Create environment API: POST /environments-Alibaba Cloud Model Studio(Model Studio)-阿里云帮助中心

Create a runtime environment. The request body defines the sandbox type, preinstalled dependencies, and network policy; the response returns the full Environment object.

Prerequisites

Endpoint and authentication are configured. See Overview and authentication.

Endpoint

POST /environments

Request body

Field	Required	Type	Description
`name`	Yes	string	Unique identifier within the workspace
`description`	No	string	Description of the environment's purpose
`scope`	No	string	Scope of the environment. `organization`: visible to and reusable by all members of the workspace. Defaults to `organization`
`config.type`	No	string	Sandbox type. `cloud` = cloud container. Immutable after creation. Defaults to `cloud` when `config` is omitted
`config.packages`	No	object	Preinstalled dependencies grouped by package manager. Keys are `apt` \| `pip` \| `npm`; values are arrays of package names
`config.networking`	No	object	Network policy object, shaped as `{"type": "unrestricted"}`. Currently only unrestricted outbound access is supported
`metadata`	No	object	Custom business key-value pairs; do not affect runtime behavior

Request example

bash

curl -X POST "$AGENTSTUDIO_URL/environments" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "data-sandbox",
    "description": "Data analysis sandbox",
    "scope": "organization",
    "metadata": {"team": "infra"},
    "config": {
      "type": "cloud",
      "packages": {
        "apt": ["ffmpeg"],
        "pip": ["pandas", "numpy", "matplotlib"]
      },
      "networking": {"type": "unrestricted"}
    }
  }'

python

env = client.environments.create(
    name="data-sandbox",
    config={
        "type": "cloud",
        "networking": {"type": "unrestricted"},
        "packages": {
            "apt": ["ffmpeg"],
            "pip": ["pandas", "numpy", "matplotlib"],
        },
    },
    description="Data analysis sandbox",
    scope="organization",
    metadata={"team": "infra"},
)

java

Environment env = client.environments().create(EnvironmentCreateParam.builder()
    .name("data-sandbox")
    .description("Data analysis sandbox")
    .build());

Response example

{
  "id": "env_xxx",
  "type": "environment",
  "name": "data-sandbox",
  "description": "Data analysis sandbox",
  "scope": "organization",
  "config": {
    "type": "cloud",
    "packages": {"apt": ["ffmpeg"], "pip": ["pandas", "numpy", "matplotlib"]},
    "networking": {"type": "unrestricted"}
  },
  "metadata": {"team": "infra"},
  "archived_at": null,
  "created_at": "2026-06-16T12:45:34+08:00",
  "updated_at": "2026-06-16T12:45:34+08:00",
  "requestId": "xxx"
}

The response is an Environment object. Fields:

Response fields

Field	Type	Description
`id`	string	Environment ID, format `env_` + base64-encoded string, for example `env_N2M2OTc4NTY4ZjRkNDEwZT`
`type`	string	Fixed value `environment`
`name` / `description` / `scope` / `config` / `metadata`	string / object	Same as the request body; `config` contains the full runtime configuration (sandbox type, preinstalled dependencies, network policy)
`archived_at`	string \| null	Archive time; `null` when not archived
`created_at` / `updated_at`	string	Creation / last update time, ISO 8601
`requestId`	string	Unique identifier for this request