source/README.md

metadata

title: Transportation AI System
emoji: 🚚
colorFrom: blue
colorTo: green
sdk: docker
pinned: false
license: mit

An AI-powered system to predict optimal transportation modes for logistics and supply chain management, deployable via Docker.

Quick Start with Docker

Option 1: Frontend Only (Gradio UI)

# Build and run frontend only
docker build -t transportation-ai .
docker run -p 7860:7860 transportation-ai

Option 2: Backend + Frontend (Recommended)

# Run both services with docker-compose
docker-compose up -d

Option 3: All-in-one Container

# Run both services in single container
docker-compose --profile all-in-one up

Development Setup

Local Development

# Install dependencies
pip install -r requirements.txt

# Start backend API
python -m src.main

# Start frontend (in another terminal)
python app.py

Windows Users

# Use the batch script
start.bat

Linux/Mac Users

# Use the shell script
chmod +x start.sh
./start.sh

Features

Transportation Prediction

• Predict optimal shipping methods (Air, Air Charter, Ocean, Truck)
• Display confidence scores and alternatives
• Interactive probability distribution charts
• Automatic weight and cost estimation

AI Chat Assistant

• Chat about transportation and logistics
• Get insights on shipping methods
• Compare different transportation modes
• Cost analysis and optimization tips

How to Use

1. Prediction Tab: Enter shipment details to get AI recommendations
2. Chat Tab: Ask questions about transportation and logistics

Docker Services

Backend API (Port 3454)

• FastAPI server với prediction endpoints
• Loads models from Hugging Face
• REST API documentation tại /docs

Frontend UI (Port 7860)

• Gradio interface
• Real-time streaming chat
• Interactive prediction forms

Technical Details

• Model: XGBoost trained on logistics data từ Hugging Face
• Input Features: Project code, country, price, vendor, weight, etc.
• Output: Transportation mode with confidence score
• Framework: FastAPI + Gradio + scikit-learn + XGBoost
• Deployment: Docker + Docker Compose

Sample Questions for Chat

• "Compare Air vs Ocean transportation"
• "What affects shipping costs?"
• "When should I use truck transport?"
• "Optimize logistics for my company"

Configuration

Environment Variables

GEMINI_API_KEY=your_gemini_api_key
ACCESS=your_huggingface_token
API_BASE_URL=http://localhost:3454/api

Docker Compose Services

• backend: FastAPI server (port 3454)
• frontend: Gradio UI (port 7860)
• app: All-in-one service (both ports)

API Endpoints

• GET / - API status
• POST /api/predict-transportation - Prediction
• GET /api/transportation-options - Available options
• POST /api/chat - AI chat (streaming)

Built with Docker, FastAPI, Gradio and XGBoost