Movie Recommender using Gemini Pro

Introduction

Welcome to the Movie Recommender using Gemini Pro! This project leverages the power of Gemini Pro's language model to provide personalized movie recommendations based on user queries. The integration with Streamlit makes it user-friendly and interactive.

How it works

The application fetches data from a CSV file, utilizing both Google's Gemini Pro (LLM) and Langchain Agents to handle user queries. The CSV agent employs a range of tools to analyze questions and produce fitting responses, with assistance from the LLM.

To enhance user interaction, the application employs Streamlit to create an intuitive graphical interface (GUI) and depends on Langchain for seamless communication with the LLM.

Installation

To run the Movie Recommender, follow these steps:

1. Install the required dependencies by running the following command:

   pip install -r requirements.txt

   Additionally, obtain a Google's API key and add it to the .env file.

Usage

Run the application by executing the main.py file using the Streamlit CLI. Ensure that Streamlit is installed before running the application. Use the following command in your terminal:

 streamlit run main.py

Contributing

Contributions and improvements to the code are welcome! If you find any issues or have suggestions for enhancements, feel free to open an issue or submit a pull request.