Скачать или смотреть How to Make ACCURATE Image Search App with Gemini AI

👉 In this video, I will show you how I built a smart semantic photo search app using Google Gemini so you can find images by meaning, not filenames. It helps you pull up product photos, inventory shots, receipts, and documents using natural language queries like contains text or can fly. If you are working on an internal tool or a quick demo, this gives you a simple way to test multimodal search with Gemini Canvas.

Prompt:
Generate an app where users can upload images through drag and drop functionality supporting multiple files at once that will be analyzed using the Gemini built-in API with semantic search capabilities. The app must use Firestore to persist uploaded images and their AI-generated metadata so that the gallery is saved across browser sessions. The app should use responsive design that adapts to all screen sizes and devices. Allow users to describe images using natural language instead of exact keywords. For example, if a user searches for "animal," the app will return images of cats, dogs, and other animals. If a user searches for "green transportation," the app will intelligently return images of bicycles, electric vehicles, or other eco-friendly transport options. Gemini will analyze both the user's descriptive request and the uploaded images to understand the meaning and context behind the query, then group and return relevant results based on semantic similarity rather than exact keyword matching.

PS: If you modify the app, earlier images may be cleared.

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