Skip to content

ibm-developer-skills-network/wnpzo-shopping_assistant

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

"Build an AI Shopping Assistant"

This repo is part of the Guided Project Build an AI Shopping Assistant for Black Friday published on CognitiveClass.ai.

Estimated time needed: 40 minutes

In today’s world of AI and automation, user expectations for intelligent applications are at an all-time high. This project teaches you how to integrate state-of-the-art AI technologies into a real-world solution, combining APIs and language models to deliver an unparalleled user experience.

Whether you are on the hunt for some Black Friday deals or you are searching for gift ideas for your loved ones on a special occasion you can leverage generative AI to optimize your search and make the best choices.

This guided project will take you through the process of building a web application that helps users find the best deals online. Combining Flask, SerpAPI, and Granite granite-3-8b-instruct model hosted on IBM's watsonx, you’ll develop a sleek, AI-powered tool that refines user queries, fetches shopping results, compares products, and highlights deals—all in real-time.

By the end of this project you have created a web application that looks like this and uses generative AI to optimize and structure searching for your desired products online.

Alt text

As demonstrated below, the app receives the user inquiry about a particular product or a shopping aim (e.g. gift ideas for my wife) and outputs several options. Behind the scenes, the LLM summarizes the best deals, unique features, trade-offs, and generates suggestions considering the available products in the market. All in the real time!

Alt text

Learning objectives

Over the course of this project, you will:

  • Work with search engine APIs: Explore the integration of SerpAPI to retrieve real-time product data, such as prices, ratings, and reviews, for building practical applications.

  • Understand query refinement, generate structured outputs and search summarization with LLMs: Learn how to use IBM Watsonx.ai's Granite model to transform general user inputs into precise search queries.

  • Develop a Flask web application: Build a functional and straightforward web application that combines Flask, APIs, and LLMs to create a user-friendly shopping assistant.

By the end of this project, you will have:

  • A fully functional shopping assistant that refines searches, fetches products, and compares them with AI precision.
  • Hands-on experience integrating real-time APIs with advanced language models to create intelligent applications.
  • A deeper understanding of how to build practical AI-driven solutions.

Prerequisites

To successfully complete this guided project, you will need:

  • Programming knowledge: Basic familiarity with Python.

  • Web browser: Use Chrome, Edge, Firefox, or Safari for development and testing.

  • SerpAPI free API Key for querying Google searches (we’ll walk you through setting this up).

  • Cloud environment: IBM Skills Network Labs provides a pre-configured workspace with all necessary tools.

Releases

No releases published

Packages

No packages published