Media Tracker: An LLM-Powered Web Platform for Tracking and Discovering Movies and Series
Resumo
The rapid growth of the streaming market has created new opportunities for online content consumption, but also challenges in organizing and discovering movies and series within increasingly large catalogs. In this context, this work presents the development of Media Tracker, an intelligent Web platform designed to help users organize their viewing history, track progress, and discover new online content through textual descriptions or images supported by Large Language Models (LLMs). The back-end is implemented with Spring Boot and JSON Web Token (JWT) authentication, while the front-end uses Angular. In addition, by using a Model Context Protocol (MCP) server, the Media Tracker integrates The Movie Database (TMDb) API and OpenAI GPT-4 Turbo for multimodal search. The resulting system provides a responsive and intuitive interface that enables personal management of streaming consumption powered by LLMs.
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