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Project Details

This project is an attempt at Theme-1 of the Appian AIgnite Hackathon, Round 3.
It is an AI-Powered Personal Shopping Assistant for E-Commerce proof-of-concept on a footwear-only dataset.

Demo Trailer

Watch on YouTube

Setup Instructions

Please use a device running Windows

Clone this repository: git clone https://github.com/Madhav-AK/AI-Shopping-Assistant/

Download the zip file in the following link (This is the dataset we trained on): https://vision.cs.utexas.edu/projects/finegrained/utzap50k/ut-zap50k-images-square.zip

Extract it and place it inside the same working directory where you cloned our repository. Create a copy of the extracted folder and place that copy in the same working directory. Rename the copy to 'shoes' If you did everything correctly, there should be 4 subfolders inside the 'ut-zap50k-images-square' folder with different kind of footwear, and a copy of that folder named 'shoes'

Run the python script shoes_init.py (This converts the shoes folder into the format we need for the app to run)

Run the python script fakeStore/dataset.py

Create a .env file and paste the following contents into it:
GEMINI_API_KEY=(insert your api key here)
SECRET_KEY=1131714638dd80d57154725d8c317937
DB_URI="sqlite:///test.db"
EMAIL=xyz@gmail.com
PASSWORD=xyz123
STRIPE_PUBLIC=pk_test_51RXG0PP9PkOnkc6Midu0uHYeERlaUiKB7I6KMChkWVIVxa7NJHxfGHZxtkAQZKGN1lGeKEZLMoA0MOvMNHZhsKYv00jd6R3Gsw
STRIPE_PRIVATE=sk_test_51RXG0PP9PkOnkc6MbJedioezSElNtO506u2rjg59THZ2ELn7bE6zvtcClfVjhJC53nyHZbPWuNqfrFOboFQW3Xvm00mQUOTLGu
ENDPOINT_SECRET=whsec_fa6637cca291e72c147ed535145a36902ba61c0bb9bb65cc831fd332f579ed48

Note that you can get a gemini api key for free at https://aistudio.google.com/app/apikey.
If there is any issue with getting Gemini running, please contact the team.
The other API keys are already directly given.

Install all the dependencies in requirements.txt

Run fakeStore/Flask-O-shop/app.py (This launches our backend website)
Parallely run app.py (This launches our AI shopping assistant app)
Ensure that both are running in parallel on different terminals on the same system

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