CineMatch 🎬

A Content-Based Movie Recommendation System with Streamlit

Overview

CineMatch is a content-based movie recommendation system built in Python using Streamlit. It analyzes genre, keywords, and overviews to provide smart movie recommendations with plot summaries and posters (powered by OMDB API).

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Features

• Content-based recommendations (using genres, keywords, overviews)
• Visual movie wordcloud
• Modern Streamlit UI
• Movie posters and plots via OMDB API
• Modular and maintainable codebase

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Installation

1. Clone the repository:

   git clone https://github.com/Suvanwita/CineMatch.git
   cd CineMatch
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Get an OMDB API Key:

   • Request your OMDB API key at omdbapi.com/apikey.aspx
   • Add it to app.py:

     OMDB_API_KEY = "your_real_omdb_key"
     

4. Prepare your movie dataset:

   • Place movies.csv in the project root.
   • Ensure it has columns: genres, keywords, overview, title.

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Usage

streamlit run app.py

• Open the provided local URL in your browser.
• Enter a movie name and click "Find Movies".
• Review recommendations with posters and plot summaries.

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File Summary

• app.py: Streamlit user interface.
• core.py: Loads and processes data, builds similarity matrices.
• recommend.py: Finds recommended movies.
• preprocess.py: Text cleaning.
• visualize.py: Visualizes the data corpus.
• omdb_utils.py: Fetches movie details/posters from OMDB.

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Credits

• OMDB API (omdbapi.com)
• Streamlit (streamlit.io)
• scikit-learn
• Wordcloud/matplotlib (for visualization)

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Enjoy new movie discoveries! 🍿