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build an AI image search app using Google's Gemini API

Last updated on 3 days ago
K
KevinMember
Posted 3 days ago
If you want to build an image search app using Google's Gemini API, you can use Google AI's Gemini Pro Vision API to analyze images and retrieve related information. Here’s a sample implementation in Python.

1️⃣ Prerequisites
Get a Google AI API key from Google AI Studio.
Install required libraries:

pip install google-generativeai pillow requests


2️⃣ Sample Code for Image Search App
This script allows users to upload an image, and the Gemini API will return a text description of the image.

import google.generativeai as genai
from PIL import Image
import io

# Set up Gemini API
API_KEY = "your_api_key_here" # Replace with your Google AI API Key
genai.configure(api_key=API_KEY)

def search_image(image_path):
 """Analyzes the image using Gemini Pro Vision API and returns a description."""
 
 # Load image
 image = Image.open(image_path)

 # Create the model
 model = genai.GenerativeModel("gemini-pro-vision")

 # Query the model with the image
 response = model.generate_content([image, "Describe this image."])

 return response.text # Extract text response

# Example usage
image_path = "sample.jpg" # Replace with your image file path
result = search_image(image_path)
print("Image Description:", result)
Edited by Kevin on 25-02-2025 10:33, 3 days ago
K
KevinMember
Posted 3 days ago
3️⃣ How It Works
The user provides an image (sample.jpg).
The script sends the image to Gemini Pro Vision API.
The model returns a text-based description of the image.
4️⃣ Extending to Image Search
If you want to build a reverse image search system:

Use Gemini API to describe the image.
Use a search engine API (Google, Bing, or an image database) to find similar images.
Display search results to the user.
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