preset
microsoft/skills
通过检查各区域的容量并部署到最佳可用选项,自动化 Azure OpenAI 模型的部署。
...展开全部将模型部署至最优区域
通过检查各区域的容量并部署到最佳可用选项,自动化智能 Azure OpenAI 模型部署过程。
此技能的功能
- 验证 Azure 身份验证和项目范围
- 检查当前项目所在区域的容量
- 若无容量:分析所有区域并显示可用的替代方案
- 按选定区域筛选项目
- 支持在需要时创建新项目
- 使用 GlobalStandard SKU 部署模型
- 监控部署进度
前提条件
- 已安装并配置 Azure CLI
- 拥有认知服务读取/创建权限的活跃 Azure 订阅
- Azure AI Foundry 项目资源 ID(
PROJECT_RESOURCE_ID环境变量或交互式提供)- 格式:
/subscriptions/{sub-id}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project} - 查找位置:Azure AI Foundry 门户 → 项目 → 概述 → 资源 ID
- 格式:
快速工作流
快速路径(当前区域有容量)
1. 检查身份验证 → 2. 获取项目 → 3. 检查当前区域容量
→ 4. 立即部署
备用区域路径(无容量)
1. 检查身份验证 → 2. 获取项目 → 3. 检查当前区域(无容量)
→ 4. 查询所有区域 → 5. 显示替代方案 → 6. 选择区域 + 项目
→ 7. 部署
部署阶段
| 阶段 | 操作 | 关键命令 |
|---|---|---|
| 1. 验证身份验证 | 检查 Azure CLI 登录和订阅 | `az account show`, `az login` |
| 2. 获取项目 | 解析 `PROJECT_RESOURCE_ID` ARM ID,验证是否存在 | `az cognitiveservices account show` |
| 3. 获取模型 | 列出可用模型,用户选择模型和版本 | `az cognitiveservices account list-models` |
| 4. 检查当前区域 | 使用 GlobalStandard SKU 查询容量 | `az rest --method GET .../modelCapacities` |
| 5. 多区域查询 | 如果本地无容量,查询所有区域 | 不带位置过滤器的相同容量 API |
| 6. 选择区域 + 项目 | 用户选择区域;查找或创建项目 | `az cognitiveservices account list`, `az cognitiveservices account create` |
| 7. 部署 | 生成唯一名称,计算容量(50% 可用,最低 50 TPM),创建部署 | `az cognitiveservices account deployment create` |
有关详细的分步说明,请参阅工作流参考。
错误处理
| 错误 | 症状 | 解决方案 |
|---|---|---|
| 身份验证失败 | `az account show` 返回错误 | 运行 `az login` 然后 `az account set --subscription |
| 无配额 | 所有区域显示容量为 0 | 转至配额技能以处理增加请求和故障排除;检查现有部署;尝试其他模型 |
| 未找到模型 | 容量列表为空 | 使用 `az cognitiveservices account list-models` 验证模型名称;检查大小写敏感性 |
| 名称冲突 | “部署已存在” | 在部署名称后附加后缀(由 `generate_deployment_name` 脚本自动处理) |
| 区域不可用 | 区域不支持该模型 | 从可用列表中选择其他区域 |
| 权限被拒绝 | “禁止”或“未经授权” | 验证认知服务贡献者角色:`az role assignment list --assignee |
高级用法
# 自定义容量
az cognitiveservices account deployment create ... --sku-capacity <value>
# 检查部署状态
az cognitiveservices account deployment show --name <acct> --resource-group <rg> --deployment-name <name> --query "{Status:properties.provisioningState}"
# 删除部署
az cognitiveservices account deployment delete --name <acct> --resource-group <rg> --deployment-name <name>注意事项
- SKU: 仅限 GlobalStandard — API 版本: 2024-10-01(GA 稳定版)
相关技能
- microsoft-foundry - Azure AI Foundry 操作的父级技能
- quota — 用于查看配额、增加请求和处理配额错误,请转至此技能
- azure-quick-review - 审查 Azure 资源以符合合规性要求
- azure-cost-estimation - 估算 Azure 部署的成本
- azure-validate - 在部署前验证 Azure 基础设施
---
name: preset
description: Automates Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.
license: MIT
---
# Deploy Model to Optimal Region
Automates intelligent Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.
