Nano Banana 2

Image generation skill powered by Google's Gemini 3.1 Flash Image model (Nano Banana 2). Enables text-to-image generation, image editing, multi-image composition, and real-time data visualization. Pro-level quality at Flash-level speed.

Default model: gemini-3.1-flash-image-preview (Nano Banana 2). Use this unless the user specifically requests Pro or an upgraded model is available.

Requirements

• GEMINI_API_KEY environment variable set
• Python packages: google-genai, Pillow

Install dependencies:

pip install -r requirements.txt

Quick Start

Generate an Image

python scripts/generate_image.py "A cat wearing a wizard hat" cat.png

Edit an Existing Image

python scripts/edit_image.py photo.png "Add a sunset to the background" edited.png

Compose Multiple Images

python scripts/compose_images.py "Create a group photo in an office" team.png person1.png person2.png

Available Scripts

Generation Options

Aspect Ratios

1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9

Resolutions

1K (1024px), 2K (default), 4K

Usage with Options

python scripts/generate_image.py "Futuristic motorcycle on Mars" mars.png --aspect 16:9 --size 4K

Override Model (for Pro when needed)

python scripts/generate_image.py "prompt" out.png --model gemini-3-pro-image-preview

Task Workflows

Logo Generation

python scripts/generate_image.py "Clean black-and-white logo with text 'Daily Grind', sans-serif font, coffee bean icon, minimalist style" logo.png --aspect 1:1

Product Mockup

python scripts/generate_image.py "Studio-lit product photo on polished concrete, 3-point softbox, 45-degree angle, professional e-commerce style" product.png --aspect 4:3 --size 4K

Photorealistic Portrait

python scripts/generate_image.py "A photorealistic close-up portrait, shot on 85mm lens, golden hour lighting, shallow depth of field, cinematic" portrait.png --size 4K

Stylized Art (Anime/Sticker)

python scripts/generate_image.py "A kawaii red panda sticker, bold outlines, cel-shading, white background, cute expression" sticker.png

Iterative Design Refinement

Use the chat script for back-and-forth refinement:

python scripts/chat_image.py

Then interact:

> Create a logo for 'Acme Corp'
[Image generated]
> Make the text bolder and add a blue gradient
[Refined image]
> save acme_logo.png

Real-Time Data Visualization

Generate infographics with current data:

python scripts/search_grounded_image.py "Visualize today's weather in Tokyo as an infographic" tokyo_weather.png --aspect 9:16

Use cases:

• Live stock-market infographics
• Breaking-news visuals
• Weather dashboards
• Current event visualizations

Multi-Image Composition

Combine reference images:

python scripts/compose_images.py "Create a product comparison shot with these items side by side, professional lighting" comparison.png item1.png item2.png item3.png --aspect 16:9

Use cases:

• Product comparison shots
• Character sheets
• Team photos
• Style-consistent image series

Inline Python Usage

For integration in larger scripts:

import os
from google import genai
from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=["A serene mountain landscape at dawn"],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
            image_size="2K"
        )
    )
)

for part in response.parts:
    if part.inline_data:
        image = part.as_image()
        image.save("landscape.png")

Editing with Inline Code

from PIL import Image
from google import genai
from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
img = Image.open("input.png")

response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=["Add dramatic clouds to the sky", img],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE']
    )
)

Prompting Guide

See PROMPTING.md for the complete deep-dive prompting guide. Key highlights:

Core Principle

Describe the scene, don't list keywords. NB2 has a 32K token context window and understands full natural language, Markdown, and JSON.

Universal Prompt Formula

[Shot type] + [Subject] + [Action/pose] + [Environment] + [Lighting] + [Mood] + [Camera/lens] + [Style] + [Aspect ratio/resolution]

Power Techniques

Markdown lists for multi-edit instructions (trained on code repos):

Make ALL of the following edits:
- Change sky to sunset
- Add birds in V-formation
- NEVER add watermarks

ALL CAPS for critical requirements: MUST, NEVER, EXACTLY

Buzzword composition: Pulitzer-prize-winning cover photo for The New York Times

JSON character specs for complex characters with precise traits

Physicality constraints to force photorealism: real-world natural uniform depth of field

Step-by-step for complex scenes: First... Then... Finally...

Photography Terms That Work

wide-angle, macro, 85mm portrait lens, Dutch angle, Hasselblad X2D, Canon EOS 90D, Kodak Portra 400, shallow depth of field, three-point softbox, rim lighting, golden hour

NB2 Strengths

• Sharp text rendering in multiple languages (put text in quotes)
• Character consistency (up to 5 chars / 14 objects)
• Search-grounded generation for real-time data
• 512px to 4K resolution
• ~$0.039/image

Common Mistakes

1. Keyword soup -- write sentences
2. Vague style -- specify camera, lens, settings
3. Ignoring lighting -- always specify
4. No aspect ratio -- be explicit
5. Re-rolling instead of editing -- use iterative refinement