Movie Recommendation Generator

AI-powered movie recommendation engine with structured output validation and a clean web interface.

Features

• AI-Powered Recommendations — Natural language queries transformed into personalized movie suggestions using GPT-4o-mini
• Structured Output — Pydantic validation ensures consistent, reliable data format with title, genre, year, rating, synopsis, and cast information
• Web Interface — Clean, responsive UI for easy interaction without technical setup
• RESTful API — FastAPI backend with automatic OpenAPI documentation
• Production Ready — Containerized with Docker, deployed on Render, health monitoring included

Tech Stack

• Backend: FastAPI (Python 3.11)
• AI Model: OpenAI GPT-4o-mini
• Validation: Pydantic v2
• Deployment: Docker on Render
• Frontend: Vanilla JavaScript

Getting Started

Local Development

# Clone the repository
git clone https://github.com/davidleocadio94/pydantic-student1-project.git
cd pydantic-student1-project

# Install dependencies
pip install -r requirements.txt

# Set up environment
cp .env.example .env  # Add your OpenAI API key

# Run the application
uvicorn src.main:app --reload

Visit http://localhost:8000 to use the web interface.

Docker

# Build and run with Docker
docker build -t movie-recommender .
docker run -p 8000:8000 -e OPENAI_API_KEY=your-key-here movie-recommender

API Documentation

Interactive API documentation is available at:

• Swagger UI: /docs
• ReDoc: /redoc

Example API Request

curl -X POST "https://pydantic-student1-project.onrender.com/recommend" \
  -H "Content-Type: application/json" \
  -d '{"query": "Recommend a sci-fi movie for a relaxing weekend"}'

Example Response

{
  "title": "Arrival",
  "genre": "sci-fi",
  "year": 2016,
  "rating": 8.0,
  "synopsis": "A linguist is recruited by the military to communicate with alien lifeforms after twelve mysterious spacecraft appear around the world.",
  "director": "Denis Villeneuve",
  "lead_actor": "Amy Adams"
}

Project Structure

movie-recommender/
├── src/
│   └── main.py          # FastAPI application with endpoints and UI
├── requirements.txt      # Python dependencies
├── Dockerfile           # Container configuration
├── .env.example         # Environment template
└── README.md

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Built as part of the DeepLearning.AI Pydantic Course