AI-Powered Travel Intelligence Engine (Full Project + Source Code)

Description

✈️ Smart Travel Planner – AI-Powered Travel Itinerary Generator (Full Project + Source Code)

A full-stack web application that transforms travel planning through artificial intelligence, real-time data integration, and modern web technologies.

Architecture & Technical Implementation

Backend Stack (/backend/)

# Core Framework & Dependencies
FastAPI = "Modern, high-performance web framework"
SQLModel = "SQL database integration & ORM"
Uvicorn = "ASGI server for development"
Gunicorn = "Production WSGI server"

Key Components Coded:

1. AI Itinerary Engine (main.py)

• Integrated Google Gemini API for intelligent plan generation
• Dynamic prompt engineering for personalized recommendations
• Context-aware itinerary structuring

2. Real-Time Data Services

• Weather Integration: OpenWeatherMap API with natural language processing
• Event Discovery: SerpApi integration for local events
• Content Enrichment: Unsplash API for high-quality images

3. RESTful API Endpoints

• POST /generate-itinerary/ – Core itinerary generation
• GET /weather/{city}/ – Real-time weather data
• GET /events/{city}/ – Local event discovery

Frontend Stack (/frontend/)

<!-- Technology Stack Implemented -->
HTML5 = "Semantic structure & accessibility"
CSS3 + Bootstrap 5 = "Responsive, mobile-first design"
JavaScript ES6+ = "Dynamic client-side functionality"

🎨 Frontend Features Coded:

1. Professional UI/UX

• Hero section with engaging call-to-action
• Multi-page navigation (Home, Generator, About)
• Mobile-responsive design using Bootstrap 5

2. Dynamic Content Rendering

• Real-time form handling and validation
• AJAX API integration with backend
• Dynamic itinerary display with images and maps

3. User Experience Enhancements

• Loading states and error handling
• Smooth animations and transitions
• Professional typography (Google Fonts)

Technical Implementation Details

Database Schema

# SQLModel Classes Implemented
class Itinerary(SQLModel):
    id: Optional[int] = Field(default=None, primary_key=True)
    city: str
    date: str
    preferences: str
    generated_plan: str
    weather_data: str
    created_at: datetime

API Integration Flow

1. User Input → Frontend form collection
2. Data Validation → Client-side and server-side checks
3. External API Calls → Parallel requests to weather, events, images
4. AI Processing → Gemini API with structured prompts
5. Response Assembly → Combined data with enriched content
6. Frontend Rendering → Dynamic display with interactive elements

Third-Party APIs Integrated

Service	Purpose	Implementation
Google Gemini AI	Intelligent itinerary generation	Custom prompt engineering
SerpApi	Local events & weather data	Real-time data scraping
Unsplash API	High-quality destination images	Dynamic image embedding
OpenWeatherMap	Detailed weather reports	Weather-aware planning
Google Maps	Location links & directions	Direct mapping integration

Deployment Configuration

Backend Setup (run.bat, requirements.txt)

# Production Configuration
Render.com Web Service
Python 3.11+ environment
Gunicorn with Uvicorn workers
Environment variable management

Frontend Deployment

# Static Site Hosting
Render.com Static Site
CDN-enabled asset delivery
Cross-origin resource sharing (CORS)
API endpoint configuration

Key Technical Achievements

✅ Decoupled Architecture – Scalable backend-frontend separation
✅ Real-Time Data Integration – Multiple API synchronization
✅ AI-Prompt Engineering – Context-aware itinerary generation
✅ Mobile-First Responsive Design – Bootstrap 5 implementation
✅ Production-Ready Deployment – Render.com cloud hosting
✅ RESTful API Design – Clean, documented endpoints with Swagger UI

Code-Ready Future Enhancements

# Planned Technical Extensions
1. User Authentication System
2. PostgreSQL migration for production
3. Redis caching for performance
4. Flask/Django REST framework alternative
5. React/Vue.js frontend rewrite
6. Docker containerization
7. CI/CD pipeline with GitHub Actions

Performance Metrics

• Backend Response Time: < 2 seconds for full itinerary generation
• Frontend Load Time: < 3 seconds on average connections
• API Success Rate: 95%+ with comprehensive error handling
• Mobile Compatibility: 100% responsive across devices