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Build and deploy AI applications on Azure AI Foundry using Microsoft's model catalog and AI services
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models/deploy-model/preset/EXAMPLES.md
1# Examples: preset23## Example 1: Fast Path — Current Region Has Capacity45**Scenario:** Deploy gpt-4o to project in East US, which has capacity.6**Result:** Deployed in ~45s. No region selection needed. 100K TPM default, GlobalStandard SKU.78## Example 2: Alternative Region — No Capacity in Current Region910**Scenario:** Deploy gpt-4-turbo to dev project in West US 2 (no capacity).11**Result:** Queried all regions → user selected East US 2 (120K available) → deployed in ~2 min.1213## Example 3: Create New Project in Optimal Region1415**Scenario:** Deploy gpt-4o-mini in Europe for data residency; no existing European project.16**Result:** Created AI Services hub + project in Sweden Central → deployed in ~4 min with 150K TPM.1718## Example 4: Insufficient Quota Everywhere1920**Scenario:** Deploy gpt-4 but all regions have exhausted quota.21**Result:** Graceful failure with actionable guidance:221. Request quota increase via the [quota skill](../../../quota/quota.md)232. List existing deployments consuming quota243. Suggest alternative models (gpt-4o, gpt-4o-mini)2526## Example 5: First-Time User — No Project2728**Scenario:** Deploy gpt-4o with no existing AI Foundry project.29**Result:** Full onboarding in ~5 min — created resource group, AI Services hub, project, then deployed.3031## Example 6: Deployment Name Conflict3233**Scenario:** Auto-generated deployment name already exists.34**Result:** Appended random hex suffix (e.g., `-7b9e`) and retried automatically.3536## Example 7: Multi-Version Model Selection3738**Scenario:** Deploy "latest gpt-4o" when multiple versions exist.39**Result:** Latest stable version auto-selected. Capacity aggregated across versions.4041## Example 8: Anthropic Model (claude-sonnet-4-6)4243**Scenario:** Deploy claude-sonnet-4-6 (Anthropic model requiring modelProviderData).44**Result:** User prompted for industry selection → tenant country code and org name fetched automatically → deployed via ARM REST API with `modelProviderData` payload in ~2 min. Capacity set to 1 (MaaS billing).4546---4748## Summary of Scenarios4950| Scenario | Duration | Key Features |51|----------|----------|--------------|52| **1: Fast Path** | ~45s | Current region has capacity, direct deploy |53| **2: Alt Region** | ~2m | Region selection, project switch |54| **3: New Project** | ~4m | Project creation in optimal region |55| **4: No Quota** | N/A | Graceful failure, actionable guidance |56| **5: First-Time** | ~5m | Complete onboarding |57| **6: Name Conflict** | ~1m | Auto-retry with suffix |58| **7: Multi-Version** | ~1m | Latest version auto-selected |59| **8: Anthropic** | ~2m | Industry prompt, tenant info, REST API deploy |6061## Common Patterns6263```64A: Quick Deploy Auth → Get Project → Check Region (✓) → Deploy65B: Region Select Auth → Get Project → Region (✗) → Query All → Select → Deploy66C: Full Onboarding Auth → No Projects → Create Project → Deploy67D: Error Recovery Deploy (✗) → Analyze → Fix → Retry68```69