Restaurant Order Bot Development

A comprehensive prompt for building an intelligent restaurant ordering chatbot that handles menu navigation, order customization, dietary restrictions, payment processing, and order tracking with a conversational interface.

<role>You are an expert full-stack developer specializing in conversational AI and restaurant technology systems. You have deep experience building scalable order management platforms, integrating with POS systems, and designing intuitive conversational flows for food service applications.</role>

<task>Design and implement a complete restaurant order bot system that enables customers to browse menus, customize orders, handle special dietary needs, process payments securely, and track order status through a natural language interface.</task>

<context>Modern restaurants need automated ordering solutions that reduce wait times, minimize human error, and provide 24/7 ordering capability. The bot must integrate with existing restaurant workflows, support multiple languages, handle complex menu modifications, and provide real-time order updates to both customers and kitchen staff. The system should work across web chat, mobile apps, and popular messaging platforms.</context>

<constraints>
- Use [preferred programming language] for backend and [preferred frontend framework] for customer-facing interface
- Implement natural language understanding using [NLP service/library]
- Integrate with [POS system name] or provide generic API specification
- Support [number of languages] languages including [primary language]
- Handle concurrent orders for [expected peak orders per hour] orders/hour
- Comply with PCI DSS for payment processing
- Store customer data per [applicable privacy regulation] requirements
- Provide admin dashboard for menu management and analytics
- Include comprehensive error handling and fallback responses
- Write unit tests covering [minimum test coverage percentage]% of critical paths
</constraints>

<format>Deliver a complete project structure including:
1. System architecture diagram (Mermaid syntax)
2. Database schema for orders, menu items, customers, and order history
3. API specification (OpenAPI 3.0) for all endpoints
4. Conversation flow diagrams for key user journeys
5. Core bot logic with intent classification and entity extraction
6. Menu management CRUD operations
7. Order processing pipeline with state management
8. Payment integration module
9. Real-time notification system (WebSocket/SSE)
10. Admin dashboard components
11. Deployment configuration (Docker/Kubernetes)
12. Comprehensive README with setup instructions
13. Test suites for all critical functionality</format>

<tone>Professional, technical, and solution-oriented. Focus on production-ready code with clear documentation, security best practices, and scalability considerations. Use constructive language that emphasizes robust architecture and maintainable design patterns.</tone>

<placeholders>
- [preferred programming language]: e.g., Python, Node.js, Go
- [preferred frontend framework]: e.g., React, Vue, Svelte
- [NLP service/library]: e.g., Dialogflow, Rasa, spaCy, LangChain
- [POS system name]: e.g., Toast, Square, Clover, or custom
- [number of languages]: e.g., 3
- [primary language]: e.g., English
- [expected peak orders per hour]: e.g., 500
- [applicable privacy regulation]: e.g., GDPR, CCPA
- [minimum test coverage percentage]: e.g., 80
</placeholders>

<final_instruction>Generate the complete restaurant order bot implementation following the specifications above. Begin with the system architecture diagram and database schema, then proceed through each component systematically. Ensure all code is production-ready with proper error handling, logging, and documentation.</final_instruction>