Image Retrieval-Augmented Generation (RAG) System

This project implements an Image Retrieval-Augmented Generation (RAG) system that allows users to query images using image embeddings for efficient and accurate retrieval. The system leverages a combination of image feature extraction and RAG retrieval to provide relevant results based on user queries.

Features

• Image Embedding-Based Retrieval: Query images using image embeddings for fast, contextually relevant results.
• RAG Architecture: Integrates image retrieval with generative models for better content understanding and response generation.
• Efficient Retrieval: Optimized for both speed and accuracy in image-based queries.

Installation

1. Clone the repository:

   git clone https://github.com/your_username/Image-RAG-System.git

2. Navigate to the project directory:

   cd Image-RAG-System

3. Install dependencies:

   pip install -r requirements.txt

Usage

1. Start the system:

   python app.py

2. Query the system: Upload an image or use a query to search for relevant images using the Image RAG model.

License

This project is licensed under the MIT License. See the LICENSE file for details.