Immersive workshop showcasing the remarkable potential of integrating SoTA foundation models to enhance product experiences and streamline backend workflows. Leverages Microsoft's Copilot stack, Semantic Kernel and Azure primitives to offer an engaging and comprehensive introduction to AI-infused app development and deployment

A sample for implementing retrieval augmented generation using Azure Open AI to generate embeddings, Azure Cosmos DB for MongoDB vCore to perform vector search, and semantic kernel.

This repository offers a solution for deploying a Generative AI (GenAI) system on Azure using Retrieval-Augmented Generation (RAG). It features a RAG Chat API integrated with CosmosDB and HTML files, enabling customer support teams to resolve issues effectively.

This project demonstrates summarizing large documents with Azure OpenAI and Durable Functions, using a Fan-out/Fan-in pattern to process sections in parallel and compile a cohesive summary. It ensures scalable and efficient document handling with Azure services.

Deploying a Retrieval-Augmented Generation (RAG) solution on Azure, featuring a RAG Chat API that uses customer data and technical HTML files to enhance customer support troubleshooting. It leverages Azure AI Search for vector storage and Azure OpenAI for model inference, ensuring security, scalability, and adherence to best practices.