community_contributions/vaibhavmanwatkar/README.md

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

License

This project is part of the community contributions for the Agents course and follows the same licensing terms.

Contributing

Feel free to fork this project and submit improvements or additional features as pull requests.

Author

Vaibhav Manwatkar

• GitHub: @learnwithvaibhavm
• This is a community contribution to the Agents course