/Sell_IT

Full Stack Application to buy and Sell product build with ML and Chat system to make product search and User interaction easier .Interactive user interface for better experience .Used firebase as database for fast connectivty

Primary LanguageJavaScript

Welcome to the SellIt App

The SellIt App is a full-stack web application built using JavaScript, React, and Firebase. This app provides a platform for users to sell their old products and connects buyers and sellers through an integrated chat system. Additionally, the application utilizes machine learning to offer product recommendations to users.

Features

  1. Sell Old Products: Users can easily list their old products for sale on the platform. They can provide product descriptions, images, and set their desired price.

  2. Buyer-Seller Chat: The app includes a real-time chat system that enables buyers and sellers to communicate with each other directly. This feature enhances the user experience by facilitating seamless communication during the buying and selling process.

  3. Machine Learning Product Recommendations: The OldProductSeller App utilizes machine learning algorithms to analyze user behavior and preferences. Based on this data, the app generates personalized product recommendations for each user, making it easier for them to discover products of interest.

Installation

To set up and run the OldProductSeller App locally, follow these steps:

  1. Clone the repository from GitHub

  2. Navigate to the project directory: cd old-product-seller-app

  3. Install the required dependencies: npm install

  4. Create a Firebase project and set up the necessary configuration for authentication and database connectivity.

  5. Modify Firebase.config

ML model

  1. Unspervised Text classification model : Text classification model to test and train dataset .Classified based on features most related to given product.

  2. Run .ipynb : Run ipynb file in jupiter notebook save pickle file

  3. Fast API : Test and run ML model Using Fast API

  4. Run Server : To access API run server in localhost using uvicorn

Video

Demo Video Click me

APPLICATION DISPLAY 👀

Screenshot 2023-08-04 110525 Screenshot 2023-08-05 145726 Screenshot 2023-08-05 145554