Intelligent Assistant Bot (2024-2025)

• Role: Project Lead & Core Developer
• Status: Completed / Legacy
• Difficulty: Intermediate
• Impact: Reduced moderator workload by 60%

The Challenge

As UAIS grew to over 700 members, administrative overhead became a bottleneck. Executives were spending hours manually syncing Google Calendar events with Discord announcements, tracking RSVPs, and answering repetitive technical questions. We needed a solution that could automate the boring stuff (like that python book!) so we could focus on AI.

The Solution

We built a multifunctional Discord bot using discord.py that served as the central nervous system for the club’s operations.

Key Features

1. Automated Event Orchestration:
   • Deep integration with the Google Calendar API.
   • Automatically fetched upcoming events and generated formatted Discord announcements with RSVP buttons, creating and assigning custom roles for said events.
   • Sent automated reminders to specific roles (e.g., “Event Attendee”) 1 hour before start time.
2. RAG-Based Technical Support:
   • We integrated a Retrieval-Augmented Generation (RAG) pipeline using GPT-4o.
   • The bot could ingest club documentation and resources to answer technical queries from members instantly, reducing the support load on executives.
3. Community Engagement:
   • Included gamification features like AI-themed trivia and quizzes to keep the server active between events.

Technical Architecture

• Language: Python 3.10+
• Framework: discord.py (Asynchronous)
• AI Engine: OpenAI GPT-4o with vector-based context retrieval
• Integrations: Google Workspace APIs (Calendar, Sheets), SQLite for RSVP tracking.

Skills Gained

• Advanced Python: Architecting large-scale, asynchronous applications using discord.py.
• LLM Integration: Implementing Retrieval-Augmented Generation (RAG) pipelines to connect GPT-4o with internal club documentation.
• API Orchestration: Authenticating and syncing data between Discord, Google Calendar, and Google Sheets APIs.
• Product Management: Identifying user pain points in a community of 700+ and iteratively building solutions to solve them.

This project laid the technical foundation for the club’s future software initiatives, proving that we could build internal tools to solve our own problems.