auto reframe

curl --request POST \
  --url https://eversince.ai/api/v1/tools/auto_reframe \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "timeline_id": "<string>"
}
'

import requests

url = "https://eversince.ai/api/v1/tools/auto_reframe"

payload = { "timeline_id": "<string>" }
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({timeline_id: '<string>'})
};

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

{
  "ok": true,
  "data": {},
  "meta": {
    "request_id": "<string>",
    "cost": {},
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  },
  "media": [
    {}
  ]
}

{
  "ok": false,
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "suggested_action": "<string>",
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}