curl --request GET \
  --url https://api.tensormesh.ai/v1/models \
  --header 'Authorization: Bearer <token>'

import requests

url = "https://api.tensormesh.ai/v1/models"

headers = {"Authorization": "Bearer <token>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};

fetch('https://api.tensormesh.ai/v1/models', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "models": [
    {
      "modelId": "<string>",
      "deploymentId": "<string>",
      "userId": "<string>",
      "description": "<string>",
      "modelPath": "<string>",
      "modelName": "<string>",
      "status": "MODEL_STATUS_UNSPECIFIED",
      "events": [
        {
          "createdAt": "2023-11-07T05:31:56Z",
          "log": "<string>",
          "eventType": "EVENT_TYPE_UNSPECIFIED"
        }
      ],
      "createdAt": "2023-11-07T05:31:56Z",
      "updatedAt": "2023-11-07T05:31:56Z",
      "modelSpec": {},
      "infra": {
        "cloudProvider": "CLOUD_PROVIDER_UNSPECIFIED",
        "nebiusRegion": "NEBIUS_REGION_UNSPECIFIED",
        "lambdaRegion": "LAMBDA_REGION_UNSPECIFIED",
        "onpremRegion": "<string>"
      },
      "gpuCount": 123,
      "gpuType": "GPU_TYPE_UNSPECIFIED",
      "replicas": 123,
      "endpoint": "<string>",
      "apiKey": "<string>"
    }
  ]
}

{
  "code": 123,
  "message": "<string>",
  "details": [
    {
      "@type": "<string>"
    }
  ]
}