Virtual Warehousing Management System

A comprehensive warehouse management system featuring an AI-powered virtual assistant for intelligent warehouse operations, inventory management, and forecasting.

Overview

This full-stack application combines modern web technologies with AI capabilities to provide:

• Real-time inventory management and tracking
• AI-powered conversational chatbot for warehouse queries
• Product expiration monitoring and alerts
• Consumption and stock forecasting using machine learning
• Interactive dashboard with data visualizations
• RESTful API for warehouse operations

Architecture

Backend

• Framework: FastAPI
• Database: PostgreSQL with SQLAlchemy ORM
• AI/LLM: LangChain + OpenAI (Meta Llama 4 Maverick via LiteLLM)
• ML Models: LightGBM, Scikit-learn for forecasting
• Scheduler: APScheduler for automated tasks
• Testing: Pytest with HTML reports

Frontend

• Framework: React 19 with TypeScript
• UI Library: Material-UI (MUI)
• Routing: React Router v7
• Charts: Recharts for data visualization
• Build Tool: Vite
• Testing: Vitest (unit) + Playwright (E2E)

Features

Warehouse Management

• Product inventory tracking with batch management
• Order processing and order details management
• Stock movement history and audit trail
• Supplier management
• Low stock alerts and expiring product notifications

AI Virtual Assistant

• Natural language query processing
• SQL query generation from user questions
• Conversational interface with context retention
• Automatic conversation cleanup
• Session management

Forecasting & Analytics

• Product consumption forecasting
• Stock level predictions
• ML model training and validation scripts
• Interactive dashboard with visual analytics

Database Management

• Automated database seeding
• Data validation scripts
• View management for complex queries
• Clean and seed utilities

Getting Started

Prerequisites

• Docker & Docker Compose
• Node.js (for local development)
• Python 3.11+ (for local development)

Environment Setup

1. Clone the repository

git clone <repository-url>
cd Virtual-Warehousing

2. Backend Configuration

Create a .env file in the backend/ directory:

DATABASE_URL=postgresql://user:password@host:port/dbname
DATABASE_URL_DEV=postgresql://user:password@localhost:5432/dbname
LITELLM_KEY=your_litellm_api_key
CORS_ALLOWED=http://localhost:3000,http://localhost:3030

3. Frontend Configuration

Create a .env file in the frontend/ directory:

VITE_API_URL=http://localhost:8080/api

For production deployment, update VITE_API_URL to point to your backend server:

VITE_API_URL=https://your-backend-domain.com/api

Note: When using Docker Compose, the VITE_API_URL is automatically set via the VITE_API_URL_ARG build argument in the docker-compose.yaml file.

Running with Docker

Production Mode (Remote Backend)

docker-compose up backend frontend

• Backend: http://localhost:8080
• Frontend: http://localhost:3000

Local Development Mode

docker-compose up backend frontend-local

• Backend: http://localhost:8080
• Frontend: http://localhost:3030

Local Development (Without Docker)

Backend

cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8080

Frontend

cd frontend
npm install
npm run dev

API Documentation

Once the backend is running, access the interactive API documentation:

• Swagger UI: http://localhost:8080/docs
• ReDoc: http://localhost:8080/redoc

📄 License

This project is licensed under the MIT License.