Montreal Explorer

Inspiration

As university students in Montreal, we were inspired by the city's complexity and the challenges of discovering its hidden gems. Our shared experiences navigating Montreal's diverse neighborhoods revealed a need for a more intelligent, personalized travel guide. Recognizing the potential of AI to transform travel planning, we developed a GPT-powered platform that provides accurate, tailored travel information, making exploration of Montreal more accessible and engaging for both locals and visitors.

What it does

Our GPT-powered platform provides intelligent, personalized travel recommendations for Montreal. It leverages AI to generate customized itineraries, suggest local attractions, restaurants, and hidden gems, and offer real-time, contextually relevant travel advice. Users receive tailored suggestions based on their preferences, interests, and travel style, transforming trip planning into a seamless, intuitive experience.

How we built it

Frontend: We developed Montreal Explorer using React.js, creating an interactive and responsive user interface. The application features modular components for pages like "Discover Montreal" and "About Us", enabling easy customization and scalability. Tailored CSS styling captures Montreal's vibrant cultural essence.
Backend: Built with Python and Flask, the backend powers core application features, processing AI-driven recommendations and managing user interactions through efficient API endpoints.
Data Infrastructure: We curated Montreal's Hotels, events, and hidden gems through web scraping(Apify) and cleaning Quebec Data Partnership csv establishing a robust data foundation that supports our personalized recommendation engine.

Challenges we ran into

We first encountered challenges with Git collaboration, especially managing pushes and pulls, which caused some script loss in the beginning. We then adapted to use branches and merging systematically, which saved us a lot of trouble and made collaboration much easier.
Frontend-Backend Integration: Ensuring smooth communication between the React.js frontend and Flask backend posed challenges, especially when handling dynamic content and real-time updates.

Accomplishments that we're proud of

We’re incredibly proud of our teamwork and collaboration, especially since, for most of us, this was our first full-stack and web project. Starting with little to no experience, we learned frontend and backend development from scratch, overcoming challenges and building a functional, aesthetic website. Seeing the website come together gave us a huge sense of accomplishment.

We also learned to use APIs for the backend, implement web scraping, and manage the project with Git. This project not only strengthened our technical skills but also taught us the value of persistence and teamwork.

What we learned

Through this project, we learned the basics of building a full-stack application, from creating a user-friendly frontend with React to developing a functional backend with Flask. We also gained experience with web scraping, API integration, RAG development, and managing version control with Git.

On top of the technical skills, we learned the importance of teamwork and effective communication. Starting with little experience, we discovered how to divide tasks, solve problems collaboratively, and adapt to challenges as they arose. This project was a valuable learning experience that pushed us to grow both technically and as a team.

What's next for Montreal Explorer

We plan to evolve Montreal Explorer into World Explorer, expanding its reach to cities worldwide. Along with this, we aim to integrate features like real-time event updates, personalized notifications, and multi-language support to make the platform accessible to a global audience. By enhancing the recommendation engine with user reviews and feedback, we aspire to create the ultimate go-to platform for discovering the best experiences anywhere in the world. PLACEHOLDER (ignore video)