Linux Installation

This guide covers how to set up Google Gemini on Linux distributions for DevOps automation and cloud infrastructure management.

Prerequisites

• Python 3.9 or higher

• pip (Python package manager)

• A Google Cloud account with Gemini API access

• Google Cloud CLI (optional, but recommended)

Installation Steps

1. Set Up Python Environment

It's recommended to use a virtual environment:

# Create a virtual environment
python -m venv gemini-env

# Activate the environment
source gemini-env/bin/activate

# Upgrade pip
pip install --upgrade pip

2. Install Google Gemini SDK

Install the official Python SDK:

pip install google-generativeai

For AI Studio integration:

pip install -U "google-cloud-aiplatform[stable]"

3. Configure Authentication

There are two main methods for authentication:

Option A: API Key (Simplest)

1. Visit Google AI Studio and create an API key
2. Store the key securely in your environment:

export GOOGLE_API_KEY="your-api-key-here"

To make this permanent, add to your .bashrc or .zshrc:

echo 'export GOOGLE_API_KEY="your-api-key-here"' >> ~/.bashrc
source ~/.bashrc

Option B: Service Account (For Production)

1. Create a service account in Google Cloud Console

2. Grant appropriate permissions (Vertex AI User or similar)

3. Download the service account key JSON file

4. Set the environment variable:

export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json"

4. Verify Installation

Create a simple test script test_gemini.py:

import google.generativeai as genai
import os

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

# Test the API with a simple prompt
model = genai.GenerativeModel('gemini-pro')
result = model.generate_content("Write a simple Terraform configuration for an AWS S3 bucket")

print(result.text)

Run the script:

python test_gemini.py

Installing Additional Components

NotebookML

For NotebookML integration:

pip install notebookml
pip install jupyter

Gemini for CLI

For a command-line interface to Gemini:

pip install google-cloud-aiplatform[stable]
gcloud components install ai-platform

Troubleshooting

Common Issues

1. API Key Not Found: Ensure your environment variable is correctly set

   echo $GOOGLE_API_KEY
   # If empty, set it again

2. Library Conflicts: If you encounter dependency conflicts:

   pip install --upgrade google-generativeai --force-reinstall

3. Quota Exceeded: Check your quota usage in Google Cloud Console

   # For API-based usage
   gcloud ai operations list

4. SSL Certificate Issues: Update certificates:

   pip install --upgrade certifi

System Integration

For DevOps workflows, you can install the Gemini CLI:

# Install the official Gemini CLI
pip install gemini-cli

# Verify installation
gemini --version

This tool allows you to use Gemini directly in shell scripts and automation workflows.