common Issues

1. ModuleNotFoundError: Install the required package:

   pip install google-generativeai

2. API Key Error: Ensure your .env file contains a valid GOOGLE_API_KEY

3. Authentication Error: Verify your API key has access to the Gemini API

Extending the Application

This basic example can be extended to:

• Ask more complex mathematical questions
• Implement conversation loops
• Add error handling for API failures
• Create a user interface for interactive queries
• Process different types of prompts beyond mathematics

Dependencies

• google-generativeai: Google's official Python client for Generative AI
• python-dotenv: Loads environment variables from .env files