Optivize - Business Management Platform

Introduction

Optivize is a business management platform that helps small businesses organize their inventory and predict product success. It's built with Jekyll for the website and Python for the backend, demonstrating full-stack web development skills.
This project was created for Computer Science coursework to showcase web development, database management, and basic AI integration.

Key Features

• Product Success Predictor: Upload business data to train an AI that predicts if products will succeed
• Inventory Manager: Organize products into groups, track quantities, search and sort everything
• Google Sheets Import: Connect your Google Sheets to automatically import inventory data
• Low Stock Alerts: Set up notifications when you're running low on items
• Search Everything: Find any product or group instantly as you type

How It Works

• Frontend: Website built with Jekyll that users interact with
• Backend: Python server that handles data and AI predictions
• Database: Stores all the inventory and user data
• External Services: Connects to Google Sheets and Zapier for extra features

Quick Start

What You Need

• Computer with Ubuntu/WSL or Mac
• Git installed
• Python installed

Setup Instructions

# Get the code
git clone https://github.com/ZafeerA123/optivize_frontend.git
git clone https://github.com/ZafeerA123/optivize_backend.git

# Start the website
cd optivize_frontend
make

# Start the server (in another terminal)
cd optivize_backend
python main.py

View the Project

• Website: Open http://127.0.0.1:4887/optivize_frontend/
• Live Version: https://optivize.opencodingsociety.com/

Project Files

Frontend (Website)

├── navigation/
│   ├── productprediction.md    # AI prediction page
│   ├── flashcards.md          # Inventory management page
│   └── about.md               # About page
├── assets/js/                 # JavaScript files
├── _config.yml               # Website settings
└── index.md                  # Homepage

Backend (Server)

├── main.py                   # Main server file
├── api/                      # API endpoints
├── models/                   # Database setup
└── requirements.txt          # Python packages needed

Main Features Explained

1. AI Product Predictor (productprediction.md)

• Users enter product details (name, price, marketing score, etc.)
• AI gives a success score from 0–100
• Shows business advice like "your price is too high"
• Users can train the AI with their own data

2. Inventory Manager (flashcards.md)

• Create groups to organize products (like "Electronics", "Clothing")
• Add items to each group with quantities and descriptions
• Search through everything instantly
• Sort by name, quantity, or date

3. Google Sheets Import

• Connect your Google account safely
• Import inventory data from your existing spreadsheets
• Automatically converts sheet data into our format

4. Smart Alerts

• Set up notifications when inventory gets low
• Works with Zapier to send emails or texts
• No more running out of stock unexpectedly

Development Commands

Frontend (Website)

• make – Start the website
• make stop – Stop the website
• make clean – Reset everything

Backend (Server)

• python main.py – Start the server
• python -m pytest – Run tests (if any)

File Organization

Adding New Pages

• Create a new .md file in the navigation/ folder
• Add it to _config.yml under header_pages:
• Write your content in markdown

Database Structure

• Groups: Store inventory categories
• Items: Store individual products with quantities
• Users: Store user accounts and settings
• Predictions: Store AI prediction history

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📅 Calendar

• The calendar helps businesses visualize important events like:

  • Product launches
  • Restock dates
  • Prediction runs
  • Inventory reviews

• Implemented with a lightweight JS library integrated into calendar.md

• Pulls events from the backend based on prediction & inventory history

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🌐 Frontend Integration

• Real-time API integration using JS fetch() to communicate with Flask backend

• Fully dynamic updates for:

  • Inventory changes
  • Prediction results
  • Calendar entries

• Frontend is modular:

  • productprediction.md: Hooks into /api/predict
  • flashcards.md: Fetches and manages inventory via /api/items and /api/groups
  • calendar.md: Loads events from /api/calendar