This project is a semandtic book recommender that uses machine learning and natural language processing to recommend books based on user input. It features a web-based dashboard built with Gradio for an interactive user experience.
- Semantic Search: Uses embeddings from Hugging Face's
sentence-transformersto find books similar to a user-provided query. - Emotion-Based Recommendations: Allows users to filter recommendations based on emotional tones like "Happy," "Sad," or "Suspensful."
- Category Filterings: Users can filter books by categories such as fiction, non-fiction, etc.
- Interactive Dashboard: Built with Gradio for a user-friendly interface.
- Clone the repository:
git clone https://github.com/minhphung152/book-recommender.git
cd book-recommender- Create a virtual environment and activate it:
python3 -m venv .venv
source .venv/bin/activate- Install the required dependencies:
pip isntall -r requirements.txt- Run the Gradio dashboard:
python gradio-dashboard.py-
Open the dashboard in your browser (usually at http://127.0.0.1:7860).
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Enter a description of a book, select a category, and choose an emotional tone to get recommendations.