---
title: Rec Project
emoji: ⚡
colorFrom: gray
colorTo: gray
sdk: streamlit
sdk_version: 1.37.1
app_file: app.py
pinned: false
---

# Shows Recs: TV Series Recommendation System

![Streamlit](https://img.shields.io/badge/Streamlit-1.37.1-brightgreen.svg) ![Docker](https://img.shields.io/badge/Docker-20.10.7-blue.svg) ![Python](https://img.shields.io/badge/Python-3.9-blue.svg)

## Overview

**Shows Recs** is a web application that provides TV series recommendations based on user input. It uses Sentence Transformers and FAISS to search and recommend series by embedding text queries and comparing them to a precomputed index of embeddings.

## Features

- **Metric Selection**: Choose from `L2`, `Dot Product`, or `Cosine Similarity`.
- **Customizable Recommendations**: Specify the number of recommendations to display.
- **Fast and Accurate**: Leverages FAISS for efficient similarity search.

## Installation & Usage

### 1. Clone the Repository

```bash
git clone https://huggingface.co/skudinov/shows_recs.git
cd shows_recs
```

### 2. Install Dependencies
Create a virtual environment and install the required packages:
```bash
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```

### 3. Run the Application
Run the Streamlit app locally:
```bash
streamlit run app.py
```
The app will be accessible at http://localhost:8501.

### 4. Run with Docker
- Build the Docker image:
```bash
docker build -t your_docker_account/your_docker_repo .
```
- Run the Docker container:
```bash
docker run -p 8501:8501 your_docker_account/your_docker_repo
```

## How to Use
- Enter a query in the text input field.
- Select a similarity metric (L2, Dot Product, Cosine Similarity).
- Choose the number of recommendations.
- Click "Search" to get a list of TV series recommendations.