BookRecs is a book recommendation service leveraging semantic search to suggest books based on user input. It utilizes a database of 7000 books from Kaggle, with vector embeddings generated using Ada v2 for semantic similarity. The frontend is built with Next.js and styled with TailwindCSS.
Key Features:
- Semantic Search: Provides book recommendations based on genre and book titles.
- Vector Database: Utilizes Weaviate for fast vector lookups.
- LLM Integration: Uses Ollama or OpenAI for vector generation and inference.
- Responsive Design: Built with TailwindCSS for a seamless user experience.
- Data Pipeline: Jupyter Notebook workflow to access and store vector embeddings in Weaviate.
