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microsoft-foundry

Deploy AI models and build RAG applications in Microsoft Foundry.

6|3|Updated Feb 9, 2026
Search Tags:#rag#ai agents#model deployment#foundry#azure ai#azure ai search
One-click install
npx skills add https://github.com/jongio/azd-copilot --skill microsoft-foundry-jongio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: microsoft-foundry
Source: https://github.com/jongio/azd-copilot/tree/main/cli/src/internal/assets/ghcp4a-skills/microsoft-foundry
Command: npx skills add https://github.com/jongio/azd-copilot --skill microsoft-foundry-jongio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the development and deployment of advanced AI applications by leveraging Microsoft Foundry's capabilities for model management, RAG, and agent creation.

Core Features & Use Cases

  • Model Deployment: Deploy AI models from the catalog to your Azure AI Foundry resource.
  • RAG Applications: Build Retrieval-Augmented Generation applications using your own data indexed in Azure AI Search.
  • AI Agent Creation: Develop and evaluate AI agents with custom tools, web search, and function calling.
  • Use Case: A developer wants to build a customer support chatbot that can answer questions based on their company's product documentation. They can use this Skill to index their documentation, create an agent that uses Azure AI Search for retrieval, and deploy it.

Quick Start

Use the microsoft-foundry skill to deploy the gpt-4o model to your Azure AI Foundry resource.

Frequently Asked Questions about microsoft-foundry

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy AI models from a catalog to Azure AI Foundry?▼

To deploy AI models in Azure AI Foundry, you use this Skill to select models from the catalog and deploy them directly to your Azure AI Foundry resource. It supports Python SDK integration for advanced automation during model deployment.

How do I build a RAG application using Azure AI Search and my own data?▼

Building a RAG application with Azure AI Search involves indexing your own data to create knowledge indexes. This Skill facilitates the construction of Retrieval-Augmented Generation applications by integrating your indexed data for retrieval.

Can I create and evaluate AI agents with custom tools in Azure AI Foundry?▼

Yes, you can create and evaluate AI agents in Azure AI Foundry. This Skill enables developing agents equipped with custom tools, web search capabilities, and function calling, allowing you to test and evaluate their performance.

Does Azure AI Foundry support Python SDK integration for custom AI workflows?▼

Azure AI Foundry supports Python SDK integration for advanced customization and automation. This allows developers to programmatically manage model deployment, RAG application construction, and AI agent creation within their custom workflows.

What is the best way to develop a customer support chatbot using Azure AI Foundry?▼

The best way to develop a customer support chatbot in Azure AI Foundry is to index your product documentation with Azure AI Search. You then create an AI agent that uses this retrieval index to answer user questions accurately.

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