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Image question answering

This example demonstrates how to use the Gemini API to analyze or understand images of cats, including using image URLs and base64 encoding.

Import necessary libraries

from google import genai
from google.genai import types
import requests
import base64

Replace with your Gemini API key

client = genai.Client(api_key="YOUR_API_KEY")

We'll start by using an image URL. Load an image of a cat from a URL

image_url = "https://cataas.com/cat"
image_response = requests.get(image_url)
image_content = image_response.content

Ask Gemini about the cat in the image

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents=["What breed of cat is this?", types.Part.from_bytes(data=image_content, mime_type="image/jpeg")]
)

print("Response from URL Image:\n", response.text)

Now we'll use a local image file. Load a local image of a cat and encode it as Base64

with open("cat.jpg", "rb") as image_file:
    encoded_string = base64.b64encode(image_file.read())

Ensure the encoded string is a string

encoded_string = encoded_string.decode('utf-8')

Ask Gemini a question about the cat, providing the image as a Base64 string

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents=["Is this cat fluffy?", types.Part.from_bytes(data=base64.b64decode(encoded_string), mime_type="image/jpeg")]
)

print("\nResponse from Base64 Image:\n", response.text)

Running the Example

First, install the Google Generative AI library and requests

$ pip install google-genai requests

Download an example cat image (replace with your own if needed)

$ wget https://cataas.com/cat -O cat.jpg

Then run the program with Python

$ python gemini-cat.py
Response from URL Image:
 This looks like a British Shorthair cat.
Response from Base64 Image:
 Yes, this cat appears to be fluffy.

Further Information