Setting Up Azure OpenAI Resources for This Course

Welcome! 👋 This guide walks you through setting up the Azure OpenAI resources you'll need to run the samples in this course. Don't worry if you're new to Azure — we've made it as straightforward as possible. Pick the path that fits your situation and you'll be up and running in minutes.

Prerequisites

Before you start, make sure you have:

• ✅ Azure subscription — Create a free account (includes $200 in credits for 30 days)
• ✅ .NET 10 SDK or later — Download here
• ✅ Azure Developer CLI (azd) — Only needed for automated setup — Install here

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Option 1: Automated Setup (Recommended)

Best for: First-time Azure users or anyone who wants everything set up automatically.

The setup.ps1 script in the repository root handles the entire process — it deploys Azure resources, configures your models, and wires up your .NET secrets so every sample just works.

Run the script

./setup.ps1

Follow the interactive prompts

The script uses azd up under the hood, which will ask you to:

1. Sign in to your Azure account (a browser window opens)
2. Select a subscription — pick the one you'd like to use
3. Choose a region — East US 2, West US 2, and North Europe tend to have the best availability
4. Name your environment — any short name works (e.g., genai-course)

Sit back for a couple of minutes while the resources deploy. ☕

Expected output

When everything succeeds, you'll see a summary like this:

========================================
  Setup Summary:
========================================
  Secrets ID:           genai-beginners-dotnet
  Chat Deployment:      gpt-5-mini
  Embedding Deployment: text-embedding-3-small
  Endpoint:             https://openai-genai-course-abc123.openai.azure.com/
========================================

Setup complete. Navigate to a sample folder and run:
  dotnet run app.cs

Verify it works

cd samples/CoreSamples/BasicChat-01MEAI
dotnet run app.cs

If you see the AI respond, you're all set! 🎉

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Option 2: I Already Have Azure OpenAI Resources

Best for: Users who already have gpt-5-mini and/or text-embedding-3-small deployed in their Azure subscription.

You don't need to deploy anything new — just tell the samples where your resources are. There are two ways to do this.

Using the setup-secrets script

The quickest approach. From the repository root, run:

./setup-secrets.ps1 -Endpoint "https://my-resource.openai.azure.com/"

That's it! The script defaults to gpt-5-mini and text-embedding-3-small as deployment names.

Parameters:

Parameter	Required	Default	Description
-Endpoint	✅ Yes	—	Your Azure OpenAI endpoint URL
-Deployment	No	gpt-5-mini	Your chat model deployment name
-EmbeddingDeployment	No	text-embedding-3-small	Your embedding model deployment name

If your deployment names are different from the defaults:

./setup-secrets.ps1 -Endpoint "https://my-resource.openai.azure.com/" -Deployment "my-gpt-model" -EmbeddingDeployment "my-embedding-model"

Using dotnet user-secrets directly

If you prefer setting things manually:

dotnet user-secrets set --id genai-beginners-dotnet "AzureOpenAI:Endpoint" "https://my-resource.openai.azure.com/"
dotnet user-secrets set --id genai-beginners-dotnet "AzureOpenAI:Deployment" "gpt-5-mini"
dotnet user-secrets set --id genai-beginners-dotnet "AzureOpenAI:EmbeddingDeployment" "text-embedding-3-small"

💡 Tip: All samples share the same User Secrets ID (genai-beginners-dotnet), so you only configure once and every sample picks up the values automatically.

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Option 3: Manual Deployment in Microsoft Foundry

Best for: Users who want to understand the Azure resources or need custom configuration.

Step 1: Create an Azure AI Foundry Hub

1. Go to Microsoft Azure AI Foundry Portal
2. Sign in with your Azure account
3. Click + New project
4. Give it a name (e.g., genai-beginners)
5. Select a Hub (create a new one if needed)
   • Region: Choose one close to you (East US 2, West US 2, North Europe recommended)
6. Click Create

Step 2: Deploy the Chat Model (gpt-5-mini)

1. Inside your project, go to Models + endpoints in the left sidebar
2. Click Deploy model → Deploy base model
3. Search for and select gpt-5-mini
4. Set the Deployment name to gpt-5-mini (keep it simple — this matches the course defaults)
5. Click Deploy

Step 3: Deploy the Embedding Model (text-embedding-3-small)

📝 Note: This is only needed for RAG and semantic search samples. You can skip this step if you only want to run chat samples.

1. Go to Models + endpoints again
2. Click Deploy model → Deploy base model
3. Search for and select text-embedding-3-small
4. Set the Deployment name to text-embedding-3-small
5. Click Deploy

Step 4: Get Your Credentials

You need three values from the portal:

1. Endpoint — Found on the project Overview page or Models + endpoints page
   • Looks like: https://your-resource-name.openai.azure.com/
2. Chat Deployment Name — The name you gave in Step 2 (e.g., gpt-5-mini)
3. Embedding Deployment Name — The name you gave in Step 3 (e.g., text-embedding-3-small)

💡 Tip: You do NOT need an API key if you're using DefaultAzureCredential (which is what most samples use). If a sample requires an API key, it will be mentioned in that sample's README.

