UAJY Builds RAG Chatbot for 2025/26 Academic Handbook Using FAISS and Gemini

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A public repository has released a Streamlit-based RAG chatbot designed to answer queries about the 2025/2026 academic handbook of Universitas Atma Jaya Yogyakarta's Faculty of Industrial Technology. The system uses pdfplumber to extract text and tables, chunks them into 350 segments from 112 pages, and stores 3,072-dimensional embeddings in a local FAISS index for similarity search. At query time, retrieved context and conversation history are sent to Google Gemini 2.5 Flash, which returns answers cited with page numbers and section titles. A similarity threshold and a system-level refusal instruction serve as anti-hallucination controls, limiting responses strictly to retrieved PDF content. An included 20-question evaluation suite reports 100% retrieval recall and refusal accuracy, though the project's own disclaimer notes the chatbot is an educational tool and does not carry official academic authority.

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