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Programmatically extract data and apply schemas to unstructured documents across text-based and multi-modal content using Azure AI Foundry, Azure OpenAI, Azure AI Content Understanding, and Cosmos DB.
Designed to help customers transition their SQL queries to new environments quickly and efficiently. This accelerator is particularly useful for organizations modernizing their data estates, as it simplifies the process of translating SQL queries from various dialects.
Fine-Tune End-to-End Distillation Models with Azure AI Foundry Models and Foundry Local
Azure AI Foundry - Agents related sample code
Enables solution engineers to customize, deploy, and collaborate on multi-agent AI solutions using Azure AI Foundry
A comprehensive guide for modernizing mainframe applications (IBM z/OS, Unisys, GCOS, ACOS) using Azure AI Foundry with GitHub and Azure DevOps, preserving existing investments while enabling modern DevOps and AI capabilities.
Automate front-end development: a hands-on workshop using Figma, GitHub Copilot, and Azure AI to turn designs into code quickly and consistently.
An example of calling Grounding with Bing Search in Semantic Kernel.
MCP Server that supports Azure AI Foundry image generation and editing capabilities.
Microsoft AI .NET Day 발표자료 리포지토리
Deploying Azure AI Services using Terraform
A chat bot to talk to your multiple PDFs (vectorized via text embedding models) at once; provides grounded answers to your queries to the GPT-4o powered bot
Optimize text embedding performance using Azure-native tools and models. For official guidance, support, or more detailed information, please refer to Microsoft's official documentation or contact Microsoft directly.
This repository provides an overview of Azure Machine Learning components for demonstration purposes only.
docuintel :bookmark_tabs: : Ai Document Intelligent # ai_document_intelligence # c#
genaifoundry :speech_balloon: : #gen_ai #ai_foundry #chat_playground #gpt-4 #ai_chatbot