







FindFest: Integrated Cultural Event Exploration Platform for Seoul
FindFest is a web service that consolidates scattered festival and event information from across Seoul into a single platform, allowing users to explore the city as if they were on a guided journey.
Problem Definition: Addressed the difficulty of searching for events due to fragmented information across various channels (district offices, SNS, etc.), the lack of personalized management systems, and poor user experiences.
Solution: Built an integrated platform providing city-wide data by incorporating an AI chatbot, user authentication, and a "Save/Favorite" feature.
Target Audience: Primarily targeting young adults in their 20s and 30s with high demand for cultural activities, social gatherings, and extracurricular experiences.
Service Architecture
Frontend: Utilized Next.js (App Router) and TypeScript to ensure fast loading speeds and data type stability.
Backend: Developed with FastAPI and SQLAlchemy; managed relational data and vector embeddings using PostgreSQL and pgvector.
AI: Implemented advanced search and chatbot functionalities using Upstage’s Solar LLM and embedding models.
Deployment: Deployed on Amazon EC2 using Docker Compose for container orchestration.
Key Features
Data Pipeline: Periodically collects the latest information via the Seoul Open Data Plaza API, performing de-duplication and vector embedding before storing it in the database.
AI Chatbot: Utilizes a LangGraph-based workflow to analyze user intent (general conversation, recommendations, date-based searches, etc.) to provide intelligent responses.
Personalization System: Implemented JWT-based authentication for secure login, allowing users to "save" events and manage them on a dedicated profile page.
Dynamic Filtering: Provides a UI that allows users to instantly explore events through categories, date pickers (calendar), and keyword searches.
Collaboration Tools: Followed a GitHub branch strategy with PR-based (Pull Request) code reviews; managed schedules and meeting minutes via Notion.
Key Results: Successfully integrated over 4,200 event data points and built a high-fidelity MVP (Minimum Viable Product) featuring both AI-driven interaction and personalized user management.
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Yonsei University
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