Nano Banana Pro Image Generator

Generate images using Google's advanced Nano Banana Pro model (gemini-3-pro-image-preview ).

Prerequisites

The user must have GEMINI_API_KEY environment variable set with a valid Google AI API key.

Usage

The script is located in the same directory as this SKILL.md file. Run it with uv run :

uv run /path/to/skills/nano-banana-pro/generate_image.py "your prompt" -o output.png

When this skill is invoked, locate generate_image.py in the skill directory and run it.

Parameters

Parameter Required Description

prompt

Yes Text description of the image to generate or transformation to apply

-o , --output

Yes Output filename (you decide the path based on context)

-i , --image

No Input image(s) for editing/transformation or as context/reference (can be used multiple times)

--aspect-ratio

No One of: 1:1 , 2:3 , 3:2 , 3:4 , 4:3 , 4:5 , 5:4 , 9:16 , 16:9 , 21:9 (default: 1:1 )

--size

No Image size: 1K , 2K , 4K (default: 1K )

Examples

Basic image generation:

uv run generate_image.py "A sunset over mountains" -o sunset.png

Infographic with specific aspect ratio:

uv run generate_image.py "Infographic showing the water cycle with labeled stages" -o water_cycle.png --aspect-ratio 9:16

High-resolution ultrawide:

uv run generate_image.py "Professional photo of a modern office space" -o office.png --aspect-ratio 21:9 --size 4K

Edit an existing image:

uv run generate_image.py "Add a sunset sky to this image" -i photo.png -o edited.png

Transform with style:

uv run generate_image.py "Make this look like a watercolor painting" -i input.jpg -o watercolor.png

Combine multiple images:

uv run generate_image.py "Create a collage blending these images together" -i img1.png -i img2.png -o collage.png

Use image as context/reference:

uv run generate_image.py "Generate a new landscape in the same style as this reference" -i reference.png -o new_landscape.png

Model Capabilities

Nano Banana Pro excels at:

• Accurate infographics with real data (uses Google Search grounding)

• Text rendering in images

• Image editing and transformation from input images

• Context-aware generation using reference images for style, composition, or subject

• Cartographic visualizations and maps

• Detailed instruction following

• Chain-of-thought reasoning for complex visual tasks

Output

The script prints:

• Progress message while generating

• Path to saved image on success

• Any text response from the model

• Error message if no image was generated