Documentation Index
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NanoBananaTools enables an Agent to generate images using Google’s Gemini 2.5 Flash Image model (Nano Banana).
Prerequisites
You need to install the google-genai and Pillow libraries.
uv pip install google-genai Pillow
Set the GOOGLE_API_KEY environment variable. You can obtain an API key from Google AI Studio.
export GOOGLE_API_KEY=****
Example
The following agent will use Nano Banana to generate an image based on a text prompt.
from pathlib import Path
from agno.agent import Agent
from agno.tools.nano_banana import NanoBananaTools
# Example 1: Basic NanoBanana agent with default settings
agent = Agent(tools=[NanoBananaTools()], name="NanoBanana Image Generator")
# Example 2: Custom aspect ratio generator
portrait_agent = Agent(
tools=[
NanoBananaTools(
aspect_ratio="2:3" # Portrait orientation
)
],
name="Portrait NanoBanana Generator",
)
# Example 3: Widescreen generator for panoramic images
widescreen_agent = Agent(
tools=[
NanoBananaTools(
aspect_ratio="16:9" # Widescreen format
)
],
name="Widescreen NanoBanana Generator",
)
# Test basic generation
agent.print_response(
"Generate an image of a futuristic city with flying cars",
markdown=True,
)
# Generate and save an image
response = widescreen_agent.run(
"Create a panoramic nature scene with mountains and a lake at sunset",
markdown=True,
)
# Save the generated image if available
if response.images and response.images[0].content:
output_path = Path("generated_image.png")
with open(output_path, "wb") as f:
f.write(response.images[0].content)
print(f"Image was successfully generated and saved to: {output_path}")
| Parameter | Type | Default | Description |
|---|
model | str | "gemini-2.5-flash-image" | The Nano Banana model to use |
aspect_ratio | str | "1:1" | Image aspect ratio. Supported: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9 |
api_key | str | None | The Google API key for authentication |
enable_create_image | bool | True | Enable the create image functionality |
| Function | Description |
|---|
create_image | Generates an image based on a text prompt |
Developer Resources