Movie Search with Gemini API, MongoDB Vector Search, and Streamlit UI

Description:

This project implements a movie search application that leverages the power of:

• Google Gemini API: For efficient vector embedding generation, capturing the semantic meaning of movie plots.
• MongoDB Vector Search: To retrieve movies with plots semantically similar to a user's search query.
• Streamlit: For creating a user-friendly and interactive web application.

Features:

• Users can enter a search query for movies.
• The application uses the Gemini API to generate a vector representation of the query.
• It then performs a vector search within MongoDB to find movies with similar plot embeddings.
• The user interface displays details of the retrieved movies, including title, plot summary (if available), and optionally, posters (if URLs are present in the data).

Requirements:

• Python 3.x
• Required libraries:
  • google-generativeai (for Gemini API)
  • pymongo (for MongoDB interaction)
  • streamlit (for web app development)

Installation:

1. Clone this repository.
2. Create a virtual environment (recommended):

   python -m venv env
   source env/bin/activate  # Windows: env\Scripts\activate.bat

3. Install the required libraries:

   pip install google-generativeai pymongo streamlit

Setup:

1. Configure Gemini API:
   • Obtain a Google Cloud project and enable the Gemini API.
   • Create an API key and set the environment variable GOOGLE_API_KEY accordingly.
2. Connect to MongoDB:
   • Set up a MongoDB database with a collection containing movie data. The collection should include documents with fields like title, plot (for vector search), and optionally poster (for image display).
   • Replace placeholders in connection_string.py with your MongoDB connection string and database/collection names.

Usage:

1. Run the application:

   streamlit run movie_recs.py

2. Enter a search query in the text input field and press "Enter".
3. The app will display a list of movies that semantically match your query, along with their details.