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GET
/
v1
/
predictions
/
{id}
!pip install vlmrun

from vlmrun.client import VLMRun
from vlmrun.client.types import PredictionResponse

client = VLMRun(api_key="<VLMRUN_API_KEY>")
response: PredictionResponse = client.predictions.get("<prediction_id>")

{
  "usage": {
    "elements_processed": 123,
    "element_type": "image",
    "credits_used": 123,
    "steps": 123,
    "message": "<string>",
    "duration_seconds": 0
  },
  "id": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "completed_at": "2023-11-07T05:31:56Z",
  "response": "<unknown>",
  "status": "pending",
  "domain": "<string>"
}
Get the predictions for a given prediction ID. 
!pip install vlmrun

from vlmrun.client import VLMRun
from vlmrun.client.types import PredictionResponse

client = VLMRun(api_key="<VLMRUN_API_KEY>")
response: PredictionResponse = client.predictions.get("<prediction_id>")

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

​
id
string
required

Response

Successful Response

Base prediction response for all API responses.

​
usage
CreditUsageResponse · object

The usage metrics for the request.

​
id
string

Unique identifier of the response.

​
created_at
string<date-time>

Date and time when the request was created (in UTC timezone)

​
completed_at
string<date-time> | null

Date and time when the response was completed (in UTC timezone)

​
response
any | null

The response from the model.

​
status
enum<string>
default:pending

The status of the job.

Available options:
pending,
enqueued,
running,
completed,
failed,
paused
​
domain
string | null

The domain of the prediction (e.g. document.invoice, image.caption).