Inspiration
We were drawn to this project by the opportunity to build a custom travel recommender system. Designing and implementing our own recommendation pipeline. From gathering user preferences to delivering personalized trip suggestions, it felt both innovative and directly applicable to real-world group travel planning.
What it does
Our solution combines three key components:
User Preference Collection We prompt travelers with open-ended questions about their interests and priorities.
Large-Language-Model Generation Using Google’s Gemini API, we translate those open responses into structured travel profiles and generate candidate travel locations.
Flight-Cost Integration Leveraging the Skyscanner Flights API, we fetch real-time airfare estimates from each participant’s origin to the proposed destinations. The result is a ranked list of trips that balance personal interests with budget considerations.
Challenges we ran into
Frontend Development Building a responsive user interface with JavaScript and Node.js pushed us outside our comfort zone.
Backend Integration Seamlessly connecting our Python-based recommendation engine and FastAPI endpoints to a Node.js frontend required careful handling of asynchronous data flows and cross-language communication.
Accomplishments that we're proud of
Delivered an end-to-end prototype in the allotted timeframe, featuring:
Dynamic, LLM-driven travel location generation
- A polished interactive frontend
Successfully blended multiple technologies: LLMs, third-party APIs, FastAPI, and a JavaScript/Node.js UI into a coherent user experience.
What we learned
Gained experience regarding Python services from a Node.js application.
Prompt Engineering: Refined techniques for extracting meaningful preferences via LLM prompting.
Log in or sign up for Devpost to join the conversation.