🎨 Vertex AI Imagen Python Client

Simple and clean Python client for Google Cloud Vertex AI Imagen

Generate AI images with just a few lines of code!

🚀 Quick Start

Installation

pip install vertex-ai-imagen

Basic Usage

import asyncio
from vertex_ai_imagen import ImagenClient

async def main():
    # Initialize client
    client = ImagenClient(project_id="your-project-id")
    client.setup_credentials("path/to/service-account-key.json")
    
    # Generate image
    image = await client.generate(
        prompt="A beautiful sunset over the ocean",
        aspect_ratio="16:9"
    )
    
    # Save image
    image.save("sunset.png")
    print(f"Image saved! Size: {image.size:,} bytes")

# Run
asyncio.run(main())

✨ Features

• 🚀 Simple API: Generate images with just a few lines
• 🎯 Type Safe: Full type hints support
• 🔒 Secure: Google Cloud service account authentication
• 📦 Clean Models: Intuitive data classes
• ⚡ Async Support: Built-in async/await patterns
• 🎛️ Full Control: Access to all Imagen parameters

📖 Advanced Usage

Multiple Images

# Generate multiple images
images = await client.generate(
    prompt="A futuristic city with flying cars",
    model="imagen-3.0-fast-generate-001",
    aspect_ratio="16:9",
    count=3,
    negative_prompt="blurry, low quality",
    seed=12345
)

# Save all images
for i, image in enumerate(images):
    image.save(f"city_{i+1}.png")

Authentication Options

# Method 1: Direct key file
client.setup_credentials("path/to/key.json")

# Method 2: Environment variable (GOOGLE_APPLICATION_CREDENTIALS)
client.setup_credentials_from_env()

Supported Models

# List available models
models = client.list_models()
print(models)

# Output:
# ['imagegeneration@006', 'imagen-3.0-generate-001', 'imagen-3.0-fast-generate-001', ...]

Aspect Ratios

• 1:1 - Square
• 16:9 - Widescreen
• 9:16 - Portrait (mobile)
• 4:3 - Traditional landscape
• 3:4 - Traditional portrait

🔧 Setup

Google Cloud Setup

1. Enable the API

   gcloud services enable aiplatform.googleapis.com
   

2. Create Service Account

   gcloud iam service-accounts create imagen-client \
     --display-name="Imagen Client"
   
   gcloud projects add-iam-policy-binding PROJECT_ID \
     --member="serviceAccount:imagen-client@PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/aiplatform.user"
   

3. Create Service Account Key

   gcloud iam service-accounts keys create key.json \
     --iam-account=imagen-client@PROJECT_ID.iam.gserviceaccount.com
   

Environment Variables

export GOOGLE_CLOUD_PROJECT="your-project-id"
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/key.json"

📝 Examples

Check out the examples directory for more usage patterns:

• Basic Usage - Simple image generation
• Advanced Usage - Complete feature demo

Jupyter Notebook

# Display image directly in notebook
image = await client.generate("A cute cat")
image.show()  # Shows image inline

Error Handling

from vertex_ai_imagen.exceptions import ImagenError, AuthenticationError

try:
    image = await client.generate("A beautiful landscape")
    image.save("landscape.png")
except AuthenticationError:
    print("Please check your credentials")
except ImagenError as e:
    print(f"Image generation failed: {e}")

📊 API Reference

ImagenClient

client = ImagenClient(
    project_id="your-project-id",
    location="us-central1"  # optional
)

Generate Images

await client.generate(
    prompt="Image description",                # required
    model="imagegeneration@006",              # optional
    aspect_ratio="1:1",                       # optional
    count=1,                                  # 1-4
    negative_prompt="Things to exclude",      # optional
    seed=12345,                              # optional
    safety_setting="block_medium_and_above",  # optional
    enhance_prompt=True                       # optional
)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - see LICENSE file for details.

🔗 Links

• PyPI Package
• GitHub Repository
• Google Cloud Vertex AI
• Imagen Documentation