An intelligent book recommendation system that leverages Large Language Models (LLMs) from Hugging Face to generate personalized suggestions based on user queries and book descriptions.
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✅ Natural Language Recommendations
Ask for book suggestions in plain English and receive context-aware responses. -
🧠 LLM-powered Semantic Search
Uses Hugging Face transformer models to embed book descriptions and perform zero-shot classification. -
📄 Document Parsing and Embedding
Loads a dataset of book descriptions and transforms them into vector representations. -
🔍 ChromaDB Vector Store
Efficient retrieval of semantically similar books using ChromaDB and LangChain. -
🎤 Gradio Frontend
Interactive web UI to chat with the recommender system. -
🧩 Modular Architecture
Easily swap models or data sources thanks to a clean and extendable structure.