Nano Banana - Image Generation + Prompt Library

Generate images using Gemini API with access to 6000+ curated professional prompts.

Quick Start

Direct Generation

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

Search Prompts First

python scripts/search_prompts.py "avatar professional"

Edit Existing Image

python scripts/edit_image.py input.png "Add rainbow background" output.png

Workflow

Step 0: Mode Detection

Classify user intent:

Mode Signal Action

Direct Clear prompt provided Generate immediately

Exploration Vague request, needs ideas Search prompts first

Content-based User provides article/context Extract themes, then search

Step 1: Prompt Search (exploration mode)

Search by category:

• avatars

• Headshots, portraits, profile pictures

• social_media

• Instagram, Twitter, Facebook content (3800+)

• product_marketing

• Ads, campaigns (1900+)

• infographic

• Data visualization

• thumbnails

• YouTube covers

• comics

• Sequential art, storyboards

• ecommerce

• Product photography

• game_assets

• Sprites, characters

• posters

• Events, announcements

• web_design

• UI mockups

Token optimization: Use grep patterns, NEVER fully load reference files.

Present max 3 matching prompts with sample images when available.

Step 2: Generation

Source Action

Curated prompt selected Use EXACT prompt text

No match / user declines Generate custom, label [AI-Generated]

Step 3: Refinement (optional)

Use multi-turn chat for iterative editing:

python scripts/multi_turn_chat.py

Prompt Categories

Category Count Best For

Social Media 3800+ Instagram, Twitter, Facebook

Product Marketing 1900+ Ads, campaigns

Avatars 700+ Headshots, portraits

Infographic 350+ Data visualization

Posters 300+ Events, announcements

Comics 200+ Sequential art

E-commerce 200+ Product shots

Game Assets 200+ Sprites, characters

Thumbnails 100+ Video covers

Web Design 100+ UI mockups

Models

Model Resolution Best For

gemini-2.5-flash-image

1024px Speed, high-volume

gemini-3-pro-image-preview

Up to 4K Professional assets, text rendering

Core API Pattern

All image generation uses the generateContent endpoint with responseModalities: ["TEXT", "IMAGE"] :

import os import base64 from google import genai

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

response = client.models.generate_content( model="gemini-2.5-flash-image", contents=["Your prompt here"], )

for part in response.parts: if part.text: print(part.text) elif part.inline_data: image = part.as_image() image.save("output.png")

Image Configuration Options

Control output with image_config :

from google.genai import types

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=[prompt], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], image_config=types.ImageConfig( aspect_ratio="16:9", # 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9 image_size="2K" # 1K, 2K, 4K (Pro only for 4K) ), ) )

Editing Images

Pass existing images with text prompts:

from PIL import Image

img = Image.open("input.png") response = client.models.generate_content( model="gemini-2.5-flash-image", contents=["Add a sunset to this scene", img], )

Multi-Turn Refinement

Use chat for iterative editing:

from google.genai import types

chat = client.chats.create( model="gemini-2.5-flash-image", config=types.GenerateContentConfig(response_modalities=['TEXT', 'IMAGE']) )

response = chat.send_message("Create a logo for 'Acme Corp'")

Save first image...

response = chat.send_message("Make the text bolder and add a blue gradient")

Save refined image...

Prompting Best Practices

Photorealistic Scenes

Include camera details: lens type, lighting, angle, mood.

"A photorealistic close-up portrait, 85mm lens, soft golden hour light, shallow depth of field"

Stylized Art

Specify style explicitly:

"A kawaii-style sticker of a happy red panda, bold outlines, cel-shading, white background"

Text in Images

Be explicit about font style and placement. Use gemini-3-pro-image-preview for best results:

"Create a logo with text 'Daily Grind' in clean sans-serif, black and white, coffee bean motif"

Product Mockups

Describe lighting setup and surface:

"Studio-lit product photo on polished concrete, three-point softbox setup, 45-degree angle"

Advanced Features (Pro Model Only)

Google Search Grounding

Generate images based on real-time data:

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=["Visualize today's weather in Tokyo as an infographic"], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], tools=[{"google_search": {}}] ) )

Multiple Reference Images (Up to 14)

Combine elements from multiple sources:

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=[ "Create a group photo of these people in an office", Image.open("person1.png"), Image.open("person2.png"), Image.open("person3.png"), ], )

Environment

Requires GEMINI_API_KEY environment variable.

Notes

• All generated images include SynthID watermarks

• Image-only mode (responseModalities: ["IMAGE"] ) won't work with Google Search grounding

• For editing, describe changes conversationally—the model understands semantic masking