Gemini 2.5 Flash Image & Nano Banana: Ultra-Fast Multimodal AI Guide

# 1. Install required packages
pip install -U google-genai python-dotenv pillow

# 2. Set up environment variables (.env file)
GEMINI_API_KEY=your_api_key_here

# 3. Complete working example
import os
from dotenv import load_dotenv
from google import genai
from PIL import Image
from io import BytesIO

# Load environment variables
load_dotenv()

# Initialize client
client = genai.Client(apikey=os.getenv("GEMINI_API_KEY"))

# Basic image generation
response = client.models.generate_content(
    model="gemini-2.5-flash-image-preview",
    contents=["A cozy coffee shop with warm lighting"]
)

# Extract and save image
for part in response.candidates[0].content.parts:
    if part.inline_data is not None:
        image = Image.open(BytesIO(part.inline_data.data))
        image.save("output.png")
        print("✅ Image saved!")

# Combining multiple images intelligently
from google import genai
from PIL import Image

# Load your base images
product_img = Image.open("product.jpg")
background_img = Image.open("background.jpg") 
style_ref = Image.open("style_reference.jpg")

# Compose with specific instructions
response = client.models.generate_content(
    model="gemini-2.5-flash-image-preview",
    contents=[
        "Place the product from Image 1 into the environment "
        "from Image 2, matching the lighting and style from "
        "Image 3. Maintain product details and brand colors.",
        product_img,
        background_img,
        style_ref
    ]
)

# The model intelligently blends all three images

# Progressive editing through conversation
chat = client.chats.create(
    model="gemini-2.5-flash-image-preview"
)

# Initial generation
response1 = chat.send_message([
    "Create a modern living room with minimalist design"
])

# First edit
response2 = chat.send_message([
    "Add a large abstract painting on the main wall",
    response1_image
])

# Second edit
response3 = chat.send_message([
    "Change the lighting to golden hour, add warm shadows",
    response2_image
])

# Each edit preserves previous changes

def generate_and_save_image(prompt, filename):
    """
    Reusable function for image generation
    """
    try:
        response = client.models.generate_content(
            model="gemini-2.5-flash-image-preview",
            contents=[prompt]
        )
        
        for part in response.candidates[0].content.parts:
            if part.inline_data is not None:
                image = Image.open(BytesIO(part.inline_data.data))
                image.save(f"images/{filename}")
                print(f"✅ Saved: {filename}")
                return True
    except Exception as e:
        print(f"❌ Error: {e}")
        return False

# Usage
generate_and_save_image(
    "Minimalist bedroom with natural light",
    "bedroom.png"
)