MovieGenie🍿🪄🎥🎞️

*** “Your wish, your movie!”🪄🎥 ***

MovieGenie is an AI-powered movie recommendation system that helps you discover your next favorite movie or show.
It currently supports Hollywood & Anime , with smart recommendations, “Surprise Me” picks, and mood-based suggestions. Future plans include adding K-Drama and expanding the dataset.

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📌 Features

• 🔎 Search & Pick: Choose a title you like from Hollywood or Anime.
• 🧠 AI Recommendations:Content-based filtering using TF-IDF and cosine similarity.
• 🎲 Surprise Me: Get a random movie/show based on your selected mood.
• 🎭 Mood-Based Picks: Action 💥, Romance ❤️, Comedy 😂, Thriller 😱, Sci-Fi 👽, Adventure 🗺️, Drama 🎭.
• 🎬 Posters & Links: Fetches posters and TMDB links dynamically using TMDB API.
• ⭐ Ratings:Displays average ratings from datasets.
• 📝 Description:Shows synopsis or combined genre/tag features.

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🌟 Wow Features

🎲 “Surprise Me” Button: Instantly discover a random movie or show based on your mood.

🧞‍♂️ AI-Powered Recommendations: Finds movies similar to your favorite picks using advanced content-based filtering.

🎭 Mood-Based Picks: Pick your mood and get suggestions tailored to it (Action 💥, Romance ❤️, Comedy 😂, etc.).

🖼️ Dynamic Posters & Links: Fetches posters and clickable TMDB URLs in real-time.

🔍 Fuzzy Search: Handles typos and close matches for smoother movie selection.

📊 Ratings & Insights: Shows average ratings and combines multiple metadata for smarter recommendations.

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🛠️ Tech Stack

-Frontend:Streamlit (Python)

• Backend / ML: Python, Pandas, NumPy, Scikit-learn

• Datasets:
  -Hollywood dataset (MovieLens: ratings, tags, movies)

  • Anime dataset (CSV curated)
  • TMDB API for posters and movie metadata

• Deployment: Streamlit Cloud / Local

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⚙️ Setup Instructions

1. Clone the repo:

git clone https://github.com/your-username/moviegenie.git cd .\project
2. Create a virtual environment: python -m venv myenv source myenv/bin/activate # Linux/Mac .\myenv\Scripts\activate # Windows

3.Install dependencies:

pip install -r requirements.txt Add your TMDB API key (optional, for posters & links) in .streamlit/secrets.toml:

TMDB_API_KEY="YOUR_API_KEY_HERE"

4.Run the app: streamlit run .\index.py

📊 Dataset Sources MovieLens (ml-latest-small): Hollywood movies, ratings, tags

Anime dataset (CSV curated): Top 10,000 anime shows

TMDB API: Posters, metadata, URLs

🚀 Future Roadmap 📺 Add K-Drama dataset for Korean dramas.

🎭 User mood profiles for better recommendations.

👤 User login & saved preferences.

🔄 Hybrid filtering: Combine content-based and collaborative filtering.

☁️ Deploy globally on Streamlit Cloud or Heroku.

🎧 Genre & mood-specific recommendations with smarter scoring.

✨ Enhanced UI/UX: Carousel posters, dark mode, and hover details.

👩‍💻 Contributors Manvi

📜 License This project is licensed under MIT License – free to use and modify.