跳转到主要内容
GET
https://api.ppinfra.com
/
gpu-instance
/
openapi
/
v1
/
templates
获取模板列表
curl --request GET \
  --url https://api.ppinfra.com/gpu-instance/openapi/v1/templates \
  --header 'Authorization: <authorization>'
{
  "template": [
    {
      "Id": "<string>",
      "name": "<string>",
      "readme": "<string>",
      "type": "<string>",
      "channel": "<string>",
      "image": "<string>",
      "imageAuth": "<string>",
      "startCommand": "<string>",
      "entrypoint": "<string>",
      "rootfsSize": 123,
      "ports": [
        {}
      ],
      "envs": [
        {}
      ],
      "tools": [
        {}
      ],
      "createdAt": "<string>",
      "recommendCards": [
        {}
      ],
      "minCudaVersion": "<string>"
    }
  ],
  "total": 123
}

​
请求头

​
Authorization
string
必填
Bearer 身份验证格式，例如：Bearer {{API 密钥}}。

​
查询参数

​
pageSize
integer
获取 x 条/页。整数，取值范围：大于等于 0。
​
pageNum
integer
获取第 x 页。整数，取值范围：大于等于 0。
​
name
string
筛选指定模板名称（支持模糊匹配）。长度：[1-255]。
​
channel
string
必填
筛选模板分类。可选值：
  • official：官方模板
  • community：社区模板
  • private：私有模板
​
isMyCommunity
boolean
必填
模板可见性。查询官方、社区模板传 false；查询私有模板传 true。

​
响应参数

​
template
object[]
必填
模板信息列表。
​
total
integer
必填
查询到的模板总数量。

​
示例

​
请求示例

curl --location --request GET 'https://api.ppinfra.com/gpu-instance/openapi/v1/templates?pageSize=10&pageNum=1&name=test&channel=private&isMyCommunity=true' \
--header 'Authorization: Bearer {{API 密钥}}'

​
响应示例

{
  "template": [
    {
      "Id": "1",
      "name": "Pytorch:v2",
      "readme": "...",
      "type": "instance",
      "channel": "official",
      "image": "test-image.ppinfra.com/test-public/pytorch:v2",
      "imageAuth": "",
      "startCommand": "",
      "entrypoint": "",
      "rootfsSize": 100,
      "ports": [
        {"type": "http", "ports": [80]},
        {"type": "tcp", "ports": [7860]}
      ],
      "envs": [{"key": "test", "value": "template"}],
      "tools": [{"name": "Jupyter", "describe": "Start Jupyter Notebook", "port": 8888, "type": "http"}],
      "createdAt": "1715760544",
      "recommendCards": [{"gpuSpecId": "4090.18c.60g", "cardNum": "2"}],
      "minCudaVersion": "11.8"
    }
  ],
  "total": 12
}