Fullstack RAG Application with PydanticAI, FastAPI, LanceDB and Streamlit part 3 Azure Deployment

Description

In this video, we take the next step in our RAG (Retrieval-Augmented Generation) application journey by deploying our Dockerized full stack app onto Microsoft Azure. Building on previous videos where we developed our RAG application using PydanticAI, Streamlit, FastAPI, and LanceDB, and subsequently containerized it with Docker, we now configure Azure Container Registry to store our images. We also set up Azure Container Apps for the backend and Azure Web Apps for the frontend. Follow along as we tweak our configs, troubleshoot deployment issues, and ultimately get our app live on Azure. Stay tuned for an informative session on modern cloud deployment! #rags #pydanticai #azure Previous videos Part 1 https://www.youtube.com/watch?v=KdeoPglfpb8&list=PLpHkXU1Ab_H97zR3_cMJDoUozxUvD1oqc Part 2 https://www.youtube.com/watch?v=I2PuHF6hyE0&list=PLpHkXU1Ab_H97zR3_cMJDoUozxUvD1oqc Github repo https://github.com/AIgineerAB/AI_engineering_course/tree/main/21_deploy_rag_azure 00:00 Introduction and Recap 00:39 Setting Up for Azure Deployment 01:23 Configuring Docker Containers 03:06 Building and Testing Locally 08:02 Creating Azure Container Registry 12:05 Deploying Backend to Azure 15:07 Deploying Frontend to Azure 19:07 Final Testing and Debugging 24:05 Conclusion and Wrap-Up