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| title: Book Recommender | |
| emoji: 👁 | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 6.6.0 | |
| app_file: app.py | |
| pinned: false | |
| short_description: 'Book search/rec based on vector search: Query - Book desc' | |
| # 📚 Semantic Book Recommender | |
| A semantic book recommendation system powered by vector search and emotion-aware ranking. | |
| ## 🚀 How It Works | |
| 1. User enters a book description. | |
| 2. The query is converted into an embedding using | |
| `sentence-transformers/all-MiniLM-L6-v2` (Hugging Face Inference API). | |
| 3. FAISS performs cosine similarity search over precomputed book embeddings. | |
| 4. Results are optionally filtered by category. | |
| 5. Results are optionally re-ranked by emotional tone (joy, surprise, anger, fear, sadness). | |
| --- | |
| ## 🧠 Features | |
| - Semantic similarity search (FAISS) | |
| - Emotion-based re-ranking | |
| - Category filtering | |
| - Fast retrieval with precomputed embeddings | |
| - Hosted on Hugging Face Spaces (Gradio) | |
| --- | |
| ## 🛠 Tech Stack | |
| - Python | |
| - Gradio | |
| - FAISS | |
| - Hugging Face Inference API | |
| - Pandas / NumPy | |
| --- | |