🎬 MovieScout: Real-Time Movie Recommendation System

MovieScout is a recommendation system that predicts movie ratings using collaborative filtering, deep learning, and real-time monitoring. This solution is built with PyTorch, Prometheus, and Angular for a complete development experience.

🌟 Key Features

• Collaborative Filtering: Recommendations using matrix factorization.
• Prometheus Monitoring: Real-time tracking with Flask metrics.
• Angular Frontend: Intuitive, interactive user interface.

🛠️ Tech Stack

• Backend: Python, Flask, PyTorch
• Frontend: Angular
• Monitoring: Prometheus, Grafana

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🚀 Getting Started (Manual Setup)

1. Clone the Repository

git clone https://github.com/ashish493/MovieScout.git
cd MovieScout

2. Set Up the Backend

1. Python Environment
   Create and activate a virtual environment:

   python3 -m venv env
   source env/bin/activate  # on Windows, use `env\Scripts\activate`

2. Install Dependencies

   pip install -r requirements.txt

3. Start the Flask API
   Run the Flask application:

   export FLASK_APP=api.py
   flask run

3. Set Up the Frontend

1. Install Angular CLI (if not installed):

   npm install -g @angular/cli

2. Navigate to the ui/ Directory and install dependencies:

   cd ui
   npm install

3. Serve the Angular App:

   ng serve

   Access the app at http://localhost:4200.

4. Set Up Prometheus Monitoring

1. Install Prometheus from Prometheus Downloads.

2. Configure Prometheus
   Update prometheus.yml to include:

   - job_name: 'flask_app'
     static_configs:
       - targets: ['localhost:5000']

3. Start Prometheus:

   ./prometheus --config.file=prometheus.yml

   Access Prometheus at http://localhost:9090.

📜 License

This project is licensed under the MIT License.