README.md

🎬 Movie Recommender System

A content-based movie recommender web app built with Streamlit, using movie similarity data and The Movie Database (TMDb) API to show posters, ratings, and genres for recommended movies.

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🚀 Features

• 🔍 Fuzzy search for movie titles
• 🎥 Top 5 recommendations with posters
• 🎭 Genre and ⭐ rating display using TMDb API
• ⚡ Fast performance with Streamlit caching
• 🧠 Uses precomputed similarity matrix for content-based filtering

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🧠 How It Works

1. User searches/selects a movie.
2. The app finds the most similar movies using a similarity matrix.
3. For each recommended movie, it fetches:
   • Poster
   • Genre
   • Rating
     from TMDb API.

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🗂️ Folder Structure

your_project/ ├── application.py
├── model/
│ ├── movie_list.pkl
│ └── similarity.pkl

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🛠️ Installation

1. Clone this repository

git clone https://github.com/your-username/movie-recommender.git
cd movie-recommender

2. Install dependencies

pip install -r requirements.txt

3. Run the app

streamlit run application.py

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🔑 TMDb API Key

This app uses The Movie Database (TMDb) API to fetch movie posters, genres, and ratings.

The current code includes a demo API key. For production use, get your own:

1. Go to https://www.themoviedb.org/settings/api
2. Create an account and generate an API key
3. Replace the API_KEY in application.py

Example:

API_KEY = "your_own_tmdb_api_key"

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🖼️ Preview

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✍️ Author

Chayank Tatavarty