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.
This repository contains code, resources, and documentation for the workshop "Building a Multi-Agent Workforce with Azure AI Foundry".
This demo project contains the CineWave frontend portal and two backend APIs for business logic and AI agent connection.
This sample has the full End2End process of creating RAG application with Prompty and Azure AI Foundry. It includes GPT-4 LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.
Demo app using Azure AI Speech and Language Services
Convert long plain-text files into speech using the Azure AI Speech service.
A very comprehensive network security using Pi-hole, Azure Artificial Intelligence, and Quantum Concepts simulations
Workshop for LLM agents
This project is a multimodal, voice-enabled assistant designed for the civil engineering domain. It uses Azure AI services and a Retrieval-Augmented Generation (RAG) pipeline, all integrated into a simple web interface.
Azure Functions and Azure AI Service (Computer Vision/Face Service) together to extract faces from images.
This repository is the official companion for the Azure AI Foundry Agent Service Webinar Series. It provides hands-on code samples, modular use cases, and practical guides for building, deploying, and scaling AI agents on Azure.
The first phase of this project aims to deliver an evolving, experimental low-cost, rapid deployment customer service chatbot for a local astronomical society, featuring Grounding LLM (e.g. RAG), embedding, Agentic AI, function calling to external service.
Comprehensive and beginner-friendly course on Azure AI Models!
This project demonstrates how to use the Azure AI Language Service—specifically, the Language Detection feature—to identify the language of any input text in real time. The app is built with ASP.NET Core Razor Pages and integrates directly with Azure AI Language Services for accurate and scalable language detection.
This project demonstrates how to use Azure AI's Text Analytics API to perform natural language processing tasks such as language detection, sentiment analysis, key phrase extraction, and entity recognition on text documents.
Passo a passo da atividade Azure Cognitive Search: Utilizando AI Search para indexação e consulta de Dados da plataforma Dio.
Lab da plataforma DIO sobre Azure Speech Studio e o Language Studio, explorando habilidades em análise de fala e linguagem no Microsoft Azure.
"Introducing 📄🚀 DocuNexus AGI, your intelligent document and media workflow agent powered by Azure and the advanced Phi-4 model. Experience AI-driven insights, automated media tasks, and boosted.
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