ChatCinema: A Conversational Movie Recommendation System Overview ChatCinema is a conversational movie recommendation system that uses natural language processing and machine learning to provide personalized movie suggestions based on user input. The system is built using Streamlit, a Python library for building web applications, and leverages the power of Groq, a vector database, to store and retrieve movie embeddings. You can check here : https://chat-cinema.streamlit.app/
Features Conversational interface for users to input movie names or descriptions Personalized movie recommendations based on user input Ability to download chat history and encrypted dataset Decryption tool for encrypted dataset Generation of new dataset using AI models Getting Started To run the application, simply execute the following command in your terminal:
Verify
Open In Editor Edit Copy code streamlit run app.py This will launch the application in your default web browser.
Tabs The application consists of four tabs:
Chatbot: Interact with the conversational movie recommendation system. Download Chat History: Download your chat history in an encrypted CSV file. Decryption: Decrypt an encrypted CSV file or text using a provided key. Generate Dataset: Generate a new dataset using AI models and download it in an encrypted ZIP file. Technical Requirements Python 3.8 or later Streamlit 1.10 or later Groq 1.3 or later SentenceTransformers 2.2 or later scikit-learn 1.0 or later NumPy 1.20 or later Cryptography 3.4 or later Torch 1.10 or later Transformers 4.12 or later License This project is licensed under the MIT License. See LICENSE for details.
Acknowledgments This project was built using the following open-source libraries and frameworks:
Streamlit Groq SentenceTransformers scikit-learn NumPy Cryptography Torch Transformers We would like to thank the maintainers and contributors of these projects for their hard work and dedication.