---
title: Book Recommender
emoji: 📉
colorFrom: gray
colorTo: blue
sdk: streamlit
sdk_version: 1.41.1
app_file: app.py
pinned: false
short_description: A basic book recommender system
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference


# Content-Based Book Recommender System

This is a content-based book recommender system built using **Streamlit**. It takes a book title as input and generates up to 5 recommendations based on content similarity. The recommendations combine textual similarity (TF-IDF) and semantic similarity (Sentence Transformers). The system also handles typos and invalid inputs.

---

## Features

1. **Content-Based Recommendations**:
   - Combines TF-IDF and semantic similarity to recommend books.
   - Handles typos and approximate matches using fuzzy matching.

2. **Error Handling**:
   - Ensures graceful failure for invalid inputs or system errors.
   - Provides fallback recommendations when similarity scores are insufficient.

3. **Interactive UI**:
   - Built with Streamlit for a user-friendly interface.



## Dependencies and Functionality
1. pandas:
    Handles data loading, preprocessing, and manipulation.

2. scikit-learn:
    Provides TF-IDF vectorization and NearestNeighbors for similarity search.

3. sentence-transformers:
    Generates semantic embeddings for textual data.

4. numpy:
Used for numerical computations like handling embeddings and arrays.

5. streamlit:
    Creates the interactive UI for the application.

6. rapidfuzz:
    Implements fuzzy matching for typos and approximate title matches.

7. re:
    Cleans special characters from book titles.