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Semantic-Search

Semantic Search for Movies

This project implements a semantic search system for a movie database using MongoDB Atlas and sentence transformers. It allows for both vector-based semantic search and traditional text-based search on movie plots and titles.

Features

  • Connect to MongoDB Atlas cluster
  • Generate embeddings for movie plots using the 'all-MiniLM-L6-v2' model
  • Create a vector search index in MongoDB
  • Perform vector-based semantic search on movie plots
  • Perform text-based search on movie titles and plots
  • Compare results from both search methods

Prerequisites

  • Python 3.9+
  • MongoDB Atlas account with a cluster set up
  • pymongo library
  • sentence_transformers library

Setup

  1. Clone this repository:

    git clone <repository-url>
cd <repository-directory>

  2. Install the required packages:

    pip install pymongo sentence_transformers

  3. Set up your MongoDB Atlas cluster and obtain the connection string.

  4. Replace the MONGO_URI in the script with your MongoDB Atlas connection string.

Usage

Run the script with:

python semanticsearch.py

The script will:

  1. Connect to your MongoDB Atlas cluster
  2. Create a vector search index (if it doesn't exist)
  3. Perform searches using predefined queries
  4. Display results from both vector-based and text-based searches

Configuration

  • Modify the queries list in the main() function to change the search queries.
  • Adjust the limit parameter in vector_search_movies() and text_search_movies() to change the number of results returned.

Notes

  • The script assumes that movie plot embeddings have already been generated and stored in the database. If you need to generate embeddings, uncomment the add_embeddings_to_movies() function call in main().
  • The vector search index creation is commented out by default. Uncomment the create_vector_index() function call in main() if you need to create the index.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available under the MIT License.