🎬 End-to-End Movie Recommendation System

An end-to-end Movie Recommendation System built with FastAPI, Scikit-learn, and Streamlit that recommends movies based on user input using NLP and machine learning. The system fetches live movie metadata from TMDB API and serves predictions through a REST API and a web UI.

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🚀 Features

• 🎥 Content-based movie recommendation
• 🧠 NLP using TF-IDF Vectorization
• ⚡ FastAPI backend for recommendations
• 🌐 Streamlit frontend interface
• 🔑 Live movie data from TMDB API
• 🧪 Pre-trained ML model with persistence
• 🔐 Environment variable support using .env

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🛠 Tech Stack

Layer	Technology
Backend API	FastAPI, Uvicorn
ML	Scikit-learn, NumPy, SciPy
NLP	TF-IDF
Frontend	Streamlit
Data	Pandas
External API	TMDB API

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📂 Project Structure

End-to-End Movie Recommendation System/
│
├── main.py # FastAPI backend
├── app.py # Streamlit frontend
├── model.pkl # Trained ML model
├── vectorizer.pkl # TF-IDF vectorizer
├── vectorizer.pkl # TF-IDF vectorizer
├── requirements.txt
└── README.md

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⚙️ Setup Instructions

1️⃣ Clone the repository

git clone <repo-url>
cd End-to-End Movie Recommendation System

2️⃣ Create and activate virtual environment

py -3.11 -m venv .venv
.venv\Scripts\Activate.ps1

3️⃣ Install dependencies

pip install -r requirements.txt

4️⃣ Create .env file

Create a file named .env in the project root:

TMDB_API_KEY=your_tmdb_api_key_here

5️⃣ Run the FastAPI server

python -m uvicorn main:app --reload


Visit: http://127.0.0.1:8000

6️⃣ Run the Streamlit frontend

streamlit run app.py

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🔑 How to Get TMDB API Key

• Go to https://www.themoviedb.org
• Create an account → Settings → API
• Generate an API key (v3 auth)

🧪 Example API Response
{
  "recommendations": [
    "Inception",
    "Interstellar",
    "The Matrix"
  ]
}

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⚠️ Notes

• Make sure scikit-learn version matches the one used for training the model.
• Do not commit .env file to GitHub.
• Use Python 3.11 for best compatibility.

📌 Future Improvements

• Collaborative filtering support
• User authentication
• Recommendation history
• Cloud deployment

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👨‍💻 Author

Suyash Singh

• GitHub: https://github.com/suyXcode
• Portfolio: https://suyxcode.netlify.app