Hotel Reservation System | Llama 3 | Flask | Front End

Welcome to StayHub – an AI‑powered hotel reservation platform.

Project details:
The luxury landing page that introduces the service
The 10‑step AI chatbot that handles the complete booking
Hotel photo gallery that shows real images before you commit
Backend automation – data storage, email confirmation, and API design

REASON
Hotel booking in Pakistan is still done via phone calls or complex forms. I wanted to replace that with a single, intelligent conversation – accessible to anyone.

TECH STACK
• Frontend: HTML, CSS, Vanilla JS (responsive, animations, IntersectionObserver)
• AI Model: Llama 3.3 70B via Groq Cloud (free tier)
• Backend: Python + Flask (REST API)
• Storage: Local CSV files (hotel_bookings.csv & guest_details.csv)
• Email: Gmail SMTP with HTML confirmation emails
• Validation: phone numbers (03XX-XXXXXXX) & email regex

WORKING
- Conversational state machine with a detailed system prompt
- JSON‑only responses for reliable data extraction
- Temperature tuned to 0.35 for consistent, natural interactions
- Full conversation history sent with each request (last 20 turns)

BOOKING FLOW (10 STEPS)
1. Number of rooms & amenities
2. Stay duration & check‑in date
3. Hotel category (Luxury / Moderate / Economy)
4. City selection
5. Photo approval (with shuffle option)
6. Guest name
7. Phone (Pakistani format validated)
8. Email (validated)
9. Summary & confirmation
10. Booking saved + confirmation email sent

EMAIL CONFIRMATION
The system sends a branded HTML email with Booking ID, stay details, and next steps – all automated.

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#HotelBooking #AIchatbot #Pakistan #Flask #Python #Llama3 #Groq #FullStackDev #WebDev #MachineLearning #PromptEngineering #Automation

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