/ShopGPT

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🛍️ ShopGPT 🛍️

An AI-revamped shopping experience

A LLM-assisted Amazon shopping assistant that simplifies reviewing online feedback, helping to analyze product summaries and gain better insight to advise on Amazon purchases.

🌐 Motivation

Reviews play a central role in the path to purchase, and many consumers don’t just skim them before purchasing or passing on a product. 53% of users within the age group 18-34 read Amazon review for more than 10 minutes before deciding to buy a product. It is also useful to compare products in terms of user reviews side-by-side to appreciate their strengths, weaknesses and other related issues, as well as, interpret reviews based on personalized requirements.

📕 System Architecture

A high-level design for the proposed system is presented below:

HLD

Key Components:

Our key components all use the OpenAI API, with GPT3.5-turbo as a base model for AI-driven predictions.

  • Prompt Classifier : Classifies whether the user wants a summary, comparison or recommendation. Internal backend component.

  • Review Summarizer : Summarizes multiple reviews in JSON format and returns structured product review summaries. An example is shown below:

    summarization-gif.gif

  • Product Comparisons: Performs structured comparison across pairs of products. An example is shown below:

    comparison.gif

  • Personalized Product Recommendations: Given a user input, generates product recommendations by comparison of summaries guided by the user's requirements. An example is shown below:

    reco.gif

  • Keyword Extraction: Extract keywords from the summarized reviews and allow to filter the summary according to a keyword. An example is shown below:

    keywords.gif

🚀 Technology Stack:

  • Frontend:
  • GPT 3.5 API:
  • Database:

🗄️ Dataset Used and Data Storage

We use the Amazon Review Dataset Provided by UCSD (2018) with 233.1 million reviews. The dataset contains reviews in the range May 1996 - Oct 2018. We host a subset of this dataset in JSON format, along with associated metadata on MongoDB Atlas.

✍️ Instructions to Run

  • Clone the repository: git clone https://github.com/VijayrajS/ShopGPT
  • Create a Python virtual environment: If you do not have Python virtualenv installed, please run the following command to install virtualenv:

pip install virtualenv or pip3 install virtualenv or,

python3 -m pip install virtualenv

Setup the virtualenv by running the following commands:

python3 -m virtualenv .shopgpt_env
source .shopgpt_env/bin/activate
  • Install necessary Python packages: pip install -r requirements.txt
  • Set up your own OpenAI API key: Follow instructions from OpenAI API docs. Update your API key in line3 of GPTGateway.py.
  • Download the dataset from UCSD Amazon Reviews Dataset
  • Host your Database: Host the downloaded dataset on MongoDB Atlas. Update your MongoDB Atlas URI in line10 of DataSource.py.
  • Run the App Locally: Run python UI_v0.py

Demo (YouTube)

hurriCARE