AI Chatbot Platform
LLM Deployment & Conversation Infrastructure
The AI Chatbot Platform is a modular infrastructure project that decouples conversation management from LLM provider implementation — allowing any language model deployed on Hugging Face Spaces to power the chat experience without architectural changes. The separation of concerns design means switching from one model to another requires only a configuration change, not a code rewrite.
Conversation state is persisted in Supabase PostgreSQL with a structured schema tracking sessions, message history, user preferences, and model metadata. The database schema evolved through v1-v4 migrations with zero-downtime strategies, demonstrating production database management practices. Hugging Face Spaces provides scalable GPU-backed LLM inference without the operational overhead of self-hosted GPU infrastructure.
This project was built as a reusable infrastructure layer — the same conversation management, session handling, and storage patterns can be composed with any domain-specific chatbot application. The modular architecture reflects a platform engineering mindset: build the infrastructure once, deploy many chat applications on top.
Key Highlights
- Hugging Face Spaces deployment for scalable LLM inference
- Supabase PostgreSQL for persistent conversation history and user sessions
- v1-v4 schema migration system for zero-downtime database evolution
- Modular architecture separating chatbot logic from LLM provider