UET GPT

University information lives scattered across dozens of pages, PDFs, and notice boards: students waste hours hunting for answers about admissions, fees, and courses.

UET GPT is a ChatGPT-style assistant built specifically for University of Engineering and Technology students. Ask it a question and it answers using up-to-date university information collected by its own crawler, instead of making things up. Live at uet-gpt.vercel.app.

The full production stack: a Next.js frontend, a Convex backend using its Agent, RAG, and Workflow components, sign-in with Clerk, rate limiting with Upstash Redis, and error monitoring with Sentry. A separate Python crawler (Crawl4AI) collects university content and feeds it into the knowledge base. Answers are routed across three LLM providers (Groq, Google Gemini, and Cerebras) so the app stays fast and available even when one provider is down or rate-limited.

My most complete system to date: auth, rate limiting, observability, automated testing (Playwright + Vitest), and a data-ingestion pipeline.

The hardest lesson: retrieval quality beats model quality. Most wrong answers trace back to bad chunking or stale crawls, not the LLM, so the crawler and index deserve as much engineering as the chat loop.