Brain Aboze
Aboze Brain John is a Data Scientist with extensive experience in Data Science and Analytics, Product Research, and Technical Writing, Brain has successfully executed end-to-end data analytics projects. His expertise spans data collection, exploration, transformation/wrangling, modeling, and deriving actionable business insights, providing knowledge leadership in these areas.
Brain has authored multiple articles on Artificial Intelligence and Software Engineering. His master’s dissertation at the university of Sunderland involved extensive research on Large Language Models (LLMs) and LLM agents, reflecting his deep engagement with cutting-edge AI technologies.
@AbozeBrain
Session
Docker is a game-changer for deploying AI applications, offering portable and consistent environments across platforms. In this tutorial, we’ll explore how to build and deploy a Retrieval-Augmented Generation (RAG) application using Docker. RAG applications combine data retrieval with generative AI to produce contextually relevant and accurate responses, making them powerful tools for interactive Q&A systems.
We will build a document-based Q&A application that allows users to upload files, retrieve context from them, and answer questions interactively. We will use LlamaIndex to build the RAG pipeline and use both open-source LLM from Groq and closed-source LLM, such as OpenAI models, for LLM access. This tutorial will guide you through the entire lifecycle—from building the app to deploying it using Docker on Hugging Face Spaces. Whether you’re new to Docker or experienced with RAG, this guide offers a hands-on approach to deploying scalable and efficient AI solutions.