mindsync
fastapi · qdrant · next.js — rag document q&a delivered over whatsapp, with an admin dashboard and cited answers
the problem
Campus regulations, schedules and announcements live in PDFs that nobody reads, so students ask staff the same questions over and over. The answers already exist in writing — they are just not reachable from where students actually are.
what i built
Administrators upload the official documents, including scans, which are OCR'd, chunked and embedded into Qdrant. Students then ask questions in plain language over WhatsApp and get an answer with a citation back to the source document, so nothing is invented. The admin dashboard covers document management and categorisation, usage analytics, an editable system prompt, and a RAG playground for testing retrieval before it reaches students. The WhatsApp side runs through self-hosted WAHA with typing indicators and rate limiting. LiteLLM sits in front of the model layer so providers can be swapped without touching the retrieval code.
stack
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