Gemini Service Account Example

Example GCP project setup demonstrating how to access Gemini via Vertex AI using service account authentication with proper security configuration.

This reference implementation shows the correct way to set up service accounts, IAM permissions, and authentication flows for production Gemini deployments.

What This Solves

Many developers struggle with authenticating to Vertex AI Gemini APIs from applications, especially in production environments. This example provides:

• Service account configuration - Proper IAM roles and permissions
• Authentication flow - How to generate and use credentials
• Security best practices - Least-privilege access, key rotation
• Production patterns - Environment-specific configuration

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Key Features

• Step-by-step setup guide - From GCP project creation to API calls
• Working code examples - Python, Node.js authentication patterns
• IAM configuration - Exact roles and permissions needed
• Troubleshooting guide - Common authentication issues and solutions

When to Use This

This example is essential for:

• Production Gemini deployments - Moving beyond user credentials
• CI/CD integration - Automated pipelines calling Gemini APIs
• Multi-environment setups - Separate service accounts per environment
• Security compliance - Proper credential management

Reference this when building applications that need programmatic access to Gemini without user authentication.