Google Gemini¶
Google Gemini CLI provides conversational AI capabilities from Google's generative AI models.
Overview¶
- Conversational AI via command line
- Multiple models supported
- Automatic installation via npm
- Direct API access (not routed through Databricks)
Authentication¶
Gemini CLI requires authentication with Google's AI services. On initial startup, you'll need to configure authentication.
Method 1: Personal Google Account (Recommended for Free Tier)¶
On first run, Gemini CLI will open a browser for authentication. Once authenticated, credentials are cached locally for subsequent runs.
Free Access: Login with a personal Google account to get a free Gemini Code Assist license with access to Gemini 2.5 Pro and its 1 million token context window.
Method 2: API Key¶
# Set your Gemini API key
export GEMINI_API_KEY="..."
# Or set Google API key
export GOOGLE_API_KEY="..."
# Add to ~/.bashrc for persistence
echo 'export GEMINI_API_KEY="..."' >> ~/.bashrc
# Run gemini
gemini
Get your API key from Google AI Studio.
Method 3: Google Cloud / Vertex AI¶
For production use with Google Cloud:
# Ensure Vertex AI API is enabled in your project
# Unset API key environment variables
unset GOOGLE_API_KEY
unset GEMINI_API_KEY
# Use Application Default Credentials
gemini
Method 4: Cloud Shell¶
When running in Google Cloud Shell, authentication is automatic using your logged-in credentials.
Switching Authentication¶
To change authentication methods:
Usage¶
Interactive Chat¶
Single Prompt¶
Configuration¶
Gemini requires a Google API key (not automatically configured):
Note: In Databricks DevBox, Gemini is installed but not pre-configured for Databricks models. It's included for completeness but requires manual API key setup.
When to Use¶
Use Gemini for:
- ✅ General AI conversations
- ✅ Non-coding questions
- ✅ Google-specific integrations
Use Claude Code instead for:
- ❌ Databricks-integrated workflows
- ❌ Pre-configured setup
- ❌ Code-specific tasks
Next Steps¶
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Recommended for Databricks
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