## What This Skill Does
1. Verifies Azure authentication and project scope
2. Checks capacity in current project's region
3. If no capacity: analyzes all regions and shows available alternatives
4. Filters projects by selected region
5. Supports creating new projects if needed
6. Deploys model with GlobalStandard SKU
7. Monitors deployment progress
## Prerequisites
- Azure CLI installed and configured
- Active Azure subscription with Cognitive Services read/create permissions
- Azure AI Foundry project resource ID (`PROJECT_RESOURCE_ID` env var or provided interactively)
- Format: `/subscriptions/{sub-id}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project}`
- Found in: Azure AI Foundry portal → Project → Overview → Resource ID
## Quick Workflow
### Fast Path (Current Region Has Capacity)
```
1. Check authentication → 2. Get project → 3. Check current region capacity
→ 4. Deploy immediately
```
### Alternative Region Path (No Capacity)
```
1. Check authentication → 2. Get project → 3. Check current region (no capacity)
→ 4. Query all regions → 5. Show alternatives → 6. Select region + project
→ 7. Deploy
```
---
## Deployment Phases
| Phase | Action | Key Commands |
|-------|--------|-------------|
| 1. Verify Auth | Check Azure CLI login and subscription | `az account show`, `az login` |
| 2. Get Project | Parse `PROJECT_RESOURCE_ID` ARM ID, verify exists | `az cognitiveservices account show` |
| 3. Get Model | List available models, user selects model + version | `az cognitiveservices account list-models` |
| 4. Check Current Region | Query capacity using GlobalStandard SKU | `az rest --method GET .../modelCapacities` |
| 5. Multi-Region Query | If no local capacity, query all regions | Same capacity API without location filter |
| 6. Select Region + Project | User picks region; find or create project | `az cognitiveservices account list`, `az cognitiveservices account create` |
| 7. Deploy | Generate unique name, calculate capacity (50% available, min 50 TPM), create deployment | `az cognitiveservices account deployment create` |
For detailed step-by-step instructions, see [workflow reference](references/workflow.md).
---
## Error Handling
| Error | Symptom | Resolution |
|-------|---------|------------|
| Auth failure | `az account show` returns error | Run `az login` then `az account set --subscription <id>` |
| No quota | All regions show 0 capacity | Defer to the [quota skill](../../../quota/quota.md) for increase requests and troubleshooting; check existing deployments; try alternative models |
| Model not found | Empty capacity list | Verify model name with `az cognitiveservices account list-models`; check case sensitivity |
| Name conflict | "deployment already exists" | Append suffix to deployment name (handled automatically by `generate_deployment_name` script) |
| Region unavailable | Region doesn't support model | Select a different region from the available list |
| Permission denied | "Forbidden" or "Unauthorized" | Verify Cognitive Services Contributor role: `az role assignment list --assignee <user>` |
---
## Advanced Usage
```bash
# Custom capacity
az cognitiveservices account deployment create ... --sku-capacity <value>
# Check deployment status
az cognitiveservices account deployment show --name <acct> --resource-group <rg> --deployment-name <name> --query "{Status:properties.provisioningState}"
# Delete deployment
az cognitiveservices account deployment delete --name <acct> --resource-group <rg> --deployment-name <name>
```
## Notes
- **SKU:** GlobalStandard only — **API Version:** 2024-10-01 (GA stable)
---
## Related Skills
- **microsoft-foundry** - Parent skill for Azure AI Foundry operations
- **[quota](../../../quota/quota.md)** — For quota viewing, increase requests, and troubleshooting quota errors, defer to this skill
- **azure-quick-review** - Review Azure resources for compliance
- **azure-cost-estimation** - Estimate costs for Azure deployments
- **azure-validate** - Validate Azure infrastructure before deployment
所有文件
0 个文件安装 preset
将技能文件下载并解压至你的 .claude/skills/ 目录。
下载ZIP克隆仓库并复制技能文件到您的项目中。
git clone https://github.com/microsoft/skills/tree/main/.github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/preset # Copy SKILL.md to your .claude/skills/ directory
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