Generate structured prediction for the given document.
document domains, see the Hub Catalog.
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Request to the VLM API using a document (doc, docx, pptx, pdf).
The domain identifier (e.g. document.invoice).
document.invoice, document.markdown, document.receipt, document.resume, document.us-drivers-license, healthcare.patient-referral, healthcare.patient-identification, healthcare.physician-order, healthcare.claims-processing, construction.blueprint, document.layout-detection Optional metadata to pass to the model.
The VLM generation config to be used for /
The URL of the file (provide either file_id or url).
The ID of the uploaded file (provide either file_id or url).
Unique identifier of the request.
Date and time when the request was created (in UTC timezone)
The URL to call when the request is completed.
1The model to use for generating the response.
"vlm-1"Whether to process the document in batch mode (async).
Successful Response
Base prediction response for all API responses.
The usage metrics for the request.
Unique identifier of the response.
Date and time when the request was created (in UTC timezone)
Date and time when the response was completed (in UTC timezone)
The response from the model.
The status of the job.
pending, enqueued, running, completed, failed, paused The domain of the prediction (e.g. document.invoice, image.caption).