A powerful command-line tool for setting up and testing Google Cloud Vertex AI integration. This tool automates the process of enabling Vertex AI services, managing authentication, and testing API calls.
- 🔧 Automatic Service Enablement: Checks and enables Vertex AI service if needed
- 📋 Model Discovery: Lists available Vertex AI models in your project
- 🔑 Authentication Setup: Automatically configures Application Default Credentials (ADC)
- 🔍 Environment Management: Sets up and manages environment variables
- 🎨 Rich Terminal Interface: Beautiful ASCII art, animations, and color-coded information
- 🔬 API Testing: Built-in test functionality with Gemini Pro 2 model
- 📚 Comprehensive Documentation: Detailed instructions for future API usage
Before using this tool, ensure you have:
- Rust and Cargo installed
- Google Cloud SDK (gcloud CLI) installed and configured
- Active Google Cloud project with billing enabled
- Appropriate IAM permissions (e.g.,
roles/aiplatform.user)
cargo install hvertex# Clone the repository
git clone git@github.com:RustSandbox/Vertex-AI-Setup-Tool.git
cd Vertex-AI-Setup-Tool
# Build in release mode
cargo build --release
# Run the tool
cargo run --releaseIf you prefer to install manually:
# Build the release version
cargo build --release
# Copy to a directory in your PATH
mkdir -p ~/.local/bin
cp target/release/hvertex ~/.local/bin/
chmod +x ~/.local/bin/hvertex
# Add to PATH if needed
echo 'export PATH=$PATH:~/.local/bin' >> ~/.zshrc # or ~/.bashrc
source ~/.zshrc # or ~/.bashrcRun the application:
hvertexThe application will guide you through:
- 🔍 Checking/enabling Vertex AI service
- 📊 Listing available models
- 🔑 Setting up authentication
- 🔍 Verifying environment variables
- 🔬 Testing the API with Gemini Pro 2
- 📚 Displaying usage instructions
- The tool checks if Vertex AI service is enabled in your project
- Lists available Vertex AI models in your project
- Sets up authentication using Application Default Credentials (ADC)
- Configures environment variables for API access
- Tests the API using the Gemini Pro 2 model
- Provides comprehensive documentation for future use
The application includes:
- 📊 ASCII Art Banner: Beautiful welcome banner
- 🎬 Animations: Typing effects, spinners, and progress bars
- 🎨 Color-Coded Information: Different colors for different types of information
- 📦 Boxed Messages: Important information displayed in stylish boxes
Modify the config.rs file to customize:
- Animation Settings: Enable/disable animations and timing
- Color Schemes: Change the color theme
- Emojis: Customize emojis used for different messages
If you encounter issues:
- Ensure you're authenticated with gcloud:
gcloud auth login - Verify your active project:
gcloud config get-value project - Check Vertex AI permissions in Google Cloud Console
- Run with verbose output:
RUST_LOG=debug hvertex
I'm Hamze Ghalebi, CTO at Remolab, passionate about building tools that improve developer workflows. This Vertex AI Setup Tool is part of a collection of tools I originally built for my own use, and I've decided to open source it in case others find it helpful.
Many of the tools I create solve specific pain points in my daily workflow with cloud infrastructure and development environments. If you have any feedback or suggestions for improvements, please feel free to contribute!
- GitHub: hghalebi
- Twitter/X: @hamzeml
- LinkedIn: Hamze Ghalebi
If you find this tool useful, please consider sponsoring me on GitHub to support continued development and maintenance.
This project is licensed under the MIT License - see the LICENSE file for details.
- 🎨 Enhanced terminal interface with improved ASCII art and animations
- 🔧 Added support for Gemini Pro 2 model testing
- 📚 Improved documentation and usage instructions
- 🐛 Fixed environment variable handling
- 🔑 Streamlined authentication setup process
- 🚀 Initial release
- ✨ Basic Vertex AI service setup and configuration
- 🔍 Model discovery functionality
- 🔑 Authentication management
- 📊 Environment variable configuration