Get OCR Result
mindee.get_ocr_result
ActionAI & modelsconnection required
Calls the Mindee API with the connection's credentials.
Fetch a finished OCR inference by id and return its per-page text.
Connection
- Required
- Yes — the node will not save without one
- Auth type
- API key
- Providers
- Mindee
- Secret shape
- the V2 API key, or {"api_key": "…"}
- Config it needs
- base_url, model_id
- Resolved by
- config.connection_id, else node.connection_id
Configuration
1 field, 1 required. A dotted path is a nested object and name[] an array of objects — the editor renders the same tree.
| Field | Type | Required | Default | Constraints | Example |
|---|---|---|---|---|---|
inference_id UUID of the finished inference — the tail of the job's result_url. | string | Yes | — | — | — |
Output
One shape.
result
| Field | Type | Example |
|---|---|---|
product Which product ran: extraction, ocr, classification, split or crop. | string | — |
inference_id UUID of the inference. | string | — |
page_count Number of pages Mindee found in the file. | number | — |
mime_type MIME type Mindee detected for the file. | string | — |
inference The whole inference object exactly as Mindee returned it. | object | — |
completed Always true — a fetched inference has finished. | boolean | — |
model_id UUID of the model that produced the inference. | string | — |
filename File name as Mindee recorded it. | string | — |
text The document's text, with pages joined by newlines. | string | — |
pages One entry per page, each with its content and word polygons. | array | — |
{
"completed": false,
"filename": "",
"inference": {},
"inference_id": "",
"mime_type": "",
"model_id": "",
"page_count": 0,
"pages": [],
"product": "",
"text": ""
}See Get OCR Result run in a workflow.
In a technical demo we add the Mindee connection, drop the node on the canvas and let Workflow Health pre-flight it before the first real run.