 |
VOOZH | about |
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.
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.
A simple example implementation of the VoiceRAG pattern to power interactive voice generative AI experiences using RAG with Azure AI Search and Azure OpenAI's gpt-4o-realtime-preview model.
A creative writing multi-agent solution to help users write articles.
A TypeScript sample app for the Retrieval Augmented Generation pattern running on Azure, using Azure AI Search for retrieval and Azure OpenAI and LangChain large language models (LLMs) to power ChatGPT-style and Q&A experiences.
Build a generative AI application using LangChain.js, from local to Azure
A creative writing multi-agent solution to help users write articles using Aspire and Semantic Kernel
Learn How To Observe, Manage, and Scale, Agentic AI Apps Using Azure AI Foundry - with this hands-on workshop
This repository offers a Python framework for a retrieval-augmented generation (RAG) pipeline using text and images from MHTML documents, leveraging Azure AI and OpenAI services. It includes ingestion and enrichment flows, a RAG with Vision pipeline, and evaluation tools.
Resources for the AI Tour Talk on "Advanced Retrieval for your AI Apps and Agents" on Azure - slides, talk recording, demo recording, demo setup instructions.
Workshop for building intelligent AI solutions using Azure AI Foundry, featuring Vector Search, RAG, Agentic AI, and multi-agent orchestration with LangChain and Azure AI Search.
A simple sample UI for your Azure AI Search index. Built with React, TypeScript and Azure Static Web Apps
AZD template for deploying Azure Copilot Studio with Azure AI search
🧠 Stop building AI that forgets. Master MCP (Model Context Protocol) with production-ready semantic memory, hybrid RAG, and the WARNERCO Schematica teaching app. FastMCP + LangGraph + Vector/Graph stores. Your AI assistant's long-term memory starts here.
ASP.NET Core with Azure AI Search
Labs for agentic AI — covering Microsoft Foundry, Foundry Agent Service, Foundry Models, Workflow Designer, Foundry IQ, Foundry Tools, Foundry Control Plane and Azure AI Search
File-first memory infrastructure for AI agents, built with .NET 8 and Azure backends
a solution that simulates AI-driven contact center scenarios using synthetic data and real-time voice interaction.
This project combines Azure AI Search, Azure OpenAI Service, LangChain, React.JS, and Python FastAPI to create an intelligent system for managing Jira issues. It features advanced AI search for seamless document retrieval, a user-friendly React.JS front-end, and a robust Python FastAPI back-end.
Twilio Signal's 2025 keynote demonstration. Featuring multi-agent voice AI using Twilio, Azure Foundry, and Azure AI Search.
Add a description, image, and links to the azure-ai-search topic page so that developers can more easily learn about it.
To associate your repository with the azure-ai-search topic, visit your repo's landing page and select "manage topics."