Stream Scouter, now available on your phone!

Overview

Stream Scouter is a lightweight recommendation tool for matching Netflix titles to user queries using multilingual sentence transformers and semantic similarity. The project is designed to provide accurate and efficient content recommendations across different languages.

Features

• 🚀 Fast and Efficient: Uses pre-trained sentence transformers for quick semantic matching.
• 🌍 Multilingual Support: Works with multiple languages for diverse audiences.
• 🔎 Semantic Similarity Matching: Finds the most relevant Netflix titles based on user input.
• 📊 Notebook Implementation: Fully implemented in Jupyter Notebook for ease of experimentation and deployment.
• 📱 Mobility and accessibility: Stream scouter now available on android, you can download it and try.

Installation

To set up and run StreamScouter locally, follow these steps:

Prerequisites

• Python 3.8+
• Jupyter Notebook
• Required dependencies (listed in requirements.txt)

Steps

1. Clone the repository:

   git clone https://github.com/r4nol/StreamScouter.git
   cd StreamScouter

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt

3. Launch Jupyter Notebook and open StreamScouter.ipynb:

   jupyter notebook

To install app on your phone, download this apk file.

Usage

1. Run the cells in the Jupyter Notebook.
2. Enter a query (e.g., "After meeting at a party, a Cape Town teen tests a private-school swimmer's reputation") to get recommendations.
3. View the ranked list of matching Netflix titles.

Technologies Used

• Python 🐍
• Jupyter Notebook 📓
• Sentence Transformers 🤖
• Pandas & NumPy 📊
• Kotlin 🏝
• Coil 🖼
• Retrofit 🌐
• Okhttp 🌐

Contributing

We welcome contributions! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

🐙 GitHub: @r4nol & @w1lderrrr