Fashion Forward: AI-Driven Personalized Outfit Suggestions Using Meta Llama-3 And E-Commerce Data

Abstract

This paper outlines an AI-driven clothing recommendation system that uses machine learning and natural language processing to offer personalized outfit suggestions. By integrating the Meta Llama-3 70B model through the TogetherLLM API, the system processes user preferences like age, gender, color choices, and budget. It also pulls product data from external sources, such as Flipkart, to suggest relevant outfits in real-time. The system features a user profiling module, a recommendation engine, and a feedback loop for continuous interaction. Through this combination of AI models and ecommerce data, the system delivers tailored fashion suggestions, demonstrating how language models can enhance online shopping experiences. The approach is scalable and offers significant potential for virtual shopping assistants in e-commerce platforms.