Inventory System

📦 Project Overview

The Inventory System is a web-based solution designed to efficiently manage and track inventory. It offers various features for monitoring products, updating stock levels, and automating basic inventory-related tasks. The project is containerized using Docker, making deployment across different environments simple and quick.

Demo 🤖

Screencast.from.16-10-24.01.29.35.AM.IST.webm

🚀 Features

• Track Products: Manage product details, including SKU, quantity, price, and more.
• Stock Updates: Automatically update stock levels when products are added or removed.
• Customizable According to Your Data: You can retrain the model by adding your inventory historical data in csv format according to sample file.
• Analytics and Reports: Generate detailed analytics and reports on stock levels, sales, and purchases.
• Docker Support: Easily deploy the system using Docker.

📂 Project Structure

├── client/                     # Frontend source code
├── model/                      # Random forest Model
├── server/                     # Backend API and server code
├── .gitignore                  # Files and directories to be ignored by Git
├── docker-compose.yml          # Docker Compose file for multi-container setup
├── makefile                    # Automation tasks for building and running the project
├── bulk_upload.py              # Generate random Product Data
├── test_data_generator.py      # Generate random test historical inventory data
└── README.md                   # Project documentation

🛠️ Installation

Prerequisites

• Docker: Make sure Docker is installed and running on your machine.
• Download the random_forest_model.pkl file: This is required for sales prediction. You can download it from the following Kaggle link. Place the file in the model directory of the project before proceeding.

Steps

1. Clone the repository:

   git clone https://github.com/CulturalProfessor/inventory-system.git
   cd inventory-system

2. Build and run the Docker container:

   make build
   # or alternatively
   docker-compose up --build

3. Access the system:

   Once the containers are up and running, open your browser and navigate to:

   http://localhost:5137
   

   This will allow you to access the inventory management dashboard.