Get RAG Document
mindee.get_rag_document
ActionAI & modelsconnection required
Calls the Mindee API with the connection's credentials.
Read one indexed RAG document, including its status and match count.
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 |
|---|---|---|---|---|---|
document_id UUID of the indexed RAG document. | string | Yes | — | — | — |
Output
One shape.
result
| Field | Type | Example |
|---|---|---|
id UUID of the RAG document. | string | — |
model_id UUID of the extraction model it is indexed against. | string | — |
filename Original file name of the indexed document. | string | — |
created_at When the document was indexed, ISO 8601. | string | — |
status Processing, Failed, Draft or Active. | string | — |
total_matches How many inferences have used this document. | number | — |
last_match_at When it was last used by an inference, ISO 8601. | string | — |
{
"created_at": "",
"filename": "",
"id": "",
"last_match_at": "",
"model_id": "",
"status": "",
"total_matches": 0
}See Get RAG Document 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.