Popular GitHub Repositories for Azure Ai Foundry

This sample has the full End2End process of creating RAG application with Prompty and Azure AI Foundry. It includes GPT 3.5 Turbo LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.

Open-WebUI-Functions is a collection of custom pipelines, filters, and integrations designed to enhance Open WebUI. These functions enable seamless interactions with Azure AI, N8N, and other AI models, providing dynamic request handling, preprocessing, and automation.

The LLMAgentOps Toolkit is a repository that provides a foundational structure for building LLM Agent-based applications using the Semantic Kernel. It serves as a starting point for data scientists and developers, facilitating experimentation, evaluation, and deployment of LLM Agent-based applications to production.

WhatsApp Bot built with Azure Functions, Azure AI Foundry and Azure OpenAI Whisper model, using Python.

DataSage is an AI-powered question-answering system for tabular (SQL) data, leveraging Azure AI Foundry, LangGraph, Azure SQL DB, and Streamlit. It enables users to query databases using natural language and retrieve intelligent, context-aware responses. Deployment is supported via Python and Bicep for seamless Azure resource provisioning.

使用 Azure AI Foundry 打造智能 AI 解决方案的研讨会，涵盖向量搜索、检索式增强生成 (RAG)、自主式 AI 以及结合 LangChain 和 Azure AI 搜索的多智能体协同工作。

Creating a multi turn chat bot using DeepSeek model from Azure Model Catalog. Deploying the model in Azure Cloud

Demonstrates a workflow for LLM function calling evaluation. Uses GitHub Copilot to generate synthetic eval data and Azure AI Foundry for handling results.

Deploy your own deepseek-r1 on Azure and integrate with VsCode Cline and Open WebUI etc.

Deploys Azure AI Foundry using the Azure AI Baseline Reference Architecture, following best practices for networking, security, and model integration. It provisions infrastructure for chatting over data using Azure AI Search, event-driven processing for indexing, Bicep for IaC, and testing in the Playground interface.

DeepSeek R1 on Azure AI Foundry and deploying and inferencing the model from the Microsoft Azure cloud