Azure Samples
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- A Solution Accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.
- A blueprint for getting a React web app with a Node.js API and a MongoDB database onto Azure. The blueprint includes sample application code (a ToDo web app) which can be removed and replaced with your own application code. Add your own source code and leverage the Infrastructure as Code assets (written in Bicep) to get up and running quickly.
- This repository provides a playground to safely experiment with and learn Azure API Management (APIM) policies in various architectures.
- A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
azd-functions-sharepoint-webhooks
Public templateazd template that deploys an Azure function app to create webhooks on your SharePoint Online tenant- Automated pipeline for generating, verifying, and preparing high-quality function calling datasets for model fine-tuning. Reduces manual annotation through multi-stage validation and conversion to training formats. Built for Azure ML with permissive license models (Phi3.5 MoE, Phi4 etc).
- APIM ❤️ AI - This repo contains experiments on Azure API Management's AI capabilities, integrating with Azure OpenAI, AI Foundry, and much more 🚀 . New workshop experience at https://aka.ms/ai-gateway/workshop
openai-mcp-agent-dotnet
PublicSample to create an AI Agent using OpenAI models with any MCP server running on Azure Container Apps- Samples on how to use SQL Server and Azure SQL with .NET Aspire
- This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments
- Facilitates creating modular specialized agents that coordinate across diverse data types and tools like M365 and Teams to assist multi-disciplinary healthcare workflows—such as cancer care.