Nano Banana Pro: Google's New Dominant Image Generation Model

GEMINI_API_KEY=your_key_here

pip install google-genai python-dotenv pillow

import os
from google import genai
from google.genai import types
from dotenv import load_dotenv

# Load API key
load_dotenv()
client = genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))

# Generate image
response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents="Vast cosmic nebula in deep space. Swirling purple and blue gas clouds with bright star clusters. Ethereal glow. Epic space photography. 16:9 cinematic composition. No planets visible.",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
            image_size="1K"
        ),
    )
)

# Save the image
for part in response.parts:
    if image := part.as_image():
        image.save("cosmic_base.png")
        print("Image saved!")

# Load the base image
from PIL import Image
base_image = Image.open("cosmic_base.png")

# Create a chat session for editing
chat = client.chats.create(
    model="gemini-3-pro-image-preview",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
            image_size="1K"
        ),
    )
)

# Edit: Transform colors
response = chat.send_message([
    base_image,
    "Transform this nebula to warm orange and red tones, like a different type of stellar nursery. Keep the same swirling structure and composition."
])

# Save edited image
for part in response.parts:
    if image := part.as_image():
        image.save("cosmic_orange.png")

# Generate comet reference
comet_response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents="Massive comet with bright glowing nucleus and long ion tail streaming behind. Detailed surface texture on comet head. Ethereal blue-white tail against black space. Dramatic cosmic photography.",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(aspect_ratio="16:9", image_size="1K"),
    )
)

# Save comet
for part in comet_response.parts:
    if image := part.as_image():
        image.save("comet.png")

# Generate ancient alien monolith
monolith_response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents="Massive ancient alien monolith floating in space. Towering black rectangular obelisk with subtle geometric patterns. Mysterious glowing symbols etched on surface. 2001 Space Odyssey style. Epic scale.",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(aspect_ratio="16:9", image_size="1K"),
    )
)

# Save monolith
for part in monolith_response.parts:
    if image := part.as_image():
        image.save("monolith.png")

# Load all three images
nebula = Image.open("cosmic_orange.png")
comet = Image.open("comet.png")
monolith = Image.open("monolith.png")

# Blend them into one composition
blend_response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=[
        "Combine these images into one epic space scene. Place the ancient alien monolith in the right side, towering and mysterious. Show the bright comet with its glowing tail streaking diagonally across the left side. Keep the orange nebula as the dramatic backdrop. Cinematic space composition.",
        nebula,
        comet,
        monolith
    ],
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(aspect_ratio="16:9", image_size="1K"),
    )
)

# Save final composition
for part in blend_response.parts:
    if image := part.as_image():
        image.save("cosmic_final.png")

def generate_image(prompt, filename, aspect_ratio="16:9", size="1K", use_google_search=False):
    
    config = types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(
            aspect_ratio=aspect_ratio,
            image_size=size
        ),
    )
    
    # Add Google Search grounding if requested
    if use_google_search:
        config.tools = [{"google_search": {}}]
    
    response = client.models.generate_content(
        model="gemini-3-pro-image-preview",
        contents=prompt,
        config=config
    )

    for part in response.parts:
        if image := part.as_image():
            image.save(f"{filename}.png")
            return image

# Generate movie poster with cast and credits
image = generate_image(
    prompt="""Sci-fi movie poster. Large title "STELLAR HORIZON" at top. Actor names "SARAH CHEN" "MARCUS RODRIGUEZ" "AISHA WILLIAMS". Production credits "Directed by James Park" "Produced by Luna Studios" at bottom. Deep space background with nebula. Professional film poster typography. Crisp readable text.""",
    filename="movie_poster"
)

# SaaS website hero section
image = generate_image(
    prompt="""Modern SaaS website hero section. Large headline "Automate Your Workflow in Minutes" with subheadline "Connect your tools and boost productivity by 10x". Two buttons "Start Free Trial" and "Watch Demo". Trust badges showing "500K+ Users" "99.9% Uptime" "SOC 2 Certified". Clean typography. Gradient purple to blue background. Professional web design layout.""",
    filename="saas_hero"
)

# Conference poster with English and Japanese
image = generate_image(
    prompt="""Tech conference poster. Top section English text: "GLOBAL AI SUMMIT 2025" "March 15-17, Tokyo". Bottom section Japanese text: "グローバルAIサミット2025" "3月15日-17日、東京". Modern geometric design. Vibrant gradient background blue to purple. Professional bilingual typography.""",
    filename="multilingual_poster"
)

# Generate base product image
base_image = generate_image(
    prompt="""Premium wireless earbuds with charging case. Front-facing straight-on view. Sleek matte black finish. Modern minimalist design. Clean white studio background. Professional product photography. Sharp focus throughout. Contemporary tech aesthetic.""",
    filename="earbuds_front"
)

# Create chat for editing
chat = client.chats.create(
    model="gemini-3-pro-image-preview",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(aspect_ratio="16:9", image_size="1K"),
    )
)

# Edit camera angle conversationally
edit_response = chat.send_message([
    base_image,
    """Show these exact same wireless earbuds from bird's eye view, looking straight down from above. Keep the same earbuds and charging case. Overhead flat lay composition. Professional product photography."""
])

# Save edited image
for part in edit_response.parts:
    if image := part.as_image():
        image.save("earbuds_overhead.png")

# Create brand logo
brand_logo = generate_image(
    prompt="""Abstract geometric ribbon logo. Flowing infinity loop shape with metallic gradient silver to deep purple. Smooth curved surfaces. Elegant minimalist design. Clean white background. Premium brand identity element. Modern corporate aesthetic. No face. No eyes.""",
    filename="ribbon_logo"
)

# Create chat for editing
chat = client.chats.create(
    model="gemini-3-pro-image-preview",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(aspect_ratio="16:9", image_size="1K"),
    )
)

# Show logo in app interface
app_response = chat.send_message([
    brand_logo,
    """Show this exact ribbon logo in a complete mobile app home screen. Top status bar with time and battery. Logo in header next to app name. Content cards below showing features. Bottom tab navigation with icons and labels. Modern mobile app UI. Gradient purple background. Professional startup app design. Full mobile interface layout."""
])

# Save
for part in app_response.parts:
    if image := part.as_image():
        image.save("ribbon_app.png")

# Show logo on merchandise
merch_response = chat.send_message([
    brand_logo,
    """Show this exact ribbon logo on brand merchandise collection. Flat lay showing: white tote bag with logo, coffee mug with logo, t-shirt with logo printed on chest, product packaging box with logo. All items arranged together. Premium brand identity mockup. Minimalist aesthetic. Professional product photography. Same ribbon on each item."""
])

# Save
for part in merch_response.parts:
    if image := part.as_image():
        image.save("ribbon_merchandise.png")

# Generate solar energy infographic with Search grounding
image = generate_image(
    prompt="""Educational infographic explaining solar panel energy conversion. Show photovoltaic cells converting to DC power, then inverter converting to AC power for the grid. Clear labels and arrows.""",
    filename="solar_infographic",
    use_google_search=True  # Enable Search for factual accuracy
)

# Generate neural network diagram with Search grounding
image = generate_image(
    prompt="""Neural network architecture diagram. Left: 4 input nodes labeled "Input 1" "Input 2" "Input 3" "Input 4". Middle: two hidden layers each with 5 nodes labeled "Hidden Layer 1" and "Hidden Layer 2". Right: 3 output nodes labeled "Output 1" "Output 2" "Output 3". Connection lines between all layers. Clean technical illustration. Educational ML diagram. Professional data science aesthetic.""",
    filename="ml_architecture",
    use_google_search=True  # Enable Search for accuracy
)