Step 5: Configure Your Environment

Run the setup-secrets script with your values:

./setup-secrets.ps1 -Endpoint "https://your-resource-name.openai.azure.com/"

Or set secrets manually (see Option 2 above).

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Verify Your Setup

After any option, verify everything works:

# Check your secrets are set
dotnet user-secrets list --id genai-beginners-dotnet

# Run a sample
cd samples/CoreSamples/BasicChat-01MEAI
dotnet run app.cs

You should see your three secrets listed (AzureOpenAI:Endpoint, AzureOpenAI:Deployment, AzureOpenAI:EmbeddingDeployment) and the sample should start chatting with the AI.

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Additional Secrets for Specialized Samples

Some samples require extra configuration beyond the core Azure OpenAI setup. Each sample's README specifies exactly what's needed, but here's a quick reference:

Sample Type	Additional Secrets	Used By
AI Foundry Agents	AIFoundry:Endpoint, AIFoundry:TenantId	Agent framework samples
RAG / Search	AzureAISearch:Endpoint, AzureAISearch:Key	Semantic search samples
Audio / Speech	AzureSpeech:Key, AzureSpeech:Region	Voice and transcription

# Example: Setting AI Foundry secrets
dotnet user-secrets set --id genai-beginners-dotnet "AIFoundry:Endpoint" "https://your-project.ai.azure.com/"
dotnet user-secrets set --id genai-beginners-dotnet "AIFoundry:TenantId" "your-tenant-id"

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Resource Cleanup

When you're done with the course, remove Azure resources to avoid charges:

./cleanup.ps1

This deletes all Azure resources and clears your local secrets.

Manual Cleanup

If the script doesn't work:

azd down --purge --force
dotnet user-secrets clear --id genai-beginners-dotnet
Remove-Item -Path ".azure" -Recurse -Force

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🔍 Want to Know More? How the Scripts Work

What setup.ps1 does under the hood

The setup script automates these steps:

1. Checks prerequisites — Verifies azd and dotnet are installed
2. Deploys Azure infrastructure — Runs azd up, which uses Bicep templates (infra/main.bicep) to create:
   • An Azure OpenAI Service (Cognitive Services account, S0 tier)
   • A gpt-5-mini model deployment (GlobalStandard SKU, 10K tokens-per-minute)
   • A text-embedding-3-small model deployment (Standard SKU, 10K tokens-per-minute)
3. Extracts the endpoint — Reads the deployed endpoint from azd env get-values
4. Configures .NET User Secrets — Sets AzureOpenAI:Endpoint, AzureOpenAI:Deployment, and AzureOpenAI:EmbeddingDeployment under the shared secrets ID genai-beginners-dotnet
5. Detects your tenant — If Azure CLI is installed, reminds you to az login --tenant <id> for token-based auth

All samples share the same User Secrets ID (genai-beginners-dotnet), so you configure once and every sample picks up the values automatically.

What cleanup.ps1 does under the hood

1. Deletes Azure resources — Runs azd down --purge --force to remove all deployed resources and purge soft-deleted resources
2. Removes local state — Deletes the .azure/ folder (azd environment config)
3. Clears secrets — Runs dotnet user-secrets clear --id genai-beginners-dotnet

What setup-secrets.ps1 does under the hood

This is a simpler script for users who already have Azure resources:

1. Takes your endpoint (required), deployment name (defaults to gpt-5-mini), and embedding deployment name (defaults to text-embedding-3-small) as parameters
2. Runs dotnet user-secrets set for each value using the shared ID genai-beginners-dotnet
3. Prints a summary of what was configured
4. Shows additional secrets you might need for specialized samples

The infrastructure (Bicep templates)

The infra/ folder contains Azure Bicep templates that define what gets deployed:

• main.bicep — Orchestrator that creates a resource group and deploys the modules
• modules/cognitive-services.bicep — Azure OpenAI account (S0 tier)
• modules/model-deployment-chat.bicep — gpt-5-mini deployment (version 2025-08-07, GlobalStandard SKU)
• modules/model-deployment-embedding.bicep — text-embedding-3-small deployment (version 1, Standard SKU)

You can customize these templates before running setup.ps1 — for example, to change the model, region, or capacity.

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Troubleshooting

"azd up" fails with a subscription error

az account set --subscription "<subscription-id>"

Then re-run ./setup.ps1.

Region not available or models not available in your region

Azure OpenAI models are not available in all regions. Check the official model availability page to see which models are available in your region. Try East US 2, West US 2, or North Europe if your region doesn't have the models you need.

If no Azure regions work for you: Use Ollama for local model execution instead — it runs AI models on your machine without requiring Azure resources.

Quota exceeded (429 errors)

Wait a few minutes for rate limits to reset, or request a quota increase in the Azure Portal.

User secrets not found

dotnet user-secrets list --id genai-beginners-dotnet

If empty, re-run setup or set secrets manually.

PowerShell execution policy error

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

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