End-to-end Retrieval-Augmented Generation (RAG) system built for Applied AI Engineering workflows: ingest PDF textbooks, chunk + enrich metadata, embed into a vector database, evaluate retrieval quality, and ship a lightweight Gradio UI for interactive Q&A.
Live repo:
https://github.com/zainabahmed4626-lab/AIEngineeringWeek2V1Production-shaped RAG: not “call an LLM”—a full pipeline… See the full description on the dataset page:
https://huggingface.co/datasets/Zainab4626/AIEngineeringWeek2V1.
