CRS Web

AIFinal Year Project

A web-based conversational recommender system that uses AI to recommend movies in natural conversation.

Final Year Project

CRS Web

A conversational movie recommender — chat with an AI to discover your next favorite film.

CRS Web is a web-based conversational recommender system that allows an AI to recommend movies in a short conversation based on user preferences. Built as my Final Year Project during 2022–2023.

How It Works

The system combines a React frontend with a Python Flask backend and a modified version of CRSLab — an open-source toolkit for building conversational recommender systems. Users can chat naturally with the AI, which understands preferences and suggests movies with poster images fetched via Google Search API.

Screenshots

Conversational movie recommendations

Key screens showing the chat interface, search, and recommendation flow.

Chat interface — natural language conversation with the recommendation engine

English conversation — responsive chat with movie suggestions and rich media cards

Chinese conversation — full Chinese language support with localized recommendations

Login page — secure authentication with form validation and error handling

Registration page — new user sign-up with profile setup and preference selection

Features

Key Features

What makes this recommender system unique.

🤖

AI Conversational Recommender

Natural language conversation with an AI that learns your movie preferences through dialogue — not just filters and checkboxes.

🌐

Bilingual Support

Full English and Chinese language support, from the chat interface to movie recommendations and UI labels.

🎬

Movie Poster Display

Automatically fetches and displays movie posters based on keywords using Google Custom Search API.

👤

User Accounts

Simple login and registration system that saves conversation history so users can revisit past recommendations.

💬

Conversation Management

Create new conversations or browse past ones — each session is saved with its full context and recommendations.

🐳

Dockerized MySQL

Database runs in a Docker container for easy setup and consistent development environments across machines.

Built With

Tech Stack

The full technology stack powering CRS Web.

React

Tailwind CSS

Flowbite

Python Flask

MySQL

Docker

CRSLab

Google Search API

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Learn More

Explore the Project

Check out the code, architecture, and conversation examples on GitHub.

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