Lab Description

Organizations often need to extract insights from sensitive internal documents while maintaining strict data privacy and governance standards. Relying on external cloud based AI services can introduce risks related to data exposure and compliance. To address this, local AI solutions are becoming increasingly important for secure and controlled deployments.

This lab guides learners through building a complete Retrieval Augmented Generation (RAG) pipeline using local technologies. By integrating Ollama for local language model inference, LangChain for orchestration, and FAISS for efficient vector storage, participants will create a system capable of retrieving and answering questions from documents. The addition of a Streamlit interface allows users to interact with the application in a user-friendly manner, enabling secure, real-time document querying.

What You Will Learn

Program Curriculum

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