Price Pilot

An intelligent multi-agent system for e-commerce operations, featuring AI-powered chat, inventory management, order processing, logistics tracking, demand forecasting, and product recommendations.

Architecture

Price Pilot consists of specialized AI agents that work together to handle different aspects of e-commerce operations:

• ChatAgent: Natural language interface and task delegation
• InventoryAgent: Stock level monitoring and management
• OrderAgent: Order processing and ERP integration
• LogisticsAgent: Shipment tracking with Aramex and Naqel carriers
• ForecastAgent: Demand prediction using ARIMA models
• RecommendAgent: AI-powered product recommendations

Quick Start

Prerequisites

• Python 3.12+
• Node.js 16+
• Docker & Docker Compose

Environment Setup

# Copy environment template
cp .env.example .env

# Edit .env with your configurations

Using Docker (Recommended)

Option 1: Pre-built Images

# Pull from Docker Hub
docker pull mozaloom/price-pilot-backend
docker pull mozaloom/price-pilot-frontend

# Or pull from GitHub Container Registry
docker pull ghcr.io/medgan-ai/price-pilot-backend:latest
docker pull ghcr.io/medgan-ai/price-pilot-frontend:latest

# Start all services
docker compose up -d

Option 2: Build from Source

# Start all services (builds images locally)
docker compose up -d --build

# Access the application
# Frontend: http://localhost:5173
# Backend API: http://localhost:8000

Manual Setup

Backend

cd backend
pip install -r requirements.txt
python main.py

Frontend

cd frontend
npm install
npm run dev

Project Structure

price-pilot/
├── backend/           # Python FastAPI backend
│   ├── src/agents/   # AI agent implementations
│   ├── src/core/     # Base classes and utilities
│   ├── src/graphs/   # Agent orchestration logic
│   └── models/       # ML models and data
├── frontend/         # React frontend application
├── infra/            # Infrastructure and deployment
└── sql/              # Database schemas

Key Features

• Multi-Agent AI System: Specialized agents for different business functions
• Real-time Chat Interface: Natural language interaction with the system
• Inventory Management: Automated stock monitoring and alerts
• Order Processing: Seamless ERP integration and order fulfillment
• Logistics Tracking: Real-time shipment monitoring across multiple carriers
• Demand Forecasting: ML-powered sales prediction using ARIMA models
• Smart Recommendations: AI-driven product suggestion engine
• Vector Search: Embedding-based product discovery

Technology Stack

Backend:

• Python 3.12 with FastAPI
• LangChain for AI agent orchestration
• Supabase for database and real-time features
• MLflow for model management
• SQLite for local caching

Frontend:

• React with modern JavaScript
• Real-time UI updates
• Responsive design

Infrastructure:

• Docker containerization
• Docker Compose for local development
• Modular deployment architecture

Monitoring & Logging

• Application logs in backend/app.log
• Shipment monitoring database
• LangChain caching for performance optimization

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests: make test
5. Submit a pull request

License

This project is licensed under the terms specified in the LICENSE file.

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