A modern multi-agent AI concierge system that provides seamless hotel services through natural conversation.
- 🤖 Multi-Agent System - Specialized agents for concierge, room service, and maintenance
- 💬 Natural Conversation - Human-like interactions powered by GPT-4
- 🔍 Smart Web Search - Integrated SerpAPI for real-time information
- 🌐 Website Content Access - Crawl4AI integration for rich web content
- 📝 Context Awareness - Maintains conversation history for better assistance
- 📊 Usage Monitoring - Built-in tracking and limits
Our multi-agent system consists of specialized AI agents, each with unique capabilities:
graph TD
U[User Request] --> S[Sofia - Supervisor]
S --> C[Michael - Concierge]
S --> R[Room Service]
S --> M[Alex - Maintenance]
C --> S
R --> S
M --> S
S --> U
The system operates through a coordinated hierarchy:
- Supervisor Agent (Sofia) analyzes requests and delegates to specialists
- Concierge Agent (Michael) handles local information and arrangements
- Room Service Agent manages all food and beverage requests
- Maintenance Agent (Alex) coordinates room-related services
Each agent is powered by GPT-4 and equipped with specialized tools for their domain. The supervisor ensures seamless coordination and maintains conversation context across all interactions.
- Role: Hotel Concierge Manager with 15 years of luxury hospitality experience
- Responsibilities:
- Analyzes and routes guest requests to specialized agents
- Coordinates responses from multiple agents
- Maintains conversation context and history
- Ensures consistent service quality
- Role: Knowledgeable local expert and guest experience specialist
- Capabilities:
- Local recommendations and information
- Real-time web searches via SerpAPI
- Website content retrieval with Crawl4AI
- Transportation and activity arrangements
- Event bookings and reservations
- Role: Food and beverage specialist
- Features:
- Full menu access and availability checking
- Special dietary requirements handling
- Meal customization and modifications
- Service timing coordination
- Hours: 24/7 with specialized menus for:
- Breakfast (6:00 AM - 11:00 AM)
- All-day dining (11:00 AM - 10:00 PM)
- Late night (10:00 PM - 6:00 AM)
- Role: Maintenance and Housekeeping Specialist
- Services:
- Room supplies and amenities
- Climate control management
- Housekeeping requests
- Basic repairs and maintenance
- Response Times:
- Room Supplies: 5-10 minutes
- Climate Control: 10-15 minutes
- Housekeeping: 20-30 minutes
- Basic Repairs: 30-45 minutes
- Clone and set up:
git clone <repository-url>
cd hotel-service-coordinator
cp .env.example .env- Add your API keys to
.env:
OPENAI_API_KEY=your-key-here
SERPAPI_API_KEY=your-key-here- Run with Docker:
docker compose up --buildVisit http://localhost:8000 to start using your AI concierge!
- Set up environment:
# Create conda environment
conda create -n hotel-coordinator python=3.11 -y
conda activate hotel-coordinator
# Install dependencies
pip install poetry
poetry install- Run the application:
poetry run chainlit run src/app.pysrc/
├── agents/ # Specialized AI agents
│ ├── concierge_agent.py # Local recommendations & info
│ ├── room_service_agent.py # Food & beverage orders
│ ├── maintenance_agent.py # Room services & maintenance
│ ├── supervisor_agent.py # Request coordination
│ └── tools/ # Shared agent tools
├── models/ # Data models & types
└── app.py # Main Chainlit application
The project uses modern Python tools:
- Poetry - Dependency management
- Black - Code formatting
- Ruff - Fast linting
- MyPy - Static type checking
Run development tools:
poetry run black .
poetry run ruff check .
poetry run mypy .Required API keys (add to .env):
OPENAI_API_KEY- OpenAI API key for GPT-4SERPAPI_API_KEY- SerpAPI key for web searches
- Agent System - Details on the multi-agent architecture
- API Integration - Guide to the external API integrations
- Development Guide - Setting up for development
Contributions are welcome! Please check our Contributing Guidelines.
This project is MIT licensed.
