Trip Planner Ai – Hotel Suggestions Platform
Overview:
I developed a user-friendly web-based platform to assist travelers in planning their trips by offering personalized hotel suggestions and itinerary management. This AI-powered trip planner leverages data from multiple sources, such as OpenCage for geolocation, TripAdvisor for hotel details, and ChatGPT for generating AI-based hotel review summaries. Users can input details such as the city, specific location (neighborhood), travel dates, and budget, and the platform suggests the most suitable hotels for each day of the trip, while also providing direct links to booking platforms.
Technologies Used:
Backend: Python, Flask
Frontend: HTML, CSS, Bootstrap
APIs and Libraries: RapidAPI (TripAdvisor), OpenWeatherMap, OpenCage, Geolocation API, GPT-4 for AI responses and reviews, jQuery
Integration: Direct booking links from Hotels.com, Booking.com, Trip.com, and Agoda.com
User Experience: Real-time form validation, loading animations, and dynamic content display
Key Features:
Personalized Hotel Suggestions: Provides daily hotel recommendations based on the user’s selected city, budget, and dates. The suggestions are optimized to fit the user’s financial constraints and location preferences, including specific neighborhoods.
AI-Powered Hotel Reviews: Summarizes user reviews for each hotel using GPT-4 to provide concise and informative insights, saving users time and effort.
Budget Optimization: Users can input their total trip budget, and the platform intelligently distributes it across the length of the stay, ensuring affordable and high-quality accommodations each day.
Direct Booking Links: Each hotel suggestion includes a direct link to the relevant booking platform (e.g., Hotels.com, Booking.com, Trip.com, Agoda.com), allowing users to conveniently book their preferred accommodation with dates pre-filled.
Neighborhood-Specific Searches: Users can narrow their hotel search to specific areas within a city, ensuring proximity to attractions or specific travel requirements.
Responsive Design: A modern and intuitive interface ensures an optimal user experience across devices, from desktop to mobile.
Challenges and Learning Outcomes:
This project deepened my understanding of integrating third-party APIs, such as TripAdvisor, OpenCage, and OpenAI’s ChatGPT API, into a web application while handling dynamic user input. The challenge of providing intelligent budget distribution and accommodating variable hotel data from multiple providers helped me refine my skills in data handling and user experience design. The AI-powered hotel review summarization using GPT-4 was an exciting learning opportunity to improve the value of the hotel recommendations for users.
I also learned how to improve application responsiveness and performance by implementing smart filtering and fallback mechanisms for when initial hotel suggestions do not meet the budget constraints. Additionally, the project enhanced my experience with API integration, security best practices (e.g., handling sensitive API keys with environment variables), and building robust and user-friendly web interfaces tailored to real-world travel needs.