Ayesha Siddiqui@Ayesha_Siddiqui

ChatCinema is a multifaceted Streamlit application that combines a sophisticated movie information chatbot with advanced data processing and generation capabilities. The project integrates various cutting-edge technologies to create a versatile platform for movie enthusiasts, data scientists, and AI researchers. At its core, ChatCinema features a highly interactive movie chatbot. This chatbot utilizes a CSV file ('Hydra-Movie-Scrape.csv') as its primary data source, containing a wealth of information about various movies. To enable efficient and relevant movie retrieval, the application employs the 'all-MiniLM-L6-v2' sentence transformer model to generate embeddings for movie summaries. These embeddings are then used in conjunction with cosine similarity calculations to find the most relevant movie based on user queries. The chatbot's natural language processing capabilities are powered by the Groq API, specifically using the 'llama3-8b-8192' model. This integration allows for dynamic and context-aware responses to user inquiries. When a user inputs a movie-related query, the system retrieves the most similar movie from its database and uses this information as context for generating a response. The output includes comprehensive movie details such as title, year, summary, genres, IMDB ID, YouTube trailer link, rating, movie poster URL, director, writers, and cast information. Additionally, the chatbot generates relevant dialogues or additional information about the movie using the AI model. A key feature of ChatCinema is its ability to maintain and manage chat history. The application stores conversation logs in Streamlit's session state, allowing for a continuous and contextual chat experience. Users have the option to download their chat history, which is provided as an encrypted CSV file for enhanced privacy and security.