microsoft-foundry

Microsoft Foundry Skill

This skill helps developers work with Microsoft Foundry resources, covering model discovery and deployment, RAG (Retrieval-Augmented Generation) applications, AI agent creation, evaluation workflows, and troubleshooting.

When to Use This Skill

Use this skill when the user wants to:

• Discover and deploy AI models from the Microsoft Foundry catalog
• Build RAG applications using knowledge indexes and vector search
• Create AI agents with tools like Azure AI Search, web search, or custom functions
• Evaluate agent performance using built-in evaluators
• Set up monitoring and continuous evaluation for production agents
• Troubleshoot issues with deployments, agents, or evaluations

Prerequisites

Azure Resources

• An Azure subscription with an active account
• Appropriate permissions to create Microsoft Foundry resources (e.g., Azure AI Owner role)
• Resource group for organizing Foundry resources

Tools

• Azure CLI installed and authenticated (az login)
• Azure Developer CLI (azd) for deployment workflows (optional but recommended)

Language-Specific Requirements

For SDK examples and implementation details in specific programming languages, refer to:

• Python: See language/python.md for Python SDK setup, authentication, and examples

Core Workflows

1. Getting Started - Model Discovery and Deployment

Use Case

A developer new to Microsoft Foundry wants to explore available models and deploy their first one.

Step 1: List Available Resources

First, help the user discover their Microsoft Foundry resources.

Using Azure CLI:

Bash

# List all Microsoft Foundry resources in subscription
az resource list \
  --resource-type "Microsoft.CognitiveServices/accounts" \
  --query "[?kind=='AIServices'].{Name:name, ResourceGroup:resourceGroup, Location:location}" \
  --output table

# List resources in a specific resource group
az resource list \
  --resource-group <resource-group-name> \
  --resource-type "Microsoft.CognitiveServices/accounts" \
  --output table