Welcome!
Web Application for Multimodal Data Search and Analysis Based on RAG Architecture and GPT Module
About the Project
This project focuses on creating a web application that enables multimodal data search and analysis, combining multiple sources of information and leveraging modern natural language processing techniques.
Key components of the project:
- RAG Architecture (Retrieval-Augmented Generation) — provides intelligent search across large volumes of data with the ability to generate context-aware responses.
- GPT Module — allows interpreting, summarizing, and formulating answers based on the retrieved information.
- Web Interface — a user-friendly interface for searching, analyzing, and visualizing data.
Project Goals
- Enable analysis of multimodal data (text, images, and possibly video).
- Demonstrate the capabilities of RAG + GPT in a practical application.
Features
- Search across textual and multimodal data
- Generate summarized responses and provide context-aware information
- User-friendly web interface for working with data
Contact
Author: Matthew Alexandrovich Vishniakov Institute: Institute of Advanced Technologies and Industrial Programming Course: Fullstack Development / 2026
Thank you for your interest in the project!