customize

# Customize Model Deployment

Interactive guided workflow for deploying Azure OpenAI models with full customization control over version, SKU, capacity, content filtering, and advanced options.

## Quick Reference

| Property           | Description                                                    |
| ------------------ | -------------------------------------------------------------- |
| **Flow**           | Interactive step-by-step guided deployment                     |
| **Customization**  | Version, SKU, Capacity, RAI Policy, Advanced Options           |
| **SKU Support**    | GlobalStandard, Standard, ProvisionedManaged, DataZoneStandard |
| **Best For**       | Precise control over deployment configuration                  |
| **Authentication** | Azure CLI (`az login`)                                         |
| **Tools**          | Azure CLI, MCP tools (optional)                                |

## When to Use This Skill

Use this skill when you need **precise control** over deployment configuration:

- ✅ **Choose specific model version** (not just latest)
- ✅ **Select deployment SKU** (GlobalStandard vs Standard vs PTU)
- ✅ **Set exact capacity** within available range
- ✅ **Configure content filtering** (RAI policy selection)
- ✅ **Enable advanced features** (dynamic quota, priority processing, spillover)
- ✅ **PTU deployments** (Provisioned Throughput Units)

**Alternative:** Use `preset` for quick deployment to the best available region with automatic configuration.

### Comparison: customize vs preset

| Feature               | customize                                                      | preset                                     |
| --------------------- | -------------------------------------------------------------- | ------------------------------------------ |
| **Focus**             | Full customization control                                     | Optimal region selection                   |
| **Version Selection** | User chooses from available                                    | Uses latest automatically                  |
| **SKU Selection**     | User chooses (GlobalStandard/Standard/PTU)                     | GlobalStandard only                        |
| **Capacity**          | User specifies exact value                                     | Auto-calculated (50% of available)         |
| **RAI Policy**        | User selects from options                                      | Default policy only                        |
| **Region**            | Current region first, falls back to all regions if no capacity | Checks capacity across all regions upfront |
| **Use Case**          | Precise deployment requirements                                | Quick deployment to best region            |

## Prerequisites

- Azure subscription with Cognitive Services Contributor or Owner role
- Azure AI Foundry project resource ID (format: `/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project}`)
- Azure CLI installed and authenticated (`az login`)
- Optional: Set `PROJECT_RESOURCE_ID` environment variable

## Workflow Overview

### Complete Flow (14 Phases)

```
1. Verify Authentication
2. Get Project Resource ID
3. Verify Project Exists
4. Get Model Name (if not provided)
5. List Model Versions → User Selects
6. List SKUs for Version → User Selects
7. Get Capacity Range → User Configures
   7b. If no capacity: Cross-Region Fallback → Query all regions → User selects region/project
8. List RAI Policies → User Selects
9. Configure Advanced Options (if applicable)
10. Configure Version Upgrade Policy
11. Generate Deployment Name
12. Review Configuration
13. Execute Deployment & Monitor
```

### Fast Path (Defaults)

If user accepts all defaults (latest version, GlobalStandard SKU, recommended capacity, default RAI policy, standard upgrade policy), deployment completes in ~5 interactions.

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## Phase Summaries

> ⚠️ **MUST READ:** Before executing any phase, load [references/customize-workflow.md](references/customize-workflow.md) for the full scripts and implementation details. The summaries below describe _what_ each phase does — the reference file contains the _how_ (CLI commands, quota patterns, capacity formulas, cross-region fallback logic).

| Phase                     | Action                                                                             | Key Details                                            |
| ------------------------- | ---------------------------------------------------------------------------------- | ------------------------------------------------------ |
| **1. Verify Auth**        | Check `az account show`; prompt `az login` if needed                               | Verify correct subscription is active                  |
| **2. Get Project ID**     | Read `PROJECT_RESOURCE_ID` env var or prompt user                                  | ARM resource ID format required                        |
| **3. Verify Project**     | Parse resource ID, call `az cognitiveservices account show`                        | Extracts subscription, RG, account, project, region    |
| **4. Get Model**          | List models via `az cognitiveservices account list-models`                         | User selects from available or enters custom name      |
| **5. Select Version**     | Query versions for chosen model                                                    | Recommend latest; user picks from list                 |
| **6. Select SKU**         | Query model catalog + subscription quota, show only deployable SKUs                | ⚠️ Never hardcode SKU lists — always query live data   |
| **7. Configure Capacity** | Query capacity API, validate min/max/step, user enters value                       | Cross-region fallback if no capacity in current region |
| **8. Select RAI Policy**  | Present content filter options                                                     | Default: `Microsoft.DefaultV2`