An AI-driven shopping assistant that recommends products, compares prices, and finds the best deals based on user preferences. The system uses multiple AI agents to provide a seamless shopping experience.
What you'll build
An AI-driven shopping assistant that recommends products, compares prices, and finds the best deals based on user preferences. The system uses multiple AI agents to provide a seamless shopping experience. The assistant will have the following features:
Product Recommendation: Suggests products based on user preferences and history using collaborative filtering.
Price Comparison: Scrapes and compares prices from multiple e-commerce websites like Amazon, Flipkart, and BestBuy.
Review Analysis: Summarizes customer reviews and highlights pros and cons using sentiment analysis.
Discount Finder: Finds and applies discount codes from various stores using RetailMeNot API or web scraping.
User Preferences Management: Stores user data such as purchase history, preferred brands, and price range in a database.
Dashboard: A user-friendly interface built with Streamlit to display recommendations, price comparisons, and deals.
The system will be built using Python, with web scraping using Selenium and BeautifulSoup, sentiment analysis using OpenAI GPT-4, and data storage using DataStax Astra. The dashboard will provide a clean and sortable interface for users to make informed purchasing decisions.
What you'll learn
Roadmap
5 steps · tasks unfold as you work
