魔搭创空间部署Skill

SKILL.md 节选

# ModelScope Studio Deployment

> Verified live against ModelScope OpenAPI ｜ modelscope 1.37.1 / modelscope_hub 0.1.2 (2026-06-29)

Deploy a local project to a ModelScope Studio. **This Skill uses OpenAPI as the source of truth**, with the `ms` CLI as an equivalent convenience alias, `modelscope_hub.HubApi` as the API-first Python client, and MCP tools as optional.

## Quick Decision Guide

```
User wants to...
│
├── Deploy a local project to a Studio
│   └── Follow the 10 steps in "Full Deployment Workflow" below
│
├── Update an already-deployed Studio
│   └── Modify code → git push → POST /studios/{o}/{r}/deploy (or ms deploy)
│
├── View Studio status/logs
│   └── GET /studios/{o}/{r}/logs/run (or ms logs --log-type run)
│
├── Manage variables
│   ├── Plaintext variables: GET/POST/PUT/DELETE /studios/{o}/{r}/variables
│   └── Secrets: GET/POST/PUT/DELETE /studios/{o}/{r}/secrets (or ms secret ...)
│
└── Repository file management / model & dataset operations
    └── hand off → ms-hub
```

## Prerequisites

### 1. MODELSCOPE_API_KEY

The entire workflow depends on this token (API authentication, Git push, variable/secret configuration); it must be confirmed first.

```bash
# 1. First check the environment variable
echo $MODELSCOPE_API_KEY

# 2. If empty, try extracting from the git remote (may have been configured before)
git remote -v 2>/dev/null | grep modelscope.cn
```

If the environment variable is empty but the git remote contains an address of the form `https://oauth2:<token>@www.modelscope.cn/studios/...` (or `www.modelscope.ai/...` for the international site), extract `<token>` from it as `MODELSCOPE_API_KEY`.
If neither is available, guide the user:

1. Visit $MODELSCOPE_ENDPOINT/my/myaccesstoken to obtain a token
2. `export MODELSCOPE_API_KEY=your_token`

> **Site routing:** this skill targets whichever site `$MODELSCOPE_ENDPOINT` points to (default domestic `https://modelscope.cn`; international `https://www.modelscope.ai`). Export `MODELSCOPE_ENDPOINT` plus a **site-scoped** token before deploying — the OpenAPI base and the git remote host below both derive from it. Full guidance: ms-hub → "Site selection & endpoint routing".

### 2. Runtime Environment

```bash
pip install modelscope          # Also provides the OpenAPI/SDK and the ms CLI
```

OpenAPI basic conventions:

| Item | Value |
|------|-----|
| **Base URL** | `$MODELSCOPE_ENDPOINT/openapi/v1` (default `https://modelscope.cn`) |
| **Authentication** | `Authorization: Bearer $MODELSCOPE_API_KEY` |
| **Success response** | `{"success": true, "data": {...}, "request_id": "..."}` |
| **Default branch** | `master` (not main) |

### 3. Git Environment

Studio code is synced via Git; ensure Git is installed and user information is configured.

## Operations Overview: OpenAPI (source of truth) ↔ CLI ↔ Python

| Operation | OpenAPI (source of truth) | ms CLI (equivalent alias) | `modelscope_hub.HubApi` (Python) | MCP tool (optional) |
|------|---------------------|---------------------|-----------------------------------|------------------|
| User info | `GET /users/me` | `ms whoami` | `api.whoami()` | `getCurrentUser` |
| Create Studio | `POST /studios` | `ms create o/r --repo-type studio` | `api.create_repo("o/r", repo_type="studio", ...)` | `createStudio` |
| Get details | `GET /studios/{o}/{r}` | `ms info o/r --repo-type studio` | `api.get_repo("o/r", repo_type="studio")` | `getStudio` |
| Deploy/restart | `POST /studios/{o}/{r}/deploy` | `ms deploy o/r --repo-type studio` | `api.deploy_repo("o/r")` | `deployStudio` |
| Stop | `POST /studios/{o}/{r}/stop` | `ms stop o/r --repo-type studio` | `api.stop_repo("o/r")` | `stopStudio` |
| Logs | `GET /studios/{o}/{r}/logs/{run\|build}` | `ms logs o/r --log-type run` | `api.get_repo_logs("o/r", log_type="run")` | `getStudioLogs` |
| Update settings | `PATCH /studios/{o}/{r}/settings` | `ms settings o/r --repo-type studio k=v` | `api.update_repo_settings("o/r","studio",**kw)` | `updateStudioSettings` |

SKILL.md 不止这些内容，安装后可阅读全文。